datetime:\n return timestamp_to_datetime(0)","def timestamp(self, offset=0):\n return int(self._base_ts + offset) * 1000","def _from_microseconds(value):\n return _UTC_EPOCH + datetime.timedelta(microseconds=value)","def get_subtitle_offset(annotation, seen_annotations, clip):\n if not annotation[\"time\"] in seen_annotations:\n return clip.h - SUBTILE_OFFSET\n else:\n return clip.h - SUBTILE_OFFSET * (seen_annotations[annotation[\"time\"]] + 1)","def _get_timestamp(self, timestamp):\n return int(timestamp * 1e6)","def convert_delta_time(\n delta_time: np.ndarray,\n epoch1: str | tuple | list | np.datetime64 | None = None,\n epoch2: str | tuple | list | np.datetime64 | None = None,\n scale: float = 1.0\n ):\n # convert epochs to datetime variables\n if isinstance(epoch1, (tuple, list)):\n epoch1 = np.datetime64(datetime.datetime(*epoch1))\n elif isinstance(epoch1, str):\n epoch1 = np.datetime64(parse(epoch1))\n if isinstance(epoch2, (tuple, list)):\n epoch2 = np.datetime64(datetime.datetime(*epoch2))\n elif isinstance(epoch2, str):\n epoch2 = np.datetime64(parse(epoch2))\n # calculate the total difference in time in seconds\n delta_time_epochs = (epoch2 - epoch1) / np.timedelta64(1, 's')\n # subtract difference in time and rescale to output units\n return scale*(delta_time - delta_time_epochs)","def convert_delta_time(\n delta_time: np.ndarray,\n epoch1: str | tuple | list | np.datetime64 | None = None,\n epoch2: str | tuple | list | np.datetime64 | None = None,\n scale: float = 1.0\n ):\n # convert epochs to datetime variables\n if isinstance(epoch1, (tuple, list)):\n epoch1 = np.datetime64(datetime.datetime(*epoch1))\n elif isinstance(epoch1, str):\n epoch1 = np.datetime64(parse(epoch1))\n if isinstance(epoch2, (tuple, list)):\n epoch2 = np.datetime64(datetime.datetime(*epoch2))\n elif isinstance(epoch2, str):\n epoch2 = np.datetime64(parse(epoch2))\n # calculate the total difference in time in seconds\n delta_time_epochs = (epoch2 - epoch1) / np.timedelta64(1, 's')\n # subtract difference in time and rescale to output units\n return scale*(delta_time - delta_time_epochs)","def startup_time_delta(self):\n return int((time.time() - self.startup_timestamp) * 1000.0)","def duration(self):\n return self._end - self._begin"],"string":"[\n \"def get_epoch_duration(self):\\n\\n now = time.time()\\n epoch_duration = datetime.datetime.fromtimestamp(now - self.prev_time).strftime(\\\"%M:%S.%f\\\")[:-4]\\n self.prev_time = now\\n return epoch_duration\",\n \"def ms2pts(ms, dt):\\n return int(ms/dt)\",\n \"def np_dt_epoch_msec(value):\\n return value.astype(long) / 1000\",\n \"def epoch():\\n\\treturn time.time()\",\n \"def epoch():\\n return datetime2epoch(datetime.now())\",\n \"def dt_epoch_msecs(value):\\n return long(calendar.timegm(value.timetuple())) * 1000\",\n \"def epoch_time(start_time, end_time):\\n elapsed_time = end_time - start_time\\n elapsed_mins = int(elapsed_time / 60)\\n elapsed_secs = int(elapsed_time - (elapsed_mins * 60))\\n return elapsed_mins, elapsed_secs\",\n \"def epoch_time(when):\\n if not when: return 0\\n epoch = datetime.utcfromtimestamp(0)\\n delta = when - epoch\\n return int(delta.total_seconds())\",\n \"def epoch_time(start_time, end_time):\\n elapsed_time = end_time - start_time\\n elapsed_mins = int(elapsed_time / 60)\\n elapsed_secs = int(elapsed_time - (elapsed_mins * 60))\\n\\n return elapsed_mins, elapsed_secs\",\n \"def epoch(value):\\n if isinstance(value, datetime.datetime):\\n return int(calendar.timegm(value.timetuple())*1000)\\n return '' #fails silently for non-datetime objects\",\n \"def _convert_time(self, duration):\\n in_sec = int(int(duration) / 1000)\\n in_time = int(in_sec / 60) + (0.01 * (in_sec % 60))\\n return in_time\",\n \"def pts2ms(pts, dt):\\n return pts*dt\",\n \"def epoch_time(self, start_time, end_time):\\n elapsed_time = end_time - start_time\\n elapsed_mins = int(elapsed_time / 60)\\n elapsed_secs = int(elapsed_time - (elapsed_mins * 60))\\n return elapsed_mins, elapsed_secs\",\n \"def milliseconds_offset(cls, timestamp, now=None):\\n if isinstance(timestamp, (int, float)):\\n base = timestamp\\n else:\\n base = cls.to_unix(timestamp)\\n if now is None:\\n now = time.time()\\n return (now - base) * 1000\",\n \"def datetime2epoch(dt):\\n return int(mktime(dt.timetuple())*1000)\",\n \"def __get_duration_from_line(self, line):\\n # TODO: catch exceptions\\n duration_str = line.split('=')[1]\\n return int(duration_str)\",\n \"def event_time_1970(event_time):\\n return event_time + start_time\",\n \"def add_milliseconds_to_epoch_time(epoch_time):\\n epoch_time = int(epoch_time / 1000 + 1) / 1000\\n return epoch_time\",\n \"def _TIME2STEPS(time):\\n return int(time*1000)\",\n \"def parse_time(s):\\n\\n dt = dateutil.parser.parse(s)\\n# epoch_time = int((dt - datetime(1970, 1, 1, tzinfo=timezone.utc)).total_seconds())\\n epoch_time = int(dt.replace(tzinfo=timezone.utc).timestamp())\\n\\n return epoch_time\",\n \"def __timedelta_millis(td):\\n return int(round(td.total_seconds(), 3) * 1000)\",\n \"def epoch_time(start_time: float, end_time: float) -> Tuple[int, int]:\\n elapsed_time = end_time - start_time\\n elapsed_mins = int(elapsed_time / 60)\\n elapsed_secs = int(elapsed_time - (elapsed_mins * 60))\\n return elapsed_mins, elapsed_secs\",\n \"def run_duration(self) -> Optional[pulumi.Input['DurationArgs']]:\\n return pulumi.get(self, \\\"run_duration\\\")\",\n \"def sbetime2unixtime(value):\\n if not isinstance(value, int):\\n raise InstrumentParameterException(\\\"value not a int\\\")\\n\\n return SBE_EPOCH + value\",\n \"def start_delta_string(self):\\r\\n delta = int(self.start_time) - int(self.root().start_time)\\r\\n return '%02d:%02d' % (delta / 60, delta % 60)\",\n \"def ms_from_timedelta(td):\\n return (td.seconds * 1000) + (td.microseconds / 1000.0)\",\n \"def to_unix_milli(self):\\n try:\\n dt_obj = duparser.parse(timestamp)\\n self.out_unix_milli = str(int((dt_obj - self.epoch_1970).total_seconds()*1000))\\n except Exception as e:\\n if not args.log:\\n pass\\n else:\\n logging.error(str(type(e)) + \\\",\\\" + str(e))\\n self.out_unix_milli = False\\n return self.out_unix_milli\",\n \"def epoch2datetime(t):\\n return datetime.fromtimestamp(t/1000.0)\",\n \"def convert_to_epoch(event_time_date) -> int:\\n pattern = '%Y-%m-%d %H:%M'\\n return int(time.mktime(time.strptime(event_time_date, pattern)))#to epoch value\",\n \"def unix_time_nanos(dt):\\n return timedelta_to_micros(dt - epoch)\",\n \"def epoch_time_now():\\n return int(time.time())\",\n \"def as_millis(self):\\n return int(ntplib.ntp_to_system_time(self.start) * 1000), int(ntplib.ntp_to_system_time(self.stop) * 1000)\",\n \"def _time_ms(dt):\\n epoch = datetime.datetime.utcfromtimestamp(0)\\n diff = dt - epoch\\n return diff.total_seconds() * 1000\",\n \"def epoch2time(time):\\n\\tvalue = datetime.datetime.fromtimestamp(time)\\n\\tNormal = value.strftime('%Y-%m-%d %H:%M:%S')\\n\\tprint(normal)\\n\\treturn normal\",\n \"def _duration_to_secs(duration):\\n secs = int(duration[:-1])\\n if duration[-1] == 's':\\n pass\\n elif duration[-1] == 'm':\\n secs *= 60\\n elif duration[-1] == 'h':\\n secs *= 60 * 60\\n elif duration[-1] == 'd':\\n secs *= 60 * 60 * 24\\n else:\\n raise ValueError('Invalid duration: %r' % duration)\\n\\n return secs\",\n \"def epochnow():\\n return time.time()\",\n \"def epoch(self):\\n return _coordsys.coordsys_epoch(self)\",\n \"def get_unixtime(self):\\n if not self.Complete():\\n raise DateTimeError(\\\"get_unixtime requires complete timepoint\\\")\\n zoffset = self.time.GetZoneOffset()\\n if zoffset is None:\\n raise DateTimeError(\\\"get_unixtime requires timezone\\\")\\n elif zoffset == 0:\\n zt = self\\n else:\\n zt = self.ShiftZone(zDirection=0)\\n days = zt.date.GetAbsoluteDay() - EPOCH.date.GetAbsoluteDay()\\n seconds = zt.time.GetTotalSeconds() - EPOCH.time.GetTotalSeconds()\\n return 86400 * days + seconds\",\n \"def get_track_length(duration):\\n try:\\n length = time.strptime(duration, '%M:%S')\\n except ValueError:\\n return None\\n return length.tm_min * 60 + length.tm_sec\",\n \"def convert_epoch(aepoch):\\n\\tprint \\\"time given: \\\" + aepoch\\n\\tepoch = time.strftime(\\\"%a %d %b %Y %H:%M:%S +0000\\\", time.gmtime(float(aepoch)))\\n\\tprint \\\"converted time: \\\" + epoch\",\n \"def get_annotation_duration(annotation):\\n return ANNOTATION_INITIAL_PAUSE_TIME + len(annotation[\\\"text\\\"]) * 0.2\",\n \"def pcr_delta_time_ms(pcr_t1, pcr_t2, offset = 0):\\n return float(pcr_t2-pcr_t1)/90000.0 + offset\",\n \"def _current_epoch_secs():\\n now = datetime.datetime.utcnow()\\n epoch = datetime.datetime(1970, 1, 1)\\n return (now - epoch).total_seconds()\",\n \"def to_deltatime(self,\\n epoch: str | tuple | list | np.ndarray,\\n scale: float = 1.0\\n ):\\n # convert epochs to numpy datetime variables\\n epoch1 = np.datetime64(datetime.datetime(*_mjd_epoch))\\n if isinstance(epoch, (tuple, list)):\\n epoch = np.datetime64(datetime.datetime(*epoch))\\n elif isinstance(epoch, str):\\n epoch = np.datetime64(parse(epoch))\\n # calculate the difference in epochs in days\\n delta_time_epochs = (epoch - epoch1) / np.timedelta64(1, 'D')\\n # return the date in time (default days) since epoch\\n return scale*np.array(self.MJD - delta_time_epochs, dtype=np.float64)\",\n \"def time_to_point(distance):\\n if distance <= (125 / 9) ** 2:\\n return distance ** .5\\n return distance * 9 / 250 + 125 / 18\",\n \"def millis() -> int:\",\n \"def epoch(self):\\n return self._epoch\",\n \"def datetime_to_epoch(datetime_obj):\\n return int(datetime_obj.strftime(\\\"%s\\\")) * 1000\",\n \"def elapsed_millis(start: int, /) -> int:\",\n \"def elapsed_micros(start: int, /) -> int:\",\n \"def chrome_timestamp_to_epoch(chrome_timestamp):\\n return (chrome_timestamp / 1000000) - 11644473600\",\n \"def extract_from_date(epochseconds, offset=0):\\n return time.gmtime(epochseconds+offset*3600)\",\n \"def _parse_duration(path):\\n tag = \\\"[FlowShaper] Application complete after \\\" # xxx ms\\n found = None\\n with (path / \\\"stdout.txt\\\").open(mode=\\\"r\\\") as stdout:\\n found = [line for line in stdout if line.startswith(tag)][-1]\\n assert found, f\\\"Run never completed! {path}\\\"\\n\\n # Parse the next word as an integer\\n return int(found[len(tag):].split()[0])\",\n \"def to_prtime(self):\\n try:\\n dt_obj = duparser.parse(timestamp)\\n self.out_prtime = str(int((dt_obj - self.epoch_1970).total_seconds() * 1000000))\\n except Exception as e:\\n if not args.log:\\n pass\\n else:\\n logging.error(str(type(e)) + \\\",\\\" + str(e))\\n self.out_prtime = False\\n return self.out_prtime\",\n \"def epoch_M(self):\\n return self._epoch_M\",\n \"def get_running_time(self):\\n with open(self.running_time_file, 'r') as file:\\n return int(file.read().strip())\",\n \"def parse_duration_str(self, duration):\\n try:\\n dl = duration.split(\\\":\\\")\\n except Exception:\\n return None\\n if len(dl) > 4:\\n return None\\n while len(dl) < 4:\\n dl.insert(0, 0)\\n\\n ret = int(dl[0]) * 60 * 60 * 24 + int(dl[1]) * \\\\\\n 60 * 60 + int(dl[2]) * 60 + int(dl[3])\\n return ret * 1000\",\n \"def epoch2UTCstr(timestamp=time(), fmat=\\\"%Y-%m-%d %H:%M:%S\\\"):\\n return strftime(fmat, gmtime(timestamp))\",\n \"def timestamp_to_unix(timestamp):\\n return timestamp / 1e6\",\n \"def get_epoch(timestamp):\\n timestamp_dt = datetime.datetime.strptime(timestamp, \\\"%Y-%m-%dT%H:%M:%SZ\\\")\\n epoch = calendar.timegm(timestamp_dt.timetuple())\\n return epoch\",\n \"def get_utc_offset(timestamp: str):\\n offset_direction = timestamp[-5] # A plus or minus sign\\n offset_hours = int(timestamp[-4:-2])\\n offset_minutes = int(timestamp[-2:])\\n offset_seconds = offset_hours * 3600 + offset_minutes * 60\\n return datetime.timezone(datetime.timedelta(seconds=int(offset_direction + str(offset_seconds))))\",\n \"def getEpochTime(self, time_str=None):\\n self.pushMode(CLI_MODES.shell)\\n if time_str is None:\\n system_time = self.sendCmd(r\\\"date +%s\\\")\\n else:\\n system_time = self.sendCmd(\\\"date -d '%s' \\\" % time_str + r\\\"+%s\\\")\\n\\n try:\\n system_time = float(system_time)\\n logger.info(\\\"Time %f\\\" % system_time)\\n except:\\n logger.error(\\\"Invalid system time '%s' on node '%s'\\\" % (system_time, self))\\n raise ValueError(\\\"Invalid system time '%s' on node '%s'\\\" % (system_time, self))\\n self.popMode()\\n return system_time\",\n \"def get_annotations_added_duration(annotations):\\n if (len(annotations)) == 0:\\n return ANNOTATION_INITIAL_PAUSE_TIME\\n\\n duration = 0\\n for annotation in annotations:\\n duration += get_annotation_duration(annotation)\\n return duration\",\n \"def set_epoch(self, epoch):\\r\\n pass\",\n \"def get_utc_offset():\\n timedelta = datetime.datetime.now() - datetime.datetime.utcnow()\\n # XXX: `return -time.timezone`?\\n return timedelta.total_seconds()\",\n \"def _STEPS2TIME(step):\\n return step/1000.\",\n \"def get_duration(f):\\n return 0\",\n \"def datetime_to_utc(timestamp):\\n\\n epoch = datetime.utcfromtimestamp(0)\\n delta = timestamp-epoch\\n\\n return long(delta.total_seconds() * 1000)\",\n \"async def toEpochTime(self, ctx, *, timeStr:str):\\n\\t\\t_, time = (search_dates(\\n\\t\\t\\ttimeStr.upper(), settings={'RETURN_AS_TIMEZONE_AWARE': True})[0])\\n\\t\\tawait ctx.send(f\\\"`{int(time.timestamp())}` is the timestamp for `{time.strftime('%c in timezone %Z')}`\\\\nThe basic timestamp would look like this: <t:{int(time.timestamp())}:F>\\\")\",\n \"def checktime(dt=None):\\n if dt is None:\\n epoch_time = str(int(time()))\\n else:\\n epoch_time = str(int(mktime(dt.timetuple())))\\n return epoch_time + \\\"000\\\"\",\n \"def _hx_time_to_epoch(self, timestr: str) -> int: # pragma: no cover\\n\\n time_obj = datetime.datetime.strptime(timestr, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n\\n return int(time_obj.strftime(\\\"%s\\\"))\",\n \"def stringTimeToUnix_NEW(st):\\n y, m, d, h, n, s, ms = stringTimeToTuple(st)\\n epochSecs = mktime(map(int ,(y, m, d, h, n, s, 0, 0, 0)))-timezone\\n #print \\\"seconds is %f\\\\n\\\" % (epochSecs + int(ms)/1000.0)\\n return epochSecs + int(ms)/1000.0\",\n \"def training_time_left(current_epoch, total_epochs, epoch_time):\\n epochs_rem = total_epochs - current_epoch - 1\\n time_rem = epochs_rem * epoch_time\\n return str(datetime.timedelta(seconds=time_rem))\",\n \"def datetime_to_epoch(datetime):\\n return datetime.astype('int64') // 1e9\",\n \"def get_epoch_time(utc_datetime=None):\\n if not utc_datetime:\\n utc_datetime = datetime.datetime.utcnow()\\n return math.ceil((utc_datetime - EPOCH_START).total_seconds())\",\n \"def get_duration(file):\\n cmd = 'ffprobe -i \\\"{}\\\" -show_entries format=duration -v quiet -of csv=\\\"p=0\\\"'.format(file)\\n try:\\n output = subprocess.check_output(\\n cmd,\\n shell=True, # Let this run in the shell\\n stderr=subprocess.STDOUT)\\n except subprocess.CalledProcessError as e:\\n print(e.output)\\n output = 0\\n # return round(float(output)) # ugly, but rounds your seconds up or down\\n return float(output)\",\n \"def duration(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"duration\\\")\",\n \"def _time_ms(self, dt):\\n if dt.tzinfo is None:\\n dt = dt.replace(tzinfo=pytz.utc)\\n return int((dt - self._EPOCH).total_seconds() * 1000)\",\n \"def epochCalc(timestamps):\\n\\tsplitTimes = unixTimeConv(timestamps)\\n\\tepochTimes = []\\n\\thour=int(splitTimes[3])\\n\\n\\tif (hour >0 and hour <=9) or hour>=23:\\n\\t\\tepoch='night'\\n\\telse:\\n\\t\\tepoch='not_night'\\n\\tepochTimes.append((epoch,splitTimes[6]))\\n\\treturn epochTimes\",\n \"def run_duration(self) -> 'outputs.DurationResponse':\\n return pulumi.get(self, \\\"run_duration\\\")\",\n \"def EpochNano():\\n return int(time.time() * 1000000000)\",\n \"def conv_time(l, h):\\n\\t# Function modified from post on ActiveState by John Nielsen\\n\\n\\t#converts 64-bit integer specifying the number of 100-nanosecond\\n\\t#intervals which have passed since January 1, 1601.\\n\\t#This 64-bit value is split into the\\n\\t#two 32 bits stored in the structure.\\n\\td = 116444736000000000L \\n\\n\\t# Some LNK files do not have time field populated \\n\\tif l + h != 0:\\n\\t\\tnewTime = (((long(h) << 32) + long(l)) - d)/10000000 \\n\\telse:\\n\\t\\tnewTime = 0\\n\\n\\treturn time.strftime(\\\"%Y/%m/%d %H:%M:%S %a\\\", time.localtime(newTime))\",\n \"def _arrival_time(self):\\n \\n return self.mkt_time + timedelta(0, 0, self.latency)\",\n \"def duration():\\r\\n elapsed_time, duration = video_time()\\r\\n return duration\",\n \"def calc_time(self, distance):\\r\\n if distance < 400:\\r\\n return 2*math.sqrt(distance / 1406.25)\\r\\n else:\\r\\n distance -= 400\\r\\n return distance / 750 + 16 / 15\",\n \"def track_length_string(length):\\n return str(timedelta(microseconds=length))\",\n \"def get_duration(distance, power):\\n assert power == 1\\n if distance <= 16.8:\\n t = distance_polynomial(distance) * 1000.0\\n else:\\n # s = (t - 300) * 0.063 + 18.9\\n t = (distance - 16.8) / 0.063 + 300\\n return int(t)\",\n \"def get_duration(self):\\n try:\\n if self.is_skipped:\\n return \\\"00:00\\\"\\n assert self.start_time\\n assert self.stop_time\\n if self.stop_time < self.start_time:\\n return \\\"XX:XX\\\"\\n return(\\n f\\\"{str(int(self.stop_time - self.start_time) // 60).zfill(2)}:\\\"\\n f\\\"{str(int(self.stop_time - self.start_time) % 60).zfill(2)}\\\")\\n\\n except Exception: # pylint: disable=broad-except\\n self.__logger.error(\\\"Please run test before getting the duration\\\")\\n return \\\"XX:XX\\\"\",\n \"def get_game_length(self, duration):\\n minutes = int(duration / 60)\\n seconds = int(duration % 60)\\n return \\\"{0}:{1}\\\".format(minutes, str(seconds).zfill(2))\",\n \"def duration(self):\\n return self.end_abs - self.start\",\n \"def _get_tell_time(elem):\\n return int(elem[3])\",\n \"def set_epoch(self, epoch=None):\\n params = {'epoch': epoch if epoch is not None else int(time.time())}\\n return self._jadeRpc('set_epoch', params)\",\n \"def datetime_utc_epoch_start() -> datetime:\\n return timestamp_to_datetime(0)\",\n \"def timestamp(self, offset=0):\\n return int(self._base_ts + offset) * 1000\",\n \"def _from_microseconds(value):\\n return _UTC_EPOCH + datetime.timedelta(microseconds=value)\",\n \"def get_subtitle_offset(annotation, seen_annotations, clip):\\n if not annotation[\\\"time\\\"] in seen_annotations:\\n return clip.h - SUBTILE_OFFSET\\n else:\\n return clip.h - SUBTILE_OFFSET * (seen_annotations[annotation[\\\"time\\\"]] + 1)\",\n \"def _get_timestamp(self, timestamp):\\n return int(timestamp * 1e6)\",\n \"def convert_delta_time(\\n delta_time: np.ndarray,\\n epoch1: str | tuple | list | np.datetime64 | None = None,\\n epoch2: str | tuple | list | np.datetime64 | None = None,\\n scale: float = 1.0\\n ):\\n # convert epochs to datetime variables\\n if isinstance(epoch1, (tuple, list)):\\n epoch1 = np.datetime64(datetime.datetime(*epoch1))\\n elif isinstance(epoch1, str):\\n epoch1 = np.datetime64(parse(epoch1))\\n if isinstance(epoch2, (tuple, list)):\\n epoch2 = np.datetime64(datetime.datetime(*epoch2))\\n elif isinstance(epoch2, str):\\n epoch2 = np.datetime64(parse(epoch2))\\n # calculate the total difference in time in seconds\\n delta_time_epochs = (epoch2 - epoch1) / np.timedelta64(1, 's')\\n # subtract difference in time and rescale to output units\\n return scale*(delta_time - delta_time_epochs)\",\n \"def convert_delta_time(\\n delta_time: np.ndarray,\\n epoch1: str | tuple | list | np.datetime64 | None = None,\\n epoch2: str | tuple | list | np.datetime64 | None = None,\\n scale: float = 1.0\\n ):\\n # convert epochs to datetime variables\\n if isinstance(epoch1, (tuple, list)):\\n epoch1 = np.datetime64(datetime.datetime(*epoch1))\\n elif isinstance(epoch1, str):\\n epoch1 = np.datetime64(parse(epoch1))\\n if isinstance(epoch2, (tuple, list)):\\n epoch2 = np.datetime64(datetime.datetime(*epoch2))\\n elif isinstance(epoch2, str):\\n epoch2 = np.datetime64(parse(epoch2))\\n # calculate the total difference in time in seconds\\n delta_time_epochs = (epoch2 - epoch1) / np.timedelta64(1, 's')\\n # subtract difference in time and rescale to output units\\n return scale*(delta_time - delta_time_epochs)\",\n \"def startup_time_delta(self):\\n return int((time.time() - self.startup_timestamp) * 1000.0)\",\n \"def duration(self):\\n return self._end - self._begin\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5740035","0.56960464","0.55968964","0.5498718","0.54860854","0.5484328","0.5429148","0.54070693","0.53953534","0.53865397","0.53487533","0.5276387","0.52748066","0.52547956","0.52436954","0.52381575","0.5197884","0.5156624","0.51419455","0.5118423","0.5093782","0.5069282","0.5063411","0.5059325","0.5058929","0.5048091","0.50435907","0.50280434","0.50262785","0.50115514","0.5010826","0.5007418","0.5006992","0.4980454","0.497187","0.49706444","0.49691653","0.49669665","0.4961616","0.4936073","0.49223015","0.49190468","0.49143624","0.49131238","0.49023747","0.4901729","0.48892078","0.48775604","0.48763993","0.48587692","0.4847619","0.48448938","0.48413882","0.48381653","0.4823335","0.48084617","0.48028553","0.4796588","0.47929507","0.4780423","0.476925","0.47661272","0.47599286","0.47573486","0.475518","0.4747802","0.4745858","0.4729913","0.47226653","0.4721929","0.47146732","0.471362","0.47133383","0.4705931","0.47033358","0.47001725","0.46994978","0.46962976","0.46841857","0.46841788","0.46794772","0.46740955","0.46730113","0.46646568","0.46639442","0.4662792","0.46459842","0.4643234","0.46385413","0.46335572","0.46307093","0.46298242","0.4628809","0.46273786","0.46242326","0.46224645","0.4619042","0.46156088","0.46156088","0.46083117","0.46066943"],"string":"[\n \"0.5740035\",\n \"0.56960464\",\n \"0.55968964\",\n \"0.5498718\",\n \"0.54860854\",\n \"0.5484328\",\n \"0.5429148\",\n \"0.54070693\",\n \"0.53953534\",\n \"0.53865397\",\n \"0.53487533\",\n \"0.5276387\",\n \"0.52748066\",\n \"0.52547956\",\n \"0.52436954\",\n \"0.52381575\",\n \"0.5197884\",\n \"0.5156624\",\n \"0.51419455\",\n \"0.5118423\",\n \"0.5093782\",\n \"0.5069282\",\n \"0.5063411\",\n \"0.5059325\",\n \"0.5058929\",\n \"0.5048091\",\n \"0.50435907\",\n \"0.50280434\",\n \"0.50262785\",\n \"0.50115514\",\n \"0.5010826\",\n \"0.5007418\",\n \"0.5006992\",\n \"0.4980454\",\n \"0.497187\",\n \"0.49706444\",\n \"0.49691653\",\n \"0.49669665\",\n \"0.4961616\",\n \"0.4936073\",\n \"0.49223015\",\n \"0.49190468\",\n \"0.49143624\",\n \"0.49131238\",\n \"0.49023747\",\n \"0.4901729\",\n \"0.48892078\",\n \"0.48775604\",\n \"0.48763993\",\n \"0.48587692\",\n \"0.4847619\",\n \"0.48448938\",\n \"0.48413882\",\n \"0.48381653\",\n \"0.4823335\",\n \"0.48084617\",\n \"0.48028553\",\n \"0.4796588\",\n \"0.47929507\",\n \"0.4780423\",\n \"0.476925\",\n \"0.47661272\",\n \"0.47599286\",\n \"0.47573486\",\n \"0.475518\",\n \"0.4747802\",\n \"0.4745858\",\n \"0.4729913\",\n \"0.47226653\",\n \"0.4721929\",\n \"0.47146732\",\n \"0.471362\",\n \"0.47133383\",\n \"0.4705931\",\n \"0.47033358\",\n \"0.47001725\",\n \"0.46994978\",\n \"0.46962976\",\n \"0.46841857\",\n \"0.46841788\",\n \"0.46794772\",\n \"0.46740955\",\n \"0.46730113\",\n \"0.46646568\",\n \"0.46639442\",\n \"0.4662792\",\n \"0.46459842\",\n \"0.4643234\",\n \"0.46385413\",\n \"0.46335572\",\n \"0.46307093\",\n \"0.46298242\",\n \"0.4628809\",\n \"0.46273786\",\n \"0.46242326\",\n \"0.46224645\",\n \"0.4619042\",\n \"0.46156088\",\n \"0.46156088\",\n \"0.46083117\",\n \"0.46066943\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":2279,"cells":{"query":{"kind":"string","value":"Convert Input JSON file into TableSchema message."},"document":{"kind":"string","value":"def BqTableSchemaFileProcessor(file_arg):\n table_schema_type = GetApiMessage('TableSchema')\n schema_field_type = GetApiMessage('TableFieldSchema')\n\n try:\n schema_json = yaml.load(file_arg)\n schema_json = schema_json.get('schema', None)\n\n if not schema_json or not isinstance(schema_json, list):\n raise SchemaFileError(\n 'Error parsing schema file: no schema field list defined in file')\n\n all_fields = []\n for field in schema_json:\n new_field = schema_field_type(name=field['name'],\n type=field['type'],\n mode=field.get('mode', 'NULLABLE'))\n all_fields.append(new_field)\n\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\n except yaml.YAMLParseError as ype:\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\n except (AttributeError, KeyError) as e:\n raise SchemaFileError(\n 'Error parsing schema file, invalid field definition [{}]'.format(e))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ReadSchemaFile(schema_file, bigquery_messages):\n\n if os.path.exists(schema_file):\n with open(schema_file, mode='r') as f:\n try:\n def UpperOrNone(string):\n return string and string.upper()\n field_schemas = [\n bigquery_messages.TableFieldSchema(\n name=json_object.get('name'),\n type=json_object.get('type').upper(),\n mode=UpperOrNone(json_object.get('mode')))\n for json_object in json.load(f)]\n return bigquery_messages.TableSchema(fields=field_schemas)\n except ValueError as e:\n raise bigquery.SchemaError(\n 'Error decoding JSON schema from file {0}: {1}.'.format(\n schema_file, e))\n else:\n raise bigquery.SchemaError(\n 'Error reading schema: File \"{0}\" was not found.'.format(schema_file))","def _create_input_data(self):\n SCHEMA = parse_table_schema_from_json(\n '{\"fields\": [{\"name\": \"data\", \"type\": \"BYTES\"}]}')\n\n def format_record(record):\n # Since Synthetic Source returns data as a dictionary, we should skip one\n # of the part\n import base64\n return {'data': base64.b64encode(record[1])}\n\n with TestPipeline() as p:\n ( # pylint: disable=expression-not-assigned\n p\n | 'Produce rows' >> Read(\n SyntheticSource(self.parse_synthetic_source_options()))\n | 'Format' >> Map(format_record)\n | 'Write to BigQuery' >> WriteToBigQuery(\n dataset=self.input_dataset,\n table=self.input_table,\n schema=SCHEMA,\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\n write_disposition=BigQueryDisposition.WRITE_EMPTY))","def CreateTableFromFile(self, table_name, schema_path):\n try:\n schema_file = open(schema_path)\n schema_json = schema_file.read()\n schema_file.close()\n except IOError, e:\n raise SchemaError('Could not read file (%s):\\n%s' %\n (schema_path, str(e)))\n return self.CreateTableFromJson(table_name, schema_json)","def read_json(file) -> Table:\n try:\n with Path(file).open(mode=\"r\", encoding=\"utf-8\") as __f:\n res = load(__f)\n print(str(res)[:100])\n return res\n except JSONDecodeError as err:\n if err.msg != \"Extra data\":\n raise\n # Extra data, so try load line by line\n res = []\n for line in Path(file).read_text(encoding=\"utf-8\").splitlines():\n try:\n if line.strip() == \"\":\n continue\n res.append(loads(line))\n except Exception:\n ic(line)\n ic(\"exc2\")\n raise\n return res","def __json_schema_generator(file):\n try:\n data = json.load(file)\n metadata_set = set()\n try:\n for datum in data['meta']['view']['columns']:\n metadata_set.add(datum['name'])\n except Exception as e:\n metadata_set.clear()\n for datum in data:\n if isinstance(datum, str):\n metadata_set.add(datum)\n else:\n for datum_property in datum:\n metadata_set.add(str(datum_property))\n\n metadata_list = list(metadata_set)\n # assumes list of objects with sparsse data\n # OR\n # for data_property in data[0]:\n # metadata_list.append(data_property)\n # assumes list of objects and that first entry has full list of properties\n\n return SchemaGenerator.__build_schema(metadata_list)\n except Exception as e:\n logging.error('Failed to parse json file into schema: ' + str(e))\n raise FailedCreatingSchemaException(\"Failed to create schema from json file.\")","def CreateTableFromJson(self, table_name, schema_json):\n try:\n schema = json.JSONDecoder().decode(schema_json)\n except ValueError, e:\n raise SchemaError('Could not parse fields:\\n%s\\n%s' %\n (schema_json, str(e)))\n\n conn = self._Connect()\n result = conn.Call(\n dict(method='bigquery.tables.insert',\n collection='tables',\n operation=bq.REST.INSERT,\n params=dict(name=table_name, fields=schema)))\n return result","def ReadSchema(schema, bigquery_messages):\n\n return bigquery_messages.TableSchema(\n fields=[\n _TableFieldSchemaForEntry(entry, bigquery_messages)\n for entry in schema.split(',')])","def insert_data(table, jsonfile):\n with open(jsonfile) as infile:\n data = json.load(infile)\n table_models_map[table]['insert'](data)","def generate_wc_schema():\n json_str = json.dumps({'fields': [\n {'name': 'word', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'percent', 'type': 'FLOAT', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def main(input_json, output_markdown):\n parser = Parser()\n output_md = parser.parse_schema(json.load(input_json))\n output_markdown.writelines(output_md)\n click.secho(\"✔ Successfully parsed schema!\", bold=True, fg=\"green\")","def _convert(self, fn, suffix='json', path='jsonschema', name=None,\n root_class_name=None, data_files=[], target_class=None):\n ie = JsonSchemaImportEngine()\n d = os.path.join(INPUT_DIR, path)\n schema = ie.load(os.path.join(d, f'{fn}.{suffix}'), name=name, format=suffix, root_class_name=root_class_name)\n model_path = os.path.join(OUTPUT_DIR, f'{fn}.yaml')\n write_schema(schema, model_path)\n roundtrip_path = os.path.join(OUTPUT_DIR, f'{fn}.roundtrip.json')\n with open(roundtrip_path, 'w') as stream:\n stream.write(JsonSchemaGenerator(model_path).serialize())\n python_path = os.path.join(OUTPUT_DIR, f'{fn}.py')\n with open(python_path, 'w') as stream:\n stream.write(PythonGenerator(model_path).serialize())\n compile_python(python_path)\n # TODO: test data_files\n return schema","def load_schema(filename):\n with open(filename) as f:\n schema = json.load(f)\n\n return schema","def test_convert_json():\n schema = pa.schema([\n pa.field(\"foo\", pa.int32()),\n pa.field(\"bar\", pa.int64())\n ])\n\n input_path = \"{}/tests/fixtures/simple_json.txt\".format(os.getcwd())\n expected_file = \"{}/tests/fixtures/simple.parquet\".format(os.getcwd())\n with tempfile.NamedTemporaryFile() as f:\n output_file = f.name\n client.convert_json(input_path, output_file, schema)\n output = pq.ParquetFile(output_file)\n expected = pq.ParquetFile(expected_file)\n assert output.metadata.num_columns == expected.metadata.num_columns\n assert output.metadata.num_rows == expected.metadata.num_rows\n assert output.schema.equals(expected.schema)\n assert output.read_row_group(0).to_pydict() == expected.read_row_group(0).to_pydict()","def from_json_file(cls, json_file:str):\n with open(json_file) as file:\n data = json.load(file)\n validate(data, schema)\n instance = cls.from_dict(data)\n return instance","def process_data(data):\n # Table Name from Json file\n table_name = data['table_name']\n\n # No of Column\n column_count = data['column_count']\n\n # No of Row\n row_count = data['row_count']\n\n # Table columns schema from Json file\n column_properties = data['column_properties']\n\n # Get the row row_properties\n row_properties = data['row_properties']\n return table_name, column_count, row_count, column_properties, row_properties","def deduce_schema(self, input_data, *, schema_map=None):\n\n if self.input_format == 'csv':\n if self.csv_dialect:\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\n else:\n reader = csv.DictReader(input_data)\n elif self.input_format == 'json' or self.input_format is None:\n reader = json_reader(input_data)\n elif self.input_format == 'dict':\n reader = input_data\n else:\n raise Exception(f\"Unknown input_format '{self.input_format}'\")\n\n if schema_map is None:\n schema_map = OrderedDict()\n\n try:\n for json_object in reader:\n\n # Print a progress message periodically.\n self.line_number += 1\n if self.line_number % self.debugging_interval == 0:\n logging.info(f'Processing line {self.line_number}')\n\n # Deduce the schema from this given data record.\n if isinstance(json_object, dict):\n self.deduce_schema_for_record(\n json_object=json_object,\n schema_map=schema_map,\n )\n elif isinstance(json_object, Exception):\n self.log_error(\n f'Record could not be parsed: Exception: {json_object}'\n )\n if not self.ignore_invalid_lines:\n raise json_object\n else:\n self.log_error(\n 'Record should be a JSON Object '\n f'but was a {type(json_object)}'\n )\n if not self.ignore_invalid_lines:\n raise Exception(f'Record must be a JSON Object '\n f'but was a {type(json_object)}')\n finally:\n logging.info(f'Processed {self.line_number} lines')\n\n return schema_map, self.error_logs","def _create_schema(self, cypher_file):\n if len(self.graph.nodes) > 0:\n msg = \"Cypher file specified but the graph is not empty. Aborting.\"\n raise ValueError(msg)\n cyp = open(cypher_file, 'r').read()\n self.graph.run(cyp)","def BqTableDataFileProcessor(file_arg):\n data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')\n insert_row_type = data_insert_request_type.RowsValueListEntry\n data_row_type = GetApiMessage('JsonObject')\n\n try:\n data_json = yaml.load(file_arg)\n\n if not data_json or not isinstance(data_json, list):\n raise TableDataFileError(\n 'Error parsing data file: no data records defined in file')\n\n rows = []\n for row in data_json:\n rows.append(insert_row_type(json=encoding.DictToMessage(\n row, data_row_type)))\n\n return rows\n except yaml.YAMLParseError as ype:\n raise TableDataFileError('Error parsing data file [{}]'.format(ype))","def _load_json_schema(filename):\n\n relative_path = join('schemas', filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n with open(absolute_path) as schema_file:\n return json.loads(schema_file.read())","def _load_json_schema(filename: str):\n relative_path = path.join('schemas', filename)\n absolute_path = path.join(path.dirname(__file__), relative_path)\n\n with open(absolute_path, 'r', encoding='utf-8') as schema_file:\n schema = json.loads(schema_file.read())\n\n return schema","def create_json_table(cur, country_json, body_json):\n print(\"Creating table from JSON file\")\n cur.execute('CREATE TABLE IF NOT EXISTS state_json(id INTEGER PRIMARY KEY, state TEXT, album TEXT)')\n for idx, album in enumerate(country_json[body_json['state']]):\n cur.execute('INSERT INTO state_json VALUES (\"%s\", \"%s\", \"%s\")' % (idx, body_json['state'], album))","def run(\n self,\n input_file=sys.stdin,\n output_file=sys.stdout,\n schema_map=None,\n ):\n schema_map, error_logs = self.deduce_schema(\n input_file, schema_map=schema_map\n )\n\n for error in error_logs:\n logging.info(\n f\"Problem on line {error['line_number']}: {error['msg']}\"\n )\n\n if self.debugging_map:\n json.dump(schema_map, output_file, indent=2)\n print(file=output_file)\n else:\n schema = self.flatten_schema(schema_map)\n json.dump(schema, output_file, indent=2)\n print(file=output_file)","def create_db(db, schema_json):\n with open(schema_json) as of:\n schema = json.load(of, object_pairs_hook=OrderedDict)\n # OrderedDict so that tables are created in the order specified,\n # allowing foreign keys to reference previously defined tables\n\n for table_name, columns in schema.items():\n col_types = columns.items() # dict -> tuple\n make_table(db, table_name, col_types)","def main(event, context):\n # pylint: enable=unused-argument\n data = decode(event[\"data\"])\n to_table([data], PROJECT, DATASET, TABLE)","def parse_raw(sqlContext, input, user):\n df = sqlContext.read.json(input + \"/\" + user + \"/\" + user + \".json\", multiLine=True)\n return df","def json_to_thrift(json_str, root_thrift_class):\r\n return json.loads(json_str, cls=ThriftJSONDecoder, root_thrift_class=root_thrift_class)","def extract_data(filename: str, schema_filename: str) -> DataFrame:\n data = []\n try:\n with open(schema_filename) as f:\n schema = json.load(f)\n with open(filename) as f:\n for line in f:\n json_doc = json.loads(line)\n if is_valid_data(json_doc, schema):\n data.append(json_doc)\n except ValueError as e:\n log.error(f\"Error parsing json: {e}\")\n except FileNotFoundError as e:\n log.error(f\"File not found error: {e}\")\n raise e\n except Exception as e:\n log.error(e)\n raise e\n return DataFrame(data)","def _schema_write(self, table: TableSchema) -> None:\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\n json.dump(table, f, indent=True)","def read_json(self, inputfile):\n transtransfile = json.load(inputfile)\n self.language = transfile['lang']\n self.translations = transfile['strings']","def generate_cooccur_schema():\n json_str = json.dumps({'fields': [\n {'name': 'w1', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'w2', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\n {'name': 'log_weight', 'type': 'FLOAT', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def generate_url_schema():\n json_str = json.dumps({'fields': [\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def generate_bq_schema(self, file_name, schema_file_name=None):\n if not schema_file_name:\n schema_file_name = f'{self.directory}/schema_temp.json'\n os.system(f\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\")\n\n schema = open(schema_file_name, 'r').read()\n\n os.remove(schema_file_name)\n\n return json.loads(schema)","def generate_data(self):\n print(\"generate_data - init\")\n with open(self.input_file, \"r\") as f:\n\n # read JSON data from input file\n data = json.loads(f.read())\n\n for idx, row in enumerate(data): \n # serialize Python dict to string\n msg = self.serialize_json(row)\n #print(f\"Linha: {row}\")\n self.send(self.topic, msg)\n self.flush()\n #print(\"Sleeping\")\n time.sleep(1)","def from_dict(cls, dikt) -> 'SourceSchema':\n return util.deserialize_model(dikt, cls)","def test_test_body_with_file_schema(self):\n pass","def _load_fixture(filename):\n\n # Read the binary data into text\n with open(filename, 'rb') as stream:\n content = stream.read().decode('utf-8')\n\n # Decode the data as JSON\n data = json.loads(content)\n\n # Instantiate a session.\n session = Session()\n\n # Iterate through the entries to add them one by one.\n for item in data:\n # Resolve model from the table reference.\n table = Base.metadata.tables[item['model'].split('.')[-1]]\n\n # Add the primary key.\n item['fields']['id'] = item['pk']\n\n # Add a new row.\n session.connection().execute(table.insert().values(**item['fields']))\n\n # Commit the session to the database.\n session.commit()","def load_json_schema(filename):\n relative_path = join('../schema', filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n base_path = dirname(absolute_path)\n base_uri = 'file://{}/'.format(base_path)\n\n with open(absolute_path) as schema_file:\n return jsonref.loads(\n schema_file.read(), base_uri=base_uri, jsonschema=True)","def convert_json_to_flatbuffer_binary(json, schema, out_dir):\n command = [FLATC, '-o', out_dir, '-b', schema, json]\n run_subprocess(command)","def _load_data_from_file(self, input_file_path):\n with FileOrBufferHandler(input_file_path, 'r', \n encoding=self.file_encoding) as input_file:\n try:\n data = json.load(input_file)\n except (json.JSONDecodeError, UnicodeDecodeError):\n input_file.seek(0)\n data = data_utils.read_json(\n data_generator=input_file,\n selected_columns=self.selected_keys,\n read_in_string=False\n )\n return data","def load_schema(self, schema_file):\n with open(schema_file) as fp:\n for line in io.lines_in(fp):\n parts = line.strip().split('\\t')\n if len(parts) != 3:\n raise ValueError('invalid type declaration %r' % line.strip())\n self.declare_relation(parts[0], parts[1], parts[2])","def transform_file(input_file_path: str, output_file_path: str):\n\n # Open json\n with open(input_file_path, mode=\"r\") as in_file:\n input_data = json.load(in_file)\n\n # Transform and write\n with jsonlines.open(output_file_path, mode=\"w\", compact=True) as out_file:\n for item in input_data[\"items\"]:\n out_file.write(transform_item(item))","def parse(json_string):\n try:\n json_data = json.loads(json_string)\n except Exception as exn:\n raise SchemaParseException(\n 'Error parsing schema from JSON: %r. '\n 'Error message: %r.'\n % (json_string, exn))\n\n # Initialize the names object\n names = Names()\n\n # construct the Avro Schema object\n return schema_from_json_data(json_data, names)","def get_inputs_from_file(filename=\"\"):\n import json\n\n with open(filename) as input_text:\n json_obj = json.load(input_text)\n return json_obj","def json_input():\r\n with open (FILE_INPUT,'rb') as file:\r\n data = json.load(file)\r\n return data['input_data'][0]","def intermediary_to_schema(tables, relationships, output):\n dot_file = _intermediary_to_dot(tables, relationships)\n #graph = AGraph()\n #graph = graph.from_string(dot_file)\n extension = output.split('.')[-1]\n #graph.draw(path=output, prog='dot', format=extension)\n #Source.from_file(filename, engine='dot', format=extension)\n return Source(dot_file, engine='dot', format=extension)","def populate_from_json(db: Session, model: DatabaseModel, json_file: str):\n data_exists = db.query(model).first()\n if data_exists:\n return\n with open(json_file, \"r\") as file:\n data = json.loads(file.read())\n for obj in data:\n db.add(model(**obj))\n db.commit()","def parse_and_format(file_in_path: str, file_out_path: str) -> None:\n\n with open(file_in_path) as input:\n payload = json.load(input)\n\n records = [\"# Data is in the format:\",\n \"# kem_id,kdf_id,aead_id,info,skRm,skEm,pkRm,pkEm,exporter_context,L,exported_value\"]\n\n for key in payload:\n # Skip these to test only capabilities exposed by BoringSSL\n if (key[\"mode\"] != MODE_BASE or\n key[\"kem_id\"] != KEM_DHKEM_X25519_SHA256 or\n key[\"kdf_id\"] != KDF_HKDF_SHA256 or\n key[\"aead_id\"] == AEAD_EXPORT_ONLY):\n continue\n\n for exportKey in key[\"exports\"]:\n records.append(\"{},{},{},{},{},{},{},{},{},{},{}\"\n .format(str(key[\"kem_id\"]),\n str(key[\"kdf_id\"]),\n str(key[\"aead_id\"]),\n str(key[\"info\"]),\n str(key[\"skRm\"]),\n str(key[\"skEm\"]),\n str(key[\"pkRm\"]),\n str(key[\"pkEm\"]),\n str(exportKey[\"exporter_context\"]),\n str(exportKey[\"L\"]),\n str(exportKey[\"exported_value\"])))\n\n\n with open(file_out_path, \"w\") as output:\n output.write(\"\\n\".join(records))","def jsons_to_table(dir_jsons, dir_out, name, format='html'):\n # sanity of paths\n dir_out = sanity_util.safe_dir_path(dir_path=dir_out)\n file_name = sanity_util.unique_file_name(dir=dir_out, fn=name, suffix='.{}'.format(format))\n # reading JSON files\n p_files = sorted([os.path.join(dir_jsons, p_json) for p_json in os.listdir(dir_jsons)])\n table = defaultdict(list)\n keys = set()\n for p_f in p_files:\n if p_f.lower().endswith('.json'):\n with open(p_f, 'r') as f_json:\n el = json.load(f_json)\n for k in el.keys():\n keys.add(k)\n for p_f in p_files:\n if p_f.lower().endswith('.json'):\n with open(p_f, 'r') as f_json:\n el = json.load(f_json)\n for k in el.keys():\n table[k].append(el[k])\n for k in keys.difference(set(el.keys())):\n table[k].append(None)\n # DataFrame conversion\n df = pd.DataFrame.from_dict(table)\n # writing HTML table\n if format == 'html':\n table_str = df.to_html()\n else:\n table_str = df.to_latex()\n table_str += '<script type=\"text/javascript\" src=\"stylize.js\"></script>'\n stylize_js = js_stylize()\n with open(os.path.join(dir_out, 'stylize.js'), 'w') as f_js:\n f_js.write(stylize_js)\n with open(file_name, 'w') as f_out:\n f_out.write(table_str)","def decide_schema(self, json_data):\n pass","def decide_schema(self, json_data):\n pass","def _read_json(cls, input_file):\n with open(input_file) as f:\n return json.load(f)","def _read_json(cls, input_file):\n with open(input_file) as f:\n return json.load(f)","def all_to_intermediary(filename_or_input, schema=None):\n # Try to convert from the name of the class\n input_class_name = filename_or_input.__class__.__name__\n try:\n this_to_intermediary = switch_input_class_to_method[input_class_name]\n tables, relationships = this_to_intermediary(filename_or_input)\n return tables, relationships\n except KeyError:\n pass\n\n # try to read markdown file.\n if isinstance(filename_or_input, basestring):\n if filename_or_input.split('.')[-1] == 'er':\n return markdown_file_to_intermediary(filename_or_input)\n\n # try to read a markdown in a string\n if not isinstance(filename_or_input, basestring):\n if all(isinstance(e, basestring) for e in filename_or_input):\n return line_iterator_to_intermediary(filename_or_input)\n\n # try to read DB URI.\n try:\n make_url(filename_or_input)\n return database_to_intermediary(filename_or_input, schema=schema)\n except ArgumentError:\n pass\n\n msg = 'Cannot process filename_or_input {}'.format(input_class_name)\n raise ValueError(msg)","def __csv_schema_generator(file):\n try:\n # Parses the first line of the file to get all the headers.\n metadata = str(file.readline().decode('utf-8')).strip().split(',')\n # Will be further implemented in phase 3.\n return SchemaGenerator.__build_schema(metadata)\n except Exception as e:\n logging.error('Failed to parse csv file into schema: ' + str(e))\n raise FailedCreatingSchemaException(\"Failed to create schema from csv file.\")","def schema_load(filename):\n print(uc.schema_load(filename))","def read_json_schema(schema_file_path):\n with open(schema_file_path) as f:\n schema = json.load(f)\n return schema","def _read_json(cls, input_file):\n with open(input_file, 'rb') as f:\n return json.load(f)","def _read_json(cls, input_file):\n with open(input_file, 'rb') as f:\n return json.load(f)","def _read_data(cls, input_file): # 这里是对文件的处理\r\n with open(input_file, encoding='utf-8') as f:\r\n lines = []\r\n\r\n for line in f:\r\n line = json.loads(line)\r\n words = ' '.join(list(line['natural']))\r\n labels = ' '.join(line['tag_seq'])\r\n poss = line['pos_seq']\r\n dps = line['dp_seq']\r\n head = line['head_seq']\r\n lines.append([labels, words, poss, dps, head])\r\n\r\n return lines","def from_json_file(cls, json_file):\n with tf.io.gfile.GFile(json_file, \"r\") as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def load_from_json(self, json_fp: str):\n # TODO:\n pass","def from_json_file(cls, json_file):\n with tf.io.gfile.GFile(json_file, \"r\") as reader:\n text = reader.read()\n return cls(**json.loads(text))","def from_json(self, file_path):\n with open(file_path) as file:\n jsonstr = file.read()\n handler_dict = json.loads(jsonstr)\n self.from_dict(handler_dict)","def import_schemas_from_file():\n with open('./tblSchemas') as schemas_file:\n schemas = {}\n for line in schemas_file:\n line = line.split()\n if len(line) == 0: continue\n if line[0] == 'tblname':\n tbl_name = line[1]\n schemas[tbl_name] = []\n else:\n schemas[tbl_name].append(line)\n return schemas","def get_schema():\n if not os.path.isfile(_schema_file):\n create_schema()\n with open(_schema_file, 'r') as fd:\n out = decode_json(fd)\n return out","def convert_schema(bco, filename, mapping_dict):\n for item in mapping_dict['to_swap']:\n value_list = mapping_dict['to_swap'][item]\n for i in range(0, len(value_list)):\n rename_dict_key_HELPER(bco, value_list[i]['index'],\n value_list[i]['value']) # Change key name\n\n for item in mapping_dict['to_delete']:\n value_list = mapping_dict['to_delete'][item]\n for i in range(0, len(value_list)):\n delete_key_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # delete key\n\n for item in mapping_dict['to_add']:\n value_list = mapping_dict['to_add'][item]\n for i in range(0, len(value_list)):\n set_key_in_dict_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # add key\n\n new_bco = bco\n try:\n new_bco['provenance_domain'][\n 'modified'] = datetime.now().isoformat() # change date to current\n\n temp_bco = dict(new_bco)\n del temp_bco['object_id'], temp_bco['etag'], temp_bco['spec_version']\n\n new_bco['spec_version'] = \"https://w3id.org/ieee/ieee-2791-schema/2791object.json\"\n new_bco[\"etag\"] = sha256(json.dumps(temp_bco).encode('utf-8')).hexdigest()\n except KeyError: # Vital field was missing, will be caught by final error checker\n pass\n file = open(filename, \"w\")\n json.dump(new_bco, file, indent=4)","def test_json():\n schemas = {\n 'schema-languages': 'bible/languages.json',\n 'schema-book-metadata': 'bible/book-metadata.json',\n 'schema-bible': 'bible/bible-*.json'\n }\n for schema_name, data_path_glob in schemas.items():\n schema_path = 'schemas/{}.json'.format(schema_name)\n with open(schema_path) as schema_file:\n schema = json.load(schema_file)\n data_paths = glob.iglob(data_path_glob)\n for data_path in data_paths:\n with open(data_path) as data_file:\n data = json.load(data_file)\n yield jsonschema.validate, data, schema","def _load_schema(self, json_schema):\n # use jsonrefs to resolve all $refs in json\n data = jsonref.loads(json.dumps(json_schema))\n return self.__initialise_template(data)","def test_read_json_schema():\n json_schema = os.path.join(TEST_DATA_PATH, 'example_schema.json')\n schema_tree = schema.load_schema(json_schema, resolve_references=True)\n schema.check_schema(schema_tree)","def get_schema(filename: str) -> dict:\n return _load_json_schema(filename)","def _import(format, input, config):\n if input:\n with open(input, 'rb') as f:\n data = f.read()\n else:\n data = sys.stdin.read()\n\n dataset = tablib.Dataset()\n setattr(dataset, format, data)\n\n _add_changelogs(config, dataset.dict)","def read_json(self, filename, multi_line=False, schema=None):\n self.logger.info(\"# Reading a JSON file \" + filename)\n sql_context = SQLContext(self.spark)\n df = None\n if schema is None and multi_line == False:\n df = sql_context.read.json(filename)\n elif multi_line:\n df = sql_context.read.json(filename, multiLine=multi_line)\n elif schema is not None:\n df = sql_context.read.json(filename, schema=schema)\n return df","def _load_json_schema(filename):\n\n relative_path = join(\"schemas\", filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n base_path = dirname(absolute_path)\n base_uri = 'file://{}/'.format(base_path)\n\n print(f\"base uri {base_uri}\")\n print(f\"base path {base_path}\")\n print(f\"relative_path {relative_path}\")\n print(f\"absolute_path {absolute_path}\")\n\n with open(absolute_path) as schema_file:\n return jsonref.loads(schema_file.read(), base_uri=base_uri, jsonschema=True)","def readjamschema(schema):\n raise NotImplementedError(msg)","def load(file_name):\n with open(file_name, newline='') as f:\n reader = csv.reader(f)\n data = list(reader)\n\n schema = [x.strip() for x in data[0]]\n table = [[int(el) for el in row] for row in data[1:]]\n\n return schema, table","def get_schema(path):\n with open(path, 'r') as f:\n return json.load(f)","def test_schema_invalid_json(self):\n schema_0_input = schema_nested_2_invalid_JSON\n\n # if you uncomment this line:\n # schema_0_input = schema_nested_2\n # this will fail the test: Failed: DID NOT RAISE <class 'simplejson.scanner.JSONDecodeError'>\n # because this is a valid schema\n\n with pytest.raises(simplejson.scanner.JSONDecodeError):\n msg = singer.parse_message(schema_0_input)","def create_table_from_file():\n\n full_path = os.getcwd()\n file_name = full_path + \"/inventory/inventory.csv\"\n\n if os.path.exists(file_name):\n table = data_manager.get_table_from_file(file_name)\n\n else:\n ui.print_error_message(\"There is no file to read!\")\n table = []\n\n return table","def tsv_to_json(tsv_file, json_file):\n import csv\n import json\n\n try:\n with open(tsv_file, 'r') as tsvFile:\n file_reader = csv.DictReader(tsvFile, dialect='excel-tab')\n row_list = list(file_reader)\n with open(json_file, 'w+') as jsonFile:\n jsonFile.write(json.dumps(row_list, indent=4))\n return 1\n except (ValueError, FileNotFoundError):\n return 0","async def _process_create_data(self, data: dict) -> dict:\n return self.SCHEMA(data)","def read_data(self):\n if self._file.is_file():\n try:\n self._data = read_json_file(self._file)\n except (OSError, json.JSONDecodeError):\n _LOGGER.warning(\"Can't read %s\", self._file)\n self._data = {}\n\n # Validate\n try:\n self._data = self._schema(self._data)\n except vol.Invalid as ex:\n _LOGGER.error(\"Can't parse %s: %s\",\n self._file, humanize_error(self._data, ex))\n\n # Reset data to default\n _LOGGER.warning(\"Reset %s to default\", self._file)\n self._data = self._schema({})","def _mashup_json_to_table(json_obj, col_config=None):\n\n dataTable = Table(masked=True)\n absCorr = None\n\n if not all(x in json_obj.keys() for x in ['fields', 'data']):\n raise KeyError(\"Missing required key(s) 'data' and/or 'fields.'\")\n\n for col, atype in [(x['name'], x['type']) for x in json_obj['fields']]:\n\n # Removing \"_selected_\" column\n if col == \"_selected_\":\n continue\n\n # reading the colum config if given\n ignoreValue = None\n if col_config:\n colProps = col_config.get(col, {})\n ignoreValue = colProps.get(\"ignoreValue\", None)\n\n # making type adjustments\n if atype == \"string\":\n atype = \"str\"\n ignoreValue = \"\" if (ignoreValue is None) else ignoreValue\n if atype == \"boolean\":\n atype = \"bool\"\n if atype == \"int\": # int arrays do not admit Non/nan vals\n atype = np.int64\n ignoreValue = -999 if (ignoreValue is None) else ignoreValue\n if atype == \"date\":\n atype = \"str\"\n ignoreValue = \"\" if (ignoreValue is None) else ignoreValue\n\n # Make the column list (don't assign final type yet or there will be errors)\n colData = np.array([x.get(col, ignoreValue) for x in json_obj['data']], dtype=object)\n if ignoreValue is not None:\n colData[np.where(np.equal(colData, None))] = ignoreValue\n\n # no consistant way to make the mask because np.equal fails on ''\n # and array == value fails with None\n if atype == 'str':\n colMask = (colData == ignoreValue)\n else:\n colMask = np.equal(colData, ignoreValue)\n\n # add the column\n dataTable.add_column(MaskedColumn(colData.astype(atype), name=col, mask=colMask))\n\n return dataTable","def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\n table_to_col_names_dict = {}\n table_to_col_names_dict[\"transaction_fabs\"] = TRANSACTION_FABS_COLUMNS\n table_to_col_names_dict[\"transaction_fpds\"] = TRANSACTION_FPDS_COLUMNS\n table_to_col_names_dict[\"transaction_normalized\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\n table_to_col_names_dict[\"awards\"] = list(AWARDS_COLUMNS)\n table_to_col_names_dict[\"financial_accounts_by_awards\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\n\n table_to_col_info_dict = {}\n for tbl_name, col_info in zip(\n (\"transaction_fabs\", \"transaction_fpds\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\n ):\n table_to_col_info_dict[tbl_name] = {}\n for col in col_info:\n table_to_col_info_dict[tbl_name][col.dest_name] = col\n\n # Make sure the table has been created first\n call_command(\n \"create_delta_table\",\n \"--destination-table\",\n table_name,\n \"--alt-db\",\n table_schema,\n \"--spark-s3-bucket\",\n s3_data_bucket,\n )\n\n if data:\n insert_sql = f\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\n\"\n row_strs = []\n for row in data:\n value_strs = []\n for col_name in table_to_col_names_dict[table_name]:\n value = row.get(col_name)\n if isinstance(value, (str, bytes)):\n # Quote strings for insertion into DB\n value_strs.append(f\"'{value}'\")\n elif isinstance(value, (date, datetime)):\n # Convert to string and quote\n value_strs.append(f\"\"\"'{value.isoformat()}'\"\"\")\n elif isinstance(value, bool):\n value_strs.append(str(value).upper())\n elif isinstance(value, (Sequence, Set)):\n # Assume \"sequences\" must be \"sequences\" of strings, so quote each item in the \"sequence\"\n value = [f\"'{item}'\" for item in value]\n value_strs.append(f\"ARRAY({', '.join(value)})\")\n elif value is None:\n col_info = table_to_col_info_dict.get(table_name)\n if (\n col_info\n and col_info[col_name].delta_type.upper() == \"BOOLEAN\"\n and not col_info[col_name].handling == \"leave_null\"\n ):\n # Convert None/NULL to false for boolean columns unless specified to leave the null\n value_strs.append(\"FALSE\")\n else:\n value_strs.append(\"NULL\")\n else:\n value_strs.append(str(value))\n\n row_strs.append(f\" ({', '.join(value_strs)})\")\n\n sql = \"\".join([insert_sql, \",\\n\".join(row_strs), \";\"])\n spark.sql(sql)","def convert_json_1(json):\n\n # TODO Add batch details to json format\n # TODO Get default direct entry batch details if not provided\n\n LOGGER.debug('convert json message:%s', json)\n direct_entry = {\n 'record_type': '1',\n 'reel_seq_num': '01',\n 'name_fin_inst': 'SUN',\n 'user_name': 'hello',\n 'user_num': '123456',\n 'file_desc': 'payroll',\n 'date_for_process': datetime.strptime(json['post_date'], '%Y-%m-%d').strftime('%d%m%y'),\n 'bsb_number': json['to_routing'],\n 'account_number': json['to_account'],\n 'indicator': ' ',\n 'tran_code': '13' if json['tran_type'] == 'db' else '53',\n 'amount': '{amount:010}'.format(amount=json['amount']), # $2.00\n 'account_title': json['to_name'],\n 'lodgement_ref': json['to_description'],\n 'trace_bsb_number': json['from_routing'],\n 'trace_account_number': json['from_account'],\n 'name_of_remitter': json['from_name'],\n 'withholding_tax_amount': '00000000',\n }\n\n return direct_entry","def create_datastructure_from_yaml_file(self):\n ## loading the YAML file\n try:\n with open(self.source) as f:\n hbaseSchemaDic = yaml.load(f) \n except:\n msg = \"Error: the HBase substructure could not be created. File %s could not be loaded. Please check the syntax of the '.yml' file.\" % self.source \n raise createDataStructureException(msg)\n status = \"failed\" \n\n try:\n c = Connection(host = self.host, port = int(self.port))\n tbls = c.tables()\n tbls = [str(t) for t in tbls]\n ## check that none of the tables already exists \n for t in hbaseSchemaDic.keys():\n if t in tbls:\n msg = \"Error: the table %s already exists. If you use starbase in python you can drop the table by using \\n>>> from starbase import Connection\\n>>> c = Connection()\\n>>> t = c.table(%s)\\n>>> t.drop()\" % (t,t) \n print(msg)\n status = \"failed\"\n raise createDataStructureException(msg)\n\n ## if none of the table(s) do(es) not exist, let's create them(it) \n for t in hbaseSchemaDic.keys():\n columnFamilies = hbaseSchemaDic[t]['columnFamilies'].keys()\n tC = c.table(t)\n tC.create(*columnFamilies)\n status = \"succeeded\"\n \n except:\n msg = \"Error: the HBase substructure could not be created. Please check your connection parameters or the syntax in your '.yml' file.\"\n raise createDataStructureException(msg)\n status = \"failed\"\n\n return(status)","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding=\"utf-8\") as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def read_json_breakdown(cls, fname):\n if not os.path.exists(fname):\n raise RuntimeError\n\n with open(fname, 'r') as data_file:\n return cls.fixup_from_json(data_file.read())","def _meta_json_to_database(self):\n\n sqlalchemy_metadata = MetaData() # this is unrelated to our meta.json\n meta_table = Table('meta', sqlalchemy_metadata,\n Column('meta', String))\n\n sqlalchemy_metadata.create_all(self.engine)\n json_string = json.dumps(self.meta)\n ins = meta_table.insert().values(meta=json_string)\n conn = self.engine.connect()\n conn.execute(\"DELETE FROM meta;\")\n conn.execute(ins)","def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\n try:\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\n self.columns = tabels_schema.migrationTable.MigrationColumns\n except Exception as err:\n logger.error(\"parse_migration_tables [error] -> %s\" % err)","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def _read_jsonl(cls, input_file):\n with open(input_file, 'rb') as f:\n return [json.loads(ln) for ln in f]","def _read_jsonl(cls, input_file):\n with open(input_file, 'rb') as f:\n return [json.loads(ln) for ln in f]","def create_deft_table_json_mappings():\n mappings = list()\n mappings.append(JsonColumnMapping(columnName=\"rownumber\", jsonPath=\"$.rownumber\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"rowguid\", jsonPath=\"$.rowguid\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xdouble\", jsonPath=\"$.xdouble\", cslDataType=\"real\"))\n mappings.append(JsonColumnMapping(columnName=\"xfloat\", jsonPath=\"$.xfloat\", cslDataType=\"real\"))\n mappings.append(JsonColumnMapping(columnName=\"xbool\", jsonPath=\"$.xbool\", cslDataType=\"bool\"))\n mappings.append(JsonColumnMapping(columnName=\"xint16\", jsonPath=\"$.xint16\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"xint32\", jsonPath=\"$.xint32\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"xint64\", jsonPath=\"$.xint64\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint8\", jsonPath=\"$.xuint8\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint16\", jsonPath=\"$.xuint16\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint32\", jsonPath=\"$.xuint32\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint64\", jsonPath=\"$.xuint64\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xdate\", jsonPath=\"$.xdate\", cslDataType=\"datetime\"))\n mappings.append(JsonColumnMapping(columnName=\"xsmalltext\", jsonPath=\"$.xsmalltext\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xtext\", jsonPath=\"$.xtext\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xnumberAsText\", jsonPath=\"$.xnumberAsText\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xtime\", jsonPath=\"$.xtime\", cslDataType=\"timespan\"))\n mappings.append(\n JsonColumnMapping(columnName=\"xtextWithNulls\", jsonPath=\"$.xtextWithNulls\", cslDataType=\"string\")\n )\n mappings.append(\n JsonColumnMapping(columnName=\"xdynamicWithNulls\", jsonPath=\"$.xdynamicWithNulls\", cslDataType=\"dynamic\")\n )\n return mappings","def create_schema(overwrite=False):\n if (not overwrite) and os.path.isfile(_schema_file):\n raise RuntimeError(\"Schema file already exists.\")\n schema = {\n 'title': 'obj',\n 'description': 'A mapping container for Obj 3D data.',\n 'type': 'object',\n 'required': ['vertices', 'faces'],\n 'definitions': {\n 'vertex': {\n 'description': 'Map describing a single vertex.',\n 'type': 'object', 'required': ['x', 'y', 'z'],\n 'additionalProperties': False,\n 'properties': {'x': {'type': _coord_type},\n 'y': {'type': _coord_type},\n 'z': {'type': _coord_type},\n 'red': {'type': _color_type},\n 'blue': {'type': _color_type},\n 'green': {'type': _color_type},\n 'w': {'type': _coord_type, 'default': 1.0}}},\n 'param': {\n 'description': 'Map describing a single parameter space point.',\n 'type': 'object', 'required': ['u', 'v'],\n 'additionalProperties': False,\n 'properties': {'u': {'type': _coord_type},\n 'v': {'type': _coord_type},\n 'w': {'type': _coord_type, 'default': 1.0}}},\n 'normal': {\n 'description': 'Map describing a single normal.',\n 'type': 'object', 'required': ['i', 'j', 'k'],\n 'additionalProperties': False,\n 'properties': {'i': {'type': _coord_type},\n 'j': {'type': _coord_type},\n 'k': {'type': _coord_type}}},\n 'texcoord': {\n 'description': 'Map describing a single texture vertex.',\n 'type': 'object', 'required': ['u'],\n 'additionalProperties': False,\n 'properties': {'u': {'type': _coord_type},\n 'v': {'type': _coord_type, 'default': 0.0},\n 'w': {'type': _coord_type, 'default': 0.0}}},\n 'point': {\n 'description': 'Array of vertex indices describing a set of points.',\n 'type': 'array', 'minItems': 1,\n 'items': {'type': _index_type}},\n 'line': {\n 'description': ('Array of vertex indices and texture indices '\n + 'describing a line.'),\n 'type': 'array', 'minItems': 2,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties':\n {'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type}}}},\n 'face': {\n 'description': ('Array of vertex, texture, and normal indices '\n + 'describing a face.'),\n 'type': 'array', 'minItems': 3,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties':\n {'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type},\n 'normal_index': {'type': _index_type}}}},\n 'curve': {\n 'description': 'Properties of describing a curve.',\n 'type': 'object', 'required': ['starting_param', 'ending_param',\n 'vertex_indices'],\n 'additionalProperties': False,\n 'properties': {\n 'starting_param': {'type': _coord_type},\n 'ending_param': {'type': _coord_type},\n 'vertex_indices': {\n 'type': 'array', 'minItems': 2,\n 'items': {'type': _index_type}}}},\n 'curve2D': {\n 'description': ('Array of parameter indices describine a 2D curve on '\n + 'a surface.'),\n 'type': 'array', 'minItems': 2,\n 'items': {'type': _index_type}},\n 'surface': {\n 'description': 'Properties describing a surface.',\n 'type': 'object', 'required': ['starting_param_u', 'ending_param_u',\n 'starting_param_v', 'ending_param_v',\n 'vertex_indices'],\n 'additionalProperties': False,\n 'properties': {\n 'starting_param_u': {'type': _coord_type},\n 'ending_param_u': {'type': _coord_type},\n 'starting_param_v': {'type': _coord_type},\n 'ending_param_v': {'type': _coord_type},\n 'vertex_indices': {\n 'type': 'array', 'minItems': 2,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties': {\n 'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type},\n 'normal_index': {'type': _index_type}}}}}}},\n 'properties': {\n 'material': {\n 'description': 'Name of the material to use.',\n 'type': ['unicode', 'string']},\n 'vertices': {\n 'description': 'Array of vertices.',\n 'type': 'array', 'items': {'$ref': '#/definitions/vertex'}},\n 'params': {\n 'description': 'Array of parameter coordinates.',\n 'type': 'array', 'items': {'$ref': '#/definitions/param'}},\n 'normals': {\n 'description': 'Array of normals.',\n 'type': 'array', 'items': {'$ref': '#/definitions/normal'}},\n 'texcoords': {\n 'description': 'Array of texture vertices.',\n 'type': 'array', 'items': {'$ref': '#/definitions/texcoord'}},\n 'points': {\n 'description': 'Array of points.',\n 'type': 'array', 'items': {'$ref': '#/definitions/point'}},\n 'lines': {\n 'description': 'Array of lines.',\n 'type': 'array', 'items': {'$ref': '#/definitions/line'}},\n 'faces': {\n 'description': 'Array of faces.',\n 'type': 'array', 'items': {'$ref': '#/definitions/face'}},\n 'curves': {\n 'description': 'Array of curves.',\n 'type': 'array', 'items': {'$ref': '#/definitions/curve'}},\n 'curve2Ds': {\n 'description': 'Array of curve2Ds.',\n 'type': 'array', 'items': {'$ref': '#/definitions/curve2D'}},\n 'surfaces': {\n 'description': 'Array of surfaces.',\n 'type': 'array', 'items': {'$ref': '#/definitions/surface'}}},\n 'dependencies': {\n 'lines': ['vertices'],\n 'faces': ['vertices'],\n 'curves': ['vertices'],\n 'curve2Ds': ['params'],\n 'surfaces': ['vertices']}}\n with open(_schema_file, 'w') as fd:\n encode_json(schema, fd, indent='\\t')","def generate_package_from_report_filepath(input_path, options = None):\n try:\n vt_file = open(input_path, 'r')\n vt_dict = json.load(vt_file)\n except:\n print('\\nError: Error in parsing input file. Please check to ensure that it is valid JSON.')\n return\n \n return vtpack.vt_report_to_maec_package(vt_dict, options)","def import_into_db(json_file):\n db = get_db()\n\n with current_app.open_resource(json_file) as f:\n reports = json.load(f)\n\n for element in reports[\"elements\"]:\n entry = (\n element[\"id\"],\n element[\"source\"],\n element[\"sourceIdentityId\"],\n element[\"state\"],\n element[\"created\"],\n element[\"reference\"][\"referenceId\"],\n element[\"reference\"][\"referenceType\"],\n element[\"payload\"][\"reportType\"],\n element[\"payload\"][\"reportId\"],\n element[\"payload\"][\"referenceResourceId\"],\n element[\"payload\"][\"referenceResourceType\"],\n element[\"payload\"][\"message\"],\n )\n db.execute(INSERT_INTO_REPORTS, entry)\n\n db.commit()","def json_schema(schema_file=None, output=\"-\"):\n schemas = read_yaml(schema_file)\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))","def from_json_file(cls, json_file):\n with open(json_file, 'r', encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))"],"string":"[\n \"def ReadSchemaFile(schema_file, bigquery_messages):\\n\\n if os.path.exists(schema_file):\\n with open(schema_file, mode='r') as f:\\n try:\\n def UpperOrNone(string):\\n return string and string.upper()\\n field_schemas = [\\n bigquery_messages.TableFieldSchema(\\n name=json_object.get('name'),\\n type=json_object.get('type').upper(),\\n mode=UpperOrNone(json_object.get('mode')))\\n for json_object in json.load(f)]\\n return bigquery_messages.TableSchema(fields=field_schemas)\\n except ValueError as e:\\n raise bigquery.SchemaError(\\n 'Error decoding JSON schema from file {0}: {1}.'.format(\\n schema_file, e))\\n else:\\n raise bigquery.SchemaError(\\n 'Error reading schema: File \\\"{0}\\\" was not found.'.format(schema_file))\",\n \"def _create_input_data(self):\\n SCHEMA = parse_table_schema_from_json(\\n '{\\\"fields\\\": [{\\\"name\\\": \\\"data\\\", \\\"type\\\": \\\"BYTES\\\"}]}')\\n\\n def format_record(record):\\n # Since Synthetic Source returns data as a dictionary, we should skip one\\n # of the part\\n import base64\\n return {'data': base64.b64encode(record[1])}\\n\\n with TestPipeline() as p:\\n ( # pylint: disable=expression-not-assigned\\n p\\n | 'Produce rows' >> Read(\\n SyntheticSource(self.parse_synthetic_source_options()))\\n | 'Format' >> Map(format_record)\\n | 'Write to BigQuery' >> WriteToBigQuery(\\n dataset=self.input_dataset,\\n table=self.input_table,\\n schema=SCHEMA,\\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\\n write_disposition=BigQueryDisposition.WRITE_EMPTY))\",\n \"def CreateTableFromFile(self, table_name, schema_path):\\n try:\\n schema_file = open(schema_path)\\n schema_json = schema_file.read()\\n schema_file.close()\\n except IOError, e:\\n raise SchemaError('Could not read file (%s):\\\\n%s' %\\n (schema_path, str(e)))\\n return self.CreateTableFromJson(table_name, schema_json)\",\n \"def read_json(file) -> Table:\\n try:\\n with Path(file).open(mode=\\\"r\\\", encoding=\\\"utf-8\\\") as __f:\\n res = load(__f)\\n print(str(res)[:100])\\n return res\\n except JSONDecodeError as err:\\n if err.msg != \\\"Extra data\\\":\\n raise\\n # Extra data, so try load line by line\\n res = []\\n for line in Path(file).read_text(encoding=\\\"utf-8\\\").splitlines():\\n try:\\n if line.strip() == \\\"\\\":\\n continue\\n res.append(loads(line))\\n except Exception:\\n ic(line)\\n ic(\\\"exc2\\\")\\n raise\\n return res\",\n \"def __json_schema_generator(file):\\n try:\\n data = json.load(file)\\n metadata_set = set()\\n try:\\n for datum in data['meta']['view']['columns']:\\n metadata_set.add(datum['name'])\\n except Exception as e:\\n metadata_set.clear()\\n for datum in data:\\n if isinstance(datum, str):\\n metadata_set.add(datum)\\n else:\\n for datum_property in datum:\\n metadata_set.add(str(datum_property))\\n\\n metadata_list = list(metadata_set)\\n # assumes list of objects with sparsse data\\n # OR\\n # for data_property in data[0]:\\n # metadata_list.append(data_property)\\n # assumes list of objects and that first entry has full list of properties\\n\\n return SchemaGenerator.__build_schema(metadata_list)\\n except Exception as e:\\n logging.error('Failed to parse json file into schema: ' + str(e))\\n raise FailedCreatingSchemaException(\\\"Failed to create schema from json file.\\\")\",\n \"def CreateTableFromJson(self, table_name, schema_json):\\n try:\\n schema = json.JSONDecoder().decode(schema_json)\\n except ValueError, e:\\n raise SchemaError('Could not parse fields:\\\\n%s\\\\n%s' %\\n (schema_json, str(e)))\\n\\n conn = self._Connect()\\n result = conn.Call(\\n dict(method='bigquery.tables.insert',\\n collection='tables',\\n operation=bq.REST.INSERT,\\n params=dict(name=table_name, fields=schema)))\\n return result\",\n \"def ReadSchema(schema, bigquery_messages):\\n\\n return bigquery_messages.TableSchema(\\n fields=[\\n _TableFieldSchemaForEntry(entry, bigquery_messages)\\n for entry in schema.split(',')])\",\n \"def insert_data(table, jsonfile):\\n with open(jsonfile) as infile:\\n data = json.load(infile)\\n table_models_map[table]['insert'](data)\",\n \"def generate_wc_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'word', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'percent', 'type': 'FLOAT', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def main(input_json, output_markdown):\\n parser = Parser()\\n output_md = parser.parse_schema(json.load(input_json))\\n output_markdown.writelines(output_md)\\n click.secho(\\\"✔ Successfully parsed schema!\\\", bold=True, fg=\\\"green\\\")\",\n \"def _convert(self, fn, suffix='json', path='jsonschema', name=None,\\n root_class_name=None, data_files=[], target_class=None):\\n ie = JsonSchemaImportEngine()\\n d = os.path.join(INPUT_DIR, path)\\n schema = ie.load(os.path.join(d, f'{fn}.{suffix}'), name=name, format=suffix, root_class_name=root_class_name)\\n model_path = os.path.join(OUTPUT_DIR, f'{fn}.yaml')\\n write_schema(schema, model_path)\\n roundtrip_path = os.path.join(OUTPUT_DIR, f'{fn}.roundtrip.json')\\n with open(roundtrip_path, 'w') as stream:\\n stream.write(JsonSchemaGenerator(model_path).serialize())\\n python_path = os.path.join(OUTPUT_DIR, f'{fn}.py')\\n with open(python_path, 'w') as stream:\\n stream.write(PythonGenerator(model_path).serialize())\\n compile_python(python_path)\\n # TODO: test data_files\\n return schema\",\n \"def load_schema(filename):\\n with open(filename) as f:\\n schema = json.load(f)\\n\\n return schema\",\n \"def test_convert_json():\\n schema = pa.schema([\\n pa.field(\\\"foo\\\", pa.int32()),\\n pa.field(\\\"bar\\\", pa.int64())\\n ])\\n\\n input_path = \\\"{}/tests/fixtures/simple_json.txt\\\".format(os.getcwd())\\n expected_file = \\\"{}/tests/fixtures/simple.parquet\\\".format(os.getcwd())\\n with tempfile.NamedTemporaryFile() as f:\\n output_file = f.name\\n client.convert_json(input_path, output_file, schema)\\n output = pq.ParquetFile(output_file)\\n expected = pq.ParquetFile(expected_file)\\n assert output.metadata.num_columns == expected.metadata.num_columns\\n assert output.metadata.num_rows == expected.metadata.num_rows\\n assert output.schema.equals(expected.schema)\\n assert output.read_row_group(0).to_pydict() == expected.read_row_group(0).to_pydict()\",\n \"def from_json_file(cls, json_file:str):\\n with open(json_file) as file:\\n data = json.load(file)\\n validate(data, schema)\\n instance = cls.from_dict(data)\\n return instance\",\n \"def process_data(data):\\n # Table Name from Json file\\n table_name = data['table_name']\\n\\n # No of Column\\n column_count = data['column_count']\\n\\n # No of Row\\n row_count = data['row_count']\\n\\n # Table columns schema from Json file\\n column_properties = data['column_properties']\\n\\n # Get the row row_properties\\n row_properties = data['row_properties']\\n return table_name, column_count, row_count, column_properties, row_properties\",\n \"def deduce_schema(self, input_data, *, schema_map=None):\\n\\n if self.input_format == 'csv':\\n if self.csv_dialect:\\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\\n else:\\n reader = csv.DictReader(input_data)\\n elif self.input_format == 'json' or self.input_format is None:\\n reader = json_reader(input_data)\\n elif self.input_format == 'dict':\\n reader = input_data\\n else:\\n raise Exception(f\\\"Unknown input_format '{self.input_format}'\\\")\\n\\n if schema_map is None:\\n schema_map = OrderedDict()\\n\\n try:\\n for json_object in reader:\\n\\n # Print a progress message periodically.\\n self.line_number += 1\\n if self.line_number % self.debugging_interval == 0:\\n logging.info(f'Processing line {self.line_number}')\\n\\n # Deduce the schema from this given data record.\\n if isinstance(json_object, dict):\\n self.deduce_schema_for_record(\\n json_object=json_object,\\n schema_map=schema_map,\\n )\\n elif isinstance(json_object, Exception):\\n self.log_error(\\n f'Record could not be parsed: Exception: {json_object}'\\n )\\n if not self.ignore_invalid_lines:\\n raise json_object\\n else:\\n self.log_error(\\n 'Record should be a JSON Object '\\n f'but was a {type(json_object)}'\\n )\\n if not self.ignore_invalid_lines:\\n raise Exception(f'Record must be a JSON Object '\\n f'but was a {type(json_object)}')\\n finally:\\n logging.info(f'Processed {self.line_number} lines')\\n\\n return schema_map, self.error_logs\",\n \"def _create_schema(self, cypher_file):\\n if len(self.graph.nodes) > 0:\\n msg = \\\"Cypher file specified but the graph is not empty. Aborting.\\\"\\n raise ValueError(msg)\\n cyp = open(cypher_file, 'r').read()\\n self.graph.run(cyp)\",\n \"def BqTableDataFileProcessor(file_arg):\\n data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')\\n insert_row_type = data_insert_request_type.RowsValueListEntry\\n data_row_type = GetApiMessage('JsonObject')\\n\\n try:\\n data_json = yaml.load(file_arg)\\n\\n if not data_json or not isinstance(data_json, list):\\n raise TableDataFileError(\\n 'Error parsing data file: no data records defined in file')\\n\\n rows = []\\n for row in data_json:\\n rows.append(insert_row_type(json=encoding.DictToMessage(\\n row, data_row_type)))\\n\\n return rows\\n except yaml.YAMLParseError as ype:\\n raise TableDataFileError('Error parsing data file [{}]'.format(ype))\",\n \"def _load_json_schema(filename):\\n\\n relative_path = join('schemas', filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n with open(absolute_path) as schema_file:\\n return json.loads(schema_file.read())\",\n \"def _load_json_schema(filename: str):\\n relative_path = path.join('schemas', filename)\\n absolute_path = path.join(path.dirname(__file__), relative_path)\\n\\n with open(absolute_path, 'r', encoding='utf-8') as schema_file:\\n schema = json.loads(schema_file.read())\\n\\n return schema\",\n \"def create_json_table(cur, country_json, body_json):\\n print(\\\"Creating table from JSON file\\\")\\n cur.execute('CREATE TABLE IF NOT EXISTS state_json(id INTEGER PRIMARY KEY, state TEXT, album TEXT)')\\n for idx, album in enumerate(country_json[body_json['state']]):\\n cur.execute('INSERT INTO state_json VALUES (\\\"%s\\\", \\\"%s\\\", \\\"%s\\\")' % (idx, body_json['state'], album))\",\n \"def run(\\n self,\\n input_file=sys.stdin,\\n output_file=sys.stdout,\\n schema_map=None,\\n ):\\n schema_map, error_logs = self.deduce_schema(\\n input_file, schema_map=schema_map\\n )\\n\\n for error in error_logs:\\n logging.info(\\n f\\\"Problem on line {error['line_number']}: {error['msg']}\\\"\\n )\\n\\n if self.debugging_map:\\n json.dump(schema_map, output_file, indent=2)\\n print(file=output_file)\\n else:\\n schema = self.flatten_schema(schema_map)\\n json.dump(schema, output_file, indent=2)\\n print(file=output_file)\",\n \"def create_db(db, schema_json):\\n with open(schema_json) as of:\\n schema = json.load(of, object_pairs_hook=OrderedDict)\\n # OrderedDict so that tables are created in the order specified,\\n # allowing foreign keys to reference previously defined tables\\n\\n for table_name, columns in schema.items():\\n col_types = columns.items() # dict -> tuple\\n make_table(db, table_name, col_types)\",\n \"def main(event, context):\\n # pylint: enable=unused-argument\\n data = decode(event[\\\"data\\\"])\\n to_table([data], PROJECT, DATASET, TABLE)\",\n \"def parse_raw(sqlContext, input, user):\\n df = sqlContext.read.json(input + \\\"/\\\" + user + \\\"/\\\" + user + \\\".json\\\", multiLine=True)\\n return df\",\n \"def json_to_thrift(json_str, root_thrift_class):\\r\\n return json.loads(json_str, cls=ThriftJSONDecoder, root_thrift_class=root_thrift_class)\",\n \"def extract_data(filename: str, schema_filename: str) -> DataFrame:\\n data = []\\n try:\\n with open(schema_filename) as f:\\n schema = json.load(f)\\n with open(filename) as f:\\n for line in f:\\n json_doc = json.loads(line)\\n if is_valid_data(json_doc, schema):\\n data.append(json_doc)\\n except ValueError as e:\\n log.error(f\\\"Error parsing json: {e}\\\")\\n except FileNotFoundError as e:\\n log.error(f\\\"File not found error: {e}\\\")\\n raise e\\n except Exception as e:\\n log.error(e)\\n raise e\\n return DataFrame(data)\",\n \"def _schema_write(self, table: TableSchema) -> None:\\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\\n json.dump(table, f, indent=True)\",\n \"def read_json(self, inputfile):\\n transtransfile = json.load(inputfile)\\n self.language = transfile['lang']\\n self.translations = transfile['strings']\",\n \"def generate_cooccur_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'w1', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'w2', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\\n {'name': 'log_weight', 'type': 'FLOAT', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def generate_url_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def generate_bq_schema(self, file_name, schema_file_name=None):\\n if not schema_file_name:\\n schema_file_name = f'{self.directory}/schema_temp.json'\\n os.system(f\\\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\\\")\\n\\n schema = open(schema_file_name, 'r').read()\\n\\n os.remove(schema_file_name)\\n\\n return json.loads(schema)\",\n \"def generate_data(self):\\n print(\\\"generate_data - init\\\")\\n with open(self.input_file, \\\"r\\\") as f:\\n\\n # read JSON data from input file\\n data = json.loads(f.read())\\n\\n for idx, row in enumerate(data): \\n # serialize Python dict to string\\n msg = self.serialize_json(row)\\n #print(f\\\"Linha: {row}\\\")\\n self.send(self.topic, msg)\\n self.flush()\\n #print(\\\"Sleeping\\\")\\n time.sleep(1)\",\n \"def from_dict(cls, dikt) -> 'SourceSchema':\\n return util.deserialize_model(dikt, cls)\",\n \"def test_test_body_with_file_schema(self):\\n pass\",\n \"def _load_fixture(filename):\\n\\n # Read the binary data into text\\n with open(filename, 'rb') as stream:\\n content = stream.read().decode('utf-8')\\n\\n # Decode the data as JSON\\n data = json.loads(content)\\n\\n # Instantiate a session.\\n session = Session()\\n\\n # Iterate through the entries to add them one by one.\\n for item in data:\\n # Resolve model from the table reference.\\n table = Base.metadata.tables[item['model'].split('.')[-1]]\\n\\n # Add the primary key.\\n item['fields']['id'] = item['pk']\\n\\n # Add a new row.\\n session.connection().execute(table.insert().values(**item['fields']))\\n\\n # Commit the session to the database.\\n session.commit()\",\n \"def load_json_schema(filename):\\n relative_path = join('../schema', filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n base_path = dirname(absolute_path)\\n base_uri = 'file://{}/'.format(base_path)\\n\\n with open(absolute_path) as schema_file:\\n return jsonref.loads(\\n schema_file.read(), base_uri=base_uri, jsonschema=True)\",\n \"def convert_json_to_flatbuffer_binary(json, schema, out_dir):\\n command = [FLATC, '-o', out_dir, '-b', schema, json]\\n run_subprocess(command)\",\n \"def _load_data_from_file(self, input_file_path):\\n with FileOrBufferHandler(input_file_path, 'r', \\n encoding=self.file_encoding) as input_file:\\n try:\\n data = json.load(input_file)\\n except (json.JSONDecodeError, UnicodeDecodeError):\\n input_file.seek(0)\\n data = data_utils.read_json(\\n data_generator=input_file,\\n selected_columns=self.selected_keys,\\n read_in_string=False\\n )\\n return data\",\n \"def load_schema(self, schema_file):\\n with open(schema_file) as fp:\\n for line in io.lines_in(fp):\\n parts = line.strip().split('\\\\t')\\n if len(parts) != 3:\\n raise ValueError('invalid type declaration %r' % line.strip())\\n self.declare_relation(parts[0], parts[1], parts[2])\",\n \"def transform_file(input_file_path: str, output_file_path: str):\\n\\n # Open json\\n with open(input_file_path, mode=\\\"r\\\") as in_file:\\n input_data = json.load(in_file)\\n\\n # Transform and write\\n with jsonlines.open(output_file_path, mode=\\\"w\\\", compact=True) as out_file:\\n for item in input_data[\\\"items\\\"]:\\n out_file.write(transform_item(item))\",\n \"def parse(json_string):\\n try:\\n json_data = json.loads(json_string)\\n except Exception as exn:\\n raise SchemaParseException(\\n 'Error parsing schema from JSON: %r. '\\n 'Error message: %r.'\\n % (json_string, exn))\\n\\n # Initialize the names object\\n names = Names()\\n\\n # construct the Avro Schema object\\n return schema_from_json_data(json_data, names)\",\n \"def get_inputs_from_file(filename=\\\"\\\"):\\n import json\\n\\n with open(filename) as input_text:\\n json_obj = json.load(input_text)\\n return json_obj\",\n \"def json_input():\\r\\n with open (FILE_INPUT,'rb') as file:\\r\\n data = json.load(file)\\r\\n return data['input_data'][0]\",\n \"def intermediary_to_schema(tables, relationships, output):\\n dot_file = _intermediary_to_dot(tables, relationships)\\n #graph = AGraph()\\n #graph = graph.from_string(dot_file)\\n extension = output.split('.')[-1]\\n #graph.draw(path=output, prog='dot', format=extension)\\n #Source.from_file(filename, engine='dot', format=extension)\\n return Source(dot_file, engine='dot', format=extension)\",\n \"def populate_from_json(db: Session, model: DatabaseModel, json_file: str):\\n data_exists = db.query(model).first()\\n if data_exists:\\n return\\n with open(json_file, \\\"r\\\") as file:\\n data = json.loads(file.read())\\n for obj in data:\\n db.add(model(**obj))\\n db.commit()\",\n \"def parse_and_format(file_in_path: str, file_out_path: str) -> None:\\n\\n with open(file_in_path) as input:\\n payload = json.load(input)\\n\\n records = [\\\"# Data is in the format:\\\",\\n \\\"# kem_id,kdf_id,aead_id,info,skRm,skEm,pkRm,pkEm,exporter_context,L,exported_value\\\"]\\n\\n for key in payload:\\n # Skip these to test only capabilities exposed by BoringSSL\\n if (key[\\\"mode\\\"] != MODE_BASE or\\n key[\\\"kem_id\\\"] != KEM_DHKEM_X25519_SHA256 or\\n key[\\\"kdf_id\\\"] != KDF_HKDF_SHA256 or\\n key[\\\"aead_id\\\"] == AEAD_EXPORT_ONLY):\\n continue\\n\\n for exportKey in key[\\\"exports\\\"]:\\n records.append(\\\"{},{},{},{},{},{},{},{},{},{},{}\\\"\\n .format(str(key[\\\"kem_id\\\"]),\\n str(key[\\\"kdf_id\\\"]),\\n str(key[\\\"aead_id\\\"]),\\n str(key[\\\"info\\\"]),\\n str(key[\\\"skRm\\\"]),\\n str(key[\\\"skEm\\\"]),\\n str(key[\\\"pkRm\\\"]),\\n str(key[\\\"pkEm\\\"]),\\n str(exportKey[\\\"exporter_context\\\"]),\\n str(exportKey[\\\"L\\\"]),\\n str(exportKey[\\\"exported_value\\\"])))\\n\\n\\n with open(file_out_path, \\\"w\\\") as output:\\n output.write(\\\"\\\\n\\\".join(records))\",\n \"def jsons_to_table(dir_jsons, dir_out, name, format='html'):\\n # sanity of paths\\n dir_out = sanity_util.safe_dir_path(dir_path=dir_out)\\n file_name = sanity_util.unique_file_name(dir=dir_out, fn=name, suffix='.{}'.format(format))\\n # reading JSON files\\n p_files = sorted([os.path.join(dir_jsons, p_json) for p_json in os.listdir(dir_jsons)])\\n table = defaultdict(list)\\n keys = set()\\n for p_f in p_files:\\n if p_f.lower().endswith('.json'):\\n with open(p_f, 'r') as f_json:\\n el = json.load(f_json)\\n for k in el.keys():\\n keys.add(k)\\n for p_f in p_files:\\n if p_f.lower().endswith('.json'):\\n with open(p_f, 'r') as f_json:\\n el = json.load(f_json)\\n for k in el.keys():\\n table[k].append(el[k])\\n for k in keys.difference(set(el.keys())):\\n table[k].append(None)\\n # DataFrame conversion\\n df = pd.DataFrame.from_dict(table)\\n # writing HTML table\\n if format == 'html':\\n table_str = df.to_html()\\n else:\\n table_str = df.to_latex()\\n table_str += '<script type=\\\"text/javascript\\\" src=\\\"stylize.js\\\"></script>'\\n stylize_js = js_stylize()\\n with open(os.path.join(dir_out, 'stylize.js'), 'w') as f_js:\\n f_js.write(stylize_js)\\n with open(file_name, 'w') as f_out:\\n f_out.write(table_str)\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def _read_json(cls, input_file):\\n with open(input_file) as f:\\n return json.load(f)\",\n \"def _read_json(cls, input_file):\\n with open(input_file) as f:\\n return json.load(f)\",\n \"def all_to_intermediary(filename_or_input, schema=None):\\n # Try to convert from the name of the class\\n input_class_name = filename_or_input.__class__.__name__\\n try:\\n this_to_intermediary = switch_input_class_to_method[input_class_name]\\n tables, relationships = this_to_intermediary(filename_or_input)\\n return tables, relationships\\n except KeyError:\\n pass\\n\\n # try to read markdown file.\\n if isinstance(filename_or_input, basestring):\\n if filename_or_input.split('.')[-1] == 'er':\\n return markdown_file_to_intermediary(filename_or_input)\\n\\n # try to read a markdown in a string\\n if not isinstance(filename_or_input, basestring):\\n if all(isinstance(e, basestring) for e in filename_or_input):\\n return line_iterator_to_intermediary(filename_or_input)\\n\\n # try to read DB URI.\\n try:\\n make_url(filename_or_input)\\n return database_to_intermediary(filename_or_input, schema=schema)\\n except ArgumentError:\\n pass\\n\\n msg = 'Cannot process filename_or_input {}'.format(input_class_name)\\n raise ValueError(msg)\",\n \"def __csv_schema_generator(file):\\n try:\\n # Parses the first line of the file to get all the headers.\\n metadata = str(file.readline().decode('utf-8')).strip().split(',')\\n # Will be further implemented in phase 3.\\n return SchemaGenerator.__build_schema(metadata)\\n except Exception as e:\\n logging.error('Failed to parse csv file into schema: ' + str(e))\\n raise FailedCreatingSchemaException(\\\"Failed to create schema from csv file.\\\")\",\n \"def schema_load(filename):\\n print(uc.schema_load(filename))\",\n \"def read_json_schema(schema_file_path):\\n with open(schema_file_path) as f:\\n schema = json.load(f)\\n return schema\",\n \"def _read_json(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return json.load(f)\",\n \"def _read_json(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return json.load(f)\",\n \"def _read_data(cls, input_file): # 这里是对文件的处理\\r\\n with open(input_file, encoding='utf-8') as f:\\r\\n lines = []\\r\\n\\r\\n for line in f:\\r\\n line = json.loads(line)\\r\\n words = ' '.join(list(line['natural']))\\r\\n labels = ' '.join(line['tag_seq'])\\r\\n poss = line['pos_seq']\\r\\n dps = line['dp_seq']\\r\\n head = line['head_seq']\\r\\n lines.append([labels, words, poss, dps, head])\\r\\n\\r\\n return lines\",\n \"def from_json_file(cls, json_file):\\n with tf.io.gfile.GFile(json_file, \\\"r\\\") as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def load_from_json(self, json_fp: str):\\n # TODO:\\n pass\",\n \"def from_json_file(cls, json_file):\\n with tf.io.gfile.GFile(json_file, \\\"r\\\") as reader:\\n text = reader.read()\\n return cls(**json.loads(text))\",\n \"def from_json(self, file_path):\\n with open(file_path) as file:\\n jsonstr = file.read()\\n handler_dict = json.loads(jsonstr)\\n self.from_dict(handler_dict)\",\n \"def import_schemas_from_file():\\n with open('./tblSchemas') as schemas_file:\\n schemas = {}\\n for line in schemas_file:\\n line = line.split()\\n if len(line) == 0: continue\\n if line[0] == 'tblname':\\n tbl_name = line[1]\\n schemas[tbl_name] = []\\n else:\\n schemas[tbl_name].append(line)\\n return schemas\",\n \"def get_schema():\\n if not os.path.isfile(_schema_file):\\n create_schema()\\n with open(_schema_file, 'r') as fd:\\n out = decode_json(fd)\\n return out\",\n \"def convert_schema(bco, filename, mapping_dict):\\n for item in mapping_dict['to_swap']:\\n value_list = mapping_dict['to_swap'][item]\\n for i in range(0, len(value_list)):\\n rename_dict_key_HELPER(bco, value_list[i]['index'],\\n value_list[i]['value']) # Change key name\\n\\n for item in mapping_dict['to_delete']:\\n value_list = mapping_dict['to_delete'][item]\\n for i in range(0, len(value_list)):\\n delete_key_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # delete key\\n\\n for item in mapping_dict['to_add']:\\n value_list = mapping_dict['to_add'][item]\\n for i in range(0, len(value_list)):\\n set_key_in_dict_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # add key\\n\\n new_bco = bco\\n try:\\n new_bco['provenance_domain'][\\n 'modified'] = datetime.now().isoformat() # change date to current\\n\\n temp_bco = dict(new_bco)\\n del temp_bco['object_id'], temp_bco['etag'], temp_bco['spec_version']\\n\\n new_bco['spec_version'] = \\\"https://w3id.org/ieee/ieee-2791-schema/2791object.json\\\"\\n new_bco[\\\"etag\\\"] = sha256(json.dumps(temp_bco).encode('utf-8')).hexdigest()\\n except KeyError: # Vital field was missing, will be caught by final error checker\\n pass\\n file = open(filename, \\\"w\\\")\\n json.dump(new_bco, file, indent=4)\",\n \"def test_json():\\n schemas = {\\n 'schema-languages': 'bible/languages.json',\\n 'schema-book-metadata': 'bible/book-metadata.json',\\n 'schema-bible': 'bible/bible-*.json'\\n }\\n for schema_name, data_path_glob in schemas.items():\\n schema_path = 'schemas/{}.json'.format(schema_name)\\n with open(schema_path) as schema_file:\\n schema = json.load(schema_file)\\n data_paths = glob.iglob(data_path_glob)\\n for data_path in data_paths:\\n with open(data_path) as data_file:\\n data = json.load(data_file)\\n yield jsonschema.validate, data, schema\",\n \"def _load_schema(self, json_schema):\\n # use jsonrefs to resolve all $refs in json\\n data = jsonref.loads(json.dumps(json_schema))\\n return self.__initialise_template(data)\",\n \"def test_read_json_schema():\\n json_schema = os.path.join(TEST_DATA_PATH, 'example_schema.json')\\n schema_tree = schema.load_schema(json_schema, resolve_references=True)\\n schema.check_schema(schema_tree)\",\n \"def get_schema(filename: str) -> dict:\\n return _load_json_schema(filename)\",\n \"def _import(format, input, config):\\n if input:\\n with open(input, 'rb') as f:\\n data = f.read()\\n else:\\n data = sys.stdin.read()\\n\\n dataset = tablib.Dataset()\\n setattr(dataset, format, data)\\n\\n _add_changelogs(config, dataset.dict)\",\n \"def read_json(self, filename, multi_line=False, schema=None):\\n self.logger.info(\\\"# Reading a JSON file \\\" + filename)\\n sql_context = SQLContext(self.spark)\\n df = None\\n if schema is None and multi_line == False:\\n df = sql_context.read.json(filename)\\n elif multi_line:\\n df = sql_context.read.json(filename, multiLine=multi_line)\\n elif schema is not None:\\n df = sql_context.read.json(filename, schema=schema)\\n return df\",\n \"def _load_json_schema(filename):\\n\\n relative_path = join(\\\"schemas\\\", filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n base_path = dirname(absolute_path)\\n base_uri = 'file://{}/'.format(base_path)\\n\\n print(f\\\"base uri {base_uri}\\\")\\n print(f\\\"base path {base_path}\\\")\\n print(f\\\"relative_path {relative_path}\\\")\\n print(f\\\"absolute_path {absolute_path}\\\")\\n\\n with open(absolute_path) as schema_file:\\n return jsonref.loads(schema_file.read(), base_uri=base_uri, jsonschema=True)\",\n \"def readjamschema(schema):\\n raise NotImplementedError(msg)\",\n \"def load(file_name):\\n with open(file_name, newline='') as f:\\n reader = csv.reader(f)\\n data = list(reader)\\n\\n schema = [x.strip() for x in data[0]]\\n table = [[int(el) for el in row] for row in data[1:]]\\n\\n return schema, table\",\n \"def get_schema(path):\\n with open(path, 'r') as f:\\n return json.load(f)\",\n \"def test_schema_invalid_json(self):\\n schema_0_input = schema_nested_2_invalid_JSON\\n\\n # if you uncomment this line:\\n # schema_0_input = schema_nested_2\\n # this will fail the test: Failed: DID NOT RAISE <class 'simplejson.scanner.JSONDecodeError'>\\n # because this is a valid schema\\n\\n with pytest.raises(simplejson.scanner.JSONDecodeError):\\n msg = singer.parse_message(schema_0_input)\",\n \"def create_table_from_file():\\n\\n full_path = os.getcwd()\\n file_name = full_path + \\\"/inventory/inventory.csv\\\"\\n\\n if os.path.exists(file_name):\\n table = data_manager.get_table_from_file(file_name)\\n\\n else:\\n ui.print_error_message(\\\"There is no file to read!\\\")\\n table = []\\n\\n return table\",\n \"def tsv_to_json(tsv_file, json_file):\\n import csv\\n import json\\n\\n try:\\n with open(tsv_file, 'r') as tsvFile:\\n file_reader = csv.DictReader(tsvFile, dialect='excel-tab')\\n row_list = list(file_reader)\\n with open(json_file, 'w+') as jsonFile:\\n jsonFile.write(json.dumps(row_list, indent=4))\\n return 1\\n except (ValueError, FileNotFoundError):\\n return 0\",\n \"async def _process_create_data(self, data: dict) -> dict:\\n return self.SCHEMA(data)\",\n \"def read_data(self):\\n if self._file.is_file():\\n try:\\n self._data = read_json_file(self._file)\\n except (OSError, json.JSONDecodeError):\\n _LOGGER.warning(\\\"Can't read %s\\\", self._file)\\n self._data = {}\\n\\n # Validate\\n try:\\n self._data = self._schema(self._data)\\n except vol.Invalid as ex:\\n _LOGGER.error(\\\"Can't parse %s: %s\\\",\\n self._file, humanize_error(self._data, ex))\\n\\n # Reset data to default\\n _LOGGER.warning(\\\"Reset %s to default\\\", self._file)\\n self._data = self._schema({})\",\n \"def _mashup_json_to_table(json_obj, col_config=None):\\n\\n dataTable = Table(masked=True)\\n absCorr = None\\n\\n if not all(x in json_obj.keys() for x in ['fields', 'data']):\\n raise KeyError(\\\"Missing required key(s) 'data' and/or 'fields.'\\\")\\n\\n for col, atype in [(x['name'], x['type']) for x in json_obj['fields']]:\\n\\n # Removing \\\"_selected_\\\" column\\n if col == \\\"_selected_\\\":\\n continue\\n\\n # reading the colum config if given\\n ignoreValue = None\\n if col_config:\\n colProps = col_config.get(col, {})\\n ignoreValue = colProps.get(\\\"ignoreValue\\\", None)\\n\\n # making type adjustments\\n if atype == \\\"string\\\":\\n atype = \\\"str\\\"\\n ignoreValue = \\\"\\\" if (ignoreValue is None) else ignoreValue\\n if atype == \\\"boolean\\\":\\n atype = \\\"bool\\\"\\n if atype == \\\"int\\\": # int arrays do not admit Non/nan vals\\n atype = np.int64\\n ignoreValue = -999 if (ignoreValue is None) else ignoreValue\\n if atype == \\\"date\\\":\\n atype = \\\"str\\\"\\n ignoreValue = \\\"\\\" if (ignoreValue is None) else ignoreValue\\n\\n # Make the column list (don't assign final type yet or there will be errors)\\n colData = np.array([x.get(col, ignoreValue) for x in json_obj['data']], dtype=object)\\n if ignoreValue is not None:\\n colData[np.where(np.equal(colData, None))] = ignoreValue\\n\\n # no consistant way to make the mask because np.equal fails on ''\\n # and array == value fails with None\\n if atype == 'str':\\n colMask = (colData == ignoreValue)\\n else:\\n colMask = np.equal(colData, ignoreValue)\\n\\n # add the column\\n dataTable.add_column(MaskedColumn(colData.astype(atype), name=col, mask=colMask))\\n\\n return dataTable\",\n \"def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\\n table_to_col_names_dict = {}\\n table_to_col_names_dict[\\\"transaction_fabs\\\"] = TRANSACTION_FABS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_fpds\\\"] = TRANSACTION_FPDS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_normalized\\\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\\n table_to_col_names_dict[\\\"awards\\\"] = list(AWARDS_COLUMNS)\\n table_to_col_names_dict[\\\"financial_accounts_by_awards\\\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\\n\\n table_to_col_info_dict = {}\\n for tbl_name, col_info in zip(\\n (\\\"transaction_fabs\\\", \\\"transaction_fpds\\\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\\n ):\\n table_to_col_info_dict[tbl_name] = {}\\n for col in col_info:\\n table_to_col_info_dict[tbl_name][col.dest_name] = col\\n\\n # Make sure the table has been created first\\n call_command(\\n \\\"create_delta_table\\\",\\n \\\"--destination-table\\\",\\n table_name,\\n \\\"--alt-db\\\",\\n table_schema,\\n \\\"--spark-s3-bucket\\\",\\n s3_data_bucket,\\n )\\n\\n if data:\\n insert_sql = f\\\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\\\n\\\"\\n row_strs = []\\n for row in data:\\n value_strs = []\\n for col_name in table_to_col_names_dict[table_name]:\\n value = row.get(col_name)\\n if isinstance(value, (str, bytes)):\\n # Quote strings for insertion into DB\\n value_strs.append(f\\\"'{value}'\\\")\\n elif isinstance(value, (date, datetime)):\\n # Convert to string and quote\\n value_strs.append(f\\\"\\\"\\\"'{value.isoformat()}'\\\"\\\"\\\")\\n elif isinstance(value, bool):\\n value_strs.append(str(value).upper())\\n elif isinstance(value, (Sequence, Set)):\\n # Assume \\\"sequences\\\" must be \\\"sequences\\\" of strings, so quote each item in the \\\"sequence\\\"\\n value = [f\\\"'{item}'\\\" for item in value]\\n value_strs.append(f\\\"ARRAY({', '.join(value)})\\\")\\n elif value is None:\\n col_info = table_to_col_info_dict.get(table_name)\\n if (\\n col_info\\n and col_info[col_name].delta_type.upper() == \\\"BOOLEAN\\\"\\n and not col_info[col_name].handling == \\\"leave_null\\\"\\n ):\\n # Convert None/NULL to false for boolean columns unless specified to leave the null\\n value_strs.append(\\\"FALSE\\\")\\n else:\\n value_strs.append(\\\"NULL\\\")\\n else:\\n value_strs.append(str(value))\\n\\n row_strs.append(f\\\" ({', '.join(value_strs)})\\\")\\n\\n sql = \\\"\\\".join([insert_sql, \\\",\\\\n\\\".join(row_strs), \\\";\\\"])\\n spark.sql(sql)\",\n \"def convert_json_1(json):\\n\\n # TODO Add batch details to json format\\n # TODO Get default direct entry batch details if not provided\\n\\n LOGGER.debug('convert json message:%s', json)\\n direct_entry = {\\n 'record_type': '1',\\n 'reel_seq_num': '01',\\n 'name_fin_inst': 'SUN',\\n 'user_name': 'hello',\\n 'user_num': '123456',\\n 'file_desc': 'payroll',\\n 'date_for_process': datetime.strptime(json['post_date'], '%Y-%m-%d').strftime('%d%m%y'),\\n 'bsb_number': json['to_routing'],\\n 'account_number': json['to_account'],\\n 'indicator': ' ',\\n 'tran_code': '13' if json['tran_type'] == 'db' else '53',\\n 'amount': '{amount:010}'.format(amount=json['amount']), # $2.00\\n 'account_title': json['to_name'],\\n 'lodgement_ref': json['to_description'],\\n 'trace_bsb_number': json['from_routing'],\\n 'trace_account_number': json['from_account'],\\n 'name_of_remitter': json['from_name'],\\n 'withholding_tax_amount': '00000000',\\n }\\n\\n return direct_entry\",\n \"def create_datastructure_from_yaml_file(self):\\n ## loading the YAML file\\n try:\\n with open(self.source) as f:\\n hbaseSchemaDic = yaml.load(f) \\n except:\\n msg = \\\"Error: the HBase substructure could not be created. File %s could not be loaded. Please check the syntax of the '.yml' file.\\\" % self.source \\n raise createDataStructureException(msg)\\n status = \\\"failed\\\" \\n\\n try:\\n c = Connection(host = self.host, port = int(self.port))\\n tbls = c.tables()\\n tbls = [str(t) for t in tbls]\\n ## check that none of the tables already exists \\n for t in hbaseSchemaDic.keys():\\n if t in tbls:\\n msg = \\\"Error: the table %s already exists. If you use starbase in python you can drop the table by using \\\\n>>> from starbase import Connection\\\\n>>> c = Connection()\\\\n>>> t = c.table(%s)\\\\n>>> t.drop()\\\" % (t,t) \\n print(msg)\\n status = \\\"failed\\\"\\n raise createDataStructureException(msg)\\n\\n ## if none of the table(s) do(es) not exist, let's create them(it) \\n for t in hbaseSchemaDic.keys():\\n columnFamilies = hbaseSchemaDic[t]['columnFamilies'].keys()\\n tC = c.table(t)\\n tC.create(*columnFamilies)\\n status = \\\"succeeded\\\"\\n \\n except:\\n msg = \\\"Error: the HBase substructure could not be created. Please check your connection parameters or the syntax in your '.yml' file.\\\"\\n raise createDataStructureException(msg)\\n status = \\\"failed\\\"\\n\\n return(status)\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding=\\\"utf-8\\\") as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def read_json_breakdown(cls, fname):\\n if not os.path.exists(fname):\\n raise RuntimeError\\n\\n with open(fname, 'r') as data_file:\\n return cls.fixup_from_json(data_file.read())\",\n \"def _meta_json_to_database(self):\\n\\n sqlalchemy_metadata = MetaData() # this is unrelated to our meta.json\\n meta_table = Table('meta', sqlalchemy_metadata,\\n Column('meta', String))\\n\\n sqlalchemy_metadata.create_all(self.engine)\\n json_string = json.dumps(self.meta)\\n ins = meta_table.insert().values(meta=json_string)\\n conn = self.engine.connect()\\n conn.execute(\\\"DELETE FROM meta;\\\")\\n conn.execute(ins)\",\n \"def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\\n try:\\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\\n self.columns = tabels_schema.migrationTable.MigrationColumns\\n except Exception as err:\\n logger.error(\\\"parse_migration_tables [error] -> %s\\\" % err)\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def _read_jsonl(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return [json.loads(ln) for ln in f]\",\n \"def _read_jsonl(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return [json.loads(ln) for ln in f]\",\n \"def create_deft_table_json_mappings():\\n mappings = list()\\n mappings.append(JsonColumnMapping(columnName=\\\"rownumber\\\", jsonPath=\\\"$.rownumber\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"rowguid\\\", jsonPath=\\\"$.rowguid\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xdouble\\\", jsonPath=\\\"$.xdouble\\\", cslDataType=\\\"real\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xfloat\\\", jsonPath=\\\"$.xfloat\\\", cslDataType=\\\"real\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xbool\\\", jsonPath=\\\"$.xbool\\\", cslDataType=\\\"bool\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint16\\\", jsonPath=\\\"$.xint16\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint32\\\", jsonPath=\\\"$.xint32\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint64\\\", jsonPath=\\\"$.xint64\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint8\\\", jsonPath=\\\"$.xuint8\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint16\\\", jsonPath=\\\"$.xuint16\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint32\\\", jsonPath=\\\"$.xuint32\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint64\\\", jsonPath=\\\"$.xuint64\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xdate\\\", jsonPath=\\\"$.xdate\\\", cslDataType=\\\"datetime\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xsmalltext\\\", jsonPath=\\\"$.xsmalltext\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xtext\\\", jsonPath=\\\"$.xtext\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xnumberAsText\\\", jsonPath=\\\"$.xnumberAsText\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xtime\\\", jsonPath=\\\"$.xtime\\\", cslDataType=\\\"timespan\\\"))\\n mappings.append(\\n JsonColumnMapping(columnName=\\\"xtextWithNulls\\\", jsonPath=\\\"$.xtextWithNulls\\\", cslDataType=\\\"string\\\")\\n )\\n mappings.append(\\n JsonColumnMapping(columnName=\\\"xdynamicWithNulls\\\", jsonPath=\\\"$.xdynamicWithNulls\\\", cslDataType=\\\"dynamic\\\")\\n )\\n return mappings\",\n \"def create_schema(overwrite=False):\\n if (not overwrite) and os.path.isfile(_schema_file):\\n raise RuntimeError(\\\"Schema file already exists.\\\")\\n schema = {\\n 'title': 'obj',\\n 'description': 'A mapping container for Obj 3D data.',\\n 'type': 'object',\\n 'required': ['vertices', 'faces'],\\n 'definitions': {\\n 'vertex': {\\n 'description': 'Map describing a single vertex.',\\n 'type': 'object', 'required': ['x', 'y', 'z'],\\n 'additionalProperties': False,\\n 'properties': {'x': {'type': _coord_type},\\n 'y': {'type': _coord_type},\\n 'z': {'type': _coord_type},\\n 'red': {'type': _color_type},\\n 'blue': {'type': _color_type},\\n 'green': {'type': _color_type},\\n 'w': {'type': _coord_type, 'default': 1.0}}},\\n 'param': {\\n 'description': 'Map describing a single parameter space point.',\\n 'type': 'object', 'required': ['u', 'v'],\\n 'additionalProperties': False,\\n 'properties': {'u': {'type': _coord_type},\\n 'v': {'type': _coord_type},\\n 'w': {'type': _coord_type, 'default': 1.0}}},\\n 'normal': {\\n 'description': 'Map describing a single normal.',\\n 'type': 'object', 'required': ['i', 'j', 'k'],\\n 'additionalProperties': False,\\n 'properties': {'i': {'type': _coord_type},\\n 'j': {'type': _coord_type},\\n 'k': {'type': _coord_type}}},\\n 'texcoord': {\\n 'description': 'Map describing a single texture vertex.',\\n 'type': 'object', 'required': ['u'],\\n 'additionalProperties': False,\\n 'properties': {'u': {'type': _coord_type},\\n 'v': {'type': _coord_type, 'default': 0.0},\\n 'w': {'type': _coord_type, 'default': 0.0}}},\\n 'point': {\\n 'description': 'Array of vertex indices describing a set of points.',\\n 'type': 'array', 'minItems': 1,\\n 'items': {'type': _index_type}},\\n 'line': {\\n 'description': ('Array of vertex indices and texture indices '\\n + 'describing a line.'),\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties':\\n {'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type}}}},\\n 'face': {\\n 'description': ('Array of vertex, texture, and normal indices '\\n + 'describing a face.'),\\n 'type': 'array', 'minItems': 3,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties':\\n {'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type},\\n 'normal_index': {'type': _index_type}}}},\\n 'curve': {\\n 'description': 'Properties of describing a curve.',\\n 'type': 'object', 'required': ['starting_param', 'ending_param',\\n 'vertex_indices'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'starting_param': {'type': _coord_type},\\n 'ending_param': {'type': _coord_type},\\n 'vertex_indices': {\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': _index_type}}}},\\n 'curve2D': {\\n 'description': ('Array of parameter indices describine a 2D curve on '\\n + 'a surface.'),\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': _index_type}},\\n 'surface': {\\n 'description': 'Properties describing a surface.',\\n 'type': 'object', 'required': ['starting_param_u', 'ending_param_u',\\n 'starting_param_v', 'ending_param_v',\\n 'vertex_indices'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'starting_param_u': {'type': _coord_type},\\n 'ending_param_u': {'type': _coord_type},\\n 'starting_param_v': {'type': _coord_type},\\n 'ending_param_v': {'type': _coord_type},\\n 'vertex_indices': {\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type},\\n 'normal_index': {'type': _index_type}}}}}}},\\n 'properties': {\\n 'material': {\\n 'description': 'Name of the material to use.',\\n 'type': ['unicode', 'string']},\\n 'vertices': {\\n 'description': 'Array of vertices.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/vertex'}},\\n 'params': {\\n 'description': 'Array of parameter coordinates.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/param'}},\\n 'normals': {\\n 'description': 'Array of normals.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/normal'}},\\n 'texcoords': {\\n 'description': 'Array of texture vertices.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/texcoord'}},\\n 'points': {\\n 'description': 'Array of points.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/point'}},\\n 'lines': {\\n 'description': 'Array of lines.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/line'}},\\n 'faces': {\\n 'description': 'Array of faces.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/face'}},\\n 'curves': {\\n 'description': 'Array of curves.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/curve'}},\\n 'curve2Ds': {\\n 'description': 'Array of curve2Ds.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/curve2D'}},\\n 'surfaces': {\\n 'description': 'Array of surfaces.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/surface'}}},\\n 'dependencies': {\\n 'lines': ['vertices'],\\n 'faces': ['vertices'],\\n 'curves': ['vertices'],\\n 'curve2Ds': ['params'],\\n 'surfaces': ['vertices']}}\\n with open(_schema_file, 'w') as fd:\\n encode_json(schema, fd, indent='\\\\t')\",\n \"def generate_package_from_report_filepath(input_path, options = None):\\n try:\\n vt_file = open(input_path, 'r')\\n vt_dict = json.load(vt_file)\\n except:\\n print('\\\\nError: Error in parsing input file. Please check to ensure that it is valid JSON.')\\n return\\n \\n return vtpack.vt_report_to_maec_package(vt_dict, options)\",\n \"def import_into_db(json_file):\\n db = get_db()\\n\\n with current_app.open_resource(json_file) as f:\\n reports = json.load(f)\\n\\n for element in reports[\\\"elements\\\"]:\\n entry = (\\n element[\\\"id\\\"],\\n element[\\\"source\\\"],\\n element[\\\"sourceIdentityId\\\"],\\n element[\\\"state\\\"],\\n element[\\\"created\\\"],\\n element[\\\"reference\\\"][\\\"referenceId\\\"],\\n element[\\\"reference\\\"][\\\"referenceType\\\"],\\n element[\\\"payload\\\"][\\\"reportType\\\"],\\n element[\\\"payload\\\"][\\\"reportId\\\"],\\n element[\\\"payload\\\"][\\\"referenceResourceId\\\"],\\n element[\\\"payload\\\"][\\\"referenceResourceType\\\"],\\n element[\\\"payload\\\"][\\\"message\\\"],\\n )\\n db.execute(INSERT_INTO_REPORTS, entry)\\n\\n db.commit()\",\n \"def json_schema(schema_file=None, output=\\\"-\\\"):\\n schemas = read_yaml(schema_file)\\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, 'r', encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6506698","0.6255999","0.6189637","0.59361964","0.5880678","0.5861754","0.5762274","0.56616706","0.56331164","0.5612857","0.55776805","0.5533528","0.55065984","0.55045223","0.548444","0.547434","0.54314774","0.53971493","0.5346988","0.5327368","0.5307453","0.5267999","0.52455944","0.52326703","0.52325064","0.5219136","0.5207536","0.5187294","0.5183731","0.51769954","0.51745486","0.51707107","0.5170645","0.5158985","0.51522464","0.51227444","0.51213485","0.5113382","0.5110196","0.5099857","0.5093744","0.5089529","0.5088614","0.508273","0.5077681","0.5069668","0.5065103","0.5055063","0.50539035","0.50539035","0.50469744","0.50469744","0.50306594","0.50274265","0.502586","0.5005657","0.5004016","0.5004016","0.4997759","0.4997609","0.4986268","0.498196","0.49683973","0.49655133","0.496366","0.49594378","0.49467462","0.49407235","0.4928758","0.492373","0.4923461","0.49174178","0.49124745","0.48915982","0.48891523","0.48878503","0.48864958","0.48769042","0.48686188","0.48567456","0.48541322","0.48476815","0.4841311","0.48368114","0.48329535","0.48315528","0.48306122","0.48293504","0.48196423","0.4817549","0.4817549","0.4817549","0.48168716","0.48168716","0.48162666","0.4815631","0.481176","0.4809378","0.48069832","0.4803606"],"string":"[\n \"0.6506698\",\n \"0.6255999\",\n \"0.6189637\",\n \"0.59361964\",\n \"0.5880678\",\n \"0.5861754\",\n \"0.5762274\",\n \"0.56616706\",\n \"0.56331164\",\n \"0.5612857\",\n \"0.55776805\",\n \"0.5533528\",\n \"0.55065984\",\n \"0.55045223\",\n \"0.548444\",\n \"0.547434\",\n \"0.54314774\",\n \"0.53971493\",\n \"0.5346988\",\n \"0.5327368\",\n \"0.5307453\",\n \"0.5267999\",\n \"0.52455944\",\n \"0.52326703\",\n \"0.52325064\",\n \"0.5219136\",\n \"0.5207536\",\n \"0.5187294\",\n \"0.5183731\",\n \"0.51769954\",\n \"0.51745486\",\n \"0.51707107\",\n \"0.5170645\",\n \"0.5158985\",\n \"0.51522464\",\n \"0.51227444\",\n \"0.51213485\",\n \"0.5113382\",\n \"0.5110196\",\n \"0.5099857\",\n \"0.5093744\",\n \"0.5089529\",\n \"0.5088614\",\n \"0.508273\",\n \"0.5077681\",\n \"0.5069668\",\n \"0.5065103\",\n \"0.5055063\",\n \"0.50539035\",\n \"0.50539035\",\n \"0.50469744\",\n \"0.50469744\",\n \"0.50306594\",\n \"0.50274265\",\n \"0.502586\",\n \"0.5005657\",\n \"0.5004016\",\n 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message."},"document":{"kind":"string","value":"def BqTableDataFileProcessor(file_arg):\n data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')\n insert_row_type = data_insert_request_type.RowsValueListEntry\n data_row_type = GetApiMessage('JsonObject')\n\n try:\n data_json = yaml.load(file_arg)\n\n if not data_json or not isinstance(data_json, list):\n raise TableDataFileError(\n 'Error parsing data file: no data records defined in file')\n\n rows = []\n for row in data_json:\n rows.append(insert_row_type(json=encoding.DictToMessage(\n row, data_row_type)))\n\n return rows\n except yaml.YAMLParseError as ype:\n raise TableDataFileError('Error parsing data file [{}]'.format(ype))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ReadSchemaFile(schema_file, bigquery_messages):\n\n if os.path.exists(schema_file):\n with open(schema_file, mode='r') as f:\n try:\n def UpperOrNone(string):\n return string and string.upper()\n field_schemas = [\n bigquery_messages.TableFieldSchema(\n name=json_object.get('name'),\n type=json_object.get('type').upper(),\n mode=UpperOrNone(json_object.get('mode')))\n for json_object in json.load(f)]\n return bigquery_messages.TableSchema(fields=field_schemas)\n except ValueError as e:\n raise bigquery.SchemaError(\n 'Error decoding JSON schema from file {0}: {1}.'.format(\n schema_file, e))\n else:\n raise bigquery.SchemaError(\n 'Error reading schema: File \"{0}\" was not found.'.format(schema_file))","def _create_input_data(self):\n SCHEMA = parse_table_schema_from_json(\n '{\"fields\": [{\"name\": \"data\", \"type\": \"BYTES\"}]}')\n\n def format_record(record):\n # Since Synthetic Source returns data as a dictionary, we should skip one\n # of the part\n import base64\n return {'data': base64.b64encode(record[1])}\n\n with TestPipeline() as p:\n ( # pylint: disable=expression-not-assigned\n p\n | 'Produce rows' >> Read(\n SyntheticSource(self.parse_synthetic_source_options()))\n | 'Format' >> Map(format_record)\n | 'Write to BigQuery' >> WriteToBigQuery(\n dataset=self.input_dataset,\n table=self.input_table,\n schema=SCHEMA,\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\n write_disposition=BigQueryDisposition.WRITE_EMPTY))","def CreateTableFromFile(self, table_name, schema_path):\n try:\n schema_file = open(schema_path)\n schema_json = schema_file.read()\n schema_file.close()\n except IOError, e:\n raise SchemaError('Could not read file (%s):\\n%s' %\n (schema_path, str(e)))\n return self.CreateTableFromJson(table_name, schema_json)","def BqTableSchemaFileProcessor(file_arg):\n table_schema_type = GetApiMessage('TableSchema')\n schema_field_type = GetApiMessage('TableFieldSchema')\n\n try:\n schema_json = yaml.load(file_arg)\n schema_json = schema_json.get('schema', None)\n\n if not schema_json or not isinstance(schema_json, list):\n raise SchemaFileError(\n 'Error parsing schema file: no schema field list defined in file')\n\n all_fields = []\n for field in schema_json:\n new_field = schema_field_type(name=field['name'],\n type=field['type'],\n mode=field.get('mode', 'NULLABLE'))\n all_fields.append(new_field)\n\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\n except yaml.YAMLParseError as ype:\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\n except (AttributeError, KeyError) as e:\n raise SchemaFileError(\n 'Error parsing schema file, invalid field definition [{}]'.format(e))","def read_json(file) -> Table:\n try:\n with Path(file).open(mode=\"r\", encoding=\"utf-8\") as __f:\n res = load(__f)\n print(str(res)[:100])\n return res\n except JSONDecodeError as err:\n if err.msg != \"Extra data\":\n raise\n # Extra data, so try load line by line\n res = []\n for line in Path(file).read_text(encoding=\"utf-8\").splitlines():\n try:\n if line.strip() == \"\":\n continue\n res.append(loads(line))\n except Exception:\n ic(line)\n ic(\"exc2\")\n raise\n return res","def __json_schema_generator(file):\n try:\n data = json.load(file)\n metadata_set = set()\n try:\n for datum in data['meta']['view']['columns']:\n metadata_set.add(datum['name'])\n except Exception as e:\n metadata_set.clear()\n for datum in data:\n if isinstance(datum, str):\n metadata_set.add(datum)\n else:\n for datum_property in datum:\n metadata_set.add(str(datum_property))\n\n metadata_list = list(metadata_set)\n # assumes list of objects with sparsse data\n # OR\n # for data_property in data[0]:\n # metadata_list.append(data_property)\n # assumes list of objects and that first entry has full list of properties\n\n return SchemaGenerator.__build_schema(metadata_list)\n except Exception as e:\n logging.error('Failed to parse json file into schema: ' + str(e))\n raise FailedCreatingSchemaException(\"Failed to create schema from json file.\")","def CreateTableFromJson(self, table_name, schema_json):\n try:\n schema = json.JSONDecoder().decode(schema_json)\n except ValueError, e:\n raise SchemaError('Could not parse fields:\\n%s\\n%s' %\n (schema_json, str(e)))\n\n conn = self._Connect()\n result = conn.Call(\n dict(method='bigquery.tables.insert',\n collection='tables',\n operation=bq.REST.INSERT,\n params=dict(name=table_name, fields=schema)))\n return result","def ReadSchema(schema, bigquery_messages):\n\n return bigquery_messages.TableSchema(\n fields=[\n _TableFieldSchemaForEntry(entry, bigquery_messages)\n for entry in schema.split(',')])","def insert_data(table, jsonfile):\n with open(jsonfile) as infile:\n data = json.load(infile)\n table_models_map[table]['insert'](data)","def generate_wc_schema():\n json_str = json.dumps({'fields': [\n {'name': 'word', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'percent', 'type': 'FLOAT', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def main(input_json, output_markdown):\n parser = Parser()\n output_md = parser.parse_schema(json.load(input_json))\n output_markdown.writelines(output_md)\n click.secho(\"✔ Successfully parsed schema!\", bold=True, fg=\"green\")","def _convert(self, fn, suffix='json', path='jsonschema', name=None,\n root_class_name=None, data_files=[], target_class=None):\n ie = JsonSchemaImportEngine()\n d = os.path.join(INPUT_DIR, path)\n schema = ie.load(os.path.join(d, f'{fn}.{suffix}'), name=name, format=suffix, root_class_name=root_class_name)\n model_path = os.path.join(OUTPUT_DIR, f'{fn}.yaml')\n write_schema(schema, model_path)\n roundtrip_path = os.path.join(OUTPUT_DIR, f'{fn}.roundtrip.json')\n with open(roundtrip_path, 'w') as stream:\n stream.write(JsonSchemaGenerator(model_path).serialize())\n python_path = os.path.join(OUTPUT_DIR, f'{fn}.py')\n with open(python_path, 'w') as stream:\n stream.write(PythonGenerator(model_path).serialize())\n compile_python(python_path)\n # TODO: test data_files\n return schema","def load_schema(filename):\n with open(filename) as f:\n schema = json.load(f)\n\n return schema","def test_convert_json():\n schema = pa.schema([\n pa.field(\"foo\", pa.int32()),\n pa.field(\"bar\", pa.int64())\n ])\n\n input_path = \"{}/tests/fixtures/simple_json.txt\".format(os.getcwd())\n expected_file = \"{}/tests/fixtures/simple.parquet\".format(os.getcwd())\n with tempfile.NamedTemporaryFile() as f:\n output_file = f.name\n client.convert_json(input_path, output_file, schema)\n output = pq.ParquetFile(output_file)\n expected = pq.ParquetFile(expected_file)\n assert output.metadata.num_columns == expected.metadata.num_columns\n assert output.metadata.num_rows == expected.metadata.num_rows\n assert output.schema.equals(expected.schema)\n assert output.read_row_group(0).to_pydict() == expected.read_row_group(0).to_pydict()","def from_json_file(cls, json_file:str):\n with open(json_file) as file:\n data = json.load(file)\n validate(data, schema)\n instance = cls.from_dict(data)\n return instance","def process_data(data):\n # Table Name from Json file\n table_name = data['table_name']\n\n # No of Column\n column_count = data['column_count']\n\n # No of Row\n row_count = data['row_count']\n\n # Table columns schema from Json file\n column_properties = data['column_properties']\n\n # Get the row row_properties\n row_properties = data['row_properties']\n return table_name, column_count, row_count, column_properties, row_properties","def deduce_schema(self, input_data, *, schema_map=None):\n\n if self.input_format == 'csv':\n if self.csv_dialect:\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\n else:\n reader = csv.DictReader(input_data)\n elif self.input_format == 'json' or self.input_format is None:\n reader = json_reader(input_data)\n elif self.input_format == 'dict':\n reader = input_data\n else:\n raise Exception(f\"Unknown input_format '{self.input_format}'\")\n\n if schema_map is None:\n schema_map = OrderedDict()\n\n try:\n for json_object in reader:\n\n # Print a progress message periodically.\n self.line_number += 1\n if self.line_number % self.debugging_interval == 0:\n logging.info(f'Processing line {self.line_number}')\n\n # Deduce the schema from this given data record.\n if isinstance(json_object, dict):\n self.deduce_schema_for_record(\n json_object=json_object,\n schema_map=schema_map,\n )\n elif isinstance(json_object, Exception):\n self.log_error(\n f'Record could not be parsed: Exception: {json_object}'\n )\n if not self.ignore_invalid_lines:\n raise json_object\n else:\n self.log_error(\n 'Record should be a JSON Object '\n f'but was a {type(json_object)}'\n )\n if not self.ignore_invalid_lines:\n raise Exception(f'Record must be a JSON Object '\n f'but was a {type(json_object)}')\n finally:\n logging.info(f'Processed {self.line_number} lines')\n\n return schema_map, self.error_logs","def _create_schema(self, cypher_file):\n if len(self.graph.nodes) > 0:\n msg = \"Cypher file specified but the graph is not empty. Aborting.\"\n raise ValueError(msg)\n cyp = open(cypher_file, 'r').read()\n self.graph.run(cyp)","def _load_json_schema(filename):\n\n relative_path = join('schemas', filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n with open(absolute_path) as schema_file:\n return json.loads(schema_file.read())","def _load_json_schema(filename: str):\n relative_path = path.join('schemas', filename)\n absolute_path = path.join(path.dirname(__file__), relative_path)\n\n with open(absolute_path, 'r', encoding='utf-8') as schema_file:\n schema = json.loads(schema_file.read())\n\n return schema","def create_json_table(cur, country_json, body_json):\n print(\"Creating table from JSON file\")\n cur.execute('CREATE TABLE IF NOT EXISTS state_json(id INTEGER PRIMARY KEY, state TEXT, album TEXT)')\n for idx, album in enumerate(country_json[body_json['state']]):\n cur.execute('INSERT INTO state_json VALUES (\"%s\", \"%s\", \"%s\")' % (idx, body_json['state'], album))","def run(\n self,\n input_file=sys.stdin,\n output_file=sys.stdout,\n schema_map=None,\n ):\n schema_map, error_logs = self.deduce_schema(\n input_file, schema_map=schema_map\n )\n\n for error in error_logs:\n logging.info(\n f\"Problem on line {error['line_number']}: {error['msg']}\"\n )\n\n if self.debugging_map:\n json.dump(schema_map, output_file, indent=2)\n print(file=output_file)\n else:\n schema = self.flatten_schema(schema_map)\n json.dump(schema, output_file, indent=2)\n print(file=output_file)","def create_db(db, schema_json):\n with open(schema_json) as of:\n schema = json.load(of, object_pairs_hook=OrderedDict)\n # OrderedDict so that tables are created in the order specified,\n # allowing foreign keys to reference previously defined tables\n\n for table_name, columns in schema.items():\n col_types = columns.items() # dict -> tuple\n make_table(db, table_name, col_types)","def main(event, context):\n # pylint: enable=unused-argument\n data = decode(event[\"data\"])\n to_table([data], PROJECT, DATASET, TABLE)","def parse_raw(sqlContext, input, user):\n df = sqlContext.read.json(input + \"/\" + user + \"/\" + user + \".json\", multiLine=True)\n return df","def json_to_thrift(json_str, root_thrift_class):\r\n return json.loads(json_str, cls=ThriftJSONDecoder, root_thrift_class=root_thrift_class)","def extract_data(filename: str, schema_filename: str) -> DataFrame:\n data = []\n try:\n with open(schema_filename) as f:\n schema = json.load(f)\n with open(filename) as f:\n for line in f:\n json_doc = json.loads(line)\n if is_valid_data(json_doc, schema):\n data.append(json_doc)\n except ValueError as e:\n log.error(f\"Error parsing json: {e}\")\n except FileNotFoundError as e:\n log.error(f\"File not found error: {e}\")\n raise e\n except Exception as e:\n log.error(e)\n raise e\n return DataFrame(data)","def _schema_write(self, table: TableSchema) -> None:\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\n json.dump(table, f, indent=True)","def read_json(self, inputfile):\n transtransfile = json.load(inputfile)\n self.language = transfile['lang']\n self.translations = transfile['strings']","def generate_cooccur_schema():\n json_str = json.dumps({'fields': [\n {'name': 'w1', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'w2', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\n {'name': 'log_weight', 'type': 'FLOAT', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def generate_url_schema():\n json_str = json.dumps({'fields': [\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def generate_bq_schema(self, file_name, schema_file_name=None):\n if not schema_file_name:\n schema_file_name = f'{self.directory}/schema_temp.json'\n os.system(f\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\")\n\n schema = open(schema_file_name, 'r').read()\n\n os.remove(schema_file_name)\n\n return json.loads(schema)","def generate_data(self):\n print(\"generate_data - init\")\n with open(self.input_file, \"r\") as f:\n\n # read JSON data from input file\n data = json.loads(f.read())\n\n for idx, row in enumerate(data): \n # serialize Python dict to string\n msg = self.serialize_json(row)\n #print(f\"Linha: {row}\")\n self.send(self.topic, msg)\n self.flush()\n #print(\"Sleeping\")\n time.sleep(1)","def from_dict(cls, dikt) -> 'SourceSchema':\n return util.deserialize_model(dikt, cls)","def test_test_body_with_file_schema(self):\n pass","def _load_fixture(filename):\n\n # Read the binary data into text\n with open(filename, 'rb') as stream:\n content = stream.read().decode('utf-8')\n\n # Decode the data as JSON\n data = json.loads(content)\n\n # Instantiate a session.\n session = Session()\n\n # Iterate through the entries to add them one by one.\n for item in data:\n # Resolve model from the table reference.\n table = Base.metadata.tables[item['model'].split('.')[-1]]\n\n # Add the primary key.\n item['fields']['id'] = item['pk']\n\n # Add a new row.\n session.connection().execute(table.insert().values(**item['fields']))\n\n # Commit the session to the database.\n session.commit()","def load_json_schema(filename):\n relative_path = join('../schema', filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n base_path = dirname(absolute_path)\n base_uri = 'file://{}/'.format(base_path)\n\n with open(absolute_path) as schema_file:\n return jsonref.loads(\n schema_file.read(), base_uri=base_uri, jsonschema=True)","def convert_json_to_flatbuffer_binary(json, schema, out_dir):\n command = [FLATC, '-o', out_dir, '-b', schema, json]\n run_subprocess(command)","def _load_data_from_file(self, input_file_path):\n with FileOrBufferHandler(input_file_path, 'r', \n encoding=self.file_encoding) as input_file:\n try:\n data = json.load(input_file)\n except (json.JSONDecodeError, UnicodeDecodeError):\n input_file.seek(0)\n data = data_utils.read_json(\n data_generator=input_file,\n selected_columns=self.selected_keys,\n read_in_string=False\n )\n return data","def load_schema(self, schema_file):\n with open(schema_file) as fp:\n for line in io.lines_in(fp):\n parts = line.strip().split('\\t')\n if len(parts) != 3:\n raise ValueError('invalid type declaration %r' % line.strip())\n self.declare_relation(parts[0], parts[1], parts[2])","def transform_file(input_file_path: str, output_file_path: str):\n\n # Open json\n with open(input_file_path, mode=\"r\") as in_file:\n input_data = json.load(in_file)\n\n # Transform and write\n with jsonlines.open(output_file_path, mode=\"w\", compact=True) as out_file:\n for item in input_data[\"items\"]:\n out_file.write(transform_item(item))","def parse(json_string):\n try:\n json_data = json.loads(json_string)\n except Exception as exn:\n raise SchemaParseException(\n 'Error parsing schema from JSON: %r. '\n 'Error message: %r.'\n % (json_string, exn))\n\n # Initialize the names object\n names = Names()\n\n # construct the Avro Schema object\n return schema_from_json_data(json_data, names)","def get_inputs_from_file(filename=\"\"):\n import json\n\n with open(filename) as input_text:\n json_obj = json.load(input_text)\n return json_obj","def json_input():\r\n with open (FILE_INPUT,'rb') as file:\r\n data = json.load(file)\r\n return data['input_data'][0]","def intermediary_to_schema(tables, relationships, output):\n dot_file = _intermediary_to_dot(tables, relationships)\n #graph = AGraph()\n #graph = graph.from_string(dot_file)\n extension = output.split('.')[-1]\n #graph.draw(path=output, prog='dot', format=extension)\n #Source.from_file(filename, engine='dot', format=extension)\n return Source(dot_file, engine='dot', format=extension)","def populate_from_json(db: Session, model: DatabaseModel, json_file: str):\n data_exists = db.query(model).first()\n if data_exists:\n return\n with open(json_file, \"r\") as file:\n data = json.loads(file.read())\n for obj in data:\n db.add(model(**obj))\n db.commit()","def parse_and_format(file_in_path: str, file_out_path: str) -> None:\n\n with open(file_in_path) as input:\n payload = json.load(input)\n\n records = [\"# Data is in the format:\",\n \"# kem_id,kdf_id,aead_id,info,skRm,skEm,pkRm,pkEm,exporter_context,L,exported_value\"]\n\n for key in payload:\n # Skip these to test only capabilities exposed by BoringSSL\n if (key[\"mode\"] != MODE_BASE or\n key[\"kem_id\"] != KEM_DHKEM_X25519_SHA256 or\n key[\"kdf_id\"] != KDF_HKDF_SHA256 or\n key[\"aead_id\"] == AEAD_EXPORT_ONLY):\n continue\n\n for exportKey in key[\"exports\"]:\n records.append(\"{},{},{},{},{},{},{},{},{},{},{}\"\n .format(str(key[\"kem_id\"]),\n str(key[\"kdf_id\"]),\n str(key[\"aead_id\"]),\n str(key[\"info\"]),\n str(key[\"skRm\"]),\n str(key[\"skEm\"]),\n str(key[\"pkRm\"]),\n str(key[\"pkEm\"]),\n str(exportKey[\"exporter_context\"]),\n str(exportKey[\"L\"]),\n str(exportKey[\"exported_value\"])))\n\n\n with open(file_out_path, \"w\") as output:\n output.write(\"\\n\".join(records))","def jsons_to_table(dir_jsons, dir_out, name, format='html'):\n # sanity of paths\n dir_out = sanity_util.safe_dir_path(dir_path=dir_out)\n file_name = sanity_util.unique_file_name(dir=dir_out, fn=name, suffix='.{}'.format(format))\n # reading JSON files\n p_files = sorted([os.path.join(dir_jsons, p_json) for p_json in os.listdir(dir_jsons)])\n table = defaultdict(list)\n keys = set()\n for p_f in p_files:\n if p_f.lower().endswith('.json'):\n with open(p_f, 'r') as f_json:\n el = json.load(f_json)\n for k in el.keys():\n keys.add(k)\n for p_f in p_files:\n if p_f.lower().endswith('.json'):\n with open(p_f, 'r') as f_json:\n el = json.load(f_json)\n for k in el.keys():\n table[k].append(el[k])\n for k in keys.difference(set(el.keys())):\n table[k].append(None)\n # DataFrame conversion\n df = pd.DataFrame.from_dict(table)\n # writing HTML table\n if format == 'html':\n table_str = df.to_html()\n else:\n table_str = df.to_latex()\n table_str += '<script type=\"text/javascript\" src=\"stylize.js\"></script>'\n stylize_js = js_stylize()\n with open(os.path.join(dir_out, 'stylize.js'), 'w') as f_js:\n f_js.write(stylize_js)\n with open(file_name, 'w') as f_out:\n f_out.write(table_str)","def decide_schema(self, json_data):\n pass","def decide_schema(self, json_data):\n pass","def _read_json(cls, input_file):\n with open(input_file) as f:\n return json.load(f)","def _read_json(cls, input_file):\n with open(input_file) as f:\n return json.load(f)","def all_to_intermediary(filename_or_input, schema=None):\n # Try to convert from the name of the class\n input_class_name = filename_or_input.__class__.__name__\n try:\n this_to_intermediary = switch_input_class_to_method[input_class_name]\n tables, relationships = this_to_intermediary(filename_or_input)\n return tables, relationships\n except KeyError:\n pass\n\n # try to read markdown file.\n if isinstance(filename_or_input, basestring):\n if filename_or_input.split('.')[-1] == 'er':\n return markdown_file_to_intermediary(filename_or_input)\n\n # try to read a markdown in a string\n if not isinstance(filename_or_input, basestring):\n if all(isinstance(e, basestring) for e in filename_or_input):\n return line_iterator_to_intermediary(filename_or_input)\n\n # try to read DB URI.\n try:\n make_url(filename_or_input)\n return database_to_intermediary(filename_or_input, schema=schema)\n except ArgumentError:\n pass\n\n msg = 'Cannot process filename_or_input {}'.format(input_class_name)\n raise ValueError(msg)","def __csv_schema_generator(file):\n try:\n # Parses the first line of the file to get all the headers.\n metadata = str(file.readline().decode('utf-8')).strip().split(',')\n # Will be further implemented in phase 3.\n return SchemaGenerator.__build_schema(metadata)\n except Exception as e:\n logging.error('Failed to parse csv file into schema: ' + str(e))\n raise FailedCreatingSchemaException(\"Failed to create schema from csv file.\")","def schema_load(filename):\n print(uc.schema_load(filename))","def read_json_schema(schema_file_path):\n with open(schema_file_path) as f:\n schema = json.load(f)\n return schema","def _read_json(cls, input_file):\n with open(input_file, 'rb') as f:\n return json.load(f)","def _read_json(cls, input_file):\n with open(input_file, 'rb') as f:\n return json.load(f)","def _read_data(cls, input_file): # 这里是对文件的处理\r\n with open(input_file, encoding='utf-8') as f:\r\n lines = []\r\n\r\n for line in f:\r\n line = json.loads(line)\r\n words = ' '.join(list(line['natural']))\r\n labels = ' '.join(line['tag_seq'])\r\n poss = line['pos_seq']\r\n dps = line['dp_seq']\r\n head = line['head_seq']\r\n lines.append([labels, words, poss, dps, head])\r\n\r\n return lines","def from_json_file(cls, json_file):\n with tf.io.gfile.GFile(json_file, \"r\") as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def load_from_json(self, json_fp: str):\n # TODO:\n pass","def from_json_file(cls, json_file):\n with tf.io.gfile.GFile(json_file, \"r\") as reader:\n text = reader.read()\n return cls(**json.loads(text))","def from_json(self, file_path):\n with open(file_path) as file:\n jsonstr = file.read()\n handler_dict = json.loads(jsonstr)\n self.from_dict(handler_dict)","def import_schemas_from_file():\n with open('./tblSchemas') as schemas_file:\n schemas = {}\n for line in schemas_file:\n line = line.split()\n if len(line) == 0: continue\n if line[0] == 'tblname':\n tbl_name = line[1]\n schemas[tbl_name] = []\n else:\n schemas[tbl_name].append(line)\n return schemas","def get_schema():\n if not os.path.isfile(_schema_file):\n create_schema()\n with open(_schema_file, 'r') as fd:\n out = decode_json(fd)\n return out","def convert_schema(bco, filename, mapping_dict):\n for item in mapping_dict['to_swap']:\n value_list = mapping_dict['to_swap'][item]\n for i in range(0, len(value_list)):\n rename_dict_key_HELPER(bco, value_list[i]['index'],\n value_list[i]['value']) # Change key name\n\n for item in mapping_dict['to_delete']:\n value_list = mapping_dict['to_delete'][item]\n for i in range(0, len(value_list)):\n delete_key_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # delete key\n\n for item in mapping_dict['to_add']:\n value_list = mapping_dict['to_add'][item]\n for i in range(0, len(value_list)):\n set_key_in_dict_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # add key\n\n new_bco = bco\n try:\n new_bco['provenance_domain'][\n 'modified'] = datetime.now().isoformat() # change date to current\n\n temp_bco = dict(new_bco)\n del temp_bco['object_id'], temp_bco['etag'], temp_bco['spec_version']\n\n new_bco['spec_version'] = \"https://w3id.org/ieee/ieee-2791-schema/2791object.json\"\n new_bco[\"etag\"] = sha256(json.dumps(temp_bco).encode('utf-8')).hexdigest()\n except KeyError: # Vital field was missing, will be caught by final error checker\n pass\n file = open(filename, \"w\")\n json.dump(new_bco, file, indent=4)","def test_json():\n schemas = {\n 'schema-languages': 'bible/languages.json',\n 'schema-book-metadata': 'bible/book-metadata.json',\n 'schema-bible': 'bible/bible-*.json'\n }\n for schema_name, data_path_glob in schemas.items():\n schema_path = 'schemas/{}.json'.format(schema_name)\n with open(schema_path) as schema_file:\n schema = json.load(schema_file)\n data_paths = glob.iglob(data_path_glob)\n for data_path in data_paths:\n with open(data_path) as data_file:\n data = json.load(data_file)\n yield jsonschema.validate, data, schema","def _load_schema(self, json_schema):\n # use jsonrefs to resolve all $refs in json\n data = jsonref.loads(json.dumps(json_schema))\n return self.__initialise_template(data)","def test_read_json_schema():\n json_schema = os.path.join(TEST_DATA_PATH, 'example_schema.json')\n schema_tree = schema.load_schema(json_schema, resolve_references=True)\n schema.check_schema(schema_tree)","def get_schema(filename: str) -> dict:\n return _load_json_schema(filename)","def _import(format, input, config):\n if input:\n with open(input, 'rb') as f:\n data = f.read()\n else:\n data = sys.stdin.read()\n\n dataset = tablib.Dataset()\n setattr(dataset, format, data)\n\n _add_changelogs(config, dataset.dict)","def read_json(self, filename, multi_line=False, schema=None):\n self.logger.info(\"# Reading a JSON file \" + filename)\n sql_context = SQLContext(self.spark)\n df = None\n if schema is None and multi_line == False:\n df = sql_context.read.json(filename)\n elif multi_line:\n df = sql_context.read.json(filename, multiLine=multi_line)\n elif schema is not None:\n df = sql_context.read.json(filename, schema=schema)\n return df","def _load_json_schema(filename):\n\n relative_path = join(\"schemas\", filename)\n absolute_path = join(dirname(__file__), relative_path)\n\n base_path = dirname(absolute_path)\n base_uri = 'file://{}/'.format(base_path)\n\n print(f\"base uri {base_uri}\")\n print(f\"base path {base_path}\")\n print(f\"relative_path {relative_path}\")\n print(f\"absolute_path {absolute_path}\")\n\n with open(absolute_path) as schema_file:\n return jsonref.loads(schema_file.read(), base_uri=base_uri, jsonschema=True)","def readjamschema(schema):\n raise NotImplementedError(msg)","def load(file_name):\n with open(file_name, newline='') as f:\n reader = csv.reader(f)\n data = list(reader)\n\n schema = [x.strip() for x in data[0]]\n table = [[int(el) for el in row] for row in data[1:]]\n\n return schema, table","def get_schema(path):\n with open(path, 'r') as f:\n return json.load(f)","def test_schema_invalid_json(self):\n schema_0_input = schema_nested_2_invalid_JSON\n\n # if you uncomment this line:\n # schema_0_input = schema_nested_2\n # this will fail the test: Failed: DID NOT RAISE <class 'simplejson.scanner.JSONDecodeError'>\n # because this is a valid schema\n\n with pytest.raises(simplejson.scanner.JSONDecodeError):\n msg = singer.parse_message(schema_0_input)","def create_table_from_file():\n\n full_path = os.getcwd()\n file_name = full_path + \"/inventory/inventory.csv\"\n\n if os.path.exists(file_name):\n table = data_manager.get_table_from_file(file_name)\n\n else:\n ui.print_error_message(\"There is no file to read!\")\n table = []\n\n return table","def tsv_to_json(tsv_file, json_file):\n import csv\n import json\n\n try:\n with open(tsv_file, 'r') as tsvFile:\n file_reader = csv.DictReader(tsvFile, dialect='excel-tab')\n row_list = list(file_reader)\n with open(json_file, 'w+') as jsonFile:\n jsonFile.write(json.dumps(row_list, indent=4))\n return 1\n except (ValueError, FileNotFoundError):\n return 0","async def _process_create_data(self, data: dict) -> dict:\n return self.SCHEMA(data)","def read_data(self):\n if self._file.is_file():\n try:\n self._data = read_json_file(self._file)\n except (OSError, json.JSONDecodeError):\n _LOGGER.warning(\"Can't read %s\", self._file)\n self._data = {}\n\n # Validate\n try:\n self._data = self._schema(self._data)\n except vol.Invalid as ex:\n _LOGGER.error(\"Can't parse %s: %s\",\n self._file, humanize_error(self._data, ex))\n\n # Reset data to default\n _LOGGER.warning(\"Reset %s to default\", self._file)\n self._data = self._schema({})","def _mashup_json_to_table(json_obj, col_config=None):\n\n dataTable = Table(masked=True)\n absCorr = None\n\n if not all(x in json_obj.keys() for x in ['fields', 'data']):\n raise KeyError(\"Missing required key(s) 'data' and/or 'fields.'\")\n\n for col, atype in [(x['name'], x['type']) for x in json_obj['fields']]:\n\n # Removing \"_selected_\" column\n if col == \"_selected_\":\n continue\n\n # reading the colum config if given\n ignoreValue = None\n if col_config:\n colProps = col_config.get(col, {})\n ignoreValue = colProps.get(\"ignoreValue\", None)\n\n # making type adjustments\n if atype == \"string\":\n atype = \"str\"\n ignoreValue = \"\" if (ignoreValue is None) else ignoreValue\n if atype == \"boolean\":\n atype = \"bool\"\n if atype == \"int\": # int arrays do not admit Non/nan vals\n atype = np.int64\n ignoreValue = -999 if (ignoreValue is None) else ignoreValue\n if atype == \"date\":\n atype = \"str\"\n ignoreValue = \"\" if (ignoreValue is None) else ignoreValue\n\n # Make the column list (don't assign final type yet or there will be errors)\n colData = np.array([x.get(col, ignoreValue) for x in json_obj['data']], dtype=object)\n if ignoreValue is not None:\n colData[np.where(np.equal(colData, None))] = ignoreValue\n\n # no consistant way to make the mask because np.equal fails on ''\n # and array == value fails with None\n if atype == 'str':\n colMask = (colData == ignoreValue)\n else:\n colMask = np.equal(colData, ignoreValue)\n\n # add the column\n dataTable.add_column(MaskedColumn(colData.astype(atype), name=col, mask=colMask))\n\n return dataTable","def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\n table_to_col_names_dict = {}\n table_to_col_names_dict[\"transaction_fabs\"] = TRANSACTION_FABS_COLUMNS\n table_to_col_names_dict[\"transaction_fpds\"] = TRANSACTION_FPDS_COLUMNS\n table_to_col_names_dict[\"transaction_normalized\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\n table_to_col_names_dict[\"awards\"] = list(AWARDS_COLUMNS)\n table_to_col_names_dict[\"financial_accounts_by_awards\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\n\n table_to_col_info_dict = {}\n for tbl_name, col_info in zip(\n (\"transaction_fabs\", \"transaction_fpds\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\n ):\n table_to_col_info_dict[tbl_name] = {}\n for col in col_info:\n table_to_col_info_dict[tbl_name][col.dest_name] = col\n\n # Make sure the table has been created first\n call_command(\n \"create_delta_table\",\n \"--destination-table\",\n table_name,\n \"--alt-db\",\n table_schema,\n \"--spark-s3-bucket\",\n s3_data_bucket,\n )\n\n if data:\n insert_sql = f\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\n\"\n row_strs = []\n for row in data:\n value_strs = []\n for col_name in table_to_col_names_dict[table_name]:\n value = row.get(col_name)\n if isinstance(value, (str, bytes)):\n # Quote strings for insertion into DB\n value_strs.append(f\"'{value}'\")\n elif isinstance(value, (date, datetime)):\n # Convert to string and quote\n value_strs.append(f\"\"\"'{value.isoformat()}'\"\"\")\n elif isinstance(value, bool):\n value_strs.append(str(value).upper())\n elif isinstance(value, (Sequence, Set)):\n # Assume \"sequences\" must be \"sequences\" of strings, so quote each item in the \"sequence\"\n value = [f\"'{item}'\" for item in value]\n value_strs.append(f\"ARRAY({', '.join(value)})\")\n elif value is None:\n col_info = table_to_col_info_dict.get(table_name)\n if (\n col_info\n and col_info[col_name].delta_type.upper() == \"BOOLEAN\"\n and not col_info[col_name].handling == \"leave_null\"\n ):\n # Convert None/NULL to false for boolean columns unless specified to leave the null\n value_strs.append(\"FALSE\")\n else:\n value_strs.append(\"NULL\")\n else:\n value_strs.append(str(value))\n\n row_strs.append(f\" ({', '.join(value_strs)})\")\n\n sql = \"\".join([insert_sql, \",\\n\".join(row_strs), \";\"])\n spark.sql(sql)","def convert_json_1(json):\n\n # TODO Add batch details to json format\n # TODO Get default direct entry batch details if not provided\n\n LOGGER.debug('convert json message:%s', json)\n direct_entry = {\n 'record_type': '1',\n 'reel_seq_num': '01',\n 'name_fin_inst': 'SUN',\n 'user_name': 'hello',\n 'user_num': '123456',\n 'file_desc': 'payroll',\n 'date_for_process': datetime.strptime(json['post_date'], '%Y-%m-%d').strftime('%d%m%y'),\n 'bsb_number': json['to_routing'],\n 'account_number': json['to_account'],\n 'indicator': ' ',\n 'tran_code': '13' if json['tran_type'] == 'db' else '53',\n 'amount': '{amount:010}'.format(amount=json['amount']), # $2.00\n 'account_title': json['to_name'],\n 'lodgement_ref': json['to_description'],\n 'trace_bsb_number': json['from_routing'],\n 'trace_account_number': json['from_account'],\n 'name_of_remitter': json['from_name'],\n 'withholding_tax_amount': '00000000',\n }\n\n return direct_entry","def create_datastructure_from_yaml_file(self):\n ## loading the YAML file\n try:\n with open(self.source) as f:\n hbaseSchemaDic = yaml.load(f) \n except:\n msg = \"Error: the HBase substructure could not be created. File %s could not be loaded. Please check the syntax of the '.yml' file.\" % self.source \n raise createDataStructureException(msg)\n status = \"failed\" \n\n try:\n c = Connection(host = self.host, port = int(self.port))\n tbls = c.tables()\n tbls = [str(t) for t in tbls]\n ## check that none of the tables already exists \n for t in hbaseSchemaDic.keys():\n if t in tbls:\n msg = \"Error: the table %s already exists. If you use starbase in python you can drop the table by using \\n>>> from starbase import Connection\\n>>> c = Connection()\\n>>> t = c.table(%s)\\n>>> t.drop()\" % (t,t) \n print(msg)\n status = \"failed\"\n raise createDataStructureException(msg)\n\n ## if none of the table(s) do(es) not exist, let's create them(it) \n for t in hbaseSchemaDic.keys():\n columnFamilies = hbaseSchemaDic[t]['columnFamilies'].keys()\n tC = c.table(t)\n tC.create(*columnFamilies)\n status = \"succeeded\"\n \n except:\n msg = \"Error: the HBase substructure could not be created. Please check your connection parameters or the syntax in your '.yml' file.\"\n raise createDataStructureException(msg)\n status = \"failed\"\n\n return(status)","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding=\"utf-8\") as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def read_json_breakdown(cls, fname):\n if not os.path.exists(fname):\n raise RuntimeError\n\n with open(fname, 'r') as data_file:\n return cls.fixup_from_json(data_file.read())","def _meta_json_to_database(self):\n\n sqlalchemy_metadata = MetaData() # this is unrelated to our meta.json\n meta_table = Table('meta', sqlalchemy_metadata,\n Column('meta', String))\n\n sqlalchemy_metadata.create_all(self.engine)\n json_string = json.dumps(self.meta)\n ins = meta_table.insert().values(meta=json_string)\n conn = self.engine.connect()\n conn.execute(\"DELETE FROM meta;\")\n conn.execute(ins)","def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\n try:\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\n self.columns = tabels_schema.migrationTable.MigrationColumns\n except Exception as err:\n logger.error(\"parse_migration_tables [error] -> %s\" % err)","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def from_json_file(cls, json_file):\n with open(json_file, \"r\", encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))","def _read_jsonl(cls, input_file):\n with open(input_file, 'rb') as f:\n return [json.loads(ln) for ln in f]","def _read_jsonl(cls, input_file):\n with open(input_file, 'rb') as f:\n return [json.loads(ln) for ln in f]","def create_deft_table_json_mappings():\n mappings = list()\n mappings.append(JsonColumnMapping(columnName=\"rownumber\", jsonPath=\"$.rownumber\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"rowguid\", jsonPath=\"$.rowguid\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xdouble\", jsonPath=\"$.xdouble\", cslDataType=\"real\"))\n mappings.append(JsonColumnMapping(columnName=\"xfloat\", jsonPath=\"$.xfloat\", cslDataType=\"real\"))\n mappings.append(JsonColumnMapping(columnName=\"xbool\", jsonPath=\"$.xbool\", cslDataType=\"bool\"))\n mappings.append(JsonColumnMapping(columnName=\"xint16\", jsonPath=\"$.xint16\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"xint32\", jsonPath=\"$.xint32\", cslDataType=\"int\"))\n mappings.append(JsonColumnMapping(columnName=\"xint64\", jsonPath=\"$.xint64\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint8\", jsonPath=\"$.xuint8\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint16\", jsonPath=\"$.xuint16\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint32\", jsonPath=\"$.xuint32\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xuint64\", jsonPath=\"$.xuint64\", cslDataType=\"long\"))\n mappings.append(JsonColumnMapping(columnName=\"xdate\", jsonPath=\"$.xdate\", cslDataType=\"datetime\"))\n mappings.append(JsonColumnMapping(columnName=\"xsmalltext\", jsonPath=\"$.xsmalltext\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xtext\", jsonPath=\"$.xtext\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xnumberAsText\", jsonPath=\"$.xnumberAsText\", cslDataType=\"string\"))\n mappings.append(JsonColumnMapping(columnName=\"xtime\", jsonPath=\"$.xtime\", cslDataType=\"timespan\"))\n mappings.append(\n JsonColumnMapping(columnName=\"xtextWithNulls\", jsonPath=\"$.xtextWithNulls\", cslDataType=\"string\")\n )\n mappings.append(\n JsonColumnMapping(columnName=\"xdynamicWithNulls\", jsonPath=\"$.xdynamicWithNulls\", cslDataType=\"dynamic\")\n )\n return mappings","def create_schema(overwrite=False):\n if (not overwrite) and os.path.isfile(_schema_file):\n raise RuntimeError(\"Schema file already exists.\")\n schema = {\n 'title': 'obj',\n 'description': 'A mapping container for Obj 3D data.',\n 'type': 'object',\n 'required': ['vertices', 'faces'],\n 'definitions': {\n 'vertex': {\n 'description': 'Map describing a single vertex.',\n 'type': 'object', 'required': ['x', 'y', 'z'],\n 'additionalProperties': False,\n 'properties': {'x': {'type': _coord_type},\n 'y': {'type': _coord_type},\n 'z': {'type': _coord_type},\n 'red': {'type': _color_type},\n 'blue': {'type': _color_type},\n 'green': {'type': _color_type},\n 'w': {'type': _coord_type, 'default': 1.0}}},\n 'param': {\n 'description': 'Map describing a single parameter space point.',\n 'type': 'object', 'required': ['u', 'v'],\n 'additionalProperties': False,\n 'properties': {'u': {'type': _coord_type},\n 'v': {'type': _coord_type},\n 'w': {'type': _coord_type, 'default': 1.0}}},\n 'normal': {\n 'description': 'Map describing a single normal.',\n 'type': 'object', 'required': ['i', 'j', 'k'],\n 'additionalProperties': False,\n 'properties': {'i': {'type': _coord_type},\n 'j': {'type': _coord_type},\n 'k': {'type': _coord_type}}},\n 'texcoord': {\n 'description': 'Map describing a single texture vertex.',\n 'type': 'object', 'required': ['u'],\n 'additionalProperties': False,\n 'properties': {'u': {'type': _coord_type},\n 'v': {'type': _coord_type, 'default': 0.0},\n 'w': {'type': _coord_type, 'default': 0.0}}},\n 'point': {\n 'description': 'Array of vertex indices describing a set of points.',\n 'type': 'array', 'minItems': 1,\n 'items': {'type': _index_type}},\n 'line': {\n 'description': ('Array of vertex indices and texture indices '\n + 'describing a line.'),\n 'type': 'array', 'minItems': 2,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties':\n {'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type}}}},\n 'face': {\n 'description': ('Array of vertex, texture, and normal indices '\n + 'describing a face.'),\n 'type': 'array', 'minItems': 3,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties':\n {'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type},\n 'normal_index': {'type': _index_type}}}},\n 'curve': {\n 'description': 'Properties of describing a curve.',\n 'type': 'object', 'required': ['starting_param', 'ending_param',\n 'vertex_indices'],\n 'additionalProperties': False,\n 'properties': {\n 'starting_param': {'type': _coord_type},\n 'ending_param': {'type': _coord_type},\n 'vertex_indices': {\n 'type': 'array', 'minItems': 2,\n 'items': {'type': _index_type}}}},\n 'curve2D': {\n 'description': ('Array of parameter indices describine a 2D curve on '\n + 'a surface.'),\n 'type': 'array', 'minItems': 2,\n 'items': {'type': _index_type}},\n 'surface': {\n 'description': 'Properties describing a surface.',\n 'type': 'object', 'required': ['starting_param_u', 'ending_param_u',\n 'starting_param_v', 'ending_param_v',\n 'vertex_indices'],\n 'additionalProperties': False,\n 'properties': {\n 'starting_param_u': {'type': _coord_type},\n 'ending_param_u': {'type': _coord_type},\n 'starting_param_v': {'type': _coord_type},\n 'ending_param_v': {'type': _coord_type},\n 'vertex_indices': {\n 'type': 'array', 'minItems': 2,\n 'items': {'type': 'object', 'required': ['vertex_index'],\n 'additionalProperties': False,\n 'properties': {\n 'vertex_index': {'type': _index_type},\n 'texcoord_index': {'type': _index_type},\n 'normal_index': {'type': _index_type}}}}}}},\n 'properties': {\n 'material': {\n 'description': 'Name of the material to use.',\n 'type': ['unicode', 'string']},\n 'vertices': {\n 'description': 'Array of vertices.',\n 'type': 'array', 'items': {'$ref': '#/definitions/vertex'}},\n 'params': {\n 'description': 'Array of parameter coordinates.',\n 'type': 'array', 'items': {'$ref': '#/definitions/param'}},\n 'normals': {\n 'description': 'Array of normals.',\n 'type': 'array', 'items': {'$ref': '#/definitions/normal'}},\n 'texcoords': {\n 'description': 'Array of texture vertices.',\n 'type': 'array', 'items': {'$ref': '#/definitions/texcoord'}},\n 'points': {\n 'description': 'Array of points.',\n 'type': 'array', 'items': {'$ref': '#/definitions/point'}},\n 'lines': {\n 'description': 'Array of lines.',\n 'type': 'array', 'items': {'$ref': '#/definitions/line'}},\n 'faces': {\n 'description': 'Array of faces.',\n 'type': 'array', 'items': {'$ref': '#/definitions/face'}},\n 'curves': {\n 'description': 'Array of curves.',\n 'type': 'array', 'items': {'$ref': '#/definitions/curve'}},\n 'curve2Ds': {\n 'description': 'Array of curve2Ds.',\n 'type': 'array', 'items': {'$ref': '#/definitions/curve2D'}},\n 'surfaces': {\n 'description': 'Array of surfaces.',\n 'type': 'array', 'items': {'$ref': '#/definitions/surface'}}},\n 'dependencies': {\n 'lines': ['vertices'],\n 'faces': ['vertices'],\n 'curves': ['vertices'],\n 'curve2Ds': ['params'],\n 'surfaces': ['vertices']}}\n with open(_schema_file, 'w') as fd:\n encode_json(schema, fd, indent='\\t')","def generate_package_from_report_filepath(input_path, options = None):\n try:\n vt_file = open(input_path, 'r')\n vt_dict = json.load(vt_file)\n except:\n print('\\nError: Error in parsing input file. Please check to ensure that it is valid JSON.')\n return\n \n return vtpack.vt_report_to_maec_package(vt_dict, options)","def import_into_db(json_file):\n db = get_db()\n\n with current_app.open_resource(json_file) as f:\n reports = json.load(f)\n\n for element in reports[\"elements\"]:\n entry = (\n element[\"id\"],\n element[\"source\"],\n element[\"sourceIdentityId\"],\n element[\"state\"],\n element[\"created\"],\n element[\"reference\"][\"referenceId\"],\n element[\"reference\"][\"referenceType\"],\n element[\"payload\"][\"reportType\"],\n element[\"payload\"][\"reportId\"],\n element[\"payload\"][\"referenceResourceId\"],\n element[\"payload\"][\"referenceResourceType\"],\n element[\"payload\"][\"message\"],\n )\n db.execute(INSERT_INTO_REPORTS, entry)\n\n db.commit()","def json_schema(schema_file=None, output=\"-\"):\n schemas = read_yaml(schema_file)\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))","def from_json_file(cls, json_file):\n with open(json_file, 'r', encoding='utf-8') as reader:\n text = reader.read()\n return cls.from_dict(json.loads(text))"],"string":"[\n \"def ReadSchemaFile(schema_file, bigquery_messages):\\n\\n if os.path.exists(schema_file):\\n with open(schema_file, mode='r') as f:\\n try:\\n def UpperOrNone(string):\\n return string and string.upper()\\n field_schemas = [\\n bigquery_messages.TableFieldSchema(\\n name=json_object.get('name'),\\n type=json_object.get('type').upper(),\\n mode=UpperOrNone(json_object.get('mode')))\\n for json_object in json.load(f)]\\n return bigquery_messages.TableSchema(fields=field_schemas)\\n except ValueError as e:\\n raise bigquery.SchemaError(\\n 'Error decoding JSON schema from file {0}: {1}.'.format(\\n schema_file, e))\\n else:\\n raise bigquery.SchemaError(\\n 'Error reading schema: File \\\"{0}\\\" was not found.'.format(schema_file))\",\n \"def _create_input_data(self):\\n SCHEMA = parse_table_schema_from_json(\\n '{\\\"fields\\\": [{\\\"name\\\": \\\"data\\\", \\\"type\\\": \\\"BYTES\\\"}]}')\\n\\n def format_record(record):\\n # Since Synthetic Source returns data as a dictionary, we should skip one\\n # of the part\\n import base64\\n return {'data': base64.b64encode(record[1])}\\n\\n with TestPipeline() as p:\\n ( # pylint: disable=expression-not-assigned\\n p\\n | 'Produce rows' >> Read(\\n SyntheticSource(self.parse_synthetic_source_options()))\\n | 'Format' >> Map(format_record)\\n | 'Write to BigQuery' >> WriteToBigQuery(\\n dataset=self.input_dataset,\\n table=self.input_table,\\n schema=SCHEMA,\\n create_disposition=BigQueryDisposition.CREATE_IF_NEEDED,\\n write_disposition=BigQueryDisposition.WRITE_EMPTY))\",\n \"def CreateTableFromFile(self, table_name, schema_path):\\n try:\\n schema_file = open(schema_path)\\n schema_json = schema_file.read()\\n schema_file.close()\\n except IOError, e:\\n raise SchemaError('Could not read file (%s):\\\\n%s' %\\n (schema_path, str(e)))\\n return self.CreateTableFromJson(table_name, schema_json)\",\n \"def BqTableSchemaFileProcessor(file_arg):\\n table_schema_type = GetApiMessage('TableSchema')\\n schema_field_type = GetApiMessage('TableFieldSchema')\\n\\n try:\\n schema_json = yaml.load(file_arg)\\n schema_json = schema_json.get('schema', None)\\n\\n if not schema_json or not isinstance(schema_json, list):\\n raise SchemaFileError(\\n 'Error parsing schema file: no schema field list defined in file')\\n\\n all_fields = []\\n for field in schema_json:\\n new_field = schema_field_type(name=field['name'],\\n type=field['type'],\\n mode=field.get('mode', 'NULLABLE'))\\n all_fields.append(new_field)\\n\\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\\n except yaml.YAMLParseError as ype:\\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\\n except (AttributeError, KeyError) as e:\\n raise SchemaFileError(\\n 'Error parsing schema file, invalid field definition [{}]'.format(e))\",\n \"def read_json(file) -> Table:\\n try:\\n with Path(file).open(mode=\\\"r\\\", encoding=\\\"utf-8\\\") as __f:\\n res = load(__f)\\n print(str(res)[:100])\\n return res\\n except JSONDecodeError as err:\\n if err.msg != \\\"Extra data\\\":\\n raise\\n # Extra data, so try load line by line\\n res = []\\n for line in Path(file).read_text(encoding=\\\"utf-8\\\").splitlines():\\n try:\\n if line.strip() == \\\"\\\":\\n continue\\n res.append(loads(line))\\n except Exception:\\n ic(line)\\n ic(\\\"exc2\\\")\\n raise\\n return res\",\n \"def __json_schema_generator(file):\\n try:\\n data = json.load(file)\\n metadata_set = set()\\n try:\\n for datum in data['meta']['view']['columns']:\\n metadata_set.add(datum['name'])\\n except Exception as e:\\n metadata_set.clear()\\n for datum in data:\\n if isinstance(datum, str):\\n metadata_set.add(datum)\\n else:\\n for datum_property in datum:\\n metadata_set.add(str(datum_property))\\n\\n metadata_list = list(metadata_set)\\n # assumes list of objects with sparsse data\\n # OR\\n # for data_property in data[0]:\\n # metadata_list.append(data_property)\\n # assumes list of objects and that first entry has full list of properties\\n\\n return SchemaGenerator.__build_schema(metadata_list)\\n except Exception as e:\\n logging.error('Failed to parse json file into schema: ' + str(e))\\n raise FailedCreatingSchemaException(\\\"Failed to create schema from json file.\\\")\",\n \"def CreateTableFromJson(self, table_name, schema_json):\\n try:\\n schema = json.JSONDecoder().decode(schema_json)\\n except ValueError, e:\\n raise SchemaError('Could not parse fields:\\\\n%s\\\\n%s' %\\n (schema_json, str(e)))\\n\\n conn = self._Connect()\\n result = conn.Call(\\n dict(method='bigquery.tables.insert',\\n collection='tables',\\n operation=bq.REST.INSERT,\\n params=dict(name=table_name, fields=schema)))\\n return result\",\n \"def ReadSchema(schema, bigquery_messages):\\n\\n return bigquery_messages.TableSchema(\\n fields=[\\n _TableFieldSchemaForEntry(entry, bigquery_messages)\\n for entry in schema.split(',')])\",\n \"def insert_data(table, jsonfile):\\n with open(jsonfile) as infile:\\n data = json.load(infile)\\n table_models_map[table]['insert'](data)\",\n \"def generate_wc_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'word', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'percent', 'type': 'FLOAT', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def main(input_json, output_markdown):\\n parser = Parser()\\n output_md = parser.parse_schema(json.load(input_json))\\n output_markdown.writelines(output_md)\\n click.secho(\\\"✔ Successfully parsed schema!\\\", bold=True, fg=\\\"green\\\")\",\n \"def _convert(self, fn, suffix='json', path='jsonschema', name=None,\\n root_class_name=None, data_files=[], target_class=None):\\n ie = JsonSchemaImportEngine()\\n d = os.path.join(INPUT_DIR, path)\\n schema = ie.load(os.path.join(d, f'{fn}.{suffix}'), name=name, format=suffix, root_class_name=root_class_name)\\n model_path = os.path.join(OUTPUT_DIR, f'{fn}.yaml')\\n write_schema(schema, model_path)\\n roundtrip_path = os.path.join(OUTPUT_DIR, f'{fn}.roundtrip.json')\\n with open(roundtrip_path, 'w') as stream:\\n stream.write(JsonSchemaGenerator(model_path).serialize())\\n python_path = os.path.join(OUTPUT_DIR, f'{fn}.py')\\n with open(python_path, 'w') as stream:\\n stream.write(PythonGenerator(model_path).serialize())\\n compile_python(python_path)\\n # TODO: test data_files\\n return schema\",\n \"def load_schema(filename):\\n with open(filename) as f:\\n schema = json.load(f)\\n\\n return schema\",\n \"def test_convert_json():\\n schema = pa.schema([\\n pa.field(\\\"foo\\\", pa.int32()),\\n pa.field(\\\"bar\\\", pa.int64())\\n ])\\n\\n input_path = \\\"{}/tests/fixtures/simple_json.txt\\\".format(os.getcwd())\\n expected_file = \\\"{}/tests/fixtures/simple.parquet\\\".format(os.getcwd())\\n with tempfile.NamedTemporaryFile() as f:\\n output_file = f.name\\n client.convert_json(input_path, output_file, schema)\\n output = pq.ParquetFile(output_file)\\n expected = pq.ParquetFile(expected_file)\\n assert output.metadata.num_columns == expected.metadata.num_columns\\n assert output.metadata.num_rows == expected.metadata.num_rows\\n assert output.schema.equals(expected.schema)\\n assert output.read_row_group(0).to_pydict() == expected.read_row_group(0).to_pydict()\",\n \"def from_json_file(cls, json_file:str):\\n with open(json_file) as file:\\n data = json.load(file)\\n validate(data, schema)\\n instance = cls.from_dict(data)\\n return instance\",\n \"def process_data(data):\\n # Table Name from Json file\\n table_name = data['table_name']\\n\\n # No of Column\\n column_count = data['column_count']\\n\\n # No of Row\\n row_count = data['row_count']\\n\\n # Table columns schema from Json file\\n column_properties = data['column_properties']\\n\\n # Get the row row_properties\\n row_properties = data['row_properties']\\n return table_name, column_count, row_count, column_properties, row_properties\",\n \"def deduce_schema(self, input_data, *, schema_map=None):\\n\\n if self.input_format == 'csv':\\n if self.csv_dialect:\\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\\n else:\\n reader = csv.DictReader(input_data)\\n elif self.input_format == 'json' or self.input_format is None:\\n reader = json_reader(input_data)\\n elif self.input_format == 'dict':\\n reader = input_data\\n else:\\n raise Exception(f\\\"Unknown input_format '{self.input_format}'\\\")\\n\\n if schema_map is None:\\n schema_map = OrderedDict()\\n\\n try:\\n for json_object in reader:\\n\\n # Print a progress message periodically.\\n self.line_number += 1\\n if self.line_number % self.debugging_interval == 0:\\n logging.info(f'Processing line {self.line_number}')\\n\\n # Deduce the schema from this given data record.\\n if isinstance(json_object, dict):\\n self.deduce_schema_for_record(\\n json_object=json_object,\\n schema_map=schema_map,\\n )\\n elif isinstance(json_object, Exception):\\n self.log_error(\\n f'Record could not be parsed: Exception: {json_object}'\\n )\\n if not self.ignore_invalid_lines:\\n raise json_object\\n else:\\n self.log_error(\\n 'Record should be a JSON Object '\\n f'but was a {type(json_object)}'\\n )\\n if not self.ignore_invalid_lines:\\n raise Exception(f'Record must be a JSON Object '\\n f'but was a {type(json_object)}')\\n finally:\\n logging.info(f'Processed {self.line_number} lines')\\n\\n return schema_map, self.error_logs\",\n \"def _create_schema(self, cypher_file):\\n if len(self.graph.nodes) > 0:\\n msg = \\\"Cypher file specified but the graph is not empty. Aborting.\\\"\\n raise ValueError(msg)\\n cyp = open(cypher_file, 'r').read()\\n self.graph.run(cyp)\",\n \"def _load_json_schema(filename):\\n\\n relative_path = join('schemas', filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n with open(absolute_path) as schema_file:\\n return json.loads(schema_file.read())\",\n \"def _load_json_schema(filename: str):\\n relative_path = path.join('schemas', filename)\\n absolute_path = path.join(path.dirname(__file__), relative_path)\\n\\n with open(absolute_path, 'r', encoding='utf-8') as schema_file:\\n schema = json.loads(schema_file.read())\\n\\n return schema\",\n \"def create_json_table(cur, country_json, body_json):\\n print(\\\"Creating table from JSON file\\\")\\n cur.execute('CREATE TABLE IF NOT EXISTS state_json(id INTEGER PRIMARY KEY, state TEXT, album TEXT)')\\n for idx, album in enumerate(country_json[body_json['state']]):\\n cur.execute('INSERT INTO state_json VALUES (\\\"%s\\\", \\\"%s\\\", \\\"%s\\\")' % (idx, body_json['state'], album))\",\n \"def run(\\n self,\\n input_file=sys.stdin,\\n output_file=sys.stdout,\\n schema_map=None,\\n ):\\n schema_map, error_logs = self.deduce_schema(\\n input_file, schema_map=schema_map\\n )\\n\\n for error in error_logs:\\n logging.info(\\n f\\\"Problem on line {error['line_number']}: {error['msg']}\\\"\\n )\\n\\n if self.debugging_map:\\n json.dump(schema_map, output_file, indent=2)\\n print(file=output_file)\\n else:\\n schema = self.flatten_schema(schema_map)\\n json.dump(schema, output_file, indent=2)\\n print(file=output_file)\",\n \"def create_db(db, schema_json):\\n with open(schema_json) as of:\\n schema = json.load(of, object_pairs_hook=OrderedDict)\\n # OrderedDict so that tables are created in the order specified,\\n # allowing foreign keys to reference previously defined tables\\n\\n for table_name, columns in schema.items():\\n col_types = columns.items() # dict -> tuple\\n make_table(db, table_name, col_types)\",\n \"def main(event, context):\\n # pylint: enable=unused-argument\\n data = decode(event[\\\"data\\\"])\\n to_table([data], PROJECT, DATASET, TABLE)\",\n \"def parse_raw(sqlContext, input, user):\\n df = sqlContext.read.json(input + \\\"/\\\" + user + \\\"/\\\" + user + \\\".json\\\", multiLine=True)\\n return df\",\n \"def json_to_thrift(json_str, root_thrift_class):\\r\\n return json.loads(json_str, cls=ThriftJSONDecoder, root_thrift_class=root_thrift_class)\",\n \"def extract_data(filename: str, schema_filename: str) -> DataFrame:\\n data = []\\n try:\\n with open(schema_filename) as f:\\n schema = json.load(f)\\n with open(filename) as f:\\n for line in f:\\n json_doc = json.loads(line)\\n if is_valid_data(json_doc, schema):\\n data.append(json_doc)\\n except ValueError as e:\\n log.error(f\\\"Error parsing json: {e}\\\")\\n except FileNotFoundError as e:\\n log.error(f\\\"File not found error: {e}\\\")\\n raise e\\n except Exception as e:\\n log.error(e)\\n raise e\\n return DataFrame(data)\",\n \"def _schema_write(self, table: TableSchema) -> None:\\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\\n json.dump(table, f, indent=True)\",\n \"def read_json(self, inputfile):\\n transtransfile = json.load(inputfile)\\n self.language = transfile['lang']\\n self.translations = transfile['strings']\",\n \"def generate_cooccur_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'w1', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'w2', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\\n {'name': 'log_weight', 'type': 'FLOAT', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def generate_url_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def generate_bq_schema(self, file_name, schema_file_name=None):\\n if not schema_file_name:\\n schema_file_name = f'{self.directory}/schema_temp.json'\\n os.system(f\\\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\\\")\\n\\n schema = open(schema_file_name, 'r').read()\\n\\n os.remove(schema_file_name)\\n\\n return json.loads(schema)\",\n \"def generate_data(self):\\n print(\\\"generate_data - init\\\")\\n with open(self.input_file, \\\"r\\\") as f:\\n\\n # read JSON data from input file\\n data = json.loads(f.read())\\n\\n for idx, row in enumerate(data): \\n # serialize Python dict to string\\n msg = self.serialize_json(row)\\n #print(f\\\"Linha: {row}\\\")\\n self.send(self.topic, msg)\\n self.flush()\\n #print(\\\"Sleeping\\\")\\n time.sleep(1)\",\n \"def from_dict(cls, dikt) -> 'SourceSchema':\\n return util.deserialize_model(dikt, cls)\",\n \"def test_test_body_with_file_schema(self):\\n pass\",\n \"def _load_fixture(filename):\\n\\n # Read the binary data into text\\n with open(filename, 'rb') as stream:\\n content = stream.read().decode('utf-8')\\n\\n # Decode the data as JSON\\n data = json.loads(content)\\n\\n # Instantiate a session.\\n session = Session()\\n\\n # Iterate through the entries to add them one by one.\\n for item in data:\\n # Resolve model from the table reference.\\n table = Base.metadata.tables[item['model'].split('.')[-1]]\\n\\n # Add the primary key.\\n item['fields']['id'] = item['pk']\\n\\n # Add a new row.\\n session.connection().execute(table.insert().values(**item['fields']))\\n\\n # Commit the session to the database.\\n session.commit()\",\n \"def load_json_schema(filename):\\n relative_path = join('../schema', filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n base_path = dirname(absolute_path)\\n base_uri = 'file://{}/'.format(base_path)\\n\\n with open(absolute_path) as schema_file:\\n return jsonref.loads(\\n schema_file.read(), base_uri=base_uri, jsonschema=True)\",\n \"def convert_json_to_flatbuffer_binary(json, schema, out_dir):\\n command = [FLATC, '-o', out_dir, '-b', schema, json]\\n run_subprocess(command)\",\n \"def _load_data_from_file(self, input_file_path):\\n with FileOrBufferHandler(input_file_path, 'r', \\n encoding=self.file_encoding) as input_file:\\n try:\\n data = json.load(input_file)\\n except (json.JSONDecodeError, UnicodeDecodeError):\\n input_file.seek(0)\\n data = data_utils.read_json(\\n data_generator=input_file,\\n selected_columns=self.selected_keys,\\n read_in_string=False\\n )\\n return data\",\n \"def load_schema(self, schema_file):\\n with open(schema_file) as fp:\\n for line in io.lines_in(fp):\\n parts = line.strip().split('\\\\t')\\n if len(parts) != 3:\\n raise ValueError('invalid type declaration %r' % line.strip())\\n self.declare_relation(parts[0], parts[1], parts[2])\",\n \"def transform_file(input_file_path: str, output_file_path: str):\\n\\n # Open json\\n with open(input_file_path, mode=\\\"r\\\") as in_file:\\n input_data = json.load(in_file)\\n\\n # Transform and write\\n with jsonlines.open(output_file_path, mode=\\\"w\\\", compact=True) as out_file:\\n for item in input_data[\\\"items\\\"]:\\n out_file.write(transform_item(item))\",\n \"def parse(json_string):\\n try:\\n json_data = json.loads(json_string)\\n except Exception as exn:\\n raise SchemaParseException(\\n 'Error parsing schema from JSON: %r. '\\n 'Error message: %r.'\\n % (json_string, exn))\\n\\n # Initialize the names object\\n names = Names()\\n\\n # construct the Avro Schema object\\n return schema_from_json_data(json_data, names)\",\n \"def get_inputs_from_file(filename=\\\"\\\"):\\n import json\\n\\n with open(filename) as input_text:\\n json_obj = json.load(input_text)\\n return json_obj\",\n \"def json_input():\\r\\n with open (FILE_INPUT,'rb') as file:\\r\\n data = json.load(file)\\r\\n return data['input_data'][0]\",\n \"def intermediary_to_schema(tables, relationships, output):\\n dot_file = _intermediary_to_dot(tables, relationships)\\n #graph = AGraph()\\n #graph = graph.from_string(dot_file)\\n extension = output.split('.')[-1]\\n #graph.draw(path=output, prog='dot', format=extension)\\n #Source.from_file(filename, engine='dot', format=extension)\\n return Source(dot_file, engine='dot', format=extension)\",\n \"def populate_from_json(db: Session, model: DatabaseModel, json_file: str):\\n data_exists = db.query(model).first()\\n if data_exists:\\n return\\n with open(json_file, \\\"r\\\") as file:\\n data = json.loads(file.read())\\n for obj in data:\\n db.add(model(**obj))\\n db.commit()\",\n \"def parse_and_format(file_in_path: str, file_out_path: str) -> None:\\n\\n with open(file_in_path) as input:\\n payload = json.load(input)\\n\\n records = [\\\"# Data is in the format:\\\",\\n \\\"# kem_id,kdf_id,aead_id,info,skRm,skEm,pkRm,pkEm,exporter_context,L,exported_value\\\"]\\n\\n for key in payload:\\n # Skip these to test only capabilities exposed by BoringSSL\\n if (key[\\\"mode\\\"] != MODE_BASE or\\n key[\\\"kem_id\\\"] != KEM_DHKEM_X25519_SHA256 or\\n key[\\\"kdf_id\\\"] != KDF_HKDF_SHA256 or\\n key[\\\"aead_id\\\"] == AEAD_EXPORT_ONLY):\\n continue\\n\\n for exportKey in key[\\\"exports\\\"]:\\n records.append(\\\"{},{},{},{},{},{},{},{},{},{},{}\\\"\\n .format(str(key[\\\"kem_id\\\"]),\\n str(key[\\\"kdf_id\\\"]),\\n str(key[\\\"aead_id\\\"]),\\n str(key[\\\"info\\\"]),\\n str(key[\\\"skRm\\\"]),\\n str(key[\\\"skEm\\\"]),\\n str(key[\\\"pkRm\\\"]),\\n str(key[\\\"pkEm\\\"]),\\n str(exportKey[\\\"exporter_context\\\"]),\\n str(exportKey[\\\"L\\\"]),\\n str(exportKey[\\\"exported_value\\\"])))\\n\\n\\n with open(file_out_path, \\\"w\\\") as output:\\n output.write(\\\"\\\\n\\\".join(records))\",\n \"def jsons_to_table(dir_jsons, dir_out, name, format='html'):\\n # sanity of paths\\n dir_out = sanity_util.safe_dir_path(dir_path=dir_out)\\n file_name = sanity_util.unique_file_name(dir=dir_out, fn=name, suffix='.{}'.format(format))\\n # reading JSON files\\n p_files = sorted([os.path.join(dir_jsons, p_json) for p_json in os.listdir(dir_jsons)])\\n table = defaultdict(list)\\n keys = set()\\n for p_f in p_files:\\n if p_f.lower().endswith('.json'):\\n with open(p_f, 'r') as f_json:\\n el = json.load(f_json)\\n for k in el.keys():\\n keys.add(k)\\n for p_f in p_files:\\n if p_f.lower().endswith('.json'):\\n with open(p_f, 'r') as f_json:\\n el = json.load(f_json)\\n for k in el.keys():\\n table[k].append(el[k])\\n for k in keys.difference(set(el.keys())):\\n table[k].append(None)\\n # DataFrame conversion\\n df = pd.DataFrame.from_dict(table)\\n # writing HTML table\\n if format == 'html':\\n table_str = df.to_html()\\n else:\\n table_str = df.to_latex()\\n table_str += '<script type=\\\"text/javascript\\\" src=\\\"stylize.js\\\"></script>'\\n stylize_js = js_stylize()\\n with open(os.path.join(dir_out, 'stylize.js'), 'w') as f_js:\\n f_js.write(stylize_js)\\n with open(file_name, 'w') as f_out:\\n f_out.write(table_str)\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def _read_json(cls, input_file):\\n with open(input_file) as f:\\n return json.load(f)\",\n \"def _read_json(cls, input_file):\\n with open(input_file) as f:\\n return json.load(f)\",\n \"def all_to_intermediary(filename_or_input, schema=None):\\n # Try to convert from the name of the class\\n input_class_name = filename_or_input.__class__.__name__\\n try:\\n this_to_intermediary = switch_input_class_to_method[input_class_name]\\n tables, relationships = this_to_intermediary(filename_or_input)\\n return tables, relationships\\n except KeyError:\\n pass\\n\\n # try to read markdown file.\\n if isinstance(filename_or_input, basestring):\\n if filename_or_input.split('.')[-1] == 'er':\\n return markdown_file_to_intermediary(filename_or_input)\\n\\n # try to read a markdown in a string\\n if not isinstance(filename_or_input, basestring):\\n if all(isinstance(e, basestring) for e in filename_or_input):\\n return line_iterator_to_intermediary(filename_or_input)\\n\\n # try to read DB URI.\\n try:\\n make_url(filename_or_input)\\n return database_to_intermediary(filename_or_input, schema=schema)\\n except ArgumentError:\\n pass\\n\\n msg = 'Cannot process filename_or_input {}'.format(input_class_name)\\n raise ValueError(msg)\",\n \"def __csv_schema_generator(file):\\n try:\\n # Parses the first line of the file to get all the headers.\\n metadata = str(file.readline().decode('utf-8')).strip().split(',')\\n # Will be further implemented in phase 3.\\n return SchemaGenerator.__build_schema(metadata)\\n except Exception as e:\\n logging.error('Failed to parse csv file into schema: ' + str(e))\\n raise FailedCreatingSchemaException(\\\"Failed to create schema from csv file.\\\")\",\n \"def schema_load(filename):\\n print(uc.schema_load(filename))\",\n \"def read_json_schema(schema_file_path):\\n with open(schema_file_path) as f:\\n schema = json.load(f)\\n return schema\",\n \"def _read_json(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return json.load(f)\",\n \"def _read_json(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return json.load(f)\",\n \"def _read_data(cls, input_file): # 这里是对文件的处理\\r\\n with open(input_file, encoding='utf-8') as f:\\r\\n lines = []\\r\\n\\r\\n for line in f:\\r\\n line = json.loads(line)\\r\\n words = ' '.join(list(line['natural']))\\r\\n labels = ' '.join(line['tag_seq'])\\r\\n poss = line['pos_seq']\\r\\n dps = line['dp_seq']\\r\\n head = line['head_seq']\\r\\n lines.append([labels, words, poss, dps, head])\\r\\n\\r\\n return lines\",\n \"def from_json_file(cls, json_file):\\n with tf.io.gfile.GFile(json_file, \\\"r\\\") as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def load_from_json(self, json_fp: str):\\n # TODO:\\n pass\",\n \"def from_json_file(cls, json_file):\\n with tf.io.gfile.GFile(json_file, \\\"r\\\") as reader:\\n text = reader.read()\\n return cls(**json.loads(text))\",\n \"def from_json(self, file_path):\\n with open(file_path) as file:\\n jsonstr = file.read()\\n handler_dict = json.loads(jsonstr)\\n self.from_dict(handler_dict)\",\n \"def import_schemas_from_file():\\n with open('./tblSchemas') as schemas_file:\\n schemas = {}\\n for line in schemas_file:\\n line = line.split()\\n if len(line) == 0: continue\\n if line[0] == 'tblname':\\n tbl_name = line[1]\\n schemas[tbl_name] = []\\n else:\\n schemas[tbl_name].append(line)\\n return schemas\",\n \"def get_schema():\\n if not os.path.isfile(_schema_file):\\n create_schema()\\n with open(_schema_file, 'r') as fd:\\n out = decode_json(fd)\\n return out\",\n \"def convert_schema(bco, filename, mapping_dict):\\n for item in mapping_dict['to_swap']:\\n value_list = mapping_dict['to_swap'][item]\\n for i in range(0, len(value_list)):\\n rename_dict_key_HELPER(bco, value_list[i]['index'],\\n value_list[i]['value']) # Change key name\\n\\n for item in mapping_dict['to_delete']:\\n value_list = mapping_dict['to_delete'][item]\\n for i in range(0, len(value_list)):\\n delete_key_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # delete key\\n\\n for item in mapping_dict['to_add']:\\n value_list = mapping_dict['to_add'][item]\\n for i in range(0, len(value_list)):\\n set_key_in_dict_HELPER(bco, value_list[i]['index'], value_list[i]['value']) # add key\\n\\n new_bco = bco\\n try:\\n new_bco['provenance_domain'][\\n 'modified'] = datetime.now().isoformat() # change date to current\\n\\n temp_bco = dict(new_bco)\\n del temp_bco['object_id'], temp_bco['etag'], temp_bco['spec_version']\\n\\n new_bco['spec_version'] = \\\"https://w3id.org/ieee/ieee-2791-schema/2791object.json\\\"\\n new_bco[\\\"etag\\\"] = sha256(json.dumps(temp_bco).encode('utf-8')).hexdigest()\\n except KeyError: # Vital field was missing, will be caught by final error checker\\n pass\\n file = open(filename, \\\"w\\\")\\n json.dump(new_bco, file, indent=4)\",\n \"def test_json():\\n schemas = {\\n 'schema-languages': 'bible/languages.json',\\n 'schema-book-metadata': 'bible/book-metadata.json',\\n 'schema-bible': 'bible/bible-*.json'\\n }\\n for schema_name, data_path_glob in schemas.items():\\n schema_path = 'schemas/{}.json'.format(schema_name)\\n with open(schema_path) as schema_file:\\n schema = json.load(schema_file)\\n data_paths = glob.iglob(data_path_glob)\\n for data_path in data_paths:\\n with open(data_path) as data_file:\\n data = json.load(data_file)\\n yield jsonschema.validate, data, schema\",\n \"def _load_schema(self, json_schema):\\n # use jsonrefs to resolve all $refs in json\\n data = jsonref.loads(json.dumps(json_schema))\\n return self.__initialise_template(data)\",\n \"def test_read_json_schema():\\n json_schema = os.path.join(TEST_DATA_PATH, 'example_schema.json')\\n schema_tree = schema.load_schema(json_schema, resolve_references=True)\\n schema.check_schema(schema_tree)\",\n \"def get_schema(filename: str) -> dict:\\n return _load_json_schema(filename)\",\n \"def _import(format, input, config):\\n if input:\\n with open(input, 'rb') as f:\\n data = f.read()\\n else:\\n data = sys.stdin.read()\\n\\n dataset = tablib.Dataset()\\n setattr(dataset, format, data)\\n\\n _add_changelogs(config, dataset.dict)\",\n \"def read_json(self, filename, multi_line=False, schema=None):\\n self.logger.info(\\\"# Reading a JSON file \\\" + filename)\\n sql_context = SQLContext(self.spark)\\n df = None\\n if schema is None and multi_line == False:\\n df = sql_context.read.json(filename)\\n elif multi_line:\\n df = sql_context.read.json(filename, multiLine=multi_line)\\n elif schema is not None:\\n df = sql_context.read.json(filename, schema=schema)\\n return df\",\n \"def _load_json_schema(filename):\\n\\n relative_path = join(\\\"schemas\\\", filename)\\n absolute_path = join(dirname(__file__), relative_path)\\n\\n base_path = dirname(absolute_path)\\n base_uri = 'file://{}/'.format(base_path)\\n\\n print(f\\\"base uri {base_uri}\\\")\\n print(f\\\"base path {base_path}\\\")\\n print(f\\\"relative_path {relative_path}\\\")\\n print(f\\\"absolute_path {absolute_path}\\\")\\n\\n with open(absolute_path) as schema_file:\\n return jsonref.loads(schema_file.read(), base_uri=base_uri, jsonschema=True)\",\n \"def readjamschema(schema):\\n raise NotImplementedError(msg)\",\n \"def load(file_name):\\n with open(file_name, newline='') as f:\\n reader = csv.reader(f)\\n data = list(reader)\\n\\n schema = [x.strip() for x in data[0]]\\n table = [[int(el) for el in row] for row in data[1:]]\\n\\n return schema, table\",\n \"def get_schema(path):\\n with open(path, 'r') as f:\\n return json.load(f)\",\n \"def test_schema_invalid_json(self):\\n schema_0_input = schema_nested_2_invalid_JSON\\n\\n # if you uncomment this line:\\n # schema_0_input = schema_nested_2\\n # this will fail the test: Failed: DID NOT RAISE <class 'simplejson.scanner.JSONDecodeError'>\\n # because this is a valid schema\\n\\n with pytest.raises(simplejson.scanner.JSONDecodeError):\\n msg = singer.parse_message(schema_0_input)\",\n \"def create_table_from_file():\\n\\n full_path = os.getcwd()\\n file_name = full_path + \\\"/inventory/inventory.csv\\\"\\n\\n if os.path.exists(file_name):\\n table = data_manager.get_table_from_file(file_name)\\n\\n else:\\n ui.print_error_message(\\\"There is no file to read!\\\")\\n table = []\\n\\n return table\",\n \"def tsv_to_json(tsv_file, json_file):\\n import csv\\n import json\\n\\n try:\\n with open(tsv_file, 'r') as tsvFile:\\n file_reader = csv.DictReader(tsvFile, dialect='excel-tab')\\n row_list = list(file_reader)\\n with open(json_file, 'w+') as jsonFile:\\n jsonFile.write(json.dumps(row_list, indent=4))\\n return 1\\n except (ValueError, FileNotFoundError):\\n return 0\",\n \"async def _process_create_data(self, data: dict) -> dict:\\n return self.SCHEMA(data)\",\n \"def read_data(self):\\n if self._file.is_file():\\n try:\\n self._data = read_json_file(self._file)\\n except (OSError, json.JSONDecodeError):\\n _LOGGER.warning(\\\"Can't read %s\\\", self._file)\\n self._data = {}\\n\\n # Validate\\n try:\\n self._data = self._schema(self._data)\\n except vol.Invalid as ex:\\n _LOGGER.error(\\\"Can't parse %s: %s\\\",\\n self._file, humanize_error(self._data, ex))\\n\\n # Reset data to default\\n _LOGGER.warning(\\\"Reset %s to default\\\", self._file)\\n self._data = self._schema({})\",\n \"def _mashup_json_to_table(json_obj, col_config=None):\\n\\n dataTable = Table(masked=True)\\n absCorr = None\\n\\n if not all(x in json_obj.keys() for x in ['fields', 'data']):\\n raise KeyError(\\\"Missing required key(s) 'data' and/or 'fields.'\\\")\\n\\n for col, atype in [(x['name'], x['type']) for x in json_obj['fields']]:\\n\\n # Removing \\\"_selected_\\\" column\\n if col == \\\"_selected_\\\":\\n continue\\n\\n # reading the colum config if given\\n ignoreValue = None\\n if col_config:\\n colProps = col_config.get(col, {})\\n ignoreValue = colProps.get(\\\"ignoreValue\\\", None)\\n\\n # making type adjustments\\n if atype == \\\"string\\\":\\n atype = \\\"str\\\"\\n ignoreValue = \\\"\\\" if (ignoreValue is None) else ignoreValue\\n if atype == \\\"boolean\\\":\\n atype = \\\"bool\\\"\\n if atype == \\\"int\\\": # int arrays do not admit Non/nan vals\\n atype = np.int64\\n ignoreValue = -999 if (ignoreValue is None) else ignoreValue\\n if atype == \\\"date\\\":\\n atype = \\\"str\\\"\\n ignoreValue = \\\"\\\" if (ignoreValue is None) else ignoreValue\\n\\n # Make the column list (don't assign final type yet or there will be errors)\\n colData = np.array([x.get(col, ignoreValue) for x in json_obj['data']], dtype=object)\\n if ignoreValue is not None:\\n colData[np.where(np.equal(colData, None))] = ignoreValue\\n\\n # no consistant way to make the mask because np.equal fails on ''\\n # and array == value fails with None\\n if atype == 'str':\\n colMask = (colData == ignoreValue)\\n else:\\n colMask = np.equal(colData, ignoreValue)\\n\\n # add the column\\n dataTable.add_column(MaskedColumn(colData.astype(atype), name=col, mask=colMask))\\n\\n return dataTable\",\n \"def load_dict_to_delta_table(spark, s3_data_bucket, table_schema, table_name, data, overwrite=False):\\n table_to_col_names_dict = {}\\n table_to_col_names_dict[\\\"transaction_fabs\\\"] = TRANSACTION_FABS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_fpds\\\"] = TRANSACTION_FPDS_COLUMNS\\n table_to_col_names_dict[\\\"transaction_normalized\\\"] = list(TRANSACTION_NORMALIZED_COLUMNS)\\n table_to_col_names_dict[\\\"awards\\\"] = list(AWARDS_COLUMNS)\\n table_to_col_names_dict[\\\"financial_accounts_by_awards\\\"] = list(FINANCIAL_ACCOUNTS_BY_AWARDS_COLUMNS)\\n\\n table_to_col_info_dict = {}\\n for tbl_name, col_info in zip(\\n (\\\"transaction_fabs\\\", \\\"transaction_fpds\\\"), (TRANSACTION_FABS_COLUMN_INFO, TRANSACTION_FPDS_COLUMN_INFO)\\n ):\\n table_to_col_info_dict[tbl_name] = {}\\n for col in col_info:\\n table_to_col_info_dict[tbl_name][col.dest_name] = col\\n\\n # Make sure the table has been created first\\n call_command(\\n \\\"create_delta_table\\\",\\n \\\"--destination-table\\\",\\n table_name,\\n \\\"--alt-db\\\",\\n table_schema,\\n \\\"--spark-s3-bucket\\\",\\n s3_data_bucket,\\n )\\n\\n if data:\\n insert_sql = f\\\"INSERT {'OVERWRITE' if overwrite else 'INTO'} {table_schema}.{table_name} VALUES\\\\n\\\"\\n row_strs = []\\n for row in data:\\n value_strs = []\\n for col_name in table_to_col_names_dict[table_name]:\\n value = row.get(col_name)\\n if isinstance(value, (str, bytes)):\\n # Quote strings for insertion into DB\\n value_strs.append(f\\\"'{value}'\\\")\\n elif isinstance(value, (date, datetime)):\\n # Convert to string and quote\\n value_strs.append(f\\\"\\\"\\\"'{value.isoformat()}'\\\"\\\"\\\")\\n elif isinstance(value, bool):\\n value_strs.append(str(value).upper())\\n elif isinstance(value, (Sequence, Set)):\\n # Assume \\\"sequences\\\" must be \\\"sequences\\\" of strings, so quote each item in the \\\"sequence\\\"\\n value = [f\\\"'{item}'\\\" for item in value]\\n value_strs.append(f\\\"ARRAY({', '.join(value)})\\\")\\n elif value is None:\\n col_info = table_to_col_info_dict.get(table_name)\\n if (\\n col_info\\n and col_info[col_name].delta_type.upper() == \\\"BOOLEAN\\\"\\n and not col_info[col_name].handling == \\\"leave_null\\\"\\n ):\\n # Convert None/NULL to false for boolean columns unless specified to leave the null\\n value_strs.append(\\\"FALSE\\\")\\n else:\\n value_strs.append(\\\"NULL\\\")\\n else:\\n value_strs.append(str(value))\\n\\n row_strs.append(f\\\" ({', '.join(value_strs)})\\\")\\n\\n sql = \\\"\\\".join([insert_sql, \\\",\\\\n\\\".join(row_strs), \\\";\\\"])\\n spark.sql(sql)\",\n \"def convert_json_1(json):\\n\\n # TODO Add batch details to json format\\n # TODO Get default direct entry batch details if not provided\\n\\n LOGGER.debug('convert json message:%s', json)\\n direct_entry = {\\n 'record_type': '1',\\n 'reel_seq_num': '01',\\n 'name_fin_inst': 'SUN',\\n 'user_name': 'hello',\\n 'user_num': '123456',\\n 'file_desc': 'payroll',\\n 'date_for_process': datetime.strptime(json['post_date'], '%Y-%m-%d').strftime('%d%m%y'),\\n 'bsb_number': json['to_routing'],\\n 'account_number': json['to_account'],\\n 'indicator': ' ',\\n 'tran_code': '13' if json['tran_type'] == 'db' else '53',\\n 'amount': '{amount:010}'.format(amount=json['amount']), # $2.00\\n 'account_title': json['to_name'],\\n 'lodgement_ref': json['to_description'],\\n 'trace_bsb_number': json['from_routing'],\\n 'trace_account_number': json['from_account'],\\n 'name_of_remitter': json['from_name'],\\n 'withholding_tax_amount': '00000000',\\n }\\n\\n return direct_entry\",\n \"def create_datastructure_from_yaml_file(self):\\n ## loading the YAML file\\n try:\\n with open(self.source) as f:\\n hbaseSchemaDic = yaml.load(f) \\n except:\\n msg = \\\"Error: the HBase substructure could not be created. File %s could not be loaded. Please check the syntax of the '.yml' file.\\\" % self.source \\n raise createDataStructureException(msg)\\n status = \\\"failed\\\" \\n\\n try:\\n c = Connection(host = self.host, port = int(self.port))\\n tbls = c.tables()\\n tbls = [str(t) for t in tbls]\\n ## check that none of the tables already exists \\n for t in hbaseSchemaDic.keys():\\n if t in tbls:\\n msg = \\\"Error: the table %s already exists. If you use starbase in python you can drop the table by using \\\\n>>> from starbase import Connection\\\\n>>> c = Connection()\\\\n>>> t = c.table(%s)\\\\n>>> t.drop()\\\" % (t,t) \\n print(msg)\\n status = \\\"failed\\\"\\n raise createDataStructureException(msg)\\n\\n ## if none of the table(s) do(es) not exist, let's create them(it) \\n for t in hbaseSchemaDic.keys():\\n columnFamilies = hbaseSchemaDic[t]['columnFamilies'].keys()\\n tC = c.table(t)\\n tC.create(*columnFamilies)\\n status = \\\"succeeded\\\"\\n \\n except:\\n msg = \\\"Error: the HBase substructure could not be created. Please check your connection parameters or the syntax in your '.yml' file.\\\"\\n raise createDataStructureException(msg)\\n status = \\\"failed\\\"\\n\\n return(status)\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding=\\\"utf-8\\\") as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def read_json_breakdown(cls, fname):\\n if not os.path.exists(fname):\\n raise RuntimeError\\n\\n with open(fname, 'r') as data_file:\\n return cls.fixup_from_json(data_file.read())\",\n \"def _meta_json_to_database(self):\\n\\n sqlalchemy_metadata = MetaData() # this is unrelated to our meta.json\\n meta_table = Table('meta', sqlalchemy_metadata,\\n Column('meta', String))\\n\\n sqlalchemy_metadata.create_all(self.engine)\\n json_string = json.dumps(self.meta)\\n ins = meta_table.insert().values(meta=json_string)\\n conn = self.engine.connect()\\n conn.execute(\\\"DELETE FROM meta;\\\")\\n conn.execute(ins)\",\n \"def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\\n try:\\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\\n self.columns = tabels_schema.migrationTable.MigrationColumns\\n except Exception as err:\\n logger.error(\\\"parse_migration_tables [error] -> %s\\\" % err)\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, \\\"r\\\", encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\",\n \"def _read_jsonl(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return [json.loads(ln) for ln in f]\",\n \"def _read_jsonl(cls, input_file):\\n with open(input_file, 'rb') as f:\\n return [json.loads(ln) for ln in f]\",\n \"def create_deft_table_json_mappings():\\n mappings = list()\\n mappings.append(JsonColumnMapping(columnName=\\\"rownumber\\\", jsonPath=\\\"$.rownumber\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"rowguid\\\", jsonPath=\\\"$.rowguid\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xdouble\\\", jsonPath=\\\"$.xdouble\\\", cslDataType=\\\"real\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xfloat\\\", jsonPath=\\\"$.xfloat\\\", cslDataType=\\\"real\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xbool\\\", jsonPath=\\\"$.xbool\\\", cslDataType=\\\"bool\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint16\\\", jsonPath=\\\"$.xint16\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint32\\\", jsonPath=\\\"$.xint32\\\", cslDataType=\\\"int\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xint64\\\", jsonPath=\\\"$.xint64\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint8\\\", jsonPath=\\\"$.xuint8\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint16\\\", jsonPath=\\\"$.xuint16\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint32\\\", jsonPath=\\\"$.xuint32\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xuint64\\\", jsonPath=\\\"$.xuint64\\\", cslDataType=\\\"long\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xdate\\\", jsonPath=\\\"$.xdate\\\", cslDataType=\\\"datetime\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xsmalltext\\\", jsonPath=\\\"$.xsmalltext\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xtext\\\", jsonPath=\\\"$.xtext\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xnumberAsText\\\", jsonPath=\\\"$.xnumberAsText\\\", cslDataType=\\\"string\\\"))\\n mappings.append(JsonColumnMapping(columnName=\\\"xtime\\\", jsonPath=\\\"$.xtime\\\", cslDataType=\\\"timespan\\\"))\\n mappings.append(\\n JsonColumnMapping(columnName=\\\"xtextWithNulls\\\", jsonPath=\\\"$.xtextWithNulls\\\", cslDataType=\\\"string\\\")\\n )\\n mappings.append(\\n JsonColumnMapping(columnName=\\\"xdynamicWithNulls\\\", jsonPath=\\\"$.xdynamicWithNulls\\\", cslDataType=\\\"dynamic\\\")\\n )\\n return mappings\",\n \"def create_schema(overwrite=False):\\n if (not overwrite) and os.path.isfile(_schema_file):\\n raise RuntimeError(\\\"Schema file already exists.\\\")\\n schema = {\\n 'title': 'obj',\\n 'description': 'A mapping container for Obj 3D data.',\\n 'type': 'object',\\n 'required': ['vertices', 'faces'],\\n 'definitions': {\\n 'vertex': {\\n 'description': 'Map describing a single vertex.',\\n 'type': 'object', 'required': ['x', 'y', 'z'],\\n 'additionalProperties': False,\\n 'properties': {'x': {'type': _coord_type},\\n 'y': {'type': _coord_type},\\n 'z': {'type': _coord_type},\\n 'red': {'type': _color_type},\\n 'blue': {'type': _color_type},\\n 'green': {'type': _color_type},\\n 'w': {'type': _coord_type, 'default': 1.0}}},\\n 'param': {\\n 'description': 'Map describing a single parameter space point.',\\n 'type': 'object', 'required': ['u', 'v'],\\n 'additionalProperties': False,\\n 'properties': {'u': {'type': _coord_type},\\n 'v': {'type': _coord_type},\\n 'w': {'type': _coord_type, 'default': 1.0}}},\\n 'normal': {\\n 'description': 'Map describing a single normal.',\\n 'type': 'object', 'required': ['i', 'j', 'k'],\\n 'additionalProperties': False,\\n 'properties': {'i': {'type': _coord_type},\\n 'j': {'type': _coord_type},\\n 'k': {'type': _coord_type}}},\\n 'texcoord': {\\n 'description': 'Map describing a single texture vertex.',\\n 'type': 'object', 'required': ['u'],\\n 'additionalProperties': False,\\n 'properties': {'u': {'type': _coord_type},\\n 'v': {'type': _coord_type, 'default': 0.0},\\n 'w': {'type': _coord_type, 'default': 0.0}}},\\n 'point': {\\n 'description': 'Array of vertex indices describing a set of points.',\\n 'type': 'array', 'minItems': 1,\\n 'items': {'type': _index_type}},\\n 'line': {\\n 'description': ('Array of vertex indices and texture indices '\\n + 'describing a line.'),\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties':\\n {'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type}}}},\\n 'face': {\\n 'description': ('Array of vertex, texture, and normal indices '\\n + 'describing a face.'),\\n 'type': 'array', 'minItems': 3,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties':\\n {'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type},\\n 'normal_index': {'type': _index_type}}}},\\n 'curve': {\\n 'description': 'Properties of describing a curve.',\\n 'type': 'object', 'required': ['starting_param', 'ending_param',\\n 'vertex_indices'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'starting_param': {'type': _coord_type},\\n 'ending_param': {'type': _coord_type},\\n 'vertex_indices': {\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': _index_type}}}},\\n 'curve2D': {\\n 'description': ('Array of parameter indices describine a 2D curve on '\\n + 'a surface.'),\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': _index_type}},\\n 'surface': {\\n 'description': 'Properties describing a surface.',\\n 'type': 'object', 'required': ['starting_param_u', 'ending_param_u',\\n 'starting_param_v', 'ending_param_v',\\n 'vertex_indices'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'starting_param_u': {'type': _coord_type},\\n 'ending_param_u': {'type': _coord_type},\\n 'starting_param_v': {'type': _coord_type},\\n 'ending_param_v': {'type': _coord_type},\\n 'vertex_indices': {\\n 'type': 'array', 'minItems': 2,\\n 'items': {'type': 'object', 'required': ['vertex_index'],\\n 'additionalProperties': False,\\n 'properties': {\\n 'vertex_index': {'type': _index_type},\\n 'texcoord_index': {'type': _index_type},\\n 'normal_index': {'type': _index_type}}}}}}},\\n 'properties': {\\n 'material': {\\n 'description': 'Name of the material to use.',\\n 'type': ['unicode', 'string']},\\n 'vertices': {\\n 'description': 'Array of vertices.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/vertex'}},\\n 'params': {\\n 'description': 'Array of parameter coordinates.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/param'}},\\n 'normals': {\\n 'description': 'Array of normals.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/normal'}},\\n 'texcoords': {\\n 'description': 'Array of texture vertices.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/texcoord'}},\\n 'points': {\\n 'description': 'Array of points.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/point'}},\\n 'lines': {\\n 'description': 'Array of lines.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/line'}},\\n 'faces': {\\n 'description': 'Array of faces.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/face'}},\\n 'curves': {\\n 'description': 'Array of curves.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/curve'}},\\n 'curve2Ds': {\\n 'description': 'Array of curve2Ds.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/curve2D'}},\\n 'surfaces': {\\n 'description': 'Array of surfaces.',\\n 'type': 'array', 'items': {'$ref': '#/definitions/surface'}}},\\n 'dependencies': {\\n 'lines': ['vertices'],\\n 'faces': ['vertices'],\\n 'curves': ['vertices'],\\n 'curve2Ds': ['params'],\\n 'surfaces': ['vertices']}}\\n with open(_schema_file, 'w') as fd:\\n encode_json(schema, fd, indent='\\\\t')\",\n \"def generate_package_from_report_filepath(input_path, options = None):\\n try:\\n vt_file = open(input_path, 'r')\\n vt_dict = json.load(vt_file)\\n except:\\n print('\\\\nError: Error in parsing input file. Please check to ensure that it is valid JSON.')\\n return\\n \\n return vtpack.vt_report_to_maec_package(vt_dict, options)\",\n \"def import_into_db(json_file):\\n db = get_db()\\n\\n with current_app.open_resource(json_file) as f:\\n reports = json.load(f)\\n\\n for element in reports[\\\"elements\\\"]:\\n entry = (\\n element[\\\"id\\\"],\\n element[\\\"source\\\"],\\n element[\\\"sourceIdentityId\\\"],\\n element[\\\"state\\\"],\\n element[\\\"created\\\"],\\n element[\\\"reference\\\"][\\\"referenceId\\\"],\\n element[\\\"reference\\\"][\\\"referenceType\\\"],\\n element[\\\"payload\\\"][\\\"reportType\\\"],\\n element[\\\"payload\\\"][\\\"reportId\\\"],\\n element[\\\"payload\\\"][\\\"referenceResourceId\\\"],\\n element[\\\"payload\\\"][\\\"referenceResourceType\\\"],\\n element[\\\"payload\\\"][\\\"message\\\"],\\n )\\n db.execute(INSERT_INTO_REPORTS, entry)\\n\\n db.commit()\",\n \"def json_schema(schema_file=None, output=\\\"-\\\"):\\n schemas = read_yaml(schema_file)\\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))\",\n \"def from_json_file(cls, json_file):\\n with open(json_file, 'r', encoding='utf-8') as reader:\\n text = reader.read()\\n return cls.from_dict(json.loads(text))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6506698","0.6255999","0.6189637","0.60093594","0.59361964","0.5880678","0.5861754","0.5762274","0.56616706","0.56331164","0.5612857","0.55776805","0.5533528","0.55065984","0.55045223","0.548444","0.547434","0.54314774","0.5346988","0.5327368","0.5307453","0.5267999","0.52455944","0.52326703","0.52325064","0.5219136","0.5207536","0.5187294","0.5183731","0.51769954","0.51745486","0.51707107","0.5170645","0.5158985","0.51522464","0.51227444","0.51213485","0.5113382","0.5110196","0.5099857","0.5093744","0.5089529","0.5088614","0.508273","0.5077681","0.5069668","0.5065103","0.5055063","0.50539035","0.50539035","0.50469744","0.50469744","0.50306594","0.50274265","0.502586","0.5005657","0.5004016","0.5004016","0.4997759","0.4997609","0.4986268","0.498196","0.49683973","0.49655133","0.496366","0.49594378","0.49467462","0.49407235","0.4928758","0.492373","0.4923461","0.49174178","0.49124745","0.48915982","0.48891523","0.48878503","0.48864958","0.48769042","0.48686188","0.48567456","0.48541322","0.48476815","0.4841311","0.48368114","0.48329535","0.48315528","0.48306122","0.48293504","0.48196423","0.4817549","0.4817549","0.4817549","0.48168716","0.48168716","0.48162666","0.4815631","0.481176","0.4809378","0.48069832","0.4803606"],"string":"[\n \"0.6506698\",\n \"0.6255999\",\n \"0.6189637\",\n \"0.60093594\",\n \"0.59361964\",\n \"0.5880678\",\n \"0.5861754\",\n \"0.5762274\",\n \"0.56616706\",\n \"0.56331164\",\n \"0.5612857\",\n \"0.55776805\",\n \"0.5533528\",\n \"0.55065984\",\n \"0.55045223\",\n \"0.548444\",\n \"0.547434\",\n \"0.54314774\",\n \"0.5346988\",\n \"0.5327368\",\n \"0.5307453\",\n \"0.5267999\",\n \"0.52455944\",\n \"0.52326703\",\n \"0.52325064\",\n \"0.5219136\",\n \"0.5207536\",\n \"0.5187294\",\n \"0.5183731\",\n \"0.51769954\",\n \"0.51745486\",\n \"0.51707107\",\n \"0.5170645\",\n \"0.5158985\",\n \"0.51522464\",\n \"0.51227444\",\n \"0.51213485\",\n \"0.5113382\",\n \"0.5110196\",\n \"0.5099857\",\n \"0.5093744\",\n \"0.5089529\",\n \"0.5088614\",\n \"0.508273\",\n \"0.5077681\",\n \"0.5069668\",\n \"0.5065103\",\n \"0.5055063\",\n \"0.50539035\",\n \"0.50539035\",\n \"0.50469744\",\n \"0.50469744\",\n \"0.50306594\",\n \"0.50274265\",\n \"0.502586\",\n \"0.5005657\",\n \"0.5004016\",\n \"0.5004016\",\n \"0.4997759\",\n \"0.4997609\",\n \"0.4986268\",\n \"0.498196\",\n \"0.49683973\",\n \"0.49655133\",\n \"0.496366\",\n \"0.49594378\",\n \"0.49467462\",\n \"0.49407235\",\n \"0.4928758\",\n \"0.492373\",\n \"0.4923461\",\n \"0.49174178\",\n \"0.49124745\",\n \"0.48915982\",\n \"0.48891523\",\n \"0.48878503\",\n \"0.48864958\",\n \"0.48769042\",\n \"0.48686188\",\n \"0.48567456\",\n \"0.48541322\",\n \"0.48476815\",\n \"0.4841311\",\n \"0.48368114\",\n \"0.48329535\",\n \"0.48315528\",\n \"0.48306122\",\n \"0.48293504\",\n \"0.48196423\",\n \"0.4817549\",\n \"0.4817549\",\n \"0.4817549\",\n \"0.48168716\",\n \"0.48168716\",\n \"0.48162666\",\n \"0.4815631\",\n \"0.481176\",\n \"0.4809378\",\n \"0.48069832\",\n \"0.4803606\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.53971493"},"document_rank":{"kind":"string","value":"18"}}},{"rowIdx":2281,"cells":{"query":{"kind":"string","value":"Set projectId value for a BigQueryXXXRequests."},"document":{"kind":"string","value":"def SetProjectId(ref, args, request):\n del ref\n project = args.project or properties.VALUES.core.project.Get(required=True)\n project_ref = resources.REGISTRY.Parse(project,\n collection='bigquery.projects')\n request.projectId = project_ref.Name()\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def set_project_quotas(self, project_id, request_model, extra_headers=None,\n use_auth=True, user_name=None):\n resp = self.client.post(\n 'project-quotas/' + project_id,\n request_model=request_model,\n response_model_type=quota_models.ProjectQuotaModel,\n extra_headers=extra_headers,\n use_auth=use_auth, user_name=user_name)\n return resp","def set_project(project_id):\n return fluent.set_project(project_id)","def set_project_id(self, project_id):\n self._project_id = project_id","def project_id(self, project_id):\n\n self._project_id = project_id","def project_id(self, project_id):\n\n self._project_id = project_id","def project(self, value):\n\n if self._project != value:\n self._project = value\n self._update_page()","def scope_project(self, project_key):\n self.raw['scope'] = 'PROJECT'\n self.raw['projectKey'] = project_key\n return self","def set_or_create_project(conn: BlitzGateway, project: Union[str, int],\n across_groups: Optional[bool] = True) -> int:\n if isinstance(project, str):\n project_id = post_project(conn, project)\n print(f'Created new Project:{project_id}')\n elif (isinstance(project, int)):\n project_id = project\n else:\n raise TypeError(\"'project' must be str or int\")\n return project_id","def change_project(self, project, project_format='id'):\n name = 'tenant' if self.api_version == 2 else 'project'\n self.creds['%s_%s' % (name, project_format)] = project\n opposite_format = 'name' if project_format == 'id' else 'id'\n del self.creds['%s_%s' % (name, opposite_format)]","def updateProject(self, projectId,payload):\n uri = \"/v1/projects/\" +str(projectId)\n response = self.client.put(uri,payload)\n return response","def project_name(self, project_name):\n\n self._project_name = project_name","def project(self, project):\n self._project = project","def project(self, project):\n self._project = project","def set_keystone_v3_project(self, **kwargs):\n LOG_OBJ.debug(\"Creating the project.\")\n\n _url = \"http://\" + self.host_ip + \":35357/v3/projects/\" + \\\n str(kwargs['project_id'])\n _headers = {'x-auth-token': self.cloud_admin_info[\"token_domain\"],\n 'content-type': 'application/json'}\n\n _project_info = {\"project\": {}}\n for argument in [\"name\", \"description\", \"domain_id\",\n \"enabled\", \"disabled\"]:\n try:\n _project_info['project'].update(\n {argument: kwargs[argument]})\n except KeyError:\n pass\n _body = json.dumps(_project_info)\n response = self.request(\"PATCH\", _url, _headers, _body)\n\n if response is None:\n LOG_OBJ.error(\"No response from Server while set the project\")\n print (\"No response from Server while set the project\")\n return response\n\n if response.status not in [200, 201, 202, 203, 204]:\n LOG_OBJ.error(\" Set project Failed with status %s and error : %s\" %\n (response.status, response.data))\n print (\" Set project Failed with status %s and error : %s\" %\n (response.status, response.data))\n return response.status\n\n return True","def update_project(self, project_id, project):\n\n with self._transaction.cursor() as cur:\n # ensure this project exists\n cur.execute(\n \"SELECT project_id \"\n \"FROM barcodes.project \"\n \"WHERE project_id=%s;\",\n (project_id,))\n\n row = cur.fetchone()\n if row is None:\n raise NotFound(\"No project with ID %s\" % project_id)\n\n query = f\"\"\"\n UPDATE barcodes.project\n SET {p.DB_PROJ_NAME_KEY}=%s,\n {p.SUBPROJECT_NAME_KEY}=%s,\n {p.ALIAS_KEY}=%s,\n {p.IS_MICROSETTA_KEY}=%s,\n {p.SPONSOR_KEY}=%s,\n {p.COORDINATION_KEY}=%s,\n {p.CONTACT_NAME_KEY}=%s,\n {p.ADDTL_CONTACT_NAME_KEY}=%s,\n {p.CONTACT_EMAIL_KEY}=%s,\n {p.DEADLINES_KEY}=%s,\n {p.NUM_SUBJECTS_KEY}=%s,\n {p.NUM_TIMEPOINTS_KEY}=%s,\n {p.START_DATE_KEY}=%s,\n {p.BANK_SAMPLES_KEY}=%s,\n {p.PLATING_START_DATE_KEY}=%s,\n {p.DISPOSITION_COMMENTS_KEY}=%s,\n {p.COLLECTION_KEY}=%s,\n {p.IS_FECAL_KEY}=%s,\n {p.IS_SALIVA_KEY}=%s,\n {p.IS_SKIN_KEY}=%s,\n {p.IS_BLOOD_KEY}=%s,\n {p.IS_OTHER_KEY}=%s,\n {p.DO_16S_KEY}=%s,\n {p.DO_SHALLOW_SHOTGUN_KEY}=%s,\n {p.DO_SHOTGUN_KEY}=%s,\n {p.DO_RT_QPCR_KEY}=%s,\n {p.DO_SEROLOGY_KEY}=%s,\n {p.DO_METATRANSCRIPTOMICS_KEY}=%s,\n {p.DO_MASS_SPEC_KEY}=%s,\n {p.MASS_SPEC_COMMENTS_KEY}=%s,\n {p.MASS_SPEC_CONTACT_NAME_KEY}=%s,\n {p.MASS_SPEC_CONTACT_EMAIL_KEY}=%s,\n {p.DO_OTHER_KEY}=%s,\n {p.BRANDING_ASSOC_INSTRUCTIONS_KEY}=%s,\n {p.BRANDING_STATUS_KEY}=%s\n WHERE project_id=%s;\"\"\"\n\n cur.execute(query,\n (\n project.project_name,\n project.subproject_name,\n project.alias,\n project.is_microsetta,\n project.sponsor,\n project.coordination,\n project.contact_name,\n project.additional_contact_name,\n project.contact_email,\n project.deadlines,\n project.num_subjects,\n project.num_timepoints,\n project.start_date,\n project.bank_samples,\n project.plating_start_date,\n project.disposition_comments,\n project.collection,\n project.is_fecal,\n project.is_saliva,\n project.is_skin,\n project.is_blood,\n project.is_other,\n project.do_16s,\n project.do_shallow_shotgun,\n project.do_shotgun,\n project.do_rt_qpcr,\n project.do_serology,\n project.do_metatranscriptomics,\n project.do_mass_spec,\n project.mass_spec_comments,\n project.mass_spec_contact_name,\n project.mass_spec_contact_email,\n project.do_other,\n project.branding_associated_instructions,\n project.branding_status,\n project_id\n ))\n return cur.rowcount == 1","def projects(self, projects):\n if (self.local_vars_configuration.client_side_validation and\n projects is not None and not isinstance(projects, int)):\n raise ValueError(\"Parameter `projects` must be an integer\") # noqa: E501\n\n self._projects = projects","def set_project(\n name\n):\n if not is_alive():\n err_msg = \"Cannot connect to getML engine. Make sure the engine is running and you are logged in.\"\n raise ConnectionRefusedError(err_msg)\n\n cmd = dict()\n cmd[\"type_\"] = \"set_project\"\n cmd[\"name_\"] = name\n\n comm.send(cmd)","def _project(request, key):\n context = request.context\n if not context.project_id:\n raise exceptions.QuotaMissingTenant()\n return {key: {key + '_id': context.project_id}}","def list_namespaced_project_request(self, **kwargs):\n\n all_params = ['pretty', 'label_selector', 'field_selector', 'watch', 'resource_version', 'timeout_seconds']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method list_namespaced_project_request\" % key\n )\n params[key] = val\n del params['kwargs']\n\n\n resource_path = '/oapi/v1/projectrequests'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n if 'label_selector' in params:\n query_params['labelSelector'] = params['label_selector']\n if 'field_selector' in params:\n query_params['fieldSelector'] = params['field_selector']\n if 'watch' in params:\n query_params['watch'] = params['watch']\n if 'resource_version' in params:\n query_params['resourceVersion'] = params['resource_version']\n if 'timeout_seconds' in params:\n query_params['timeoutSeconds'] = params['timeout_seconds']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'GET',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='UnversionedStatus',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def update_project(arn=None, name=None, defaultJobTimeoutMinutes=None):\n pass","def projects(self, projects):\n\n self._projects = projects","def project(self, project):\n\n self._project = project","def project(self, project):\n\n self._project = project","def project(self, project):\n\n self._project = project","def project(self, project):\n\n self._project = project","def create_namespaced_project_request(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_project_request\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_project_request`\")\n\n resource_path = '/oapi/v1/projectrequests'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1ProjectRequest',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def setRequestId(self, reqid) :\n self.request_id = reqid","def set_project(self, version):\n raise NotImplementedError(\"set_project is not implemented\")","def test_projects_id_put(self):\n project = Project()\n response = self.client.open('/project-tracker/projects/{id}'.format(id=3.4),\n method='PUT',\n data=json.dumps(project),\n content_type='application/json')\n self.assert200(response, \"Response body is : \" + response.data.decode('utf-8'))","def num_projects(self, num_projects):\n\n self._num_projects = num_projects","def project_task_id(self, project_task_id):\n\n self._project_task_id = project_task_id","def viewProject(self, projectId=None,size=None):\n\n uri = \"/v1/projects/\"\n if projectId:\n uri = uri + str(projectId)\n if size==0:\n uri =uri + \"?size=0\"\n response = self.client.get(uri)\n return response","def set_network_quotas(self, name_or_id, **kwargs):\n\n proj = self.get_project(name_or_id)\n if not proj:\n raise exc.OpenStackCloudException(\"project does not exist\")\n\n self.network.update_quota(proj.id, **kwargs)","def project_id(self, project_id):\n if project_id is None:\n raise ValueError(\"Invalid value for `project_id`, must not be `None`\") # noqa: E501\n\n self._project_id = project_id","def testSetupProjectNoChange(self, mock_setproj, mock_setid,\n mock_chkproj, mock_check_billing):\n # Test project didn't change, and no need to setup client id/secret\n mock_chkproj.return_value = False\n self.gcp_env_runner.client_id = \"test_client_id\"\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\n self.assertEqual(mock_setproj.call_count, 0)\n self.assertEqual(mock_setid.call_count, 0)\n mock_check_billing.assert_called_once()\n # Test project didn't change, but client_id is empty\n self.gcp_env_runner.client_id = \"\"\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\n self.assertEqual(mock_setproj.call_count, 0)\n mock_setid.assert_called_once()\n self.assertEqual(mock_check_billing.call_count, 2)","def _change_project(self):\n project_key = utils.prompt_string(\n 'You are currently managing Google Cloud Project {!r}.\\n'\n 'This project is currently saved as {!r}.\\n'\n 'All of the currently configured projects include: {}.\\n'\n 'Which project would you like to switch to?'.format(\n self._config.project, self._config.key,\n ', '.join(common.get_available_configs(self._config.path))))\n return _Manager.new(\n self._config.path, self._prefer_gcs, project_key=project_key,\n version=self._version)","def testSetupProjectChanged(self, mock_setproj, mock_setid,\n mock_chkproj, mock_check_billing):\n mock_chkproj.return_value = True\n mock_setproj.return_value = True\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\n mock_setproj.assert_called_once()\n mock_setid.assert_called_once()\n mock_check_billing.assert_called_once()","def test_set_project_limits(self):\n pass","def set_project_values(project, data):\n project.hashtag = data['hashtag']\n if 'name' in data and len(data['name']) > 0:\n project.name = data['name']\n else:\n project.name = project.hashtag.replace('-', ' ')\n if 'summary' in data and len(data['summary']) > 0:\n project.summary = data['summary']\n has_longtext = 'longtext' in data and len(data['longtext']) > 0\n if has_longtext:\n project.longtext = data['longtext']\n if 'autotext_url' in data and data['autotext_url'].startswith('http'):\n project.autotext_url = data['autotext_url']\n if not project.source_url or project.source_url == '':\n project.source_url = data['autotext_url']\n # MAX progress\n if 'levelup' in data and 0 < project.progress + data['levelup'] * 10 < 50:\n project.progress = project.progress + data['levelup'] * 10\n # return jsonify(data=data)\n if project.autotext_url is not None and not has_longtext:\n # Now try to autosync\n project = AddProjectData(project)\n return project","def main() -> None:\n parser: argparse.ArgumentParser = argparse.ArgumentParser(\n description=\"Set default expiration for BigQuery datasets and optionally tables within a specified Google Cloud Project.\"\n )\n parser.add_argument(\"project_id\", help=\"Google Cloud Project ID\")\n parser.add_argument(\"dataset_name\", help=\"BigQuery Dataset Name\")\n parser.add_argument(\"-d\", \"--days\", type=int, required=True, help=\"Number of days for expiration\")\n\n # Create a mutually exclusive group for --all-tables and --table\n table_group = parser.add_mutually_exclusive_group()\n table_group.add_argument(\"-a\", \"--all-tables\", action=\"store_true\", help=\"Set expiration for all tables\")\n table_group.add_argument(\"-t\", \"--table\", type=str, help=\"Regex pattern for tables to set expiration\")\n\n parser.add_argument(\"-s\", \"--skip-tables\", type=str, help=\"Regex pattern to skip tables that should not be affected\")\n parser.add_argument(\"-n\", \"--dry-run\", action=\"store_true\", help=\"Dry run, show changes without applying them\")\n args: argparse.Namespace = parser.parse_args()\n\n try:\n client: bigquery.Client = bigquery.Client(project=args.project_id)\n dataset_id = f\"{args.project_id}.{args.dataset_name}\"\n dataset_obj: bigquery.Dataset = client.get_dataset(dataset_id) # Fetch dataset directly\n\n # Only change the dataset's default expiration if neither --all-tables nor --table is provided\n if not (args.all_tables or args.table):\n set_expiration(client, dataset_obj, args.days, args.dry_run)\n\n if args.all_tables or args.table:\n handle_tables(client, dataset_obj, args.days, args.table, args.skip_tables, args.dry_run)\n\n except KeyboardInterrupt:\n print(\"\\nOperation canceled by user. Exiting...\")\n sys.exit(0)\n except NotFound as e:\n print(f\"Error: {str(e)}\")\n sys.exit(1)","def set_tenant_info(self, project_name, token_domain,\n token_project, project_id=None):\n old_project_info = (self.project_info[\"project_name\"],\n self.project_info[\"token_domain\"],\n self.project_info[\"token_project\"],\n self.project_info['project_id'])\n # Set the new project info.\n self.project_info['project_name'] = project_name\n self.project_info[\"token_domain\"] = token_domain\n self.project_info[\"token_project\"] = token_project\n if not project_id:\n if config.keystone_api_version == \"v3\":\n project_id = self.get_keystone_v3_project_id(project_name)\n else:\n project_id = self.get_tenant_id(project_name)\n self.project_info[\"project_id\"] = project_id\n\n LOG_OBJ.debug(\"Successfully set the project info for project: %s\" %\n project_name)\n return old_project_info","def request_id(self, request_id):\n\n self._request_id = request_id","def request_id(self, request_id):\n\n self._request_id = request_id","def request_id(self, request_id):\n\n self._request_id = request_id","def set_project(self, project: Optional[Project] = None, force: bool = False, get_only: bool = False, **kwargs):\n if self.project is not None and not force:\n info('Project is already set, to override use force=True')\n return self.project\n\n if project is None:\n project = Project(**kwargs)\n\n assert project.name is not None, 'Project name cannot be none'\n\n # does the project exist ?\n self.project = self.protocol.get_project(project)\n\n if self.project is not None:\n return self.project\n\n if get_only:\n raise RuntimeError(f'Project (name: {project.name}) was not found!')\n\n self.project = self.protocol.new_project(project)\n\n debug(f'set project to (project: {self.project.name})')\n return self.project","def test_projects_put(self):\n project = Project()\n response = self.client.open('/project-tracker/projects',\n method='PUT',\n data=json.dumps(project),\n content_type='application/json')\n self.assert200(response, \"Response body is : \" + response.data.decode('utf-8'))","def replace_namespaced_project(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method replace_namespaced_project\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `replace_namespaced_project`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `replace_namespaced_project`\")\n\n resource_path = '/oapi/v1/projects/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Project',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def get_project_quotas(self, project_id, extra_headers=None,\n use_auth=True, user_name=None):\n resp = self.client.get(\n 'project-quotas/' + project_id,\n response_model_type=quota_models.ProjectQuotaModel,\n extra_headers=extra_headers,\n use_auth=use_auth, user_name=user_name)\n return resp","def __init__(__self__, *,\n project: Optional[pulumi.Input[str]] = None):\n if project is not None:\n pulumi.set(__self__, \"project\", project)","def project_id(self) -> int:\n return pulumi.get(self, \"project_id\")","def get_project_id(self, session, **kwargs):\n return None","def _get_project_id():\n\n extras = BaseHook.get_connection('google_cloud_default').extra_dejson\n key = 'extra__google_cloud_platform__project'\n if key in extras:\n project_id = extras[key]\n else:\n raise ('Must configure project_id in google_cloud_default '\n 'connection from Airflow Console')\n return project_id","def ModifyProxiesProject(self, request):\n try:\n params = request._serialize()\n headers = request.headers\n body = self.call(\"ModifyProxiesProject\", params, headers=headers)\n response = json.loads(body)\n model = models.ModifyProxiesProjectResponse()\n model._deserialize(response[\"Response\"])\n return model\n except Exception as e:\n if isinstance(e, TencentCloudSDKException):\n raise\n else:\n raise TencentCloudSDKException(type(e).__name__, str(e))","def set_project_id(self, old_project=None, new_project=None):\n # cancel if one is no project object\n old_is_project = type(old_project) is Project\n new_is_project = type(new_project) is Project\n\n if not old_is_project or not new_is_project:\n return False\n\n # check id\n id_exists = new_project.project_id() in [\n p.project_id() for p in self.project_list\n ]\n id_is_own = old_project.project_id() == new_project.project_id()\n title_is_empty = new_project.title == ''\n\n # cancel with true, if there's no need to change the title + client_id\n if id_is_own:\n return True\n\n # cancel\n # the id already exists\n # or the new title is empty\n if id_exists or title_is_empty:\n return False\n\n # rename the file\n renamed = self.rename_project_file(\n old_project=old_project,\n new_project=new_project\n )\n\n if renamed is False:\n return False\n\n # get its index\n index = self.get_project_index(old_project)\n\n # change the title and client of the original project to the new title\n self.project_list[index].client_id = new_project.client_id\n self.project_list[index].title = new_project.title\n\n # get new project and save it\n self.save_project_to_file(project=self.project_list[index])\n\n return True","def test_projects_patch(self):\n project = Project()\n response = self.client.open('/project-tracker/projects',\n method='PATCH',\n data=json.dumps(project),\n content_type='application/json')\n self.assert200(response, \"Response body is : \" + response.data.decode('utf-8'))","def patch(self, project_id):\n authenticated_user_id = token_auth.current_user()\n if not ProjectAdminService.is_user_action_permitted_on_project(\n authenticated_user_id, project_id\n ):\n return {\n \"Error\": \"User is not a manager of the project\",\n \"SubCode\": \"UserPermissionError\",\n }, 403\n try:\n project_dto = ProjectDTO(request.get_json())\n project_dto.project_id = project_id\n project_dto.validate()\n except DataError as e:\n current_app.logger.error(f\"Error validating request: {str(e)}\")\n return {\"Error\": \"Unable to update project\", \"SubCode\": \"InvalidData\"}, 400\n\n try:\n ProjectAdminService.update_project(project_dto, authenticated_user_id)\n return {\"Status\": \"Updated\"}, 200\n except InvalidGeoJson as e:\n return {\"Invalid GeoJson\": str(e)}, 400\n except ProjectAdminServiceError as e:\n return {\"Error\": str(e).split(\"-\")[1], \"SubCode\": str(e).split(\"-\")[0]}, 403","def project_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"project_id\")","def set_review_request_field(self, review_request, field, value):\r\n rid = review_request['id']\r\n\r\n self.debug('Attempting to set field \"%s\" to \"%s\" for review request \"%s\"' %\r\n (field, value, rid))\r\n\r\n self.api_call('api/review-requests/%s/draft/set/' % rid,\r\n {field: value})","def edit_project_vm_size(\n project_name: str,\n config_client: ConfigAzureClient = Depends(get_config_azure_client),\n vm_size: VMSizes | Literal[\"\"] = Body(embed=True),\n):\n config_client.set_project_vm_size(project_name, vm_size or None)","def test_projects_endpoint(self):\n with open('demo/tests/mock_results.json', 'r') as result_file:\n data = result_file.read()\n expected_response = json.loads(data)[\"test_project_calls\"]\n\n responses.add(\n responses.GET,\n f'{os.environ[\"AIVEN_API_URL\"]}/v1/project',\n json=expected_response,\n status=200\n )\n resp = requests.get(f'{os.environ[\"AIVEN_API_URL\"]}/v1/project')\n\n assert resp.status_code == 200\n assert resp.json() == expected_response\n assert len(responses.calls) == 1\n assert responses.calls[0].request.url == f'{os.environ[\"AIVEN_API_URL\"]}/v1/project'\n assert \"MY-PROJECT-NAME\" in responses.calls[0].response.text\n assert responses.calls[0].response.json() == expected_response","def project_id() -> str:\n project_id = os.environ[\"GOOGLE_CLOUD_PROJECT\"]\n\n if not project_id:\n raise MissingProjectIdError(\n \"Set the environment variable \"\n + \"GCLOUD_PROJECT to your Google Cloud Project Id.\"\n )\n return project_id","def rename_project(request):\n data = json.loads(request.body.decode('utf-8'))\n try:\n proj = models.Project.objects.get(pk=data['projid'])\n except models.Project.DoesNotExist:\n return JsonResponse({'error': f'Project with that ID does not exist in DB'}, status=404)\n # check if new project not already exist, and user have permission for all dsets\n proj_exist = models.Project.objects.filter(name=data['newname'])\n if proj_exist.count():\n if proj_exist.get().id == proj.id:\n return JsonResponse({'error': f'Cannot change name to existing name for project {proj.name}'}, status=403)\n else:\n return JsonResponse({'error': f'There is already a project by that name {data[\"newname\"]}'}, status=403)\n if is_invalid_proj_exp_runnames(data['newname']):\n return JsonResponse({'error': f'Project name cannot contain characters except {settings.ALLOWED_PROJEXPRUN_CHARS}'}, status=403)\n dsets = models.Dataset.objects.filter(runname__experiment__project=proj)\n if not all(check_ownership(request.user, ds) for ds in dsets):\n return JsonResponse({'error': f'You do not have the rights to change all datasets in this project'}, status=403)\n # queue jobs to rename project, update project name after that since it is needed in job for path\n create_job('rename_top_lvl_projectdir', newname=data['newname'], proj_id=data['projid'])\n proj.name = data['newname']\n proj.save()\n return JsonResponse({})","def subproject(self, subproject):\n\n self.logger.debug(\"In 'subproject' setter.\")\n\n self._subproject = subproject","def get_project_ids(self, node=None, name=None):\n project_ids = []\n queries = []\n # Return all project_ids in the data commons if no node is provided or if node is program but no name provided\n if name == None and ((node == None) or (node == \"program\")):\n print(\"Getting all project_ids you have access to in the data commons.\")\n if node == \"program\":\n print(\n \"Specify a list of program names (name = ['myprogram1','myprogram2']) to get only project_ids in particular programs.\"\n )\n queries.append(\"\"\"{project (first:0){project_id}}\"\"\")\n elif name != None and node == \"program\":\n if isinstance(name, list):\n print(\n \"Getting all project_ids in the programs '\" + \",\".join(name) + \"'\"\n )\n for program_name in name:\n queries.append(\n \"\"\"{project (first:0, with_path_to:{type:\"program\",name:\"%s\"}){project_id}}\"\"\"\n % (program_name)\n )\n elif isinstance(name, str):\n print(\"Getting all project_ids in the program '\" + name + \"'\")\n queries.append(\n \"\"\"{project (first:0, with_path_to:{type:\"program\",name:\"%s\"}){project_id}}\"\"\"\n % (name)\n )\n elif isinstance(node, str) and isinstance(name, str):\n print(\n \"Getting all project_ids for projects with a path to record '\"\n + name\n + \"' in node '\"\n + node\n + \"'\"\n )\n queries.append(\n \"\"\"{project (first:0, with_path_to:{type:\"%s\",submitter_id:\"%s\"}){project_id}}\"\"\"\n % (node, name)\n )\n elif isinstance(node, str) and name == None:\n print(\n \"Getting all project_ids for projects with at least one record in the node '\"\n + node\n + \"'\"\n )\n query = \"\"\"{node (first:0,of_type:\"%s\"){project_id}}\"\"\" % (node)\n df = pd.json_normalize(self.sub.query(query)[\"data\"][\"node\"])\n project_ids = project_ids + list(set(df[\"project_id\"]))\n if len(queries) > 0:\n for query in queries:\n res = self.sub.query(query)\n df = pd.json_normalize(res[\"data\"][\"project\"])\n project_ids = project_ids + list(set(df[\"project_id\"]))\n my_ids = sorted(project_ids, key=str.lower)\n print(my_ids)\n return my_ids","def create_project():\n client = RequestManager()\n project_name = \"\".join(choices(string.ascii_letters + string.digits, k=10))\n client.set_method(\"POST\")\n client.set_endpoint(\"/projects\")\n body = {\"name\": project_name}\n client.set_body(json.dumps(body))\n response = client.execute_request()\n STORED_ID['project_id'] = response.json()['id']","def project_id(self) -> Optional[str]:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> str:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> str:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> str:\n return pulumi.get(self, \"project_id\")","def project_id(self) -> str:\n return pulumi.get(self, \"project_id\")","def set_projects(self, name_short, name, disc_path):\n if name not in conf.projects:\n pass # TODO add the project in the conf\n else:\n return \"Project already exist\"\n return self.datas.create_path(disc_path)","def increment_request_limit(self, _request, client_id, client_email):\n # Avoid value explosision and protect PII info\n if not framework_helpers.IsServiceAccount(client_email):\n client_email = 'user@email.com'\n self.api_requests.increment_by(\n 1, {'client_id': client_id, 'client_email': client_email})","def test_set_project(self):\n self.assertEqual(AppSetting.objects.count(), 0)\n self.assertIsNone(\n ProjectEvent.objects.filter(\n event_name='app_setting_set_api'\n ).first()\n )\n\n setting_name = 'project_str_setting'\n url = reverse(\n 'projectroles:api_project_setting_set',\n kwargs={'project': self.project.sodar_uuid},\n )\n post_data = {\n 'app_name': EX_APP_NAME,\n 'setting_name': setting_name,\n 'value': 'value',\n }\n response = self.request_knox(url, method='POST', data=post_data)\n\n self.assertEqual(response.status_code, 200, msg=response.content)\n self.assertEqual(AppSetting.objects.count(), 1)\n obj = AppSetting.objects.get(name=setting_name, project=self.project)\n self.assertEqual(obj.get_value(), 'value')\n tl_event = ProjectEvent.objects.filter(\n event_name='app_setting_set_api'\n ).first()\n self.assertIsNotNone(tl_event)\n self.assertEqual(tl_event.classified, True)\n self.assertEqual(tl_event.extra_data, {'value': 'value'})","def test_projects_id_post(self):\n project = Project()\n response = self.client.open('/project-tracker/projects/{id}'.format(id=3.4),\n method='POST',\n data=json.dumps(project),\n content_type='application/json')\n self.assert200(response, \"Response body is : \" + response.data.decode('utf-8'))","def put(self):\n # fetch parameter\n get_parser = reqparse.RequestParser(bundle_errors=True)\n get_parser.add_argument(\"user_id\", required=True, help=\"User ID required to acccess the user's favourite projects\")\n get_parser.add_argument(\"project_id\", required=True, help=\"Project ID required to remove a project\")\n args = get_parser.parse_args(strict=True)\n\n # get user_id and project_id\n user_id = args[\"user_id\"]\n project_id = args[\"project_id\"]\n\n # convert parameter ids into objectids\n try:\n user_id = ObjectId(user_id)\n project_id = ObjectId(project_id)\n except:\n return {\"message\": \"invalid user id or project id\"}, 400\n\n # add project to the user's favourites \n if ('user_id' or 'project_id') not in args.keys():\n return {\"message\": \"both user and project id are required\"}, 400\n else:\n # check if user is valid\n user = self.users.find_one({\"_id\": user_id})\n project = self.projects.find_one({\"_id\": project_id})\n if user is None:\n return {\"message\": \"user not found\"}, 404\n elif project is None:\n return {\"message\": \"project not found\"}, 404\n else:\n # remove project from the user's favourites\n user_favourites = self.favourites.find_one({\"user_id\": user_id})\n if user_favourites is None:\n return {\"message\": \"user does not have any favourite projects\"}, 400\n else:\n new_favourite_list = user_favourites[\"favourite_projects\"]\n\n # try to remove the project if it is in the favourites\n try:\n new_favourite_list.remove(project)\n except:\n return {\"message\": \"the project is not in the favourites list\"}, 400\n\n if new_favourite_list is None:\n new_favourite_list = []\n\n updated_list = {\"favourite_projects\": new_favourite_list}\n self.favourites.update({\"user_id\": user_id}, {\"$set\": updated_list}, upsert=False)\n \n return {\"status\": \"project has been removed from favourites successfully\"}, 200","def set_or_create_dataset(conn: BlitzGateway, project_id: Union[int, None],\n dataset: Union[str, int],\n across_groups: Optional[bool] = True\n ) -> Union[int, None]:\n if isinstance(dataset, str):\n if project_id:\n dataset_id = post_dataset(conn, dataset, project_id=project_id)\n else:\n dataset_id = post_dataset(conn, dataset)\n print(f'Created new Dataset:{dataset_id}')\n elif (isinstance(dataset, int)):\n dataset_id = dataset\n else:\n raise TypeError(\"'dataset' must be str or int\")\n return dataset_id","def assign_project_to_client(self, project=None, client_id=None):\n is_project = type(project) is Project\n one_not_set = project is None or client_id is None\n client_exists = client_id in [c.client_id for c in self.client_list]\n client_is_self = client_id == project.client_id\n\n # cancel, if either:\n # argument is not a project\n # one argument not set\n # client_id already exists\n # client already assigned\n if not is_project or one_not_set or not client_exists or client_is_self:\n return False\n\n # assign the project to the new client\n self.delete_project_file(project=project)\n project.client_id = client_id\n self.save_project_to_file(project=project)\n return True","def _get_project_id(self, request):\n project_id = request.environ[\"masakari.context\"].project_id\n if project_id in request.url:\n return project_id\n return ''","def read_project(response):\n STORED_ID['project_id'] = response.json()[\"id\"]","def patch_namespaced_project(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method patch_namespaced_project\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `patch_namespaced_project`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `patch_namespaced_project`\")\n\n resource_path = '/oapi/v1/projects/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json-patch+json', 'application/merge-patch+json', 'application/strategic-merge-patch+json'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PATCH',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Project',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def get_project(self, project):\n project_name = project\n\n try:\n # FIXME: project should be an integer or str, no both\n project_id = int(project)\n except ValueError:\n project_id = None\n\n try:\n # Find the first project occurrence\n project_found = next(p for p in self.get_projects() if p[\"id\"] == project_id\n or p[\"name\"] == project_name)\n # FIXME: use namedtuple instead? create a self.project = dict()?\n self.project_name = project_found[\"name\"]\n self.project_id = project_found[\"id\"]\n self.project_address = \"projects/%s/\" % self.project_id\n except StopIteration:\n logger.error(\"Project %s not found\" % project)\n raise KeyError","def test_create_project_request(self):\n pass","def update(self, request, pk=None):\n lot = Lot.objects.get(pk=request.data[\"lotId\"])\n\n project = Project.objects.get(pk=pk)\n project.name = request.data[\"name\"]\n project.estimatedCost = request.data[\"estimatedCost\"]\n project.estimatedCompletionDate = request.data[\"estimatedCompletionDate\"]\n #project.projectNote = Note.objects.get(pk=request.data['projectNote'])\n\n project.lotId = lot\n project.save()\n\n return Response({}, status=status.HTTP_204_NO_CONTENT)","def project(self):\n return self._properties.get(\"jobReference\", {}).get(\"projectId\")","def test_list_project_request(self):\n pass","def increment(conn, project):\n with conn:\n c = conn.cursor()\n c.execute(\"\"\"INSERT OR REPLACE \n INTO projects (project, alias, called) \n VALUES \n (?,\n (SELECT alias FROM projects WHERE project=?),\n (SELECT called FROM projects WHERE project=?) + 1\n )\"\"\", (project, project, project,))","def setJobId(self, jobid):\n self._ShREEKConfig.setJobId(jobid)","def test_set_invalid_scope_project(self):\n setting_name = 'project_str_setting'\n url = reverse('projectroles:api_user_setting_set')\n post_data = {\n 'app_name': EX_APP_NAME,\n 'setting_name': setting_name,\n 'value': 'value',\n }\n response = self.request_knox(url, method='POST', data=post_data)\n self.assertEqual(response.status_code, 400, msg=response.content)\n self.assertEqual(AppSetting.objects.count(), 0)","def __init__(self, project_id, dataset_id, sandbox_dataset_id):\n desc = 'Sandbox and update invalid zip codes found in the observation table.'\n super().__init__(issue_numbers=['DC1633'],\n description=desc,\n affected_datasets=[cdr_consts.RDR],\n affected_tables=[OBSERVATION],\n project_id=project_id,\n dataset_id=dataset_id,\n sandbox_dataset_id=sandbox_dataset_id)","def select_approved_projects(self):\r\n print \"Selecting approved projects... \"\r\n global ANNUAL_BUDGET\r\n \r\n projects_citizens_sorted = sorted(self.projects_for_vote, key=lambda project:project.units, reverse=True)\r\n projects_reps_sorted = sorted(self.projects_for_vote, key=lambda project:project.p_units, reverse=True)\r\n budget_sum = 0\r\n \r\n for p in projects_citizens_sorted:\r\n budget_sum += p.budget\r\n if budget_sum <= ANNUAL_BUDGET/2:\r\n self.projects_approved.append(p)\r\n\r\n budget_sum = 0\r\n for p in projects_reps_sorted:\r\n if p not in self.projects_approved:\r\n budget_sum += p.budget\r\n if budget_sum <= ANNUAL_BUDGET/2:\r\n self.projects_approved.append(p)\r\n\r\n\r\n \r\n# raw_input(\"select_approved_projects - antes\")\r\n for p in projects_citizens_sorted:\r\n print p\r\n print \"\\nReps\\n\"\r\n for p in projects_reps_sorted:\r\n print p\r\n print \"\\nApproved\\n\"\r\n for p in self.projects_approved:\r\n print p\r\n\r\n raw_input(\"select_approved_projects - depois\")","def create_project(project_id: str,\n admin_token: str,\n project_admin: str,\n csp: str='AWS',\n budget: float=10) -> dict:\n\n if budget == 10:\n print(\"Set the budget of Project {%s} to default value: $%.2f\" %(project_id, budget))\n print(\"Update the budget using: set_budget(amount)\")\n \n print('Cloud service provider: ', csp)\n\n if csp not in ['AWS', 'AZURE', 'GCP', 'PRIVATE']:\n print('CSP not supported: Current options: AWS, AZURE, GCP, PRIVATE')\n return\n\n resp = RestRequest(CredentialApi.create_project) \\\n .with_data({'project_id': project_id,\n 'budget': budget,\n 'admin_token': admin_token,\n 'csp': csp,\n \"project_admin_name\": project_admin}) \\\n .run()\n \n # cloud service provider is private cluster, create bucket accordingly\n if csp == 'PRIVATE':\n print(resp)\n bucket_name = resp['bucket_name']\n private_cluster = get_private_cluster()\n private_cluster.create_buckets(bucket_name)\n \n return resp","def prompt(self, console: io.IO, step: str,\n args: Dict[str, Any]) -> Dict[str, Any]:\n prompter = GoogleNewProjectId()\n\n if args.get('use_existing_project', False):\n prompter = GoogleExistingProjectId(self.project_client,\n self.active_account)\n\n return prompter.prompt(console, step, args)","def add_project(self, proj, i):\r\n self.__projects[i] = proj","def RunWithArgs(self, resource):\n client = GetClientFromFlags()\n global_params = GetGlobalParamsFromFlags()\n request = messages.IamProjectsServiceAccountsSetIamPolicyRequest(\n resource=resource.decode('utf8'),\n )\n if FLAGS['setIamPolicyRequest'].present:\n request.setIamPolicyRequest = apitools_base.JsonToMessage(messages.SetIamPolicyRequest, FLAGS.setIamPolicyRequest)\n result = client.projects_serviceAccounts.SetIamPolicy(\n request, global_params=global_params)\n print apitools_base_cli.FormatOutput(result)","def set_missing_id(self, data, **kwargs):\n if not data.get(\"project_id\"):\n data[\"project_id\"] = lambda: uuid.uuid4().hex\n\n return data","def __init__(self, project_id, namespace=None):\n self._client = datastore.Client(project=project_id, namespace=namespace)"],"string":"[\n \"def set_project_quotas(self, project_id, request_model, extra_headers=None,\\n use_auth=True, user_name=None):\\n resp = self.client.post(\\n 'project-quotas/' + project_id,\\n request_model=request_model,\\n response_model_type=quota_models.ProjectQuotaModel,\\n extra_headers=extra_headers,\\n use_auth=use_auth, user_name=user_name)\\n return resp\",\n \"def set_project(project_id):\\n return fluent.set_project(project_id)\",\n \"def set_project_id(self, project_id):\\n self._project_id = project_id\",\n \"def project_id(self, project_id):\\n\\n self._project_id = project_id\",\n \"def project_id(self, project_id):\\n\\n self._project_id = project_id\",\n \"def project(self, value):\\n\\n if self._project != value:\\n self._project = value\\n self._update_page()\",\n \"def scope_project(self, project_key):\\n self.raw['scope'] = 'PROJECT'\\n self.raw['projectKey'] = project_key\\n return self\",\n \"def set_or_create_project(conn: BlitzGateway, project: Union[str, int],\\n across_groups: Optional[bool] = True) -> int:\\n if isinstance(project, str):\\n project_id = post_project(conn, project)\\n print(f'Created new Project:{project_id}')\\n elif (isinstance(project, int)):\\n project_id = project\\n else:\\n raise TypeError(\\\"'project' must be str or int\\\")\\n return project_id\",\n \"def change_project(self, project, project_format='id'):\\n name = 'tenant' if self.api_version == 2 else 'project'\\n self.creds['%s_%s' % (name, project_format)] = project\\n opposite_format = 'name' if project_format == 'id' else 'id'\\n del self.creds['%s_%s' % (name, opposite_format)]\",\n \"def updateProject(self, projectId,payload):\\n uri = \\\"/v1/projects/\\\" +str(projectId)\\n response = self.client.put(uri,payload)\\n return response\",\n \"def project_name(self, project_name):\\n\\n self._project_name = project_name\",\n \"def project(self, project):\\n self._project = project\",\n \"def project(self, project):\\n self._project = project\",\n \"def set_keystone_v3_project(self, **kwargs):\\n LOG_OBJ.debug(\\\"Creating the project.\\\")\\n\\n _url = \\\"http://\\\" + self.host_ip + \\\":35357/v3/projects/\\\" + \\\\\\n str(kwargs['project_id'])\\n _headers = {'x-auth-token': self.cloud_admin_info[\\\"token_domain\\\"],\\n 'content-type': 'application/json'}\\n\\n _project_info = {\\\"project\\\": {}}\\n for argument in [\\\"name\\\", \\\"description\\\", \\\"domain_id\\\",\\n \\\"enabled\\\", \\\"disabled\\\"]:\\n try:\\n _project_info['project'].update(\\n {argument: kwargs[argument]})\\n except KeyError:\\n pass\\n _body = json.dumps(_project_info)\\n response = self.request(\\\"PATCH\\\", _url, _headers, _body)\\n\\n if response is None:\\n LOG_OBJ.error(\\\"No response from Server while set the project\\\")\\n print (\\\"No response from Server while set the project\\\")\\n return response\\n\\n if response.status not in [200, 201, 202, 203, 204]:\\n LOG_OBJ.error(\\\" Set project Failed with status %s and error : %s\\\" %\\n (response.status, response.data))\\n print (\\\" Set project Failed with status %s and error : %s\\\" %\\n (response.status, response.data))\\n return response.status\\n\\n return True\",\n \"def update_project(self, project_id, project):\\n\\n with self._transaction.cursor() as cur:\\n # ensure this project exists\\n cur.execute(\\n \\\"SELECT project_id \\\"\\n \\\"FROM barcodes.project \\\"\\n \\\"WHERE project_id=%s;\\\",\\n (project_id,))\\n\\n row = cur.fetchone()\\n if row is None:\\n raise NotFound(\\\"No project with ID %s\\\" % project_id)\\n\\n query = f\\\"\\\"\\\"\\n UPDATE barcodes.project\\n SET {p.DB_PROJ_NAME_KEY}=%s,\\n {p.SUBPROJECT_NAME_KEY}=%s,\\n {p.ALIAS_KEY}=%s,\\n {p.IS_MICROSETTA_KEY}=%s,\\n {p.SPONSOR_KEY}=%s,\\n {p.COORDINATION_KEY}=%s,\\n {p.CONTACT_NAME_KEY}=%s,\\n {p.ADDTL_CONTACT_NAME_KEY}=%s,\\n {p.CONTACT_EMAIL_KEY}=%s,\\n {p.DEADLINES_KEY}=%s,\\n {p.NUM_SUBJECTS_KEY}=%s,\\n {p.NUM_TIMEPOINTS_KEY}=%s,\\n {p.START_DATE_KEY}=%s,\\n {p.BANK_SAMPLES_KEY}=%s,\\n {p.PLATING_START_DATE_KEY}=%s,\\n {p.DISPOSITION_COMMENTS_KEY}=%s,\\n {p.COLLECTION_KEY}=%s,\\n {p.IS_FECAL_KEY}=%s,\\n {p.IS_SALIVA_KEY}=%s,\\n {p.IS_SKIN_KEY}=%s,\\n {p.IS_BLOOD_KEY}=%s,\\n {p.IS_OTHER_KEY}=%s,\\n {p.DO_16S_KEY}=%s,\\n {p.DO_SHALLOW_SHOTGUN_KEY}=%s,\\n {p.DO_SHOTGUN_KEY}=%s,\\n {p.DO_RT_QPCR_KEY}=%s,\\n {p.DO_SEROLOGY_KEY}=%s,\\n {p.DO_METATRANSCRIPTOMICS_KEY}=%s,\\n {p.DO_MASS_SPEC_KEY}=%s,\\n {p.MASS_SPEC_COMMENTS_KEY}=%s,\\n {p.MASS_SPEC_CONTACT_NAME_KEY}=%s,\\n {p.MASS_SPEC_CONTACT_EMAIL_KEY}=%s,\\n {p.DO_OTHER_KEY}=%s,\\n {p.BRANDING_ASSOC_INSTRUCTIONS_KEY}=%s,\\n {p.BRANDING_STATUS_KEY}=%s\\n WHERE project_id=%s;\\\"\\\"\\\"\\n\\n cur.execute(query,\\n (\\n project.project_name,\\n project.subproject_name,\\n project.alias,\\n project.is_microsetta,\\n project.sponsor,\\n project.coordination,\\n project.contact_name,\\n project.additional_contact_name,\\n project.contact_email,\\n project.deadlines,\\n project.num_subjects,\\n project.num_timepoints,\\n project.start_date,\\n project.bank_samples,\\n project.plating_start_date,\\n project.disposition_comments,\\n project.collection,\\n project.is_fecal,\\n project.is_saliva,\\n project.is_skin,\\n project.is_blood,\\n project.is_other,\\n project.do_16s,\\n project.do_shallow_shotgun,\\n project.do_shotgun,\\n project.do_rt_qpcr,\\n project.do_serology,\\n project.do_metatranscriptomics,\\n project.do_mass_spec,\\n project.mass_spec_comments,\\n project.mass_spec_contact_name,\\n project.mass_spec_contact_email,\\n project.do_other,\\n project.branding_associated_instructions,\\n project.branding_status,\\n project_id\\n ))\\n return cur.rowcount == 1\",\n \"def projects(self, projects):\\n if (self.local_vars_configuration.client_side_validation and\\n projects is not None and not isinstance(projects, int)):\\n raise ValueError(\\\"Parameter `projects` must be an integer\\\") # noqa: E501\\n\\n self._projects = projects\",\n \"def set_project(\\n name\\n):\\n if not is_alive():\\n err_msg = \\\"Cannot connect to getML engine. Make sure the engine is running and you are logged in.\\\"\\n raise ConnectionRefusedError(err_msg)\\n\\n cmd = dict()\\n cmd[\\\"type_\\\"] = \\\"set_project\\\"\\n cmd[\\\"name_\\\"] = name\\n\\n comm.send(cmd)\",\n \"def _project(request, key):\\n context = request.context\\n if not context.project_id:\\n raise exceptions.QuotaMissingTenant()\\n return {key: {key + '_id': context.project_id}}\",\n \"def list_namespaced_project_request(self, **kwargs):\\n\\n all_params = ['pretty', 'label_selector', 'field_selector', 'watch', 'resource_version', 'timeout_seconds']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method list_namespaced_project_request\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n\\n resource_path = '/oapi/v1/projectrequests'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n if 'label_selector' in params:\\n query_params['labelSelector'] = params['label_selector']\\n if 'field_selector' in params:\\n query_params['fieldSelector'] = params['field_selector']\\n if 'watch' in params:\\n query_params['watch'] = params['watch']\\n if 'resource_version' in params:\\n query_params['resourceVersion'] = params['resource_version']\\n if 'timeout_seconds' in params:\\n query_params['timeoutSeconds'] = params['timeout_seconds']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'GET',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='UnversionedStatus',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def update_project(arn=None, name=None, defaultJobTimeoutMinutes=None):\\n pass\",\n \"def projects(self, projects):\\n\\n self._projects = projects\",\n \"def project(self, project):\\n\\n self._project = project\",\n \"def project(self, project):\\n\\n self._project = project\",\n \"def project(self, project):\\n\\n self._project = project\",\n \"def project(self, project):\\n\\n self._project = project\",\n \"def create_namespaced_project_request(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_project_request\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_project_request`\\\")\\n\\n resource_path = '/oapi/v1/projectrequests'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1ProjectRequest',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def setRequestId(self, reqid) :\\n self.request_id = reqid\",\n \"def set_project(self, version):\\n raise NotImplementedError(\\\"set_project is not implemented\\\")\",\n \"def test_projects_id_put(self):\\n project = Project()\\n response = self.client.open('/project-tracker/projects/{id}'.format(id=3.4),\\n method='PUT',\\n data=json.dumps(project),\\n content_type='application/json')\\n self.assert200(response, \\\"Response body is : \\\" + response.data.decode('utf-8'))\",\n \"def num_projects(self, num_projects):\\n\\n self._num_projects = num_projects\",\n \"def project_task_id(self, project_task_id):\\n\\n self._project_task_id = project_task_id\",\n \"def viewProject(self, projectId=None,size=None):\\n\\n uri = \\\"/v1/projects/\\\"\\n if projectId:\\n uri = uri + str(projectId)\\n if size==0:\\n uri =uri + \\\"?size=0\\\"\\n response = self.client.get(uri)\\n return response\",\n \"def set_network_quotas(self, name_or_id, **kwargs):\\n\\n proj = self.get_project(name_or_id)\\n if not proj:\\n raise exc.OpenStackCloudException(\\\"project does not exist\\\")\\n\\n self.network.update_quota(proj.id, **kwargs)\",\n \"def project_id(self, project_id):\\n if project_id is None:\\n raise ValueError(\\\"Invalid value for `project_id`, must not be `None`\\\") # noqa: E501\\n\\n self._project_id = project_id\",\n \"def testSetupProjectNoChange(self, mock_setproj, mock_setid,\\n mock_chkproj, mock_check_billing):\\n # Test project didn't change, and no need to setup client id/secret\\n mock_chkproj.return_value = False\\n self.gcp_env_runner.client_id = \\\"test_client_id\\\"\\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\\n self.assertEqual(mock_setproj.call_count, 0)\\n self.assertEqual(mock_setid.call_count, 0)\\n mock_check_billing.assert_called_once()\\n # Test project didn't change, but client_id is empty\\n self.gcp_env_runner.client_id = \\\"\\\"\\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\\n self.assertEqual(mock_setproj.call_count, 0)\\n mock_setid.assert_called_once()\\n self.assertEqual(mock_check_billing.call_count, 2)\",\n \"def _change_project(self):\\n project_key = utils.prompt_string(\\n 'You are currently managing Google Cloud Project {!r}.\\\\n'\\n 'This project is currently saved as {!r}.\\\\n'\\n 'All of the currently configured projects include: {}.\\\\n'\\n 'Which project would you like to switch to?'.format(\\n self._config.project, self._config.key,\\n ', '.join(common.get_available_configs(self._config.path))))\\n return _Manager.new(\\n self._config.path, self._prefer_gcs, project_key=project_key,\\n version=self._version)\",\n \"def testSetupProjectChanged(self, mock_setproj, mock_setid,\\n mock_chkproj, mock_check_billing):\\n mock_chkproj.return_value = True\\n mock_setproj.return_value = True\\n self.gcp_env_runner._SetupProject(self.gcloud_runner)\\n mock_setproj.assert_called_once()\\n mock_setid.assert_called_once()\\n mock_check_billing.assert_called_once()\",\n \"def test_set_project_limits(self):\\n pass\",\n \"def set_project_values(project, data):\\n project.hashtag = data['hashtag']\\n if 'name' in data and len(data['name']) > 0:\\n project.name = data['name']\\n else:\\n project.name = project.hashtag.replace('-', ' ')\\n if 'summary' in data and len(data['summary']) > 0:\\n project.summary = data['summary']\\n has_longtext = 'longtext' in data and len(data['longtext']) > 0\\n if has_longtext:\\n project.longtext = data['longtext']\\n if 'autotext_url' in data and data['autotext_url'].startswith('http'):\\n project.autotext_url = data['autotext_url']\\n if not project.source_url or project.source_url == '':\\n project.source_url = data['autotext_url']\\n # MAX progress\\n if 'levelup' in data and 0 < project.progress + data['levelup'] * 10 < 50:\\n project.progress = project.progress + data['levelup'] * 10\\n # return jsonify(data=data)\\n if project.autotext_url is not None and not has_longtext:\\n # Now try to autosync\\n project = AddProjectData(project)\\n return project\",\n \"def main() -> None:\\n parser: argparse.ArgumentParser = argparse.ArgumentParser(\\n description=\\\"Set default expiration for BigQuery datasets and optionally tables within a specified Google Cloud Project.\\\"\\n )\\n parser.add_argument(\\\"project_id\\\", help=\\\"Google Cloud Project ID\\\")\\n parser.add_argument(\\\"dataset_name\\\", help=\\\"BigQuery Dataset Name\\\")\\n parser.add_argument(\\\"-d\\\", \\\"--days\\\", type=int, required=True, help=\\\"Number of days for expiration\\\")\\n\\n # Create a mutually exclusive group for --all-tables and --table\\n table_group = parser.add_mutually_exclusive_group()\\n table_group.add_argument(\\\"-a\\\", \\\"--all-tables\\\", action=\\\"store_true\\\", help=\\\"Set expiration for all tables\\\")\\n table_group.add_argument(\\\"-t\\\", \\\"--table\\\", type=str, help=\\\"Regex pattern for tables to set expiration\\\")\\n\\n parser.add_argument(\\\"-s\\\", \\\"--skip-tables\\\", type=str, help=\\\"Regex pattern to skip tables that should not be affected\\\")\\n parser.add_argument(\\\"-n\\\", \\\"--dry-run\\\", action=\\\"store_true\\\", help=\\\"Dry run, show changes without applying them\\\")\\n args: argparse.Namespace = parser.parse_args()\\n\\n try:\\n client: bigquery.Client = bigquery.Client(project=args.project_id)\\n dataset_id = f\\\"{args.project_id}.{args.dataset_name}\\\"\\n dataset_obj: bigquery.Dataset = client.get_dataset(dataset_id) # Fetch dataset directly\\n\\n # Only change the dataset's default expiration if neither --all-tables nor --table is provided\\n if not (args.all_tables or args.table):\\n set_expiration(client, dataset_obj, args.days, args.dry_run)\\n\\n if args.all_tables or args.table:\\n handle_tables(client, dataset_obj, args.days, args.table, args.skip_tables, args.dry_run)\\n\\n except KeyboardInterrupt:\\n print(\\\"\\\\nOperation canceled by user. Exiting...\\\")\\n sys.exit(0)\\n except NotFound as e:\\n print(f\\\"Error: {str(e)}\\\")\\n sys.exit(1)\",\n \"def set_tenant_info(self, project_name, token_domain,\\n token_project, project_id=None):\\n old_project_info = (self.project_info[\\\"project_name\\\"],\\n self.project_info[\\\"token_domain\\\"],\\n self.project_info[\\\"token_project\\\"],\\n self.project_info['project_id'])\\n # Set the new project info.\\n self.project_info['project_name'] = project_name\\n self.project_info[\\\"token_domain\\\"] = token_domain\\n self.project_info[\\\"token_project\\\"] = token_project\\n if not project_id:\\n if config.keystone_api_version == \\\"v3\\\":\\n project_id = self.get_keystone_v3_project_id(project_name)\\n else:\\n project_id = self.get_tenant_id(project_name)\\n self.project_info[\\\"project_id\\\"] = project_id\\n\\n LOG_OBJ.debug(\\\"Successfully set the project info for project: %s\\\" %\\n project_name)\\n return old_project_info\",\n \"def request_id(self, request_id):\\n\\n self._request_id = request_id\",\n \"def request_id(self, request_id):\\n\\n self._request_id = request_id\",\n \"def request_id(self, request_id):\\n\\n self._request_id = request_id\",\n \"def set_project(self, project: Optional[Project] = None, force: bool = False, get_only: bool = False, **kwargs):\\n if self.project is not None and not force:\\n info('Project is already set, to override use force=True')\\n return self.project\\n\\n if project is None:\\n project = Project(**kwargs)\\n\\n assert project.name is not None, 'Project name cannot be none'\\n\\n # does the project exist ?\\n self.project = self.protocol.get_project(project)\\n\\n if self.project is not None:\\n return self.project\\n\\n if get_only:\\n raise RuntimeError(f'Project (name: {project.name}) was not found!')\\n\\n self.project = self.protocol.new_project(project)\\n\\n debug(f'set project to (project: {self.project.name})')\\n return self.project\",\n \"def test_projects_put(self):\\n project = Project()\\n response = self.client.open('/project-tracker/projects',\\n method='PUT',\\n data=json.dumps(project),\\n content_type='application/json')\\n self.assert200(response, \\\"Response body is : \\\" + response.data.decode('utf-8'))\",\n \"def replace_namespaced_project(self, body, name, **kwargs):\\n\\n all_params = ['body', 'name', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method replace_namespaced_project\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `replace_namespaced_project`\\\")\\n # verify the required parameter 'name' is set\\n if ('name' not in params) or (params['name'] is None):\\n raise ValueError(\\\"Missing the required parameter `name` when calling `replace_namespaced_project`\\\")\\n\\n resource_path = '/oapi/v1/projects/{name}'.replace('{format}', 'json')\\n path_params = {}\\n if 'name' in params:\\n path_params['name'] = params['name']\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'PUT',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Project',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def get_project_quotas(self, project_id, extra_headers=None,\\n use_auth=True, user_name=None):\\n resp = self.client.get(\\n 'project-quotas/' + project_id,\\n response_model_type=quota_models.ProjectQuotaModel,\\n extra_headers=extra_headers,\\n use_auth=use_auth, user_name=user_name)\\n return resp\",\n \"def __init__(__self__, *,\\n project: Optional[pulumi.Input[str]] = None):\\n if project is not None:\\n pulumi.set(__self__, \\\"project\\\", project)\",\n \"def project_id(self) -> int:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def get_project_id(self, session, **kwargs):\\n return None\",\n \"def _get_project_id():\\n\\n extras = BaseHook.get_connection('google_cloud_default').extra_dejson\\n key = 'extra__google_cloud_platform__project'\\n if key in extras:\\n project_id = extras[key]\\n else:\\n raise ('Must configure project_id in google_cloud_default '\\n 'connection from Airflow Console')\\n return project_id\",\n \"def ModifyProxiesProject(self, request):\\n try:\\n params = request._serialize()\\n headers = request.headers\\n body = self.call(\\\"ModifyProxiesProject\\\", params, headers=headers)\\n response = json.loads(body)\\n model = models.ModifyProxiesProjectResponse()\\n model._deserialize(response[\\\"Response\\\"])\\n return model\\n except Exception as e:\\n if isinstance(e, TencentCloudSDKException):\\n raise\\n else:\\n raise TencentCloudSDKException(type(e).__name__, str(e))\",\n \"def set_project_id(self, old_project=None, new_project=None):\\n # cancel if one is no project object\\n old_is_project = type(old_project) is Project\\n new_is_project = type(new_project) is Project\\n\\n if not old_is_project or not new_is_project:\\n return False\\n\\n # check id\\n id_exists = new_project.project_id() in [\\n p.project_id() for p in self.project_list\\n ]\\n id_is_own = old_project.project_id() == new_project.project_id()\\n title_is_empty = new_project.title == ''\\n\\n # cancel with true, if there's no need to change the title + client_id\\n if id_is_own:\\n return True\\n\\n # cancel\\n # the id already exists\\n # or the new title is empty\\n if id_exists or title_is_empty:\\n return False\\n\\n # rename the file\\n renamed = self.rename_project_file(\\n old_project=old_project,\\n new_project=new_project\\n )\\n\\n if renamed is False:\\n return False\\n\\n # get its index\\n index = self.get_project_index(old_project)\\n\\n # change the title and client of the original project to the new title\\n self.project_list[index].client_id = new_project.client_id\\n self.project_list[index].title = new_project.title\\n\\n # get new project and save it\\n self.save_project_to_file(project=self.project_list[index])\\n\\n return True\",\n \"def test_projects_patch(self):\\n project = Project()\\n response = self.client.open('/project-tracker/projects',\\n method='PATCH',\\n data=json.dumps(project),\\n content_type='application/json')\\n self.assert200(response, \\\"Response body is : \\\" + response.data.decode('utf-8'))\",\n \"def patch(self, project_id):\\n authenticated_user_id = token_auth.current_user()\\n if not ProjectAdminService.is_user_action_permitted_on_project(\\n authenticated_user_id, project_id\\n ):\\n return {\\n \\\"Error\\\": \\\"User is not a manager of the project\\\",\\n \\\"SubCode\\\": \\\"UserPermissionError\\\",\\n }, 403\\n try:\\n project_dto = ProjectDTO(request.get_json())\\n project_dto.project_id = project_id\\n project_dto.validate()\\n except DataError as e:\\n current_app.logger.error(f\\\"Error validating request: {str(e)}\\\")\\n return {\\\"Error\\\": \\\"Unable to update project\\\", \\\"SubCode\\\": \\\"InvalidData\\\"}, 400\\n\\n try:\\n ProjectAdminService.update_project(project_dto, authenticated_user_id)\\n return {\\\"Status\\\": \\\"Updated\\\"}, 200\\n except InvalidGeoJson as e:\\n return {\\\"Invalid GeoJson\\\": str(e)}, 400\\n except ProjectAdminServiceError as e:\\n return {\\\"Error\\\": str(e).split(\\\"-\\\")[1], \\\"SubCode\\\": str(e).split(\\\"-\\\")[0]}, 403\",\n \"def project_id(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def set_review_request_field(self, review_request, field, value):\\r\\n rid = review_request['id']\\r\\n\\r\\n self.debug('Attempting to set field \\\"%s\\\" to \\\"%s\\\" for review request \\\"%s\\\"' %\\r\\n (field, value, rid))\\r\\n\\r\\n self.api_call('api/review-requests/%s/draft/set/' % rid,\\r\\n {field: value})\",\n \"def edit_project_vm_size(\\n project_name: str,\\n config_client: ConfigAzureClient = Depends(get_config_azure_client),\\n vm_size: VMSizes | Literal[\\\"\\\"] = Body(embed=True),\\n):\\n config_client.set_project_vm_size(project_name, vm_size or None)\",\n \"def test_projects_endpoint(self):\\n with open('demo/tests/mock_results.json', 'r') as result_file:\\n data = result_file.read()\\n expected_response = json.loads(data)[\\\"test_project_calls\\\"]\\n\\n responses.add(\\n responses.GET,\\n f'{os.environ[\\\"AIVEN_API_URL\\\"]}/v1/project',\\n json=expected_response,\\n status=200\\n )\\n resp = requests.get(f'{os.environ[\\\"AIVEN_API_URL\\\"]}/v1/project')\\n\\n assert resp.status_code == 200\\n assert resp.json() == expected_response\\n assert len(responses.calls) == 1\\n assert responses.calls[0].request.url == f'{os.environ[\\\"AIVEN_API_URL\\\"]}/v1/project'\\n assert \\\"MY-PROJECT-NAME\\\" in responses.calls[0].response.text\\n assert responses.calls[0].response.json() == expected_response\",\n \"def project_id() -> str:\\n project_id = os.environ[\\\"GOOGLE_CLOUD_PROJECT\\\"]\\n\\n if not project_id:\\n raise MissingProjectIdError(\\n \\\"Set the environment variable \\\"\\n + \\\"GCLOUD_PROJECT to your Google Cloud Project Id.\\\"\\n )\\n return project_id\",\n \"def rename_project(request):\\n data = json.loads(request.body.decode('utf-8'))\\n try:\\n proj = models.Project.objects.get(pk=data['projid'])\\n except models.Project.DoesNotExist:\\n return JsonResponse({'error': f'Project with that ID does not exist in DB'}, status=404)\\n # check if new project not already exist, and user have permission for all dsets\\n proj_exist = models.Project.objects.filter(name=data['newname'])\\n if proj_exist.count():\\n if proj_exist.get().id == proj.id:\\n return JsonResponse({'error': f'Cannot change name to existing name for project {proj.name}'}, status=403)\\n else:\\n return JsonResponse({'error': f'There is already a project by that name {data[\\\"newname\\\"]}'}, status=403)\\n if is_invalid_proj_exp_runnames(data['newname']):\\n return JsonResponse({'error': f'Project name cannot contain characters except {settings.ALLOWED_PROJEXPRUN_CHARS}'}, status=403)\\n dsets = models.Dataset.objects.filter(runname__experiment__project=proj)\\n if not all(check_ownership(request.user, ds) for ds in dsets):\\n return JsonResponse({'error': f'You do not have the rights to change all datasets in this project'}, status=403)\\n # queue jobs to rename project, update project name after that since it is needed in job for path\\n create_job('rename_top_lvl_projectdir', newname=data['newname'], proj_id=data['projid'])\\n proj.name = data['newname']\\n proj.save()\\n return JsonResponse({})\",\n \"def subproject(self, subproject):\\n\\n self.logger.debug(\\\"In 'subproject' setter.\\\")\\n\\n self._subproject = subproject\",\n \"def get_project_ids(self, node=None, name=None):\\n project_ids = []\\n queries = []\\n # Return all project_ids in the data commons if no node is provided or if node is program but no name provided\\n if name == None and ((node == None) or (node == \\\"program\\\")):\\n print(\\\"Getting all project_ids you have access to in the data commons.\\\")\\n if node == \\\"program\\\":\\n print(\\n \\\"Specify a list of program names (name = ['myprogram1','myprogram2']) to get only project_ids in particular programs.\\\"\\n )\\n queries.append(\\\"\\\"\\\"{project (first:0){project_id}}\\\"\\\"\\\")\\n elif name != None and node == \\\"program\\\":\\n if isinstance(name, list):\\n print(\\n \\\"Getting all project_ids in the programs '\\\" + \\\",\\\".join(name) + \\\"'\\\"\\n )\\n for program_name in name:\\n queries.append(\\n \\\"\\\"\\\"{project (first:0, with_path_to:{type:\\\"program\\\",name:\\\"%s\\\"}){project_id}}\\\"\\\"\\\"\\n % (program_name)\\n )\\n elif isinstance(name, str):\\n print(\\\"Getting all project_ids in the program '\\\" + name + \\\"'\\\")\\n queries.append(\\n \\\"\\\"\\\"{project (first:0, with_path_to:{type:\\\"program\\\",name:\\\"%s\\\"}){project_id}}\\\"\\\"\\\"\\n % (name)\\n )\\n elif isinstance(node, str) and isinstance(name, str):\\n print(\\n \\\"Getting all project_ids for projects with a path to record '\\\"\\n + name\\n + \\\"' in node '\\\"\\n + node\\n + \\\"'\\\"\\n )\\n queries.append(\\n \\\"\\\"\\\"{project (first:0, with_path_to:{type:\\\"%s\\\",submitter_id:\\\"%s\\\"}){project_id}}\\\"\\\"\\\"\\n % (node, name)\\n )\\n elif isinstance(node, str) and name == None:\\n print(\\n \\\"Getting all project_ids for projects with at least one record in the node '\\\"\\n + node\\n + \\\"'\\\"\\n )\\n query = \\\"\\\"\\\"{node (first:0,of_type:\\\"%s\\\"){project_id}}\\\"\\\"\\\" % (node)\\n df = pd.json_normalize(self.sub.query(query)[\\\"data\\\"][\\\"node\\\"])\\n project_ids = project_ids + list(set(df[\\\"project_id\\\"]))\\n if len(queries) > 0:\\n for query in queries:\\n res = self.sub.query(query)\\n df = pd.json_normalize(res[\\\"data\\\"][\\\"project\\\"])\\n project_ids = project_ids + list(set(df[\\\"project_id\\\"]))\\n my_ids = sorted(project_ids, key=str.lower)\\n print(my_ids)\\n return my_ids\",\n \"def create_project():\\n client = RequestManager()\\n project_name = \\\"\\\".join(choices(string.ascii_letters + string.digits, k=10))\\n client.set_method(\\\"POST\\\")\\n client.set_endpoint(\\\"/projects\\\")\\n body = {\\\"name\\\": project_name}\\n client.set_body(json.dumps(body))\\n response = client.execute_request()\\n STORED_ID['project_id'] = response.json()['id']\",\n \"def project_id(self) -> Optional[str]:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> str:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> str:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> str:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def project_id(self) -> str:\\n return pulumi.get(self, \\\"project_id\\\")\",\n \"def set_projects(self, name_short, name, disc_path):\\n if name not in conf.projects:\\n pass # TODO add the project in the conf\\n else:\\n return \\\"Project already exist\\\"\\n return self.datas.create_path(disc_path)\",\n \"def increment_request_limit(self, _request, client_id, client_email):\\n # Avoid value explosision and protect PII info\\n if not framework_helpers.IsServiceAccount(client_email):\\n client_email = 'user@email.com'\\n self.api_requests.increment_by(\\n 1, {'client_id': client_id, 'client_email': client_email})\",\n \"def test_set_project(self):\\n self.assertEqual(AppSetting.objects.count(), 0)\\n self.assertIsNone(\\n ProjectEvent.objects.filter(\\n event_name='app_setting_set_api'\\n ).first()\\n )\\n\\n setting_name = 'project_str_setting'\\n url = reverse(\\n 'projectroles:api_project_setting_set',\\n kwargs={'project': self.project.sodar_uuid},\\n )\\n post_data = {\\n 'app_name': EX_APP_NAME,\\n 'setting_name': setting_name,\\n 'value': 'value',\\n }\\n response = self.request_knox(url, method='POST', data=post_data)\\n\\n self.assertEqual(response.status_code, 200, msg=response.content)\\n self.assertEqual(AppSetting.objects.count(), 1)\\n obj = AppSetting.objects.get(name=setting_name, project=self.project)\\n self.assertEqual(obj.get_value(), 'value')\\n tl_event = ProjectEvent.objects.filter(\\n event_name='app_setting_set_api'\\n ).first()\\n self.assertIsNotNone(tl_event)\\n self.assertEqual(tl_event.classified, True)\\n self.assertEqual(tl_event.extra_data, {'value': 'value'})\",\n \"def test_projects_id_post(self):\\n project = Project()\\n response = self.client.open('/project-tracker/projects/{id}'.format(id=3.4),\\n method='POST',\\n data=json.dumps(project),\\n content_type='application/json')\\n self.assert200(response, \\\"Response body is : \\\" + response.data.decode('utf-8'))\",\n \"def put(self):\\n # fetch parameter\\n get_parser = reqparse.RequestParser(bundle_errors=True)\\n get_parser.add_argument(\\\"user_id\\\", required=True, help=\\\"User ID required to acccess the user's favourite projects\\\")\\n get_parser.add_argument(\\\"project_id\\\", required=True, help=\\\"Project ID required to remove a project\\\")\\n args = get_parser.parse_args(strict=True)\\n\\n # get user_id and project_id\\n user_id = args[\\\"user_id\\\"]\\n project_id = args[\\\"project_id\\\"]\\n\\n # convert parameter ids into objectids\\n try:\\n user_id = ObjectId(user_id)\\n project_id = ObjectId(project_id)\\n except:\\n return {\\\"message\\\": \\\"invalid user id or project id\\\"}, 400\\n\\n # add project to the user's favourites \\n if ('user_id' or 'project_id') not in args.keys():\\n return {\\\"message\\\": \\\"both user and project id are required\\\"}, 400\\n else:\\n # check if user is valid\\n user = self.users.find_one({\\\"_id\\\": user_id})\\n project = self.projects.find_one({\\\"_id\\\": project_id})\\n if user is None:\\n return {\\\"message\\\": \\\"user not found\\\"}, 404\\n elif project is None:\\n return {\\\"message\\\": \\\"project not found\\\"}, 404\\n else:\\n # remove project from the user's favourites\\n user_favourites = self.favourites.find_one({\\\"user_id\\\": user_id})\\n if user_favourites is None:\\n return {\\\"message\\\": \\\"user does not have any favourite projects\\\"}, 400\\n else:\\n new_favourite_list = user_favourites[\\\"favourite_projects\\\"]\\n\\n # try to remove the project if it is in the favourites\\n try:\\n new_favourite_list.remove(project)\\n except:\\n return {\\\"message\\\": \\\"the project is not in the favourites list\\\"}, 400\\n\\n if new_favourite_list is None:\\n new_favourite_list = []\\n\\n updated_list = {\\\"favourite_projects\\\": new_favourite_list}\\n self.favourites.update({\\\"user_id\\\": user_id}, {\\\"$set\\\": updated_list}, upsert=False)\\n \\n return {\\\"status\\\": \\\"project has been removed from favourites successfully\\\"}, 200\",\n \"def set_or_create_dataset(conn: BlitzGateway, project_id: Union[int, None],\\n dataset: Union[str, int],\\n across_groups: Optional[bool] = True\\n ) -> Union[int, None]:\\n if isinstance(dataset, str):\\n if project_id:\\n dataset_id = post_dataset(conn, dataset, project_id=project_id)\\n else:\\n dataset_id = post_dataset(conn, dataset)\\n print(f'Created new Dataset:{dataset_id}')\\n elif (isinstance(dataset, int)):\\n dataset_id = dataset\\n else:\\n raise TypeError(\\\"'dataset' must be str or int\\\")\\n return dataset_id\",\n \"def assign_project_to_client(self, project=None, client_id=None):\\n is_project = type(project) is Project\\n one_not_set = project is None or client_id is None\\n client_exists = client_id in [c.client_id for c in self.client_list]\\n client_is_self = client_id == project.client_id\\n\\n # cancel, if either:\\n # argument is not a project\\n # one argument not set\\n # client_id already exists\\n # client already assigned\\n if not is_project or one_not_set or not client_exists or client_is_self:\\n return False\\n\\n # assign the project to the new client\\n self.delete_project_file(project=project)\\n project.client_id = client_id\\n self.save_project_to_file(project=project)\\n return True\",\n \"def _get_project_id(self, request):\\n project_id = request.environ[\\\"masakari.context\\\"].project_id\\n if project_id in request.url:\\n return project_id\\n return ''\",\n \"def read_project(response):\\n STORED_ID['project_id'] = response.json()[\\\"id\\\"]\",\n \"def patch_namespaced_project(self, body, name, **kwargs):\\n\\n all_params = ['body', 'name', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method patch_namespaced_project\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `patch_namespaced_project`\\\")\\n # verify the required parameter 'name' is set\\n if ('name' not in params) or (params['name'] is None):\\n raise ValueError(\\\"Missing the required parameter `name` when calling `patch_namespaced_project`\\\")\\n\\n resource_path = '/oapi/v1/projects/{name}'.replace('{format}', 'json')\\n path_params = {}\\n if 'name' in params:\\n path_params['name'] = params['name']\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['application/json-patch+json', 'application/merge-patch+json', 'application/strategic-merge-patch+json'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'PATCH',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Project',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def get_project(self, project):\\n project_name = project\\n\\n try:\\n # FIXME: project should be an integer or str, no both\\n project_id = int(project)\\n except ValueError:\\n project_id = None\\n\\n try:\\n # Find the first project occurrence\\n project_found = next(p for p in self.get_projects() if p[\\\"id\\\"] == project_id\\n or p[\\\"name\\\"] == project_name)\\n # FIXME: use namedtuple instead? create a self.project = dict()?\\n self.project_name = project_found[\\\"name\\\"]\\n self.project_id = project_found[\\\"id\\\"]\\n self.project_address = \\\"projects/%s/\\\" % self.project_id\\n except StopIteration:\\n logger.error(\\\"Project %s not found\\\" % project)\\n raise KeyError\",\n \"def test_create_project_request(self):\\n pass\",\n \"def update(self, request, pk=None):\\n lot = Lot.objects.get(pk=request.data[\\\"lotId\\\"])\\n\\n project = Project.objects.get(pk=pk)\\n project.name = request.data[\\\"name\\\"]\\n project.estimatedCost = request.data[\\\"estimatedCost\\\"]\\n project.estimatedCompletionDate = request.data[\\\"estimatedCompletionDate\\\"]\\n #project.projectNote = Note.objects.get(pk=request.data['projectNote'])\\n\\n project.lotId = lot\\n project.save()\\n\\n return Response({}, status=status.HTTP_204_NO_CONTENT)\",\n \"def project(self):\\n return self._properties.get(\\\"jobReference\\\", {}).get(\\\"projectId\\\")\",\n \"def test_list_project_request(self):\\n pass\",\n \"def increment(conn, project):\\n with conn:\\n c = conn.cursor()\\n c.execute(\\\"\\\"\\\"INSERT OR REPLACE \\n INTO projects (project, alias, called) \\n VALUES \\n (?,\\n (SELECT alias FROM projects WHERE project=?),\\n (SELECT called FROM projects WHERE project=?) + 1\\n )\\\"\\\"\\\", (project, project, project,))\",\n \"def setJobId(self, jobid):\\n self._ShREEKConfig.setJobId(jobid)\",\n \"def test_set_invalid_scope_project(self):\\n setting_name = 'project_str_setting'\\n url = reverse('projectroles:api_user_setting_set')\\n post_data = {\\n 'app_name': EX_APP_NAME,\\n 'setting_name': setting_name,\\n 'value': 'value',\\n }\\n response = self.request_knox(url, method='POST', data=post_data)\\n self.assertEqual(response.status_code, 400, msg=response.content)\\n self.assertEqual(AppSetting.objects.count(), 0)\",\n \"def __init__(self, project_id, dataset_id, sandbox_dataset_id):\\n desc = 'Sandbox and update invalid zip codes found in the observation table.'\\n super().__init__(issue_numbers=['DC1633'],\\n description=desc,\\n affected_datasets=[cdr_consts.RDR],\\n affected_tables=[OBSERVATION],\\n project_id=project_id,\\n dataset_id=dataset_id,\\n sandbox_dataset_id=sandbox_dataset_id)\",\n \"def select_approved_projects(self):\\r\\n print \\\"Selecting approved projects... \\\"\\r\\n global ANNUAL_BUDGET\\r\\n \\r\\n projects_citizens_sorted = sorted(self.projects_for_vote, key=lambda project:project.units, reverse=True)\\r\\n projects_reps_sorted = sorted(self.projects_for_vote, key=lambda project:project.p_units, reverse=True)\\r\\n budget_sum = 0\\r\\n \\r\\n for p in projects_citizens_sorted:\\r\\n budget_sum += p.budget\\r\\n if budget_sum <= ANNUAL_BUDGET/2:\\r\\n self.projects_approved.append(p)\\r\\n\\r\\n budget_sum = 0\\r\\n for p in projects_reps_sorted:\\r\\n if p not in self.projects_approved:\\r\\n budget_sum += p.budget\\r\\n if budget_sum <= ANNUAL_BUDGET/2:\\r\\n self.projects_approved.append(p)\\r\\n\\r\\n\\r\\n \\r\\n# raw_input(\\\"select_approved_projects - antes\\\")\\r\\n for p in projects_citizens_sorted:\\r\\n print p\\r\\n print \\\"\\\\nReps\\\\n\\\"\\r\\n for p in projects_reps_sorted:\\r\\n print p\\r\\n print \\\"\\\\nApproved\\\\n\\\"\\r\\n for p in self.projects_approved:\\r\\n print p\\r\\n\\r\\n raw_input(\\\"select_approved_projects - depois\\\")\",\n \"def create_project(project_id: str,\\n admin_token: str,\\n project_admin: str,\\n csp: str='AWS',\\n budget: float=10) -> dict:\\n\\n if budget == 10:\\n print(\\\"Set the budget of Project {%s} to default value: $%.2f\\\" %(project_id, budget))\\n print(\\\"Update the budget using: set_budget(amount)\\\")\\n \\n print('Cloud service provider: ', csp)\\n\\n if csp not in ['AWS', 'AZURE', 'GCP', 'PRIVATE']:\\n print('CSP not supported: Current options: AWS, AZURE, GCP, PRIVATE')\\n return\\n\\n resp = RestRequest(CredentialApi.create_project) \\\\\\n .with_data({'project_id': project_id,\\n 'budget': budget,\\n 'admin_token': admin_token,\\n 'csp': csp,\\n \\\"project_admin_name\\\": project_admin}) \\\\\\n .run()\\n \\n # cloud service provider is private cluster, create bucket accordingly\\n if csp == 'PRIVATE':\\n print(resp)\\n bucket_name = resp['bucket_name']\\n private_cluster = get_private_cluster()\\n private_cluster.create_buckets(bucket_name)\\n \\n return resp\",\n \"def prompt(self, console: io.IO, step: str,\\n args: Dict[str, Any]) -> Dict[str, Any]:\\n prompter = GoogleNewProjectId()\\n\\n if args.get('use_existing_project', False):\\n prompter = GoogleExistingProjectId(self.project_client,\\n self.active_account)\\n\\n return prompter.prompt(console, step, args)\",\n \"def add_project(self, proj, i):\\r\\n self.__projects[i] = proj\",\n \"def RunWithArgs(self, resource):\\n client = GetClientFromFlags()\\n global_params = GetGlobalParamsFromFlags()\\n request = messages.IamProjectsServiceAccountsSetIamPolicyRequest(\\n resource=resource.decode('utf8'),\\n )\\n if FLAGS['setIamPolicyRequest'].present:\\n request.setIamPolicyRequest = apitools_base.JsonToMessage(messages.SetIamPolicyRequest, FLAGS.setIamPolicyRequest)\\n result = client.projects_serviceAccounts.SetIamPolicy(\\n request, global_params=global_params)\\n print apitools_base_cli.FormatOutput(result)\",\n \"def set_missing_id(self, data, **kwargs):\\n if not data.get(\\\"project_id\\\"):\\n data[\\\"project_id\\\"] = lambda: uuid.uuid4().hex\\n\\n return data\",\n \"def __init__(self, project_id, namespace=None):\\n self._client = datastore.Client(project=project_id, namespace=namespace)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61926836","0.6037495","0.5940458","0.58782727","0.58782727","0.5392154","0.53831047","0.5383003","0.5351515","0.5217758","0.52084017","0.51797605","0.51797605","0.51708114","0.5099718","0.5095747","0.5076841","0.50675255","0.50642264","0.5054526","0.5043689","0.5032281","0.5032281","0.5032281","0.5032281","0.50313395","0.5015842","0.50030303","0.4980436","0.4980237","0.49698266","0.48411617","0.4812488","0.4810658","0.48073867","0.4799563","0.4795049","0.4755343","0.474582","0.47347268","0.4683711","0.46784484","0.46784484","0.46784484","0.465331","0.46349317","0.45823047","0.45763767","0.45722067","0.4570607","0.4568762","0.4554865","0.4549979","0.45420465","0.45371655","0.4524065","0.4508199","0.4508199","0.4508199","0.4508199","0.4508199","0.45002657","0.44787267","0.44635788","0.44400188","0.44385755","0.4427575","0.44120008","0.4407186","0.44056413","0.44025064","0.44025064","0.44025064","0.44025064","0.4394484","0.4392009","0.43757388","0.4367188","0.4354402","0.43508613","0.43481016","0.43447968","0.4344407","0.43404222","0.43345177","0.43327397","0.43312165","0.43269286","0.43181726","0.43152732","0.43124634","0.43044785","0.4302804","0.43001324","0.4299092","0.4287585","0.42819652","0.42764556","0.42677814","0.42617783"],"string":"[\n \"0.61926836\",\n \"0.6037495\",\n \"0.5940458\",\n \"0.58782727\",\n \"0.58782727\",\n \"0.5392154\",\n \"0.53831047\",\n \"0.5383003\",\n \"0.5351515\",\n \"0.5217758\",\n \"0.52084017\",\n \"0.51797605\",\n \"0.51797605\",\n \"0.51708114\",\n \"0.5099718\",\n \"0.5095747\",\n \"0.5076841\",\n \"0.50675255\",\n \"0.50642264\",\n \"0.5054526\",\n \"0.5043689\",\n \"0.5032281\",\n \"0.5032281\",\n \"0.5032281\",\n \"0.5032281\",\n \"0.50313395\",\n \"0.5015842\",\n \"0.50030303\",\n \"0.4980436\",\n \"0.4980237\",\n \"0.49698266\",\n \"0.48411617\",\n \"0.4812488\",\n \"0.4810658\",\n \"0.48073867\",\n \"0.4799563\",\n \"0.4795049\",\n \"0.4755343\",\n \"0.474582\",\n \"0.47347268\",\n \"0.4683711\",\n \"0.46784484\",\n \"0.46784484\",\n \"0.46784484\",\n \"0.465331\",\n \"0.46349317\",\n \"0.45823047\",\n \"0.45763767\",\n \"0.45722067\",\n \"0.4570607\",\n \"0.4568762\",\n \"0.4554865\",\n \"0.4549979\",\n \"0.45420465\",\n \"0.45371655\",\n \"0.4524065\",\n \"0.4508199\",\n \"0.4508199\",\n \"0.4508199\",\n \"0.4508199\",\n \"0.4508199\",\n \"0.45002657\",\n \"0.44787267\",\n \"0.44635788\",\n \"0.44400188\",\n \"0.44385755\",\n \"0.4427575\",\n \"0.44120008\",\n \"0.4407186\",\n \"0.44056413\",\n \"0.44025064\",\n \"0.44025064\",\n \"0.44025064\",\n \"0.44025064\",\n \"0.4394484\",\n \"0.4392009\",\n \"0.43757388\",\n \"0.4367188\",\n \"0.4354402\",\n \"0.43508613\",\n \"0.43481016\",\n \"0.43447968\",\n \"0.4344407\",\n \"0.43404222\",\n \"0.43345177\",\n \"0.43327397\",\n \"0.43312165\",\n \"0.43269286\",\n \"0.43181726\",\n \"0.43152732\",\n \"0.43124634\",\n \"0.43044785\",\n \"0.4302804\",\n \"0.43001324\",\n \"0.4299092\",\n \"0.4287585\",\n \"0.42819652\",\n \"0.42764556\",\n \"0.42677814\",\n \"0.42617783\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7350548"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2282,"cells":{"query":{"kind":"string","value":"Ensure that view parameters are set properly tables create request."},"document":{"kind":"string","value":"def SetViewParameters(ref, args, request):\n del ref # unused\n\n if not args.view:\n request.table.view = None\n\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _create(self, tables, views, schema_name, config):\n if not isinstance(tables, dict):\n return False # Raise Exception That Tables Are In A Wrong Format???!!!\n success = True\n if schema_name is not None:\n self._create_schema(schema_name)\n for table_name_instance in tables.items():\n if self._create_table(table_name_instance[1]) is False:\n success = False\n break\n if isinstance(views, dict):\n for view_name_instance in views.items():\n if self._create_view(view_name_instance[1], schema_name, config) is False:\n success = False\n break\n return success","def test_create(self):\n session = self.prepare(user_table=True)\n\n result = list(session.execute((\"SELECT * FROM system_schema.views \"\n \"WHERE keyspace_name='ks' AND base_table_name='users' ALLOW FILTERING\")))\n assert len(result) == 1, \"Expecting 1 materialized view == got\" + str(result)","def createViews(views):\n ...","def create_view(self, repo, view, sql):\n return self.user_con.create_view(\n repo=repo, view=view, sql=sql)","def test_migrate_view_fields(self):\n self.test_view = RecordView.create(\n self.testcoll, test_view_id, test_view_create_values\n )\n migrate_coll_data(self.testcoll)\n # Read field definition and check for inline field list\n view_data = self.check_entity_values(\n \"_view\", test_view_id, check_values=test_view_migrated_values\n )\n return","def create_table(self):\n pass","def pre_route_table_create(self, resource_dict):\n pass","def create_all_views():\n cursor.execute(articleList)\n cursor.execute(goodViews)\n cursor.execute(authorsTitles)\n cursor.execute(titleViews)\n cursor.execute(dailyTotalView)\n cursor.execute(dailyErrorView)","def post_route_table_create(self, resource_dict):\n pass","def create_table_request_info(self):\n table_query = f\"\"\"\n Create Table If Not Exists Request_Info(\n {self.__fields[0]} INT AUTO_INCREMENT PRIMARY KEY,\n {self.__fields[1]} TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\n {self.__fields[2]} CHAR(30),\n {self.__fields[3]} CHAR(30),\n {self.__fields[4]} CHAR(30) NULL,\n {self.__fields[5]} DATE,\n {self.__fields[6]} CHAR(15),\n {self.__fields[7]} CHAR(30),\n {self.__fields[8]} CHAR(30),\n {self.__fields[9]} CHAR(30),\n {self.__fields[10]} INT(32),\n {self.__fields[11]} CHAR(30),\n {self.__fields[12]} INT(32),\n {self.__fields[13]} VARCHAR(30))\n \"\"\"\n self.execute(table_query)","def test_create_view_returns_empty(dummy_request):\n from learning_journal.views.default import new_entry\n assert new_entry(dummy_request) == {}","def _create_view(self, view, schema=None, config=None):\n viewname, vschema = view[\"__tablename__\"].split(' ')[0], view[\"__schema__\"].split(' ')[0]\n try:\n dve = SQL('NULL from {}.{}').format(Identifier(vschema),\n Identifier(viewname))\n veq = self.__session.query(self._sql_to_string(dve)).limit(1)\n self.__session.execute(veq)\n self._commit()\n except ProgrammingError:\n self._rollback()\n like = text(\"information_schema.routines.routine_name like 'crosstab%'\")\n count = self.__session.query('* FROM information_schema.routines')\n count = count.filter(like).count()\n if int(count) == 0:\n self._create_extension(config)\n self.exschema = 'public'\n else:\n like = text(\"information_schema.routines.routine_name like 'crosstab%'\")\n count = self.__session.query('routine_schema FROM'\n ' information_schema.routines')\n count = count.filter(like).limit(1)\n count = self.__session.execute(count).fetchone()[0]\n self._commit()\n self.exschema = count\n like = text(\"SELECT has_schema_privilege(:exschema, 'USAGE')\")\n like = self.__session.execute(like,\n {\"exschema\": self.exschema}).fetchone()[0]\n self._commit()\n if not like:\n self._grant_access(config)\n viewst, raw = self._sql_to_string(view[\"__statement__\"]), '{}.crosstab'\n defsch = self._sql_to_string(SQL(raw).format(Identifier(schema)))\n exsch = SQL(raw).format(Identifier(self.exschema))\n self.__session.execute(viewst.replace(defsch, self._sql_to_string(exsch)))\n self._commit()\n except Exception:\n self._rollback()\n self._reset_session()\n raise","def table_creater(self, tablename, columnnames, entries):\n createrurl = self.casjobsurl + '/contexts/MyDB/query'","def creates_view(self):\n return self.statements[0].creates_view()","def test_create_view_returns_empty_dict_on_get(dummy_request):\n from learning_journal.views.default import create_view\n result = create_view(dummy_request)\n assert result == {}","def prepare(self, request):\n pass","def _create_or_alter_view(self, survey_data):\n self.log.info(\"Creating or altering view vw_AllSurveyData \")\n edit_view = self._get_query('edit_view') + \"( \" + survey_data + \" )\"\n self.db.execute_query(edit_view)\n self.log.info(\"View was edited successfully\")","def setup_view(self, view, request, *args, **kwargs):\n view.request = request\n view.args = args\n view.kwargs = kwargs\n return view","def pre_interface_route_table_create(self, resource_dict):\n pass","def post(self):\n args = parser.parse_args()\n table = TableDetails(args.get('table_size'))\n db.session.add(table)\n db.session.commit()\n return table, 201","def create_tables( self ) :\n return self._create_tables","def propagate_view_creation_over_non_existing_table(self):\n\n cluster = self.cluster\n cluster.populate(3)\n cluster.start()\n node1, node2, node3 = self.cluster.nodelist()\n session = self.patient_cql_connection(node1, consistency_level=ConsistencyLevel.QUORUM)\n create_ks(session, 'ks', 3)\n\n session.execute('CREATE TABLE users (username varchar PRIMARY KEY, state varchar)')\n\n # create a materialized view only in nodes 1 and 2\n node3.stop(wait_other_notice=True)\n session.execute(('CREATE MATERIALIZED VIEW users_by_state AS '\n 'SELECT * FROM users WHERE state IS NOT NULL AND username IS NOT NULL '\n 'PRIMARY KEY (state, username)'))\n\n # drop the base table only in node 3\n node1.stop(wait_other_notice=True)\n node2.stop(wait_other_notice=True)\n node3.start(wait_for_binary_proto=True)\n session = self.patient_cql_connection(node3, consistency_level=ConsistencyLevel.QUORUM)\n session.execute('DROP TABLE ks.users')\n\n # restart the cluster\n cluster.stop()\n cluster.start()\n\n # node3 should have received and ignored the creation of the MV over the dropped table\n assert node3.grep_log('Not adding view users_by_state because the base table')","def test_create_table_successfully (self):\n\n new_table = self.wrapper.create_table(self.table, [self.bob, self.jane])\n self.assertIsNone(new_table)","def create_table(self, param, timeout):\n _abstract()","def create_table(self, param, timeout):\n _abstract()","def view(name, selectable, *, clear: bool = False):\n log.debug('view(%r, clear=%r)', name, clear)\n\n if clear:\n DDL[name] = None, None\n return None\n\n DDL[name] = (CreateView(name, selectable),\n DropView(name))\n\n return make_table(selectable, name=name)","def putTestData(self):\n # print 'Not Yet implement / sample DB table create'\n tkMessageBox.showinfo(\"Message\", \"Sample DB Table Create\")","def prePresent(self, request):","def beforeCreate(self):","def create(self):","def _create_tables():\n from Model.DataAccessor.DbAccessor.DbOrmAccessor import db\n db.create_tables([SubjectType, SubjectRegion, Subject])","def columns_setup(self):\n self.required = None\n self.addition = None\n self.deletion = None\n self.retention = None\n self.rename = None","def setup_view(view, request, *args, **kwargs):\n\n view.request = request\n view.args = args\n view.kwargs = kwargs\n return view","def create_all_tables(self):\n pass","def __init__(self, tables, views, config, schema=None, connection_retries=2):\n # pylint: disable=too-many-arguments\n self.__no_of_retries = connection_retries\n self._set_database_engine(config)\n self._set_session()\n self.exschema = schema\n\n if not self._is_session_valid():\n self._reset_session()\n\n if not self._create(tables, views, schema, config):\n raise DatabaseError.TableCreationError(\"Table creation failed. Check logs!\")","def _init_check_database(self):\n # FIXME add additional checks, for example that columns in BY,\n # ACROSS, ON are not the same ? (see task structure notes)\n # also that location columns are not used\n if self.verbose:\n print('checking input database {}'.format(self.database))\n\n # check that required columns are present\n cols = set(self.db.columns)\n message = (\n ' argument is invalid, check that all the provided attributes '\n 'are defined in the database {}'.format(self.database))\n # the argument of issuperset needs to be a list ...\n assert cols.issuperset(self.on), 'ON' + message\n assert cols.issuperset(self.across), 'ACROSS' + message\n assert cols.issuperset(self.by), 'BY' + message\n\n for col in cols:\n assert '_' not in col, \\\n col + ': you cannot use underscore in column names'\n assert '#' not in col, \\\n col + ': you cannot use \\'#\\' in column names'\n\n if self.verbose:\n print(\"input database verified\")","def __init__(self, view_name, cursor=None, schema=None):\n self.name = view_name\n self.type = 'view' # Saves using type() or isinstance\n self.columns = {}\n self.sql = ''\n self.triggers = {}\n if schema:\n self.schema = schema\n else:\n schema = None\n if cursor:\n self._get_view(cursor)","def test_view_set_construction(empty_model):\n viewset = ViewSet(model=empty_model)\n assert viewset.model is empty_model\n assert count(viewset.dynamic_views) == 0","def __init__( viewname, view ):","def do_createuser(self, *args):\n self.connection_obj.initialize_table()\n print(\"UserTable Created Successful\")","def create_tables():\r\n db = connect_database()\r\n table_wait = \"waiting\"\r\n table_helped = \"helped\"\r\n table_help = \"help\"\r\n param_name = ['cus_num', 'name', 'username', 'ru_id', 'os_platform', 'description']\r\n param_type1 = ['INTEGER PRIMARY KEY AUTOINCREMENT', 'TEXT', 'TEXT', 'TEXT', 'TEXT', 'TEXT']\r\n param_type2 = ['INTEGER PRIMARY KEY', 'TEXT', 'TEXT', 'TEXT', 'TEXT', 'TEXT']\r\n with db:\r\n create_table(db, table_wait, param_name, param_type1)\r\n create_table(db, table_helped, param_name, param_type2)\r\n create_table(db, table_help, param_name, param_type2)\r\n db.close()","def __init__(self, request, **kwargs):\n super(PSIHDReport, self).__init__(request, **kwargs)\n calculate_fn = lambda key, _: key[len(self.place_types) + 1]\n self.columns['demo_type'] = Column(\"Worker Type\", calculate_fn=calculate_fn)\n self.columns['demo_type'].view = FunctionView(calculate_fn=calculate_fn)\n self.function_views['demo_type'] = self.columns['demo_type'].view","def create_tables(): \n \n pk_contraint = \"CONSTRAINT {}_pk PRIMARY KEY ({})\"\n uq_contraint = \"CONSTRAINT {}_uq UNIQUE ({})\"\n fk_query = \"\"\"CONSTRAINT {}_fk_{} \n FOREIGN KEY ({}) \n REFERENCES {}({}) \n ON UPDATE CASCADE \n ON DELETE RESTRICT\n \"\"\"\n \n create_dict = {}\n index = 1\n\n\n ############################## public SCHEMA ##############################\n \n schema = 'public'\n create_schema(schema)\n\n #################### site ####################\n table_name = 'site'\n pk_id = 'site_id'\n uq_list = ['site_code']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_code CHAR(3),\n purok VARCHAR,\n sitio VARCHAR,\n barangay VARCHAR,\n municipality VARCHAR,\n province VARCHAR,\n region VARCHAR,\n psgc INTEGER,\n active BOOLEAN NOT NULL DEFAULT TRUE,\n season SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################## spatial SCHEMA ##############################\n \n schema = 'spatial'\n create_schema(schema)\n \n #################### exposure ####################\n table_name = 'exposure'\n pk_id = 'exp_id'\n uq_list = ['exp_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n exp_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### site_exposure ####################\n table_name = 'site_exposure'\n pk_id = 'se_id'\n uq_list = ['site_id', 'exp_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n exp_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### feature ####################\n table_name = 'feature'\n pk_id = 'feat_id'\n uq_list = ['feat_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n feat_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_feature ####################\n table_name = 'site_feature'\n pk_id = 'sf_id'\n uq_list = ['site_id', 'feat_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n feat_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### hazard_zone ####################\n table_name = 'hazard_zone'\n pk_id = 'hz_id'\n uq_list = ['site_id, geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### monitoring ####################\n table_name = 'monitoring'\n pk_id = 'mon_id'\n uq_list = ['mon_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n mon_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_monitoring ####################\n table_name = 'site_monitoring'\n pk_id = 'sm_id'\n uq_list = ['site_id', 'mon_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n mon_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################### comm SCHEMA ###############################\n \n schema = 'comm'\n create_schema(schema)\n\n #################### gsm_server ####################\n table_name = 'gsm_server'\n pk_id = 'server_id'\n uq_list = ['server_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_name VARCHAR,\n platform_type VARCHAR,\n version SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### server_port ####################\n table_name = 'server_port'\n pk_id = 'port_id'\n uq_list = ['server_id', 'port']\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_id INTEGER,\n port BOOLEAN,\n ser_port VARCHAR,\n pwr_on_pin SMALLINT,\n ring_pin SMALLINT,\n module_type SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- left\n 1- right'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### network_type ####################\n table_name = 'network_type'\n pk_id = 'prefix'\n uq_list = ['prefix']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} VARCHAR(3), \n carrier SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '1- globe\n 2- smart\n 3- landline'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### gsm_module ####################\n table_name = 'gsm_module'\n pk_id = 'gsm_id'\n uq_list = ['prefix', 'num', 'activated']\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n prefix VARCHAR(3),\n num CHAR(7),\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n port_id INTEGER,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################# temporal SCHEMA #############################\n \n schema = 'temporal'\n create_schema(schema)\n\n #################### marker_observation ####################\n table_name = 'marker_observation'\n pk_id = 'mo_id'\n uq_list = ['site_id', 'ts']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n ts TIMESTAMP,\n meas_type VARCHAR(7),\n weather VARCHAR,\n observer_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_history ####################\n table_name = 'marker_history'\n pk_id = 'hist_id'\n uq_list = ['sm_id', 'ts', 'event']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n sm_id BIGINT,\n ts TIMESTAMP,\n event BOOLEAN,\n label_name VARCHAR,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- rename\n 1- reposition'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_data ####################\n table_name = 'marker_data'\n pk_id = 'data_id'\n uq_list = ['sm_id', 'mo_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n mo_id BIGINT,\n sm_id BIGINT,\n measurement NUMERIC(5,1),\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_alert ####################\n table_name = 'marker_alert'\n pk_id = 'alert_id'\n uq_list = ['data_id']\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n data_id BIGINT,\n displacement NUMERIC(4,1),\n time_delta FLOAT,\n alert_level SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger_model ####################\n table_name = 'logger_model'\n pk_id = 'model_id'\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n has_tilt BOOLEAN,\n has_rain BOOLEAN,\n has_piezo BOOLEAN,\n has_soms BOOLEAN,\n logger_type SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger ####################\n table_name = 'logger'\n pk_id = 'logger_id'\n uq_list = ['sm_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n sm_id BIGINT,\n model_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### logger_mobile ####################\n table_name = 'logger_mobile'\n pk_id = 'mobile_id'\n uq_list = ['logger_id', 'activated']\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n logger_id INTEGER,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n sim_num VARCHAR(12),\n gsm_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n #################### EXECUTE QUERY TO CREATE TABLES ####################\n for index in create_dict.keys():\n dct = create_dict[index]\n schema = dct['schema']\n table_name = dct['table_name']\n query = dct['query']\n pk_id = dct['pk_id']\n uq_list = dct['uq_list']\n fk_dict = dct['fk_dict']\n if len(fk_dict.keys()) == 0:\n fk_constraint = ''\n else:\n fk_constraint_list = ['']\n for fk_id in fk_dict.keys():\n ref_schema = fk_dict.get(fk_id)['ref_schema']\n ref_table = fk_dict.get(fk_id)['ref_table']\n fk_part = fk_query.format(table_name, ref_table, fk_id,\n \"{}.{}\".format(ref_schema, ref_table),\n fk_id)\n fk_constraint_list.append(fk_part)\n fk_constraint = ', '.join(fk_constraint_list)\n \n query = query.format(schema, table_name, pk_id, \n pk_contraint.format(table_name, pk_id),\n uq_contraint.format(table_name, ', '.join(uq_list)),\n \"{}\".format(fk_constraint))\n qdb.execute(query)","def migrate(cls)->None:\n database.cursor.execute(\"\"\"CREATE TABLE IF NOT EXISTS rsvps (\n creatd_date varchar,\n meetup integer,\n user_id integer,\n response varchar,\n PRIMARY KEY(meetup,user_id)\n )\"\"\")\n database.connection.commit()","def check_and_create_table(self) -> None:\n table_ids = [t.table_id for t in self.instance.list_tables()]\n\n if not self.table_id in table_ids:\n self.table.create()\n f = self.table.column_family(self.family_id)\n f.create()\n\n f_inc = self.table.column_family(self.incrementer_family_id,\n gc_rule=MaxVersionsGCRule(1))\n f_inc.create()\n\n f_log = self.table.column_family(self.log_family_id)\n f_log.create()\n\n f_ce = self.table.column_family(self.cross_edge_family_id,\n gc_rule=MaxVersionsGCRule(1))\n f_ce.create()\n\n print(\"Table created\")","def setup_view(view, request=None, *args, **kwargs):\n view.request = request\n view.args = args\n view.kwargs = kwargs\n return view","def create_db(self):","def yield_table(\n self, table_name_and_type: Tuple[str, str]\n ) -> Iterable[Optional[CreateTableRequest]]:\n table_name, table_type = table_name_and_type\n schema_name = self.context.database_schema.name.__root__\n db_name = self.context.database.name.__root__\n try:\n\n columns, table_constraints = self.get_columns_and_constraints(\n schema_name=schema_name,\n table_name=table_name,\n db_name=db_name,\n inspector=self.inspector,\n )\n\n view_definition = self.get_view_definition(\n table_type=table_type,\n table_name=table_name,\n schema_name=schema_name,\n inspector=self.inspector,\n )\n\n table_request = CreateTableRequest(\n name=table_name,\n tableType=table_type,\n description=self.get_table_description(\n schema_name=schema_name,\n table_name=table_name,\n inspector=self.inspector,\n ),\n columns=columns,\n viewDefinition=view_definition,\n tableConstraints=table_constraints if table_constraints else None,\n databaseSchema=EntityReference(\n id=self.context.database_schema.id,\n type=\"databaseSchema\",\n ),\n tags=self.get_tag_labels(\n table_name=table_name\n ), # Pick tags from context info, if any\n )\n is_partitioned, partition_details = self.get_table_partition_details(\n table_name=table_name, schema_name=schema_name, inspector=self.inspector\n )\n if is_partitioned:\n table_request.tableType = TableType.Partitioned.value\n table_request.tablePartition = partition_details\n\n if table_type == TableType.View or view_definition:\n table_view = TableView.parse_obj(\n {\n \"table_name\": table_name,\n \"schema_name\": schema_name,\n \"db_name\": db_name,\n \"view_definition\": view_definition,\n }\n )\n self.context.table_views.append(table_view)\n\n yield table_request\n self.register_record(table_request=table_request)\n\n except Exception as exc:\n logger.debug(traceback.format_exc())\n logger.warning(f\"Unexpected exception to yield table [{table_name}]: {exc}\")\n self.status.failures.append(f\"{self.config.serviceName}.{table_name}\")","def test_create_tables_cmd_success(self):\n self.runner.invoke(cli,\n args=['create-tables'],\n env={'OS_ELASTICSEARCH_ADDRESS': LOCAL_ELASTICSEARCH})\n engine = config.get_engine()\n inspector = Inspector.from_engine(engine)\n self.assertTrue('models' not in inspector.get_table_names())","def create_view(self, start: int = 0, stop: int = 0):\n stmt = f\"\"\"create or replace view {self._view_name} as {self.qry}\"\"\"\n if start != 0 or stop != 0:\n sql = stmt + f\" limit {stop} offset {start}\"\n else:\n sql = stmt\n self.execquery(sql)","def prep(self):\n sq1 = 'create table TCVR ( ID, T, C, V, R , primary key ( ID ) ) ;'\n sq2 = 'create table IDX ( ID , A , primary key(A) ) ; '\n self.sq.SQX(sq1)\n self.sq.SQX(sq2)\n sq3 = \"insert into IDX VALUES ( 1 , 'A' ) ; \"\n self.sq.SQX(sq3)","def create_view(self, view_name='', description='', fields=None, order=None, filters=''):\n res, _ = self.clients.resource_registry.find_resources(name=view_name, id_only=True)\n if len(res) > 0:\n raise BadRequest('The view resource with name: %s, already exists.' % view_name)\n\n #======================\n # Arg Validations\n #======================\n validate_is_instance(fields,list, 'Specified fields must be a list.')\n validate_true(len(fields)>0, 'Specfied fields must be a list.')\n if order is not None:\n validate_is_instance(order,list, 'Specified order must be a list of fields')\n for field in order:\n if not field in fields:\n raise BadRequest('The specified ordering field was not part of the search fields.')\n\n fields = set(fields) # Convert fields to a set for aggregation across the catalogs\n #======================================================================================================\n # Priorty Queue Index Matching\n #======================================================================================================\n\n pq = [] # Priority queue for matching\n catalog_id = None\n catalogs, _ = self.clients.resource_registry.find_resources(restype=RT.Catalog, id_only=False)\n for catalog in catalogs:\n if set(catalog.catalog_fields).issubset(fields):\n index_num = len(self.clients.catalog_management.list_indexes(catalog._id))\n heapq.heappush(pq, (index_num,catalog))\n if pq:\n weight, catalog = heapq.heappop(pq)\n if weight < self.heuristic_cutoff:\n catalog_id = catalog._id\n\n \n if catalog_id is None:\n catalog_id = self.clients.catalog_management.create_catalog('%s_catalog'% view_name, keywords=list(fields))\n\n view_res = View(name=view_name, description=description)\n view_res.order = order\n view_res.filters = filters\n view_id, _ = self.clients.resource_registry.create(view_res)\n self.clients.resource_registry.create_association(subject=view_id, predicate=PRED.hasCatalog,object=catalog_id)\n return view_id","def _model_table(self, create_table_query, insert_query, parameters):\n try:\n self.session.execute(create_table_query)\n self._insert_data(insert_query, parameters)\n except Exception as e:\n print('Error on creating table for query. ' + str(e))","def setUp(self):\n self.theView = View()","def __create_presentations_table(self, schema=PRESENTATIONS_SCHEMA_310):\r\n log.info(\"table created\")\r\n QtSql.QSqlQuery(schema)","def test_create(self):\n pass","def column_create(request):\n try:\n dataset = DatasetSchema.objects.get(\n slug=request.matchdict['slug']\n ) \n except DatasetSchema.DoesNotExist:\n return {\n 'success': False, \n 'message': 'No dataset named: %s' % \n (request.matchdict['slug'])\n }\n # make sure required params are here\n required_params_list = ['name', 'data_type']\n for param in required_params_list:\n if not request.POST.get(param):\n return {\n 'success': False, \n 'message': 'Param: %s missing from request' % (param),\n }\n\n name = request.POST['name']\n data_type = request.POST['data_type']\n\n # make sure datatype is acceptable\n if data_type not in VALID_DATA_TYPES:\n return {\n 'success': False,\n 'message': 'Data Type: %s not a valid data type' % (data_type),\n }\n\n # start building new field\n new_field = Field(\n name = name,\n data_type = data_type,\n created_by_user_id = request.user.id,\n created_datetime = datetime.now(),\n )\n\n # if type is datetime make sure that a format is along with it\n\n if request.POST.get('data_type') == 'datetime':\n if not request.POST.get('datetime_format'):\n return {\n 'success': False,\n 'message': 'Missing a datetime format',\n }\n else:\n # add it\n new_field.datetime_format = request.POST['datetime_format']\n\n # save the new field\n dataset.fields.append(new_field)\n dataset.save()\n return HTTPMovedPermanently(location='/dataset/get/{}'.format(dataset.slug))","def create(self):\n ...","def test_create_view_updates_db_on_post(db_session, dummy_request):\n from learning_journal.views.default import create_view\n dummy_request.method = \"POST\"\n dummy_request.POST[\"title\"] = \"Some Title.\"\n dummy_request.POST[\"body\"] = \"Some Body.\"\n with pytest.raises(Exception):\n create_view(dummy_request)\n\n query = db_session.query(Entries).all()\n assert query[0].title == \"Some Title.\"\n assert query[0].body == \"Some Body.\"","def add_view(self, schema, create=True):\n if not constants.NAME_RX.match(schema[\"name\"]):\n raise ValueError(\"invalid view name\")\n if utils.name_in_nocase(schema[\"name\"], self.db[\"tables\"]):\n raise ValueError(\"name is already in use for a table\")\n if utils.name_in_nocase(schema[\"name\"], self.db[\"views\"]):\n raise ValueError(\"name is already in use for a view\")\n if create:\n sql = 'CREATE VIEW \"%s\" AS %s' % (\n schema[\"name\"],\n dbshare.query.get_sql_statement(schema[\"query\"]),\n )\n self.dbcnx.execute(sql)\n cursor = self.dbcnx.cursor()\n try:\n sql = 'PRAGMA table_info(\"%s\")' % schema[\"name\"]\n cursor.execute(sql)\n except sqlite3.Error: # Invalid view\n sql = 'DROP VIEW \"%s\"' % schema[\"name\"]\n cursor.execute(sql)\n raise ValueError(\"invalid view; maybe non-existent column?\")\n # Source names considering quotes and disregarding AS part, if any.\n schema[\"sources\"] = dbshare.query.get_from_sources(schema[\"query\"][\"from\"])\n schema[\"columns\"] = [{\"name\": row[1], \"type\": row[2]} for row in cursor]\n sql = \"INSERT INTO %s (name, schema) VALUES (?,?)\" % constants.VIEWS\n with self.dbcnx:\n self.dbcnx.execute(sql, (schema[\"name\"], json.dumps(schema)))\n self.db[\"views\"][schema[\"name\"]] = schema","def post_interface_route_table_create(self, resource_dict):\n pass","def test_create(self):\n cursor = connection.cursor()\n # It needs to take at least 2 args\n self.assertRaises(TypeError, db.create_table)\n self.assertRaises(TypeError, db.create_table, \"test1\")\n # Empty tables (i.e. no columns) are not fine, so make at least 1\n db.create_table(\"test1\", [('email_confirmed', models.BooleanField(default=False))])\n db.start_transaction()\n # And should exist\n cursor.execute(\"SELECT * FROM test1\")\n # Make sure we can't do the same query on an empty table\n try:\n cursor.execute(\"SELECT * FROM nottheretest1\")\n self.fail(\"Non-existent table could be selected!\")\n except:\n pass\n # Clear the dirty transaction\n db.rollback_transaction()\n db.start_transaction()\n # Remove the table\n db.delete_table(\"test1\")\n # Make sure it went\n try:\n cursor.execute(\"SELECT * FROM test1\")\n self.fail(\"Just-deleted table could be selected!\")\n except:\n pass\n # Clear the dirty transaction\n db.rollback_transaction()\n db.start_transaction()\n # Try deleting a nonexistent one\n try:\n db.delete_table(\"nottheretest1\")\n self.fail(\"Non-existent table could be deleted!\")\n except:\n pass\n db.rollback_transaction()","def setup(self):\r\n \r\n if self.requestedAction == admin.ACTION_EDIT or self.requestedAction == admin.ACTION_CREATE:\r\n \r\n # Set the required parameters\r\n for arg in RadiusAuthRestHandler.REQUIRED_PARAMS:\r\n self.supportedArgs.addReqArg(arg)\r\n \r\n # Set up the valid parameters\r\n for arg in RadiusAuthRestHandler.VALID_PARAMS:\r\n if arg not in RadiusAuthRestHandler.REQUIRED_PARAMS:\r\n self.supportedArgs.addOptArg(arg)","def _check_params(self):\n pass","def init(self, cr):\n\t\ttools.drop_view_if_exists(cr, 'purchase_order_line_summary')\n\n\t cr.execute(\"\"\" CREATE VIEW purchase_order_line_summary AS (\n\t SELECT max(id) as id,order_id,product_id,name,product_uom,sum(product_qty) as product_qty, \n\t\t\tsum(price_subtotal) as price_subtotal,avg(discount) as discount \n\t\t\tfrom purchase_order_line\n\t\t\tgroup by order_id,product_id,name,product_uom)\n\t\t\t\"\"\")","def setup_method(self):\n MANAGER._tables = {}\n MANAGER._views = {}","def init_tables(self) -> None:\n with self.table_access_condition:\n conn = self._get_connection()\n conn.execute(\"PRAGMA foreign_keys = 1\")\n c = conn.cursor()\n c.execute(tables.CREATE_STUDIES_TABLE)\n c.execute(tables.CREATE_SUBMISSIONS_TABLE)\n c.execute(tables.CREATE_REQUESTERS_TABLE)\n c.execute(tables.CREATE_UNITS_TABLE)\n c.execute(tables.CREATE_WORKERS_TABLE)\n c.execute(tables.CREATE_RUNS_TABLE)\n c.execute(tables.CREATE_RUN_MAP_TABLE)\n c.execute(tables.CREATE_PARTICIPANT_GROUPS_TABLE)\n c.execute(tables.CREATE_PARTICIPANT_GROUP_QUALIFICATIONS_MAPPING_TABLE)\n conn.commit()","def crearTabla(self):\n mensaje = self.base.createTable()\n showinfo('Resultado', mensaje)","def create_table_execute(self):\n self.execute(query=self.default_template.format(self.table_name), data=None)","def __init__(self, params=None):\n\n rights = access.Checker(params)\n rights['unspecified'] = ['deny']\n rights['edit'] = ['deny']\n rights['show'] = [('checkIsMyEntity', [notification_logic, 'scope_path'])]\n rights['delete'] = [('checkIsMyEntity', [notification_logic, 'scope_path'])]\n rights['list'] = ['checkIsUser']\n # create is developer only for the time being to test functionality\n rights['create'] = ['checkIsDeveloper']\n\n new_params = {}\n new_params['logic'] = notification_logic\n new_params['rights'] = rights\n\n new_params['name'] = \"Notification\"\n\n new_params['no_create_with_key_fields'] = True\n new_params['create_form'] = CreateForm\n\n new_params['edit_redirect'] = '/%(url_name)s/list'\n\n params = dicts.merge(params, new_params)\n\n super(View, self).__init__(params=params)","def test_db_table_creation_check(self):\n mock_cursor = Mock()\n mock_cursor.configure_mock(**{\"cursor.return_value.fetchone.return_value\": (\"vnf_table_2\")})\n status = misshtbtd.db_table_creation_check(mock_cursor, \"vnf_table_2\")\n self.assertEqual(status, True)","def create_tables (self):\n cursor = self.cur()\n cursor.execute('DROP TABLE IF EXISTS person')\n cursor.execute('DROP TABLE IF EXISTS room')\n cursor.execute('DROP TABLE IF EXISTS allocation')\n cursor.execute(\n 'CREATE TABLE IF NOT EXISTS person (person_id INTEGER PRIMARY KEY, name TEXT, role TEXT)WITHOUT ROWID')\n cursor.execute(\n 'CREATE TABLE IF NOT EXISTS room (name TEXT , no_of_members INTEGER, room_type TEXT)')\n cursor.execute(\n 'CREATE TABLE IF NOT EXISTS allocation (room_name TEXT , person_id INTEGER)')","def setUp(self):\n resume.objects.create(\n first_name='Nicholas',\n last_name='Bielinski',\n )\n experience.objects.create(\n title='Helpdesk Technician',\n location='L3 Technologies',\n start_date='6/26/2017',\n end_date='present',\n description='blah blah blah'\n )\n education.objects.create(\n institution_name='UNH Manchester',\n location='Manchester',\n degree='Bachelor',\n major='CIS',\n gpa = '3.5'\n )","def create(self):\n pass","def create(self):\n pass","def create(self):\n pass","def prepare(self):","def setup_view(view, request, *args, **kwargs):\n\n view.request = request\n view.args = args\n view.kwargs = kwargs\n setattr(request, \"session\", \"session\")\n messages = FallbackStorage(request)\n setattr(request, \"_messages\", messages)\n return view","def DEADcreate_v_fix_view():\n sql_view = \"\"\"create or replace view v_fix as\n SELECT \n fix.fix_ident, \n fix.fix_center,\n ST_Y(ST_Transform(fix.fix_center, 4326)) as fix_lat84,\n ST_X(ST_Transform(fix.fix_center, 4326)) as fix_lon84\n \n FROM \n fix\"\"\"\n conf.Cur.execute(sql_view)\n conf.Con.commit()","def initialize(self, view, request, *args, **kwargs):\n view.request = request\n view.args = args\n view.kwargs = kwargs\n return view","def addViewToDb(self,name):\n\t\tsql = \"INSERT INTO hudson_views(viewname) VALUES (%s)\"\n\t\tcsr = self.db.cursor()\n\t\tcsr.execute(sql,[name])","def on_pushButton_view_clicked(self):\n content = unicode(self.comboBox.currentText())\n if content == \"职称表\":\n data = self.sql_client.get_zc_info()\n self.fill_tableview(data)\n elif content == \"文化表\":\n data = self.sql_client.get_wh_info()\n self.fill_tableview(data)\n elif content == \"部门表\":\n data = self.sql_client.get_bm_info()\n self.fill_tableview(data)","def users_create():","def init_tables(self) -> None:\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\n # it to be?\n # \"How to know that schema changes?\"\n # logger.warning(\"some message\")\n with self.table_access_condition:\n conn = self._get_connection()\n conn.execute(\"PRAGMA foreign_keys = 1\")\n with conn:\n c = conn.cursor()\n c.execute(CREATE_PROJECTS_TABLE)\n c.execute(CREATE_TASKS_TABLE)\n c.execute(CREATE_REQUESTERS_TABLE)\n c.execute(CREATE_TASK_RUNS_TABLE)\n c.execute(CREATE_ASSIGNMENTS_TABLE)\n c.execute(CREATE_UNITS_TABLE)\n c.execute(CREATE_WORKERS_TABLE)\n c.execute(CREATE_AGENTS_TABLE)\n c.execute(CREATE_QUALIFICATIONS_TABLE)\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)","def createview_bad_request():\n db = psycopg2.connect(database=DBNAME)\n c = db.cursor()\n # counting only status 404\n c.execute(\"create view bad_request as select cast(time as date), \"\n \"count(*) as num \"\n \"from log \"\n \"where status = '404 NOT FOUND' \"\n \"group by cast(time as date) \"\n \"order by cast(time as date)\")\n db.commit()\n db.close()","def prepareController(self):\n pass","def set_up_tables():\n table_users = \"\"\"\n CREATE TABLE IF NOT EXISTS users (\n id SERIAL PRIMARY KEY,\n username VARCHAR (24) NOT NULL UNIQUE,\n firstname VARCHAR (24) NOT NULL,\n lastname VARCHAR (24) NOT NULL,\n othername VARCHAR (24),\n phone VARCHAR (24) NOT NULL,\n email VARCHAR (30) NOT NULL UNIQUE,\n password VARCHAR (128) NOT NULL,\n passportUrl VARCHAR (200),\n isPolitician BOOLEAN,\n isAdmin BOOLEAN\n )\"\"\"\n\n parties_table = \"\"\" \n CREATE TABLE IF NOT EXISTS parties (\n id SERIAL PRIMARY KEY,\n name VARCHAR (35) NOT NULL UNIQUE,\n hqAddress VARCHAR (30),\n logoUrl VARCHAR\n )\"\"\"\n\n offices_table = \"\"\"\n CREATE TABLE IF NOT EXISTS offices (\n id SERIAL PRIMARY KEY,\n name VARCHAR (35) NOT NULL UNIQUE,\n type VARCHAR (35)\n )\"\"\"\n\n canditates_table = \"\"\"\n CREATE TABLE IF NOT EXISTS candidates (\n id SERIAL,\n candidate INTEGER,\n office INTEGER,\n PRIMARY KEY (office, candidate),\n FOREIGN KEY (candidate) REFERENCES users(id) ON DELETE CASCADE,\n FOREIGN KEY (office) REFERENCES offices(id) ON DELETE CASCADE\n )\"\"\"\n\n voters_table = \"\"\"\n CREATE TABLE IF NOT EXISTS votes (\n id SERIAL,\n office INTEGER,\n candidate INTEGER,\n voter INTEGER,\n PRIMARY KEY (office, voter),\n FOREIGN KEY (office) REFERENCES offices(id) ON DELETE CASCADE,\n FOREIGN KEY (candidate) REFERENCES users(id) ON DELETE CASCADE,\n FOREIGN KEY (voter) REFERENCES users(id) ON DELETE CASCADE\n )\"\"\"\n\n return [table_users, parties_table,\n offices_table, canditates_table, voters_table]","def __init__(self, *args, **kwargs):\n self.organisation = kwargs.pop('organisation', None)\n self.cobrand = kwargs.pop('cobrand', None)\n super(ReviewTable, self).__init__(*args, **kwargs)","def create(self):\n\n pass","def create_stock_view_list_table(self):\n create_stock_view_list_sql = \"\"\"\n CREATE TABLE IF NOT EXISTS \"{0}\".\"{1}\" (\n stock_view_name text NOT NULL PRIMARY KEY,\n stock_view_relation text NOT NULL\n );\n \"\"\".format(Schemas.SCHEMA_META, Tables.TABLE_TICK_STOCK_VIEW_LIST)\n\n conn = self.db_engine.connect()\n try:\n conn.execute(create_stock_view_list_sql)\n except:\n self._logger.log_error(traceback.format_exc())\n return Error.ERROR_DB_EXECUTION_FAILED\n finally:\n conn.close()","def insert_ticket(request):\n required_keys = {'event_id', 'section', 'rownum', 'seat', 'price', 'seller_id', 'status'}\n param_keys = set(request.POST.keys())\n print(f\"param keys - {param_keys}\")\n #if len(param_keys) >= len(required_keys):\n # return \"Invalid Request\"\n\n try:\n print(param_keys)\n new_ticket = models.tickets()\n for param in param_keys:\n if param == 'status':\n setattr(new_ticket,param, bool(request.POST[param]))\n else:\n setattr(new_ticket,param, request.POST[param])\n print(param)\n print(new_ticket)\n request.dbsession.add(new_ticket) \n request.dbsession.flush()\n except DBAPIError:\n return \"Invalid Request\"\n return {'status':'success'}","def test_table_definition(self):\n create_table(LowercaseKeyModel)\n create_table(CapitalizedKeyModel)\n\n delete_table(LowercaseKeyModel)\n delete_table(CapitalizedKeyModel)","def __init__(self, table_view):\n QToolBar.__init__(self)\n self.table_view = table_view\n self.buildToolbarWidgets()","def _check_required_fields(self):\n assert self.title\n assert self.format","def create_tables(self):\n for query in table_create_sql:\n self.cursor.execute(query)\n\n self.commit()","def initView(self):\n return {}","def generate_psql_views(self, schema, schema_name_v1, schema_name_v2, psql_views_path):\n psql_views = open(psql_views_path, 'w')\n psql_views.write(\"SET client_min_messages TO ERROR;\\n\")\n psql_views.write(\"DROP SCHEMA IF EXISTS %s CASCADE;\\n\\n\" % schema_name_v1)\n psql_views.write(\"CREATE SCHEMA IF NOT EXISTS %s;\\n\\n\" % schema_name_v1)\n\n for table_name_v1, table_attr in schema['tables'].iteritems():\n table_name_v2 = table_attr['name']\n columns_pri, columns_ref, columns, columns_ignore = \\\n PsqlParser._get_categorized_columns(table_attr['columns'])\n\n columns = merge_dicts(columns_pri, columns_ref, columns)\n\n columns_v2 = [ '\"'+col_attr['name']+'\"' for col_name_v1, col_attr in columns.iteritems() ]\n columns_v2 += [ 'NULL' for col_name_v1, col_attr in columns_ignore.iteritems() ]\n\n columns_v1 = [ '\"'+col_name_v1+'\"' for col_name_v1, col_attr in columns.iteritems()]\n columns_v1 += [ '\"'+col_name_v1+'\"' for col_name_v1, col_attr in columns_ignore.iteritems() ]\n\n view_sql = ('CREATE VIEW %s (%s) AS \\n SELECT %s FROM %s WITH CASCADED CHECK OPTION;\\n\\n' % (\n \"%s.%s\" % (schema_name_v1, table_name_v1),\n ', '.join(columns_v1),\n ', '.join(columns_v2),\n \"%s.%s\" % (schema_name_v2, table_name_v2)\n ))\n\n psql_views.write(view_sql + \"\\n\")\n psql_views.close()","def create():","def create():","def create(self, request, *args, **kwargs):\n return super(UserViewSet, self).create(request, *args, **kwargs)"],"string":"[\n \"def _create(self, tables, views, schema_name, config):\\n if not isinstance(tables, dict):\\n return False # Raise Exception That Tables Are In A Wrong Format???!!!\\n success = True\\n if schema_name is not None:\\n self._create_schema(schema_name)\\n for table_name_instance in tables.items():\\n if self._create_table(table_name_instance[1]) is False:\\n success = False\\n break\\n if isinstance(views, dict):\\n for view_name_instance in views.items():\\n if self._create_view(view_name_instance[1], schema_name, config) is False:\\n success = False\\n break\\n return success\",\n \"def test_create(self):\\n session = self.prepare(user_table=True)\\n\\n result = list(session.execute((\\\"SELECT * FROM system_schema.views \\\"\\n \\\"WHERE keyspace_name='ks' AND base_table_name='users' ALLOW FILTERING\\\")))\\n assert len(result) == 1, \\\"Expecting 1 materialized view == got\\\" + str(result)\",\n \"def createViews(views):\\n ...\",\n \"def create_view(self, repo, view, sql):\\n return self.user_con.create_view(\\n repo=repo, view=view, sql=sql)\",\n \"def test_migrate_view_fields(self):\\n self.test_view = RecordView.create(\\n self.testcoll, test_view_id, test_view_create_values\\n )\\n migrate_coll_data(self.testcoll)\\n # Read field definition and check for inline field list\\n view_data = self.check_entity_values(\\n \\\"_view\\\", test_view_id, check_values=test_view_migrated_values\\n )\\n return\",\n \"def create_table(self):\\n pass\",\n \"def pre_route_table_create(self, resource_dict):\\n pass\",\n \"def create_all_views():\\n cursor.execute(articleList)\\n cursor.execute(goodViews)\\n cursor.execute(authorsTitles)\\n cursor.execute(titleViews)\\n cursor.execute(dailyTotalView)\\n cursor.execute(dailyErrorView)\",\n \"def post_route_table_create(self, resource_dict):\\n pass\",\n \"def create_table_request_info(self):\\n table_query = f\\\"\\\"\\\"\\n Create Table If Not Exists Request_Info(\\n {self.__fields[0]} INT AUTO_INCREMENT PRIMARY KEY,\\n {self.__fields[1]} TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\\n {self.__fields[2]} CHAR(30),\\n {self.__fields[3]} CHAR(30),\\n {self.__fields[4]} CHAR(30) NULL,\\n {self.__fields[5]} DATE,\\n {self.__fields[6]} CHAR(15),\\n {self.__fields[7]} CHAR(30),\\n {self.__fields[8]} CHAR(30),\\n {self.__fields[9]} CHAR(30),\\n {self.__fields[10]} INT(32),\\n {self.__fields[11]} CHAR(30),\\n {self.__fields[12]} INT(32),\\n {self.__fields[13]} VARCHAR(30))\\n \\\"\\\"\\\"\\n self.execute(table_query)\",\n \"def test_create_view_returns_empty(dummy_request):\\n from learning_journal.views.default import new_entry\\n assert new_entry(dummy_request) == {}\",\n \"def _create_view(self, view, schema=None, config=None):\\n viewname, vschema = view[\\\"__tablename__\\\"].split(' ')[0], view[\\\"__schema__\\\"].split(' ')[0]\\n try:\\n dve = SQL('NULL from {}.{}').format(Identifier(vschema),\\n Identifier(viewname))\\n veq = self.__session.query(self._sql_to_string(dve)).limit(1)\\n self.__session.execute(veq)\\n self._commit()\\n except ProgrammingError:\\n self._rollback()\\n like = text(\\\"information_schema.routines.routine_name like 'crosstab%'\\\")\\n count = self.__session.query('* FROM information_schema.routines')\\n count = count.filter(like).count()\\n if int(count) == 0:\\n self._create_extension(config)\\n self.exschema = 'public'\\n else:\\n like = text(\\\"information_schema.routines.routine_name like 'crosstab%'\\\")\\n count = self.__session.query('routine_schema FROM'\\n ' information_schema.routines')\\n count = count.filter(like).limit(1)\\n count = self.__session.execute(count).fetchone()[0]\\n self._commit()\\n self.exschema = count\\n like = text(\\\"SELECT has_schema_privilege(:exschema, 'USAGE')\\\")\\n like = self.__session.execute(like,\\n {\\\"exschema\\\": self.exschema}).fetchone()[0]\\n self._commit()\\n if not like:\\n self._grant_access(config)\\n viewst, raw = self._sql_to_string(view[\\\"__statement__\\\"]), '{}.crosstab'\\n defsch = self._sql_to_string(SQL(raw).format(Identifier(schema)))\\n exsch = SQL(raw).format(Identifier(self.exschema))\\n self.__session.execute(viewst.replace(defsch, self._sql_to_string(exsch)))\\n self._commit()\\n except Exception:\\n self._rollback()\\n self._reset_session()\\n raise\",\n \"def table_creater(self, tablename, columnnames, entries):\\n createrurl = self.casjobsurl + '/contexts/MyDB/query'\",\n \"def creates_view(self):\\n return self.statements[0].creates_view()\",\n \"def test_create_view_returns_empty_dict_on_get(dummy_request):\\n from learning_journal.views.default import create_view\\n result = create_view(dummy_request)\\n assert result == {}\",\n \"def prepare(self, request):\\n pass\",\n \"def _create_or_alter_view(self, survey_data):\\n self.log.info(\\\"Creating or altering view vw_AllSurveyData \\\")\\n edit_view = self._get_query('edit_view') + \\\"( \\\" + survey_data + \\\" )\\\"\\n self.db.execute_query(edit_view)\\n self.log.info(\\\"View was edited successfully\\\")\",\n \"def setup_view(self, view, request, *args, **kwargs):\\n view.request = request\\n view.args = args\\n view.kwargs = kwargs\\n return view\",\n \"def pre_interface_route_table_create(self, resource_dict):\\n pass\",\n \"def post(self):\\n args = parser.parse_args()\\n table = TableDetails(args.get('table_size'))\\n db.session.add(table)\\n db.session.commit()\\n return table, 201\",\n \"def create_tables( self ) :\\n return self._create_tables\",\n \"def propagate_view_creation_over_non_existing_table(self):\\n\\n cluster = self.cluster\\n cluster.populate(3)\\n cluster.start()\\n node1, node2, node3 = self.cluster.nodelist()\\n session = self.patient_cql_connection(node1, consistency_level=ConsistencyLevel.QUORUM)\\n create_ks(session, 'ks', 3)\\n\\n session.execute('CREATE TABLE users (username varchar PRIMARY KEY, state varchar)')\\n\\n # create a materialized view only in nodes 1 and 2\\n node3.stop(wait_other_notice=True)\\n session.execute(('CREATE MATERIALIZED VIEW users_by_state AS '\\n 'SELECT * FROM users WHERE state IS NOT NULL AND username IS NOT NULL '\\n 'PRIMARY KEY (state, username)'))\\n\\n # drop the base table only in node 3\\n node1.stop(wait_other_notice=True)\\n node2.stop(wait_other_notice=True)\\n node3.start(wait_for_binary_proto=True)\\n session = self.patient_cql_connection(node3, consistency_level=ConsistencyLevel.QUORUM)\\n session.execute('DROP TABLE ks.users')\\n\\n # restart the cluster\\n cluster.stop()\\n cluster.start()\\n\\n # node3 should have received and ignored the creation of the MV over the dropped table\\n assert node3.grep_log('Not adding view users_by_state because the base table')\",\n \"def test_create_table_successfully (self):\\n\\n new_table = self.wrapper.create_table(self.table, [self.bob, self.jane])\\n self.assertIsNone(new_table)\",\n \"def create_table(self, param, timeout):\\n _abstract()\",\n \"def create_table(self, param, timeout):\\n _abstract()\",\n \"def view(name, selectable, *, clear: bool = False):\\n log.debug('view(%r, clear=%r)', name, clear)\\n\\n if clear:\\n DDL[name] = None, None\\n return None\\n\\n DDL[name] = (CreateView(name, selectable),\\n DropView(name))\\n\\n return make_table(selectable, name=name)\",\n \"def putTestData(self):\\n # print 'Not Yet implement / sample DB table create'\\n tkMessageBox.showinfo(\\\"Message\\\", \\\"Sample DB Table Create\\\")\",\n \"def prePresent(self, request):\",\n \"def beforeCreate(self):\",\n \"def create(self):\",\n \"def _create_tables():\\n from Model.DataAccessor.DbAccessor.DbOrmAccessor import db\\n db.create_tables([SubjectType, SubjectRegion, Subject])\",\n \"def columns_setup(self):\\n self.required = None\\n self.addition = None\\n self.deletion = None\\n self.retention = None\\n self.rename = None\",\n \"def setup_view(view, request, *args, **kwargs):\\n\\n view.request = request\\n view.args = args\\n view.kwargs = kwargs\\n return view\",\n \"def create_all_tables(self):\\n pass\",\n \"def __init__(self, tables, views, config, schema=None, connection_retries=2):\\n # pylint: disable=too-many-arguments\\n self.__no_of_retries = connection_retries\\n self._set_database_engine(config)\\n self._set_session()\\n self.exschema = schema\\n\\n if not self._is_session_valid():\\n self._reset_session()\\n\\n if not self._create(tables, views, schema, config):\\n raise DatabaseError.TableCreationError(\\\"Table creation failed. Check logs!\\\")\",\n \"def _init_check_database(self):\\n # FIXME add additional checks, for example that columns in BY,\\n # ACROSS, ON are not the same ? (see task structure notes)\\n # also that location columns are not used\\n if self.verbose:\\n print('checking input database {}'.format(self.database))\\n\\n # check that required columns are present\\n cols = set(self.db.columns)\\n message = (\\n ' argument is invalid, check that all the provided attributes '\\n 'are defined in the database {}'.format(self.database))\\n # the argument of issuperset needs to be a list ...\\n assert cols.issuperset(self.on), 'ON' + message\\n assert cols.issuperset(self.across), 'ACROSS' + message\\n assert cols.issuperset(self.by), 'BY' + message\\n\\n for col in cols:\\n assert '_' not in col, \\\\\\n col + ': you cannot use underscore in column names'\\n assert '#' not in col, \\\\\\n col + ': you cannot use \\\\'#\\\\' in column names'\\n\\n if self.verbose:\\n print(\\\"input database verified\\\")\",\n \"def __init__(self, view_name, cursor=None, schema=None):\\n self.name = view_name\\n self.type = 'view' # Saves using type() or isinstance\\n self.columns = {}\\n self.sql = ''\\n self.triggers = {}\\n if schema:\\n self.schema = schema\\n else:\\n schema = None\\n if cursor:\\n self._get_view(cursor)\",\n \"def test_view_set_construction(empty_model):\\n viewset = ViewSet(model=empty_model)\\n assert viewset.model is empty_model\\n assert count(viewset.dynamic_views) == 0\",\n \"def __init__( viewname, view ):\",\n \"def do_createuser(self, *args):\\n self.connection_obj.initialize_table()\\n print(\\\"UserTable Created Successful\\\")\",\n \"def create_tables():\\r\\n db = connect_database()\\r\\n table_wait = \\\"waiting\\\"\\r\\n table_helped = \\\"helped\\\"\\r\\n table_help = \\\"help\\\"\\r\\n param_name = ['cus_num', 'name', 'username', 'ru_id', 'os_platform', 'description']\\r\\n param_type1 = ['INTEGER PRIMARY KEY AUTOINCREMENT', 'TEXT', 'TEXT', 'TEXT', 'TEXT', 'TEXT']\\r\\n param_type2 = ['INTEGER PRIMARY KEY', 'TEXT', 'TEXT', 'TEXT', 'TEXT', 'TEXT']\\r\\n with db:\\r\\n create_table(db, table_wait, param_name, param_type1)\\r\\n create_table(db, table_helped, param_name, param_type2)\\r\\n create_table(db, table_help, param_name, param_type2)\\r\\n db.close()\",\n \"def __init__(self, request, **kwargs):\\n super(PSIHDReport, self).__init__(request, **kwargs)\\n calculate_fn = lambda key, _: key[len(self.place_types) + 1]\\n self.columns['demo_type'] = Column(\\\"Worker Type\\\", calculate_fn=calculate_fn)\\n self.columns['demo_type'].view = FunctionView(calculate_fn=calculate_fn)\\n self.function_views['demo_type'] = self.columns['demo_type'].view\",\n \"def create_tables(): \\n \\n pk_contraint = \\\"CONSTRAINT {}_pk PRIMARY KEY ({})\\\"\\n uq_contraint = \\\"CONSTRAINT {}_uq UNIQUE ({})\\\"\\n fk_query = \\\"\\\"\\\"CONSTRAINT {}_fk_{} \\n FOREIGN KEY ({}) \\n REFERENCES {}({}) \\n ON UPDATE CASCADE \\n ON DELETE RESTRICT\\n \\\"\\\"\\\"\\n \\n create_dict = {}\\n index = 1\\n\\n\\n ############################## public SCHEMA ##############################\\n \\n schema = 'public'\\n create_schema(schema)\\n\\n #################### site ####################\\n table_name = 'site'\\n pk_id = 'site_id'\\n uq_list = ['site_code']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_code CHAR(3),\\n purok VARCHAR,\\n sitio VARCHAR,\\n barangay VARCHAR,\\n municipality VARCHAR,\\n province VARCHAR,\\n region VARCHAR,\\n psgc INTEGER,\\n active BOOLEAN NOT NULL DEFAULT TRUE,\\n season SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################## spatial SCHEMA ##############################\\n \\n schema = 'spatial'\\n create_schema(schema)\\n \\n #################### exposure ####################\\n table_name = 'exposure'\\n pk_id = 'exp_id'\\n uq_list = ['exp_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n exp_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### site_exposure ####################\\n table_name = 'site_exposure'\\n pk_id = 'se_id'\\n uq_list = ['site_id', 'exp_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n exp_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### feature ####################\\n table_name = 'feature'\\n pk_id = 'feat_id'\\n uq_list = ['feat_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n feat_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_feature ####################\\n table_name = 'site_feature'\\n pk_id = 'sf_id'\\n uq_list = ['site_id', 'feat_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n feat_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### hazard_zone ####################\\n table_name = 'hazard_zone'\\n pk_id = 'hz_id'\\n uq_list = ['site_id, geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### monitoring ####################\\n table_name = 'monitoring'\\n pk_id = 'mon_id'\\n uq_list = ['mon_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n mon_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_monitoring ####################\\n table_name = 'site_monitoring'\\n pk_id = 'sm_id'\\n uq_list = ['site_id', 'mon_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n mon_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################### comm SCHEMA ###############################\\n \\n schema = 'comm'\\n create_schema(schema)\\n\\n #################### gsm_server ####################\\n table_name = 'gsm_server'\\n pk_id = 'server_id'\\n uq_list = ['server_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_name VARCHAR,\\n platform_type VARCHAR,\\n version SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### server_port ####################\\n table_name = 'server_port'\\n pk_id = 'port_id'\\n uq_list = ['server_id', 'port']\\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_id INTEGER,\\n port BOOLEAN,\\n ser_port VARCHAR,\\n pwr_on_pin SMALLINT,\\n ring_pin SMALLINT,\\n module_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- left\\n 1- right'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### network_type ####################\\n table_name = 'network_type'\\n pk_id = 'prefix'\\n uq_list = ['prefix']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} VARCHAR(3), \\n carrier SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '1- globe\\n 2- smart\\n 3- landline'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### gsm_module ####################\\n table_name = 'gsm_module'\\n pk_id = 'gsm_id'\\n uq_list = ['prefix', 'num', 'activated']\\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n prefix VARCHAR(3),\\n num CHAR(7),\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n port_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################# temporal SCHEMA #############################\\n \\n schema = 'temporal'\\n create_schema(schema)\\n\\n #################### marker_observation ####################\\n table_name = 'marker_observation'\\n pk_id = 'mo_id'\\n uq_list = ['site_id', 'ts']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n ts TIMESTAMP,\\n meas_type VARCHAR(7),\\n weather VARCHAR,\\n observer_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_history ####################\\n table_name = 'marker_history'\\n pk_id = 'hist_id'\\n uq_list = ['sm_id', 'ts', 'event']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n sm_id BIGINT,\\n ts TIMESTAMP,\\n event BOOLEAN,\\n label_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- rename\\n 1- reposition'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_data ####################\\n table_name = 'marker_data'\\n pk_id = 'data_id'\\n uq_list = ['sm_id', 'mo_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n mo_id BIGINT,\\n sm_id BIGINT,\\n measurement NUMERIC(5,1),\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_alert ####################\\n table_name = 'marker_alert'\\n pk_id = 'alert_id'\\n uq_list = ['data_id']\\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n data_id BIGINT,\\n displacement NUMERIC(4,1),\\n time_delta FLOAT,\\n alert_level SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger_model ####################\\n table_name = 'logger_model'\\n pk_id = 'model_id'\\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n has_tilt BOOLEAN,\\n has_rain BOOLEAN,\\n has_piezo BOOLEAN,\\n has_soms BOOLEAN,\\n logger_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger ####################\\n table_name = 'logger'\\n pk_id = 'logger_id'\\n uq_list = ['sm_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n sm_id BIGINT,\\n model_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### logger_mobile ####################\\n table_name = 'logger_mobile'\\n pk_id = 'mobile_id'\\n uq_list = ['logger_id', 'activated']\\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n logger_id INTEGER,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n sim_num VARCHAR(12),\\n gsm_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n #################### EXECUTE QUERY TO CREATE TABLES ####################\\n for index in create_dict.keys():\\n dct = create_dict[index]\\n schema = dct['schema']\\n table_name = dct['table_name']\\n query = dct['query']\\n pk_id = dct['pk_id']\\n uq_list = dct['uq_list']\\n fk_dict = dct['fk_dict']\\n if len(fk_dict.keys()) == 0:\\n fk_constraint = ''\\n else:\\n fk_constraint_list = ['']\\n for fk_id in fk_dict.keys():\\n ref_schema = fk_dict.get(fk_id)['ref_schema']\\n ref_table = fk_dict.get(fk_id)['ref_table']\\n fk_part = fk_query.format(table_name, ref_table, fk_id,\\n \\\"{}.{}\\\".format(ref_schema, ref_table),\\n fk_id)\\n fk_constraint_list.append(fk_part)\\n fk_constraint = ', '.join(fk_constraint_list)\\n \\n query = query.format(schema, table_name, pk_id, \\n pk_contraint.format(table_name, pk_id),\\n uq_contraint.format(table_name, ', '.join(uq_list)),\\n \\\"{}\\\".format(fk_constraint))\\n qdb.execute(query)\",\n \"def migrate(cls)->None:\\n database.cursor.execute(\\\"\\\"\\\"CREATE TABLE IF NOT EXISTS rsvps (\\n creatd_date varchar,\\n meetup integer,\\n user_id integer,\\n response varchar,\\n PRIMARY KEY(meetup,user_id)\\n )\\\"\\\"\\\")\\n database.connection.commit()\",\n \"def check_and_create_table(self) -> None:\\n table_ids = [t.table_id for t in self.instance.list_tables()]\\n\\n if not self.table_id in table_ids:\\n self.table.create()\\n f = self.table.column_family(self.family_id)\\n f.create()\\n\\n f_inc = self.table.column_family(self.incrementer_family_id,\\n gc_rule=MaxVersionsGCRule(1))\\n f_inc.create()\\n\\n f_log = self.table.column_family(self.log_family_id)\\n f_log.create()\\n\\n f_ce = self.table.column_family(self.cross_edge_family_id,\\n gc_rule=MaxVersionsGCRule(1))\\n f_ce.create()\\n\\n print(\\\"Table created\\\")\",\n \"def setup_view(view, request=None, *args, **kwargs):\\n view.request = request\\n view.args = args\\n view.kwargs = kwargs\\n return view\",\n \"def create_db(self):\",\n \"def yield_table(\\n self, table_name_and_type: Tuple[str, str]\\n ) -> Iterable[Optional[CreateTableRequest]]:\\n table_name, table_type = table_name_and_type\\n schema_name = self.context.database_schema.name.__root__\\n db_name = self.context.database.name.__root__\\n try:\\n\\n columns, table_constraints = self.get_columns_and_constraints(\\n schema_name=schema_name,\\n table_name=table_name,\\n db_name=db_name,\\n inspector=self.inspector,\\n )\\n\\n view_definition = self.get_view_definition(\\n table_type=table_type,\\n table_name=table_name,\\n schema_name=schema_name,\\n inspector=self.inspector,\\n )\\n\\n table_request = CreateTableRequest(\\n name=table_name,\\n tableType=table_type,\\n description=self.get_table_description(\\n schema_name=schema_name,\\n table_name=table_name,\\n inspector=self.inspector,\\n ),\\n columns=columns,\\n viewDefinition=view_definition,\\n tableConstraints=table_constraints if table_constraints else None,\\n databaseSchema=EntityReference(\\n id=self.context.database_schema.id,\\n type=\\\"databaseSchema\\\",\\n ),\\n tags=self.get_tag_labels(\\n table_name=table_name\\n ), # Pick tags from context info, if any\\n )\\n is_partitioned, partition_details = self.get_table_partition_details(\\n table_name=table_name, schema_name=schema_name, inspector=self.inspector\\n )\\n if is_partitioned:\\n table_request.tableType = TableType.Partitioned.value\\n table_request.tablePartition = partition_details\\n\\n if table_type == TableType.View or view_definition:\\n table_view = TableView.parse_obj(\\n {\\n \\\"table_name\\\": table_name,\\n \\\"schema_name\\\": schema_name,\\n \\\"db_name\\\": db_name,\\n \\\"view_definition\\\": view_definition,\\n }\\n )\\n self.context.table_views.append(table_view)\\n\\n yield table_request\\n self.register_record(table_request=table_request)\\n\\n except Exception as exc:\\n logger.debug(traceback.format_exc())\\n logger.warning(f\\\"Unexpected exception to yield table [{table_name}]: {exc}\\\")\\n self.status.failures.append(f\\\"{self.config.serviceName}.{table_name}\\\")\",\n \"def test_create_tables_cmd_success(self):\\n self.runner.invoke(cli,\\n args=['create-tables'],\\n env={'OS_ELASTICSEARCH_ADDRESS': LOCAL_ELASTICSEARCH})\\n engine = config.get_engine()\\n inspector = Inspector.from_engine(engine)\\n self.assertTrue('models' not in inspector.get_table_names())\",\n \"def create_view(self, start: int = 0, stop: int = 0):\\n stmt = f\\\"\\\"\\\"create or replace view {self._view_name} as {self.qry}\\\"\\\"\\\"\\n if start != 0 or stop != 0:\\n sql = stmt + f\\\" limit {stop} offset {start}\\\"\\n else:\\n sql = stmt\\n self.execquery(sql)\",\n \"def prep(self):\\n sq1 = 'create table TCVR ( ID, T, C, V, R , primary key ( ID ) ) ;'\\n sq2 = 'create table IDX ( ID , A , primary key(A) ) ; '\\n self.sq.SQX(sq1)\\n self.sq.SQX(sq2)\\n sq3 = \\\"insert into IDX VALUES ( 1 , 'A' ) ; \\\"\\n self.sq.SQX(sq3)\",\n \"def create_view(self, view_name='', description='', fields=None, order=None, filters=''):\\n res, _ = self.clients.resource_registry.find_resources(name=view_name, id_only=True)\\n if len(res) > 0:\\n raise BadRequest('The view resource with name: %s, already exists.' % view_name)\\n\\n #======================\\n # Arg Validations\\n #======================\\n validate_is_instance(fields,list, 'Specified fields must be a list.')\\n validate_true(len(fields)>0, 'Specfied fields must be a list.')\\n if order is not None:\\n validate_is_instance(order,list, 'Specified order must be a list of fields')\\n for field in order:\\n if not field in fields:\\n raise BadRequest('The specified ordering field was not part of the search fields.')\\n\\n fields = set(fields) # Convert fields to a set for aggregation across the catalogs\\n #======================================================================================================\\n # Priorty Queue Index Matching\\n #======================================================================================================\\n\\n pq = [] # Priority queue for matching\\n catalog_id = None\\n catalogs, _ = self.clients.resource_registry.find_resources(restype=RT.Catalog, id_only=False)\\n for catalog in catalogs:\\n if set(catalog.catalog_fields).issubset(fields):\\n index_num = len(self.clients.catalog_management.list_indexes(catalog._id))\\n heapq.heappush(pq, (index_num,catalog))\\n if pq:\\n weight, catalog = heapq.heappop(pq)\\n if weight < self.heuristic_cutoff:\\n catalog_id = catalog._id\\n\\n \\n if catalog_id is None:\\n catalog_id = self.clients.catalog_management.create_catalog('%s_catalog'% view_name, keywords=list(fields))\\n\\n view_res = View(name=view_name, description=description)\\n view_res.order = order\\n view_res.filters = filters\\n view_id, _ = self.clients.resource_registry.create(view_res)\\n self.clients.resource_registry.create_association(subject=view_id, predicate=PRED.hasCatalog,object=catalog_id)\\n return view_id\",\n \"def _model_table(self, create_table_query, insert_query, parameters):\\n try:\\n self.session.execute(create_table_query)\\n self._insert_data(insert_query, parameters)\\n except Exception as e:\\n print('Error on creating table for query. ' + str(e))\",\n \"def setUp(self):\\n self.theView = View()\",\n \"def __create_presentations_table(self, schema=PRESENTATIONS_SCHEMA_310):\\r\\n log.info(\\\"table created\\\")\\r\\n QtSql.QSqlQuery(schema)\",\n \"def test_create(self):\\n pass\",\n \"def column_create(request):\\n try:\\n dataset = DatasetSchema.objects.get(\\n slug=request.matchdict['slug']\\n ) \\n except DatasetSchema.DoesNotExist:\\n return {\\n 'success': False, \\n 'message': 'No dataset named: %s' % \\n (request.matchdict['slug'])\\n }\\n # make sure required params are here\\n required_params_list = ['name', 'data_type']\\n for param in required_params_list:\\n if not request.POST.get(param):\\n return {\\n 'success': False, \\n 'message': 'Param: %s missing from request' % (param),\\n }\\n\\n name = request.POST['name']\\n data_type = request.POST['data_type']\\n\\n # make sure datatype is acceptable\\n if data_type not in VALID_DATA_TYPES:\\n return {\\n 'success': False,\\n 'message': 'Data Type: %s not a valid data type' % (data_type),\\n }\\n\\n # start building new field\\n new_field = Field(\\n name = name,\\n data_type = data_type,\\n created_by_user_id = request.user.id,\\n created_datetime = datetime.now(),\\n )\\n\\n # if type is datetime make sure that a format is along with it\\n\\n if request.POST.get('data_type') == 'datetime':\\n if not request.POST.get('datetime_format'):\\n return {\\n 'success': False,\\n 'message': 'Missing a datetime format',\\n }\\n else:\\n # add it\\n new_field.datetime_format = request.POST['datetime_format']\\n\\n # save the new field\\n dataset.fields.append(new_field)\\n dataset.save()\\n return HTTPMovedPermanently(location='/dataset/get/{}'.format(dataset.slug))\",\n \"def create(self):\\n ...\",\n \"def test_create_view_updates_db_on_post(db_session, dummy_request):\\n from learning_journal.views.default import create_view\\n dummy_request.method = \\\"POST\\\"\\n dummy_request.POST[\\\"title\\\"] = \\\"Some Title.\\\"\\n dummy_request.POST[\\\"body\\\"] = \\\"Some Body.\\\"\\n with pytest.raises(Exception):\\n create_view(dummy_request)\\n\\n query = db_session.query(Entries).all()\\n assert query[0].title == \\\"Some Title.\\\"\\n assert query[0].body == \\\"Some Body.\\\"\",\n \"def add_view(self, schema, create=True):\\n if not constants.NAME_RX.match(schema[\\\"name\\\"]):\\n raise ValueError(\\\"invalid view name\\\")\\n if utils.name_in_nocase(schema[\\\"name\\\"], self.db[\\\"tables\\\"]):\\n raise ValueError(\\\"name is already in use for a table\\\")\\n if utils.name_in_nocase(schema[\\\"name\\\"], self.db[\\\"views\\\"]):\\n raise ValueError(\\\"name is already in use for a view\\\")\\n if create:\\n sql = 'CREATE VIEW \\\"%s\\\" AS %s' % (\\n schema[\\\"name\\\"],\\n dbshare.query.get_sql_statement(schema[\\\"query\\\"]),\\n )\\n self.dbcnx.execute(sql)\\n cursor = self.dbcnx.cursor()\\n try:\\n sql = 'PRAGMA table_info(\\\"%s\\\")' % schema[\\\"name\\\"]\\n cursor.execute(sql)\\n except sqlite3.Error: # Invalid view\\n sql = 'DROP VIEW \\\"%s\\\"' % schema[\\\"name\\\"]\\n cursor.execute(sql)\\n raise ValueError(\\\"invalid view; maybe non-existent column?\\\")\\n # Source names considering quotes and disregarding AS part, if any.\\n schema[\\\"sources\\\"] = dbshare.query.get_from_sources(schema[\\\"query\\\"][\\\"from\\\"])\\n schema[\\\"columns\\\"] = [{\\\"name\\\": row[1], \\\"type\\\": row[2]} for row in cursor]\\n sql = \\\"INSERT INTO %s (name, schema) VALUES (?,?)\\\" % constants.VIEWS\\n with self.dbcnx:\\n self.dbcnx.execute(sql, (schema[\\\"name\\\"], json.dumps(schema)))\\n self.db[\\\"views\\\"][schema[\\\"name\\\"]] = schema\",\n \"def post_interface_route_table_create(self, resource_dict):\\n pass\",\n \"def test_create(self):\\n cursor = connection.cursor()\\n # It needs to take at least 2 args\\n self.assertRaises(TypeError, db.create_table)\\n self.assertRaises(TypeError, db.create_table, \\\"test1\\\")\\n # Empty tables (i.e. no columns) are not fine, so make at least 1\\n db.create_table(\\\"test1\\\", [('email_confirmed', models.BooleanField(default=False))])\\n db.start_transaction()\\n # And should exist\\n cursor.execute(\\\"SELECT * FROM test1\\\")\\n # Make sure we can't do the same query on an empty table\\n try:\\n cursor.execute(\\\"SELECT * FROM nottheretest1\\\")\\n self.fail(\\\"Non-existent table could be selected!\\\")\\n except:\\n pass\\n # Clear the dirty transaction\\n db.rollback_transaction()\\n db.start_transaction()\\n # Remove the table\\n db.delete_table(\\\"test1\\\")\\n # Make sure it went\\n try:\\n cursor.execute(\\\"SELECT * FROM test1\\\")\\n self.fail(\\\"Just-deleted table could be selected!\\\")\\n except:\\n pass\\n # Clear the dirty transaction\\n db.rollback_transaction()\\n db.start_transaction()\\n # Try deleting a nonexistent one\\n try:\\n db.delete_table(\\\"nottheretest1\\\")\\n self.fail(\\\"Non-existent table could be deleted!\\\")\\n except:\\n pass\\n db.rollback_transaction()\",\n \"def setup(self):\\r\\n \\r\\n if self.requestedAction == admin.ACTION_EDIT or self.requestedAction == admin.ACTION_CREATE:\\r\\n \\r\\n # Set the required parameters\\r\\n for arg in RadiusAuthRestHandler.REQUIRED_PARAMS:\\r\\n self.supportedArgs.addReqArg(arg)\\r\\n \\r\\n # Set up the valid parameters\\r\\n for arg in RadiusAuthRestHandler.VALID_PARAMS:\\r\\n if arg not in RadiusAuthRestHandler.REQUIRED_PARAMS:\\r\\n self.supportedArgs.addOptArg(arg)\",\n \"def _check_params(self):\\n pass\",\n \"def init(self, cr):\\n\\t\\ttools.drop_view_if_exists(cr, 'purchase_order_line_summary')\\n\\n\\t cr.execute(\\\"\\\"\\\" CREATE VIEW purchase_order_line_summary AS (\\n\\t SELECT max(id) as id,order_id,product_id,name,product_uom,sum(product_qty) as product_qty, \\n\\t\\t\\tsum(price_subtotal) as price_subtotal,avg(discount) as discount \\n\\t\\t\\tfrom purchase_order_line\\n\\t\\t\\tgroup by order_id,product_id,name,product_uom)\\n\\t\\t\\t\\\"\\\"\\\")\",\n \"def setup_method(self):\\n MANAGER._tables = {}\\n MANAGER._views = {}\",\n \"def init_tables(self) -> None:\\n with self.table_access_condition:\\n conn = self._get_connection()\\n conn.execute(\\\"PRAGMA foreign_keys = 1\\\")\\n c = conn.cursor()\\n c.execute(tables.CREATE_STUDIES_TABLE)\\n c.execute(tables.CREATE_SUBMISSIONS_TABLE)\\n c.execute(tables.CREATE_REQUESTERS_TABLE)\\n c.execute(tables.CREATE_UNITS_TABLE)\\n c.execute(tables.CREATE_WORKERS_TABLE)\\n c.execute(tables.CREATE_RUNS_TABLE)\\n c.execute(tables.CREATE_RUN_MAP_TABLE)\\n c.execute(tables.CREATE_PARTICIPANT_GROUPS_TABLE)\\n c.execute(tables.CREATE_PARTICIPANT_GROUP_QUALIFICATIONS_MAPPING_TABLE)\\n conn.commit()\",\n \"def crearTabla(self):\\n mensaje = self.base.createTable()\\n showinfo('Resultado', mensaje)\",\n \"def create_table_execute(self):\\n self.execute(query=self.default_template.format(self.table_name), data=None)\",\n \"def __init__(self, params=None):\\n\\n rights = access.Checker(params)\\n rights['unspecified'] = ['deny']\\n rights['edit'] = ['deny']\\n rights['show'] = [('checkIsMyEntity', [notification_logic, 'scope_path'])]\\n rights['delete'] = [('checkIsMyEntity', [notification_logic, 'scope_path'])]\\n rights['list'] = ['checkIsUser']\\n # create is developer only for the time being to test functionality\\n rights['create'] = ['checkIsDeveloper']\\n\\n new_params = {}\\n new_params['logic'] = notification_logic\\n new_params['rights'] = rights\\n\\n new_params['name'] = \\\"Notification\\\"\\n\\n new_params['no_create_with_key_fields'] = True\\n new_params['create_form'] = CreateForm\\n\\n new_params['edit_redirect'] = '/%(url_name)s/list'\\n\\n params = dicts.merge(params, new_params)\\n\\n super(View, self).__init__(params=params)\",\n \"def test_db_table_creation_check(self):\\n mock_cursor = Mock()\\n mock_cursor.configure_mock(**{\\\"cursor.return_value.fetchone.return_value\\\": (\\\"vnf_table_2\\\")})\\n status = misshtbtd.db_table_creation_check(mock_cursor, \\\"vnf_table_2\\\")\\n self.assertEqual(status, True)\",\n \"def create_tables (self):\\n cursor = self.cur()\\n cursor.execute('DROP TABLE IF EXISTS person')\\n cursor.execute('DROP TABLE IF EXISTS room')\\n cursor.execute('DROP TABLE IF EXISTS allocation')\\n cursor.execute(\\n 'CREATE TABLE IF NOT EXISTS person (person_id INTEGER PRIMARY KEY, name TEXT, role TEXT)WITHOUT ROWID')\\n cursor.execute(\\n 'CREATE TABLE IF NOT EXISTS room (name TEXT , no_of_members INTEGER, room_type TEXT)')\\n cursor.execute(\\n 'CREATE TABLE IF NOT EXISTS allocation (room_name TEXT , person_id INTEGER)')\",\n \"def setUp(self):\\n resume.objects.create(\\n first_name='Nicholas',\\n last_name='Bielinski',\\n )\\n experience.objects.create(\\n title='Helpdesk Technician',\\n location='L3 Technologies',\\n start_date='6/26/2017',\\n end_date='present',\\n description='blah blah blah'\\n )\\n education.objects.create(\\n institution_name='UNH Manchester',\\n location='Manchester',\\n degree='Bachelor',\\n major='CIS',\\n gpa = '3.5'\\n )\",\n \"def create(self):\\n pass\",\n \"def create(self):\\n pass\",\n \"def create(self):\\n pass\",\n \"def prepare(self):\",\n \"def setup_view(view, request, *args, **kwargs):\\n\\n view.request = request\\n view.args = args\\n view.kwargs = kwargs\\n setattr(request, \\\"session\\\", \\\"session\\\")\\n messages = FallbackStorage(request)\\n setattr(request, \\\"_messages\\\", messages)\\n return view\",\n \"def DEADcreate_v_fix_view():\\n sql_view = \\\"\\\"\\\"create or replace view v_fix as\\n SELECT \\n fix.fix_ident, \\n fix.fix_center,\\n ST_Y(ST_Transform(fix.fix_center, 4326)) as fix_lat84,\\n ST_X(ST_Transform(fix.fix_center, 4326)) as fix_lon84\\n \\n FROM \\n fix\\\"\\\"\\\"\\n conf.Cur.execute(sql_view)\\n conf.Con.commit()\",\n \"def initialize(self, view, request, *args, **kwargs):\\n view.request = request\\n view.args = args\\n view.kwargs = kwargs\\n return view\",\n \"def addViewToDb(self,name):\\n\\t\\tsql = \\\"INSERT INTO hudson_views(viewname) VALUES (%s)\\\"\\n\\t\\tcsr = self.db.cursor()\\n\\t\\tcsr.execute(sql,[name])\",\n \"def on_pushButton_view_clicked(self):\\n content = unicode(self.comboBox.currentText())\\n if content == \\\"职称表\\\":\\n data = self.sql_client.get_zc_info()\\n self.fill_tableview(data)\\n elif content == \\\"文化表\\\":\\n data = self.sql_client.get_wh_info()\\n self.fill_tableview(data)\\n elif content == \\\"部门表\\\":\\n data = self.sql_client.get_bm_info()\\n self.fill_tableview(data)\",\n \"def users_create():\",\n \"def init_tables(self) -> None:\\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\\n # it to be?\\n # \\\"How to know that schema changes?\\\"\\n # logger.warning(\\\"some message\\\")\\n with self.table_access_condition:\\n conn = self._get_connection()\\n conn.execute(\\\"PRAGMA foreign_keys = 1\\\")\\n with conn:\\n c = conn.cursor()\\n c.execute(CREATE_PROJECTS_TABLE)\\n c.execute(CREATE_TASKS_TABLE)\\n c.execute(CREATE_REQUESTERS_TABLE)\\n c.execute(CREATE_TASK_RUNS_TABLE)\\n c.execute(CREATE_ASSIGNMENTS_TABLE)\\n c.execute(CREATE_UNITS_TABLE)\\n c.execute(CREATE_WORKERS_TABLE)\\n c.execute(CREATE_AGENTS_TABLE)\\n c.execute(CREATE_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)\",\n \"def createview_bad_request():\\n db = psycopg2.connect(database=DBNAME)\\n c = db.cursor()\\n # counting only status 404\\n c.execute(\\\"create view bad_request as select cast(time as date), \\\"\\n \\\"count(*) as num \\\"\\n \\\"from log \\\"\\n \\\"where status = '404 NOT FOUND' \\\"\\n \\\"group by cast(time as date) \\\"\\n \\\"order by cast(time as date)\\\")\\n db.commit()\\n db.close()\",\n \"def prepareController(self):\\n pass\",\n \"def set_up_tables():\\n table_users = \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS users (\\n id SERIAL PRIMARY KEY,\\n username VARCHAR (24) NOT NULL UNIQUE,\\n firstname VARCHAR (24) NOT NULL,\\n lastname VARCHAR (24) NOT NULL,\\n othername VARCHAR (24),\\n phone VARCHAR (24) NOT NULL,\\n email VARCHAR (30) NOT NULL UNIQUE,\\n password VARCHAR (128) NOT NULL,\\n passportUrl VARCHAR (200),\\n isPolitician BOOLEAN,\\n isAdmin BOOLEAN\\n )\\\"\\\"\\\"\\n\\n parties_table = \\\"\\\"\\\" \\n CREATE TABLE IF NOT EXISTS parties (\\n id SERIAL PRIMARY KEY,\\n name VARCHAR (35) NOT NULL UNIQUE,\\n hqAddress VARCHAR (30),\\n logoUrl VARCHAR\\n )\\\"\\\"\\\"\\n\\n offices_table = \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS offices (\\n id SERIAL PRIMARY KEY,\\n name VARCHAR (35) NOT NULL UNIQUE,\\n type VARCHAR (35)\\n )\\\"\\\"\\\"\\n\\n canditates_table = \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS candidates (\\n id SERIAL,\\n candidate INTEGER,\\n office INTEGER,\\n PRIMARY KEY (office, candidate),\\n FOREIGN KEY (candidate) REFERENCES users(id) ON DELETE CASCADE,\\n FOREIGN KEY (office) REFERENCES offices(id) ON DELETE CASCADE\\n )\\\"\\\"\\\"\\n\\n voters_table = \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS votes (\\n id SERIAL,\\n office INTEGER,\\n candidate INTEGER,\\n voter INTEGER,\\n PRIMARY KEY (office, voter),\\n FOREIGN KEY (office) REFERENCES offices(id) ON DELETE CASCADE,\\n FOREIGN KEY (candidate) REFERENCES users(id) ON DELETE CASCADE,\\n FOREIGN KEY (voter) REFERENCES users(id) ON DELETE CASCADE\\n )\\\"\\\"\\\"\\n\\n return [table_users, parties_table,\\n offices_table, canditates_table, voters_table]\",\n \"def __init__(self, *args, **kwargs):\\n self.organisation = kwargs.pop('organisation', None)\\n self.cobrand = kwargs.pop('cobrand', None)\\n super(ReviewTable, self).__init__(*args, **kwargs)\",\n \"def create(self):\\n\\n pass\",\n \"def create_stock_view_list_table(self):\\n create_stock_view_list_sql = \\\"\\\"\\\"\\n CREATE TABLE IF NOT EXISTS \\\"{0}\\\".\\\"{1}\\\" (\\n stock_view_name text NOT NULL PRIMARY KEY,\\n stock_view_relation text NOT NULL\\n );\\n \\\"\\\"\\\".format(Schemas.SCHEMA_META, Tables.TABLE_TICK_STOCK_VIEW_LIST)\\n\\n conn = self.db_engine.connect()\\n try:\\n conn.execute(create_stock_view_list_sql)\\n except:\\n self._logger.log_error(traceback.format_exc())\\n return Error.ERROR_DB_EXECUTION_FAILED\\n finally:\\n conn.close()\",\n \"def insert_ticket(request):\\n required_keys = {'event_id', 'section', 'rownum', 'seat', 'price', 'seller_id', 'status'}\\n param_keys = set(request.POST.keys())\\n print(f\\\"param keys - {param_keys}\\\")\\n #if len(param_keys) >= len(required_keys):\\n # return \\\"Invalid Request\\\"\\n\\n try:\\n print(param_keys)\\n new_ticket = models.tickets()\\n for param in param_keys:\\n if param == 'status':\\n setattr(new_ticket,param, bool(request.POST[param]))\\n else:\\n setattr(new_ticket,param, request.POST[param])\\n print(param)\\n print(new_ticket)\\n request.dbsession.add(new_ticket) \\n request.dbsession.flush()\\n except DBAPIError:\\n return \\\"Invalid Request\\\"\\n return {'status':'success'}\",\n \"def test_table_definition(self):\\n create_table(LowercaseKeyModel)\\n create_table(CapitalizedKeyModel)\\n\\n delete_table(LowercaseKeyModel)\\n delete_table(CapitalizedKeyModel)\",\n \"def __init__(self, table_view):\\n QToolBar.__init__(self)\\n self.table_view = table_view\\n self.buildToolbarWidgets()\",\n \"def _check_required_fields(self):\\n assert self.title\\n assert self.format\",\n \"def create_tables(self):\\n for query in table_create_sql:\\n self.cursor.execute(query)\\n\\n self.commit()\",\n \"def initView(self):\\n return {}\",\n \"def generate_psql_views(self, schema, schema_name_v1, schema_name_v2, psql_views_path):\\n psql_views = open(psql_views_path, 'w')\\n psql_views.write(\\\"SET client_min_messages TO ERROR;\\\\n\\\")\\n psql_views.write(\\\"DROP SCHEMA IF EXISTS %s CASCADE;\\\\n\\\\n\\\" % schema_name_v1)\\n psql_views.write(\\\"CREATE SCHEMA IF NOT EXISTS %s;\\\\n\\\\n\\\" % schema_name_v1)\\n\\n for table_name_v1, table_attr in schema['tables'].iteritems():\\n table_name_v2 = table_attr['name']\\n columns_pri, columns_ref, columns, columns_ignore = \\\\\\n PsqlParser._get_categorized_columns(table_attr['columns'])\\n\\n columns = merge_dicts(columns_pri, columns_ref, columns)\\n\\n columns_v2 = [ '\\\"'+col_attr['name']+'\\\"' for col_name_v1, col_attr in columns.iteritems() ]\\n columns_v2 += [ 'NULL' for col_name_v1, col_attr in columns_ignore.iteritems() ]\\n\\n columns_v1 = [ '\\\"'+col_name_v1+'\\\"' for col_name_v1, col_attr in columns.iteritems()]\\n columns_v1 += [ '\\\"'+col_name_v1+'\\\"' for col_name_v1, col_attr in columns_ignore.iteritems() ]\\n\\n view_sql = ('CREATE VIEW %s (%s) AS \\\\n SELECT %s FROM %s WITH CASCADED CHECK OPTION;\\\\n\\\\n' % (\\n \\\"%s.%s\\\" % (schema_name_v1, table_name_v1),\\n ', '.join(columns_v1),\\n ', '.join(columns_v2),\\n \\\"%s.%s\\\" % (schema_name_v2, table_name_v2)\\n ))\\n\\n psql_views.write(view_sql + \\\"\\\\n\\\")\\n psql_views.close()\",\n \"def create():\",\n \"def create():\",\n \"def create(self, request, *args, **kwargs):\\n return super(UserViewSet, self).create(request, *args, **kwargs)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.63214684","0.6122003","0.60363513","0.59719974","0.583535","0.5826202","0.5768594","0.57384115","0.55392927","0.55050695","0.54572743","0.54387593","0.5411729","0.53755325","0.53628856","0.5360331","0.5358349","0.53566074","0.53360575","0.5325151","0.5300957","0.5295821","0.52832156","0.5261851","0.5261851","0.5245268","0.5236487","0.5225806","0.5225423","0.5215412","0.5215321","0.52086604","0.5208202","0.5180909","0.51773095","0.5176883","0.5173101","0.5169828","0.51629364","0.5160951","0.51532537","0.5152801","0.51452625","0.5145128","0.51326716","0.5123922","0.5113264","0.5110827","0.5107148","0.5094529","0.5086187","0.50802666","0.50687313","0.5061227","0.5057832","0.5050648","0.5043055","0.5039795","0.50182647","0.50099736","0.5005557","0.49996373","0.4996286","0.4991714","0.49902308","0.49871486","0.4984676","0.49800733","0.4975458","0.4970336","0.49694395","0.49692625","0.49670044","0.49665195","0.49665195","0.49665195","0.4957309","0.49526906","0.4947733","0.49427167","0.49412203","0.49392113","0.49391347","0.4930978","0.49244666","0.49228418","0.49218807","0.49068606","0.49061152","0.49052164","0.490006","0.4898409","0.48974073","0.48969144","0.48958778","0.4894352","0.48926705","0.4891448","0.4891448","0.4888753"],"string":"[\n \"0.63214684\",\n \"0.6122003\",\n \"0.60363513\",\n \"0.59719974\",\n \"0.583535\",\n \"0.5826202\",\n \"0.5768594\",\n \"0.57384115\",\n \"0.55392927\",\n \"0.55050695\",\n \"0.54572743\",\n \"0.54387593\",\n \"0.5411729\",\n \"0.53755325\",\n \"0.53628856\",\n \"0.5360331\",\n \"0.5358349\",\n \"0.53566074\",\n \"0.53360575\",\n \"0.5325151\",\n \"0.5300957\",\n \"0.5295821\",\n \"0.52832156\",\n \"0.5261851\",\n \"0.5261851\",\n \"0.5245268\",\n \"0.5236487\",\n \"0.5225806\",\n \"0.5225423\",\n \"0.5215412\",\n \"0.5215321\",\n \"0.52086604\",\n \"0.5208202\",\n \"0.5180909\",\n \"0.51773095\",\n \"0.5176883\",\n \"0.5173101\",\n \"0.5169828\",\n \"0.51629364\",\n \"0.5160951\",\n \"0.51532537\",\n \"0.5152801\",\n \"0.51452625\",\n \"0.5145128\",\n \"0.51326716\",\n \"0.5123922\",\n \"0.5113264\",\n \"0.5110827\",\n \"0.5107148\",\n \"0.5094529\",\n \"0.5086187\",\n \"0.50802666\",\n \"0.50687313\",\n \"0.5061227\",\n \"0.5057832\",\n \"0.5050648\",\n \"0.5043055\",\n \"0.5039795\",\n \"0.50182647\",\n \"0.50099736\",\n \"0.5005557\",\n \"0.49996373\",\n \"0.4996286\",\n \"0.4991714\",\n \"0.49902308\",\n \"0.49871486\",\n \"0.4984676\",\n \"0.49800733\",\n \"0.4975458\",\n \"0.4970336\",\n \"0.49694395\",\n \"0.49692625\",\n \"0.49670044\",\n \"0.49665195\",\n \"0.49665195\",\n \"0.49665195\",\n \"0.4957309\",\n \"0.49526906\",\n \"0.4947733\",\n \"0.49427167\",\n \"0.49412203\",\n \"0.49392113\",\n \"0.49391347\",\n \"0.4930978\",\n \"0.49244666\",\n \"0.49228418\",\n \"0.49218807\",\n \"0.49068606\",\n \"0.49061152\",\n \"0.49052164\",\n \"0.490006\",\n \"0.4898409\",\n \"0.48974073\",\n \"0.48969144\",\n \"0.48958778\",\n \"0.4894352\",\n \"0.48926705\",\n \"0.4891448\",\n \"0.4891448\",\n \"0.4888753\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.65944326"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2283,"cells":{"query":{"kind":"string","value":"Process the ifexists flag on datasets create."},"document":{"kind":"string","value":"def ProcessDatasetOverwrite(ref, args, request):\n del ref\n dataset_id = request.dataset.datasetReference.datasetId\n project_id = request.projectId\n\n if args.overwrite:\n if _DatasetExists(dataset_id, project_id):\n _TryDeleteDataset(dataset_id, project_id)\n\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def isExist(data):\n return True/False","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def exist(self):","def run(**kwargs):\n del kwargs # Unused args\n if os.path.exists(DATASET_PATH):\n LOGGER.info('... Dataset already exists. Skipping.')\n else:\n build()","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def test_dataset_exists(client, to_delete):\n DATASET_ID = \"get_table_dataset_{}\".format(_millis())\n dataset_ref = client.dataset(DATASET_ID)\n dataset = bigquery.Dataset(dataset_ref)\n dataset = client.create_dataset(dataset)\n to_delete.append(dataset)\n\n assert dataset_exists(client, dataset_ref)\n assert not dataset_exists(client, client.dataset(\"dataset doesnot exist\"))","def test_exists_false(self):\n self.assertFalse(SampleTemplate.exists(self.new_study.id))","def object_exists(self, fname):\n return False","def is_dataset_created(path, suffix=\"\"):\n dataset_id = None\n try:\n with open(\"%s%sdataset%s\" % (path, os.sep, suffix)) as dataset_file:\n dataset_id = dataset_file.readline().strip()\n try:\n dataset_id = bigml.api.get_dataset_id(dataset_id)\n return True, dataset_id\n except ValueError:\n return False, None\n except IOError:\n return False, None","def _does_not_exist_or_forced(self) -> bool:\n if os.path.exists(self.extracted_path) and self.force:\n logger.debug(f\"'-f/--force' flag set, deleting directory: '{self.extracted_path}'\")\n shutil.rmtree(self.extracted_path)\n logger.debug(f\"Deletion successful.\")\n elif os.path.exists(self.extracted_path) and not self.force:\n logger.warning(f\"{self.dataset_name} already exists at the destination directory '{self.extracted_path}'\")\n logger.warning(f\"If you wish to re-download the dataset, try 'sla-cli download -f/--force <DATASET>'\")\n logger.warning(f\"Skipping...\")\n return False\n\n return True","def add(self, data, check_exists=True): # pragma: no cover\n raise NotImplementedError","def object_exists(self, fname):\n return True","def exists(self, datadir):\n return False","def dataset_exists(es_url, id, es_index=\"grq\"):\n\n total, id = check_dataset(es_url, id, es_index)\n if total > 0:\n return True\n return False","def is_file_exists(self):\n pass","def _handle_exists_collection(name: str, exists: Optional[str], db: Database) -> None:\n\n if exists == \"fail\":\n if db[name].count() > 0:\n raise ValueError(f\"Collection '{name}' already exists.\")\n return\n\n if exists == \"replace\":\n if db[name].count() > 0:\n db[name].drop()\n return\n\n if exists == \"append\":\n return\n\n raise ValueError(f\"'{exists}' is not valid for if_exists\")","def test_exist_entry_on_rebuild(self):\n self.validate_attributes_in_exist_response()","def test_exists_false(self):\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))","def exists(self):\n return True","def exists(self):\n return True","def _auto_create(self):\n status = [\n os.path.exists(self.vertices_path),\n os.path.exists(self.edges_path),\n ]\n\n if not all(status):\n self._create_vertex_skel(self.path)\n self._create_edge_skel(self.path)","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def file_exist() -> bool:\n pass","def _CheckFileExistsWithData(self, logs, graph):\n self.assertTrue(graph in logs, 'File %s was not output.' % graph)\n self.assertTrue(logs[graph], 'File %s did not contain data.' % graph)","def exists(self, path):","def test_exists_true(self):\n self.assertTrue(SampleTemplate.exists(self.test_study.id))","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def test_exists_true(self):\n self.assertTrue(PrepSample.exists(self.sample_id, self.prep_template))","def test_ensure_exists(self):\n # with data\n client = kazoo.client.KazooClient()\n zkutils.ensure_exists(client, '/foo/bar', data='foo')\n kazoo.client.KazooClient.create.assert_called_with(\n '/foo/bar', b'foo', acl=mock.ANY, makepath=True,\n sequence=False)\n\n # non-data\n zkutils.ensure_exists(client, '/foo/bar')\n kazoo.client.KazooClient.create.assert_called_with(\n '/foo/bar', b'', acl=mock.ANY, makepath=True,\n sequence=False)","def test_exists_false(self):\n self.assertFalse(PrepTemplate.exists(2))","def test_ensure_exists_existing(self):\n def raise_exists(*args_unused, **kwargs_unused):\n \"\"\"zk.create side effect, raising appropriate exception.\"\"\"\n raise kazoo.client.NodeExistsError()\n\n client = kazoo.client.KazooClient()\n kazoo.client.KazooClient.create.side_effect = raise_exists\n zkutils.ensure_exists(client, '/foo/bar')\n kazoo.client.KazooClient.set_acls.assert_called_with('/foo/bar',\n mock.ANY)\n\n # ensure with data\n zkutils.ensure_exists(client, '/foo/bar', data='foo')\n kazoo.client.KazooClient.set.assert_called_with('/foo/bar', b'foo')\n kazoo.client.KazooClient.set_acls.assert_called_with('/foo/bar',\n mock.ANY)","async def create_checkpoint_if_not_exists_async(self, partition_id):","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))","def ensure_data_folder_existence() -> None:\n folder_name = params.DATA_FOLDER_NAME\n if not folder_name in os.listdir('.'):\n os.mkdir(folder_name)","def exists_dataset(self, dataset):\n assert dataset, \"Must input a valid dataset name.\"\n return any(self.get_by_dataset(dataset))","def test_exists_true(self):\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def create_dataset_folder_structure():\n\n path = Path(f'{DATASETS}/{FEATURES_DATASET}')\n if not os.path.exists(path):\n print(f'\\nWARNING: The path does not exist. Creating new directory...\\n{path}\\n')\n os.mkdir(path)\n\n try:\n for path in new_sensor_paths:\n if not os.path.exists(path):\n print(f'\\nWARNING: The path does not exist. Creating new directory...\\n{path}\\n')\n os.mkdir(path)\n else:\n print(\"\\nPath already exists!\")\n except:\n return False\n else:\n return True","def check_for_new_data(self):\n return","def test_exists_false(self):\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))","def check_file_exist(self):\n return False","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def checkfolderdata(folder = 'datas'):\n if datafolderexist(folder):\n return True\n else:\n createdatafolder(folder)\n checkfolderdata(folder)","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.split_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.split_dir))","def are_datasets_created(path, number_of_datasets, suffix='parts'):\n dataset_ids = []\n try:\n with open(\"%s%sdataset_%s\" % (path, os.sep, suffix)) as datasets_file:\n for line in datasets_file:\n dataset = line.strip()\n try:\n dataset_id = bigml.api.get_dataset_id(dataset)\n dataset_ids.append(dataset_id)\n except ValueError:\n return False, dataset_ids\n if len(dataset_ids) == number_of_datasets:\n return True, dataset_ids\n else:\n return False, dataset_ids\n except IOError:\n return False, dataset_ids","def check_and_create_sandbox_dataset(project_id, dataset_id):\n sandbox_dataset = get_sandbox_dataset_id(dataset_id)\n dataset_objs = list_datasets(project_id)\n datasets = [d.dataset_id for d in dataset_objs]\n\n if sandbox_dataset not in datasets:\n create_sandbox_dataset(project_id, dataset_id)\n return sandbox_dataset","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def entry_exists(title):\n try:\n f = default_storage.open(f\"entries/{title}.md\")\n return True\n\n except FileNotFoundError:\n return False","def document_exists(self, docid):\n raise NotImplementedError","def test_exist(self):\n with self.assertRaises(IncompetentQiitaDeveloperError):\n MetadataTemplate.exists(self.study)","def test_exists_true(self):\n self.assertTrue(PrepTemplate.exists(1))","def is_existing(self):\n return self.backend.is_existing","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.list_query_path):\n raise RuntimeError(\"'{}' is not available\".format(self.list_query_path))\n if not osp.exists(self.list_gallery_path):\n raise RuntimeError(\"'{}' is not available\".format(self.list_gallery_path))","def test_create_already_exists():\n current_folder = os.path.dirname(os.path.realpath(__file__))\n misc_folder = os.path.join(current_folder, \"misc\")\n model_file = os.path.join(misc_folder, \"model.tar\")\n create.main(\"mlp\", \"10:12:8\", model_file)\n # TODO: Check if error was logged","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_name_path):\n raise RuntimeError(\"'{}' is not available\".format(self.train_name_path))\n if not osp.exists(self.test_name_path):\n raise RuntimeError(\"'{}' is not available\".format(self.test_name_path))\n if not osp.exists(self.track_train_info_path):\n raise RuntimeError(\"'{}' is not available\".format(self.track_train_info_path))\n if not osp.exists(self.track_test_info_path):\n raise RuntimeError(\"'{}' is not available\".format(self.track_test_info_path))\n if not osp.exists(self.query_IDX_path):\n raise RuntimeError(\"'{}' is not available\".format(self.query_IDX_path))","def dataset_exists(dataset_reference, client):\n from google.cloud.exceptions import NotFound\n\n try:\n client.get_dataset(dataset_reference)\n return True\n except NotFound:\n return False","def create_file(file_path: str, override_flag: bool) -> bool:\n return (not os.path.exists(file_path)) or override_flag","async def create_checkpoint_store_if_not_exists_async(self):","def _item_exists(self, location):\n \"Does nothing\"","def _check_file_exists_helper(self, report_path, filename):\n\n if not check_data_exists(report_path, [filename]):\n raise AssertionError(\n \"{} does not exist in location {}\".format(\n filename, report_path\n )\n )","def before_dataobj_create(self, dataobj):","def _check_before_run(self):\r\n if not os.path.exists(self.dataset_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))","def check_database_exists(dbname):\n if not os.path.isfile(dbname):\n create_ivr_database(dbname)","def process(self):\n try:\n # self.alter_columns()\n self.collect_drop_fk()\n self.update_table()\n self.create_tables()\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\n return True\n except Exception as err:\n logger.error(\"create_tables [error] -> %s\" % err)","def test_filter_exists(self):\n datasets = [{\"exists\": True, \"name\": \"DATASET1\"}, {\"exists\": False, \"name\": \"DATASET2\"}]\n hits = filter_exists(\"HIT\", datasets)\n misses = filter_exists(\"MISS\", datasets)\n all = filter_exists(\"ALL\", datasets)\n nothing = filter_exists(\"NONE\", datasets)\n self.assertEqual(hits, [{\"exists\": True, \"name\": \"DATASET1\"}])\n self.assertEqual(misses, [{\"exists\": False, \"name\": \"DATASET2\"}])\n self.assertEqual(all, datasets)\n self.assertEqual(nothing, [])","def check_if_entry_exists(title: str) -> bool:\n conn = sqlite3.connect('rss.db')\n c = conn.cursor()\n try:\n c.execute(\n \"\"\"select * from entries where title = ?\"\"\",\n (title,)\n )\n records = c.fetchall()\n return len(records) > 0\n except sqlite3.OperationalError as e:\n print(f'Exception {e} caught. Recreating database.')\n c.execute('drop table if exists entries')\n conn.commit()\n conn.close()\n create()\n return False","def ResourceExists(self, name):\n pass","def test_data_source_soaps_id_exists_get(self):\n pass","def dir_exists(dirname):\n global datapath\n current_dir = './' + dirname + '/'\n parent_dir = '../' + dirname + '/'\n grandparent_dir = '../../' + dirname + '/'\n if os.path.isdir(current_dir):\n datapath = current_dir\n elif os.path.isdir(parent_dir):\n datapath = parent_dir\n elif os.path.isdir(grandparent_dir):\n datapath = grandparent_dir\n else:\n response = raw_input(\"'{}' directory does not exist. \"\n \"Create it [Y/n]? \".format(dirname))\n if not response or response[0].lower() == 'y':\n directory = os.getcwd()\n if os.path.basename(directory) == 'caribou-data-collection':\n # E.g. /caribou-data-collection/scraper.py\n datapath = current_dir\n os.makedirs(datapath)\n print 'Created', datapath\n elif os.path.basename(directory) in COUNTRIES:\n # E.g. /caribou-data-collection/country/scraper.py\n datapath = parent_dir\n os.makedirs(datapath)\n print 'Created', datapath\n elif os.path.basename(os.path.dirname(directory)) in COUNTRIES:\n # E.g. /caribou-data-collection/country/region/scraper.py\n datapath = grandparent_dir\n os.makedirs(datapath)\n print 'Created', datapath\n else:\n raise RuntimeError('Directory not created. '\n 'Please switch to the caribou-data-collection'\n ' directory and try again.')\n else:\n return False\n return True","def fileexists(cpath, create=True):\n dpath = os.path.dirname(cpath)\n if not os.path.isfile(cpath):\n if direxists(dpath) and create:\n try:\n pathlib.Path(cpath).touch()\n except os.error:\n logging.error(\"Can't create file %s!\", cpath)\n return False\n return True","def _ensure_exists(name, path=None):\n if not exists(name, path=path):\n raise CommandExecutionError(f\"Container '{name}' does not exist\")","def _check_before_run(self):\r\n if not osp.exists(self.dataset_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\r\n if not osp.exists(self.train_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))","def exists(anyid=None, **multi_match): # TODO multimatch\n if not any((anyid, multi_match)):\n raise RegistryError(\"specify at least one condition.\")\n\n if anyid:\n return ESDataset.exists(_id=anyid) or ESDataset.exists(identifier=anyid)\n\n return ESDataset.exists(**multi_match)","def _index_file_exists(idx_fn):\n if os.path.exists(idx_fn + \".npy\") and os.path.exists(idx_fn + \".info\"):\n return True\n else:\n return False","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def perform_existence_check(set_name_to_cache: bool):\n Thread(target=_perform_existence_check, args=(set_name_to_cache,)).start()","def exists(self, arg):\n raise NotImplementedError","def checkExist(self,fname,status):\n\n if (self.status == \"r\"):\n # Checks to see if it exists for reading\n # Which means it must be present\n\n if (not (os.path.exists(self.fname))):\n print(f\"Couldn't open input file: {self.fname}\")\n return False\n else:\n # Check to see if exists for reading\n # (i.e. must not exist)\n if (os.path.exists(self.fname)):\n print(f\"File {self.fname} already exists.\")\n return False\n\n return True","def checkExist(self,fname,status):\n\n if (self.status == \"r\"):\n # Checks to see if it exists for reading\n # Which means it must be present\n\n if (not (os.path.exists(self.fname))):\n print(f\"Couldn't open input file: {self.fname}\")\n return False\n else:\n # Check to see if exists for reading\n # (i.e. must not exist)\n if (os.path.exists(self.fname)):\n print(f\"File {self.fname} already exists.\")\n return False\n\n return True","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.probe_gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.probe_gallery_dir))","def Exists(self, path: str) -> bool:\n ...","def _create_file_if_needed(self):\n if not os.path.exists(self._file.filename()):\n old_umask = os.umask(0o177)\n try:\n open(self._file.filename(), 'a+b').close()\n finally:\n os.umask(old_umask)","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def exists(_env):\n return True","def exists(_env):\n return True","def images_exist(self):\n pass","def test_exists(self) -> None:\n\n expected = False\n actual = self.helper.set_name(self.test_name).exists()\n\n self.assertEqual(expected, actual)\n\n os.environ[self.test_name] = \"This is a test.\"\n\n expected = True\n actual = self.helper.exists()\n\n self.assertEqual(expected, actual)\n\n del os.environ[self.test_name]","def check_exist(filename, status):\n\n if (status == \"r\"):\n # check to see if it exists for reading\n # (i.e. must be present)\n if (not (os.path.exists(filename))):\n print(f\"Couldn't open input file: {filename}.\")\n return False\n else:\n # check to see if it exists for writing\n # (i.e. must not exist or clobber=yes)\n if (os.path.exists(filename)):\n if (status == \"w\"):\n return True\n else:\n return False\n\n return True","def check_file_creation(today_filename):\r\n\r\n if os.path.exists(today_filename):\r\n print(\"Today's file {} has been created\".format(today_filename))\r\n else:\r\n print(\"Today's file was not created\")","def object_exists(self, fname):\n return self.object_exists","def add_existing_key_fail(self, data):\n message = 'exists'\n rv = self.add_success(data)\n assert not in_response(rv, message)\n return self.add_fail(data, message)","def exists(self, obj):\n return False"],"string":"[\n \"def isExist(data):\\n return True/False\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def exist(self):\",\n \"def run(**kwargs):\\n del kwargs # Unused args\\n if os.path.exists(DATASET_PATH):\\n LOGGER.info('... Dataset already exists. Skipping.')\\n else:\\n build()\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def test_dataset_exists(client, to_delete):\\n DATASET_ID = \\\"get_table_dataset_{}\\\".format(_millis())\\n dataset_ref = client.dataset(DATASET_ID)\\n dataset = bigquery.Dataset(dataset_ref)\\n dataset = client.create_dataset(dataset)\\n to_delete.append(dataset)\\n\\n assert dataset_exists(client, dataset_ref)\\n assert not dataset_exists(client, client.dataset(\\\"dataset doesnot exist\\\"))\",\n \"def test_exists_false(self):\\n self.assertFalse(SampleTemplate.exists(self.new_study.id))\",\n \"def object_exists(self, fname):\\n return False\",\n \"def is_dataset_created(path, suffix=\\\"\\\"):\\n dataset_id = None\\n try:\\n with open(\\\"%s%sdataset%s\\\" % (path, os.sep, suffix)) as dataset_file:\\n dataset_id = dataset_file.readline().strip()\\n try:\\n dataset_id = bigml.api.get_dataset_id(dataset_id)\\n return True, dataset_id\\n except ValueError:\\n return False, None\\n except IOError:\\n return False, None\",\n \"def _does_not_exist_or_forced(self) -> bool:\\n if os.path.exists(self.extracted_path) and self.force:\\n logger.debug(f\\\"'-f/--force' flag set, deleting directory: '{self.extracted_path}'\\\")\\n shutil.rmtree(self.extracted_path)\\n logger.debug(f\\\"Deletion successful.\\\")\\n elif os.path.exists(self.extracted_path) and not self.force:\\n logger.warning(f\\\"{self.dataset_name} already exists at the destination directory '{self.extracted_path}'\\\")\\n logger.warning(f\\\"If you wish to re-download the dataset, try 'sla-cli download -f/--force <DATASET>'\\\")\\n logger.warning(f\\\"Skipping...\\\")\\n return False\\n\\n return True\",\n \"def add(self, data, check_exists=True): # pragma: no cover\\n raise NotImplementedError\",\n \"def object_exists(self, fname):\\n return True\",\n \"def exists(self, datadir):\\n return False\",\n \"def dataset_exists(es_url, id, es_index=\\\"grq\\\"):\\n\\n total, id = check_dataset(es_url, id, es_index)\\n if total > 0:\\n return True\\n return False\",\n \"def is_file_exists(self):\\n pass\",\n \"def _handle_exists_collection(name: str, exists: Optional[str], db: Database) -> None:\\n\\n if exists == \\\"fail\\\":\\n if db[name].count() > 0:\\n raise ValueError(f\\\"Collection '{name}' already exists.\\\")\\n return\\n\\n if exists == \\\"replace\\\":\\n if db[name].count() > 0:\\n db[name].drop()\\n return\\n\\n if exists == \\\"append\\\":\\n return\\n\\n raise ValueError(f\\\"'{exists}' is not valid for if_exists\\\")\",\n \"def test_exist_entry_on_rebuild(self):\\n self.validate_attributes_in_exist_response()\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))\",\n \"def exists(self):\\n return True\",\n \"def exists(self):\\n return True\",\n \"def _auto_create(self):\\n status = [\\n os.path.exists(self.vertices_path),\\n os.path.exists(self.edges_path),\\n ]\\n\\n if not all(status):\\n self._create_vertex_skel(self.path)\\n self._create_edge_skel(self.path)\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def file_exist() -> bool:\\n pass\",\n \"def _CheckFileExistsWithData(self, logs, graph):\\n self.assertTrue(graph in logs, 'File %s was not output.' % graph)\\n self.assertTrue(logs[graph], 'File %s did not contain data.' % graph)\",\n \"def exists(self, path):\",\n \"def test_exists_true(self):\\n self.assertTrue(SampleTemplate.exists(self.test_study.id))\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def test_exists_true(self):\\n self.assertTrue(PrepSample.exists(self.sample_id, self.prep_template))\",\n \"def test_ensure_exists(self):\\n # with data\\n client = kazoo.client.KazooClient()\\n zkutils.ensure_exists(client, '/foo/bar', data='foo')\\n kazoo.client.KazooClient.create.assert_called_with(\\n '/foo/bar', b'foo', acl=mock.ANY, makepath=True,\\n sequence=False)\\n\\n # non-data\\n zkutils.ensure_exists(client, '/foo/bar')\\n kazoo.client.KazooClient.create.assert_called_with(\\n '/foo/bar', b'', acl=mock.ANY, makepath=True,\\n sequence=False)\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepTemplate.exists(2))\",\n \"def test_ensure_exists_existing(self):\\n def raise_exists(*args_unused, **kwargs_unused):\\n \\\"\\\"\\\"zk.create side effect, raising appropriate exception.\\\"\\\"\\\"\\n raise kazoo.client.NodeExistsError()\\n\\n client = kazoo.client.KazooClient()\\n kazoo.client.KazooClient.create.side_effect = raise_exists\\n zkutils.ensure_exists(client, '/foo/bar')\\n kazoo.client.KazooClient.set_acls.assert_called_with('/foo/bar',\\n mock.ANY)\\n\\n # ensure with data\\n zkutils.ensure_exists(client, '/foo/bar', data='foo')\\n kazoo.client.KazooClient.set.assert_called_with('/foo/bar', b'foo')\\n kazoo.client.KazooClient.set_acls.assert_called_with('/foo/bar',\\n mock.ANY)\",\n \"async def create_checkpoint_if_not_exists_async(self, partition_id):\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\",\n \"def ensure_data_folder_existence() -> None:\\n folder_name = params.DATA_FOLDER_NAME\\n if not folder_name in os.listdir('.'):\\n os.mkdir(folder_name)\",\n \"def exists_dataset(self, dataset):\\n assert dataset, \\\"Must input a valid dataset name.\\\"\\n return any(self.get_by_dataset(dataset))\",\n \"def test_exists_true(self):\\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def create_dataset_folder_structure():\\n\\n path = Path(f'{DATASETS}/{FEATURES_DATASET}')\\n if not os.path.exists(path):\\n print(f'\\\\nWARNING: The path does not exist. Creating new directory...\\\\n{path}\\\\n')\\n os.mkdir(path)\\n\\n try:\\n for path in new_sensor_paths:\\n if not os.path.exists(path):\\n print(f'\\\\nWARNING: The path does not exist. Creating new directory...\\\\n{path}\\\\n')\\n os.mkdir(path)\\n else:\\n print(\\\"\\\\nPath already exists!\\\")\\n except:\\n return False\\n else:\\n return True\",\n \"def check_for_new_data(self):\\n return\",\n \"def test_exists_false(self):\\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))\",\n \"def check_file_exist(self):\\n return False\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def checkfolderdata(folder = 'datas'):\\n if datafolderexist(folder):\\n return True\\n else:\\n createdatafolder(folder)\\n checkfolderdata(folder)\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.split_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_dir))\",\n \"def are_datasets_created(path, number_of_datasets, suffix='parts'):\\n dataset_ids = []\\n try:\\n with open(\\\"%s%sdataset_%s\\\" % (path, os.sep, suffix)) as datasets_file:\\n for line in datasets_file:\\n dataset = line.strip()\\n try:\\n dataset_id = bigml.api.get_dataset_id(dataset)\\n dataset_ids.append(dataset_id)\\n except ValueError:\\n return False, dataset_ids\\n if len(dataset_ids) == number_of_datasets:\\n return True, dataset_ids\\n else:\\n return False, dataset_ids\\n except IOError:\\n return False, dataset_ids\",\n \"def check_and_create_sandbox_dataset(project_id, dataset_id):\\n sandbox_dataset = get_sandbox_dataset_id(dataset_id)\\n dataset_objs = list_datasets(project_id)\\n datasets = [d.dataset_id for d in dataset_objs]\\n\\n if sandbox_dataset not in datasets:\\n create_sandbox_dataset(project_id, dataset_id)\\n return sandbox_dataset\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def entry_exists(title):\\n try:\\n f = default_storage.open(f\\\"entries/{title}.md\\\")\\n return True\\n\\n except FileNotFoundError:\\n return False\",\n \"def document_exists(self, docid):\\n raise NotImplementedError\",\n \"def test_exist(self):\\n with self.assertRaises(IncompetentQiitaDeveloperError):\\n MetadataTemplate.exists(self.study)\",\n \"def test_exists_true(self):\\n self.assertTrue(PrepTemplate.exists(1))\",\n \"def is_existing(self):\\n return self.backend.is_existing\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.list_query_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.list_query_path))\\n if not osp.exists(self.list_gallery_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.list_gallery_path))\",\n \"def test_create_already_exists():\\n current_folder = os.path.dirname(os.path.realpath(__file__))\\n misc_folder = os.path.join(current_folder, \\\"misc\\\")\\n model_file = os.path.join(misc_folder, \\\"model.tar\\\")\\n create.main(\\\"mlp\\\", \\\"10:12:8\\\", model_file)\\n # TODO: Check if error was logged\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_name_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_name_path))\\n if not osp.exists(self.test_name_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.test_name_path))\\n if not osp.exists(self.track_train_info_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.track_train_info_path))\\n if not osp.exists(self.track_test_info_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.track_test_info_path))\\n if not osp.exists(self.query_IDX_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_IDX_path))\",\n \"def dataset_exists(dataset_reference, client):\\n from google.cloud.exceptions import NotFound\\n\\n try:\\n client.get_dataset(dataset_reference)\\n return True\\n except NotFound:\\n return False\",\n \"def create_file(file_path: str, override_flag: bool) -> bool:\\n return (not os.path.exists(file_path)) or override_flag\",\n \"async def create_checkpoint_store_if_not_exists_async(self):\",\n \"def _item_exists(self, location):\\n \\\"Does nothing\\\"\",\n \"def _check_file_exists_helper(self, report_path, filename):\\n\\n if not check_data_exists(report_path, [filename]):\\n raise AssertionError(\\n \\\"{} does not exist in location {}\\\".format(\\n filename, report_path\\n )\\n )\",\n \"def before_dataobj_create(self, dataobj):\",\n \"def _check_before_run(self):\\r\\n if not os.path.exists(self.dataset_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\",\n \"def check_database_exists(dbname):\\n if not os.path.isfile(dbname):\\n create_ivr_database(dbname)\",\n \"def process(self):\\n try:\\n # self.alter_columns()\\n self.collect_drop_fk()\\n self.update_table()\\n self.create_tables()\\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\\n return True\\n except Exception as err:\\n logger.error(\\\"create_tables [error] -> %s\\\" % err)\",\n \"def test_filter_exists(self):\\n datasets = [{\\\"exists\\\": True, \\\"name\\\": \\\"DATASET1\\\"}, {\\\"exists\\\": False, \\\"name\\\": \\\"DATASET2\\\"}]\\n hits = filter_exists(\\\"HIT\\\", datasets)\\n misses = filter_exists(\\\"MISS\\\", datasets)\\n all = filter_exists(\\\"ALL\\\", datasets)\\n nothing = filter_exists(\\\"NONE\\\", datasets)\\n self.assertEqual(hits, [{\\\"exists\\\": True, \\\"name\\\": \\\"DATASET1\\\"}])\\n self.assertEqual(misses, [{\\\"exists\\\": False, \\\"name\\\": \\\"DATASET2\\\"}])\\n self.assertEqual(all, datasets)\\n self.assertEqual(nothing, [])\",\n \"def check_if_entry_exists(title: str) -> bool:\\n conn = sqlite3.connect('rss.db')\\n c = conn.cursor()\\n try:\\n c.execute(\\n \\\"\\\"\\\"select * from entries where title = ?\\\"\\\"\\\",\\n (title,)\\n )\\n records = c.fetchall()\\n return len(records) > 0\\n except sqlite3.OperationalError as e:\\n print(f'Exception {e} caught. Recreating database.')\\n c.execute('drop table if exists entries')\\n conn.commit()\\n conn.close()\\n create()\\n return False\",\n \"def ResourceExists(self, name):\\n pass\",\n \"def test_data_source_soaps_id_exists_get(self):\\n pass\",\n \"def dir_exists(dirname):\\n global datapath\\n current_dir = './' + dirname + '/'\\n parent_dir = '../' + dirname + '/'\\n grandparent_dir = '../../' + dirname + '/'\\n if os.path.isdir(current_dir):\\n datapath = current_dir\\n elif os.path.isdir(parent_dir):\\n datapath = parent_dir\\n elif os.path.isdir(grandparent_dir):\\n datapath = grandparent_dir\\n else:\\n response = raw_input(\\\"'{}' directory does not exist. \\\"\\n \\\"Create it [Y/n]? \\\".format(dirname))\\n if not response or response[0].lower() == 'y':\\n directory = os.getcwd()\\n if os.path.basename(directory) == 'caribou-data-collection':\\n # E.g. /caribou-data-collection/scraper.py\\n datapath = current_dir\\n os.makedirs(datapath)\\n print 'Created', datapath\\n elif os.path.basename(directory) in COUNTRIES:\\n # E.g. /caribou-data-collection/country/scraper.py\\n datapath = parent_dir\\n os.makedirs(datapath)\\n print 'Created', datapath\\n elif os.path.basename(os.path.dirname(directory)) in COUNTRIES:\\n # E.g. /caribou-data-collection/country/region/scraper.py\\n datapath = grandparent_dir\\n os.makedirs(datapath)\\n print 'Created', datapath\\n else:\\n raise RuntimeError('Directory not created. '\\n 'Please switch to the caribou-data-collection'\\n ' directory and try again.')\\n else:\\n return False\\n return True\",\n \"def fileexists(cpath, create=True):\\n dpath = os.path.dirname(cpath)\\n if not os.path.isfile(cpath):\\n if direxists(dpath) and create:\\n try:\\n pathlib.Path(cpath).touch()\\n except os.error:\\n logging.error(\\\"Can't create file %s!\\\", cpath)\\n return False\\n return True\",\n \"def _ensure_exists(name, path=None):\\n if not exists(name, path=path):\\n raise CommandExecutionError(f\\\"Container '{name}' does not exist\\\")\",\n \"def _check_before_run(self):\\r\\n if not osp.exists(self.dataset_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\r\\n if not osp.exists(self.train_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\",\n \"def exists(anyid=None, **multi_match): # TODO multimatch\\n if not any((anyid, multi_match)):\\n raise RegistryError(\\\"specify at least one condition.\\\")\\n\\n if anyid:\\n return ESDataset.exists(_id=anyid) or ESDataset.exists(identifier=anyid)\\n\\n return ESDataset.exists(**multi_match)\",\n \"def _index_file_exists(idx_fn):\\n if os.path.exists(idx_fn + \\\".npy\\\") and os.path.exists(idx_fn + \\\".info\\\"):\\n return True\\n else:\\n return False\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def perform_existence_check(set_name_to_cache: bool):\\n Thread(target=_perform_existence_check, args=(set_name_to_cache,)).start()\",\n \"def exists(self, arg):\\n raise NotImplementedError\",\n \"def checkExist(self,fname,status):\\n\\n if (self.status == \\\"r\\\"):\\n # Checks to see if it exists for reading\\n # Which means it must be present\\n\\n if (not (os.path.exists(self.fname))):\\n print(f\\\"Couldn't open input file: {self.fname}\\\")\\n return False\\n else:\\n # Check to see if exists for reading\\n # (i.e. must not exist)\\n if (os.path.exists(self.fname)):\\n print(f\\\"File {self.fname} already exists.\\\")\\n return False\\n\\n return True\",\n \"def checkExist(self,fname,status):\\n\\n if (self.status == \\\"r\\\"):\\n # Checks to see if it exists for reading\\n # Which means it must be present\\n\\n if (not (os.path.exists(self.fname))):\\n print(f\\\"Couldn't open input file: {self.fname}\\\")\\n return False\\n else:\\n # Check to see if exists for reading\\n # (i.e. must not exist)\\n if (os.path.exists(self.fname)):\\n print(f\\\"File {self.fname} already exists.\\\")\\n return False\\n\\n return True\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.probe_gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.probe_gallery_dir))\",\n \"def Exists(self, path: str) -> bool:\\n ...\",\n \"def _create_file_if_needed(self):\\n if not os.path.exists(self._file.filename()):\\n old_umask = os.umask(0o177)\\n try:\\n open(self._file.filename(), 'a+b').close()\\n finally:\\n os.umask(old_umask)\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def exists(_env):\\n return True\",\n \"def exists(_env):\\n return True\",\n \"def images_exist(self):\\n pass\",\n \"def test_exists(self) -> None:\\n\\n expected = False\\n actual = self.helper.set_name(self.test_name).exists()\\n\\n self.assertEqual(expected, actual)\\n\\n os.environ[self.test_name] = \\\"This is a test.\\\"\\n\\n expected = True\\n actual = self.helper.exists()\\n\\n self.assertEqual(expected, actual)\\n\\n del os.environ[self.test_name]\",\n \"def check_exist(filename, status):\\n\\n if (status == \\\"r\\\"):\\n # check to see if it exists for reading\\n # (i.e. must be present)\\n if (not (os.path.exists(filename))):\\n print(f\\\"Couldn't open input file: {filename}.\\\")\\n return False\\n else:\\n # check to see if it exists for writing\\n # (i.e. must not exist or clobber=yes)\\n if (os.path.exists(filename)):\\n if (status == \\\"w\\\"):\\n return True\\n else:\\n return False\\n\\n return True\",\n \"def check_file_creation(today_filename):\\r\\n\\r\\n if os.path.exists(today_filename):\\r\\n print(\\\"Today's file {} has been created\\\".format(today_filename))\\r\\n else:\\r\\n print(\\\"Today's file was not created\\\")\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def add_existing_key_fail(self, data):\\n message = 'exists'\\n rv = self.add_success(data)\\n assert not in_response(rv, message)\\n return self.add_fail(data, message)\",\n \"def exists(self, obj):\\n return False\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61832976","0.5865549","0.58427125","0.5761497","0.57018334","0.5658679","0.55542874","0.5486935","0.5465586","0.54652494","0.54532725","0.5452605","0.5446348","0.5409404","0.5387412","0.5352073","0.53434783","0.5338109","0.53380615","0.53380615","0.5296173","0.5286036","0.5285628","0.5283233","0.5259973","0.5251596","0.52317667","0.5229633","0.5228364","0.5209805","0.5208793","0.52048177","0.51878524","0.51805085","0.5177314","0.51598644","0.5157069","0.51526797","0.514977","0.51259226","0.51156","0.51151705","0.5113204","0.5093946","0.5090204","0.5088175","0.5074226","0.5074087","0.506958","0.50680894","0.5068073","0.5049205","0.50322497","0.50210726","0.5018592","0.50182825","0.50100917","0.5006929","0.5002313","0.49974167","0.49970585","0.49929935","0.4985612","0.49854606","0.4980093","0.49792212","0.49719304","0.4971483","0.49620792","0.49550563","0.49473494","0.49467596","0.49306765","0.49229294","0.49214855","0.49177673","0.49115822","0.49114227","0.4910846","0.49080873","0.49080873","0.49078935","0.49045894","0.4900532","0.4899734","0.4899734","0.4899734","0.4899734","0.4899734","0.4899734","0.4899734","0.4898616","0.4898616","0.48984605","0.48972872","0.4891578","0.4891394","0.48863268","0.48840052","0.4881104"],"string":"[\n \"0.61832976\",\n \"0.5865549\",\n \"0.58427125\",\n \"0.5761497\",\n \"0.57018334\",\n \"0.5658679\",\n \"0.55542874\",\n \"0.5486935\",\n \"0.5465586\",\n \"0.54652494\",\n \"0.54532725\",\n \"0.5452605\",\n \"0.5446348\",\n \"0.5409404\",\n \"0.5387412\",\n \"0.5352073\",\n \"0.53434783\",\n \"0.5338109\",\n \"0.53380615\",\n \"0.53380615\",\n \"0.5296173\",\n \"0.5286036\",\n \"0.5285628\",\n \"0.5283233\",\n \"0.5259973\",\n \"0.5251596\",\n \"0.52317667\",\n \"0.5229633\",\n \"0.5228364\",\n \"0.5209805\",\n \"0.5208793\",\n \"0.52048177\",\n \"0.51878524\",\n \"0.51805085\",\n \"0.5177314\",\n \"0.51598644\",\n \"0.5157069\",\n \"0.51526797\",\n \"0.514977\",\n \"0.51259226\",\n \"0.51156\",\n \"0.51151705\",\n \"0.5113204\",\n \"0.5093946\",\n \"0.5090204\",\n \"0.5088175\",\n \"0.5074226\",\n \"0.5074087\",\n \"0.506958\",\n \"0.50680894\",\n \"0.5068073\",\n \"0.5049205\",\n \"0.50322497\",\n \"0.50210726\",\n \"0.5018592\",\n \"0.50182825\",\n \"0.50100917\",\n \"0.5006929\",\n \"0.5002313\",\n \"0.49974167\",\n \"0.49970585\",\n \"0.49929935\",\n \"0.4985612\",\n \"0.49854606\",\n \"0.4980093\",\n \"0.49792212\",\n \"0.49719304\",\n \"0.4971483\",\n \"0.49620792\",\n \"0.49550563\",\n \"0.49473494\",\n \"0.49467596\",\n \"0.49306765\",\n \"0.49229294\",\n \"0.49214855\",\n \"0.49177673\",\n \"0.49115822\",\n \"0.49114227\",\n \"0.4910846\",\n \"0.49080873\",\n \"0.49080873\",\n \"0.49078935\",\n \"0.49045894\",\n \"0.4900532\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4899734\",\n \"0.4898616\",\n \"0.4898616\",\n \"0.48984605\",\n \"0.48972872\",\n \"0.4891578\",\n \"0.4891394\",\n \"0.48863268\",\n \"0.48840052\",\n \"0.4881104\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5203899"},"document_rank":{"kind":"string","value":"32"}}},{"rowIdx":2284,"cells":{"query":{"kind":"string","value":"Process the overwrite flag on tables create."},"document":{"kind":"string","value":"def ProcessTableOverwrite(ref, args, request):\n dataset_id = ref.datasetId\n table_id = ref.Name()\n project_id = ref.projectId\n\n if args.overwrite:\n if _TableExists(dataset_id, table_id, project_id):\n _TryDeleteTable(dataset_id, table_id, project_id)\n\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_tables_and_apply_patches(self):\n\n if self.authorized and not self.db_tables_initiated:\n with self.connection.cursor() as cursor:\n for statement in self.parse_mysql_sql_file():\n cursor.execute(statement)\n\n PyFunceble.LOGGER.info(\n \"Created the missing tables. Applied all patched\"\n )\n\n self.db_tables_initiated = True","def ProcessTableCopyOverwrite(ref, args, request):\n del ref # Unused\n if args.overwrite:\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\n return request","def process(self):\n try:\n # self.alter_columns()\n self.collect_drop_fk()\n self.update_table()\n self.create_tables()\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\n return True\n except Exception as err:\n logger.error(\"create_tables [error] -> %s\" % err)","def process_overrides(self, db, dest, kvargs, lines):\n logging.info(\"process_overrides db:{} dest:{} kvargs:{} \".format(db.name,dest,kvargs))\n keyword = kvargs['keyword']\n db.create_overrides(keyword)\n return True","def s3_table_set_before_write(cls, table):\n\n update_default = cls.s3_table_name_update_default\n\n table._before_insert.append(update_default)\n table._before_update.append(lambda s, data: update_default(data))","def __new_tables_statement(self):\n new_tables = self.__new_tables()\n for table in new_tables:\n with open('./update/create_tables.sql', 'a') as f:\n create_statement = self.source.query_create_table_statement(table.name)\n f.write(create_statement)\n f.write('\\n')","def _do_action_tables_create(self):\n\n schema_shell = os.path.join(self.bento_home, \"schema-shell\", \"bin\", \"kiji-schema-shell\")\n assert os.path.isfile(schema_shell), schema_shell\n\n # Delete the table first!\n cmd = (\n \"kiji delete --target={kiji_uri} --interactive=false; \" +\n \"kiji install --kiji={kiji_uri}\" ).format(kiji_uri=self.kiji_uri)\n self._run_kiji_job(cmd)\n\n for ddl in self.ddls:\n ddl_full_path = os.path.join(self.movie_advisor_home, ddl)\n assert os.path.isfile(ddl_full_path)\n cmd = \"{schema_shell} --kiji={kiji_uri} --file={ddl_full_path}\".format(\n schema_shell=schema_shell,\n kiji_uri=self.kiji_uri,\n ddl_full_path=ddl_full_path)\n self._run_kiji_job(cmd)","def test_database_object_overwrite_parameter_is_set(self):\n database = generate_database_object(overwrite=True)\n\n self.assertEqual(\n True,\n database.overwrite == True,\n \"Database object did not have an overwrite flag, despite being created with one.\"\n )","def touch(self):\n if self.marker_table_bound is None:\n self.create_marker_table()\n\n table = self.marker_table_bound\n id_exists = self.exists()\n with self.engine.begin() as conn:\n if not id_exists:\n ins = table.insert().values(\n ParquetSource=self.parquet_source,\n Environment=self.environment,\n BackupDate=self.backup_date,\n TargetTable=self.target_table,\n InsertedDate=datetime.now())\n else:\n ins = table.update().where(sqlalchemy.and_(\n table.c.ParquetSource == self.parquet_source,\n table.c.Environment == self.environment,\n table.c.TargetTable == self.target_table)).\\\n values(ParquetSource=self.parquet_source,\n Environment=self.environment,\n BackupDate=self.backup_date,\n TargetTable=self.target_table,\n InsertedDate=datetime.now())\n conn.execute(ins)\n assert self.exists()","def check_and_create_table(self) -> None:\n table_ids = [t.table_id for t in self.instance.list_tables()]\n\n if not self.table_id in table_ids:\n self.table.create()\n f = self.table.column_family(self.family_id)\n f.create()\n\n f_inc = self.table.column_family(self.incrementer_family_id,\n gc_rule=MaxVersionsGCRule(1))\n f_inc.create()\n\n f_log = self.table.column_family(self.log_family_id)\n f_log.create()\n\n f_ce = self.table.column_family(self.cross_edge_family_id,\n gc_rule=MaxVersionsGCRule(1))\n f_ce.create()\n\n print(\"Table created\")","def create_all_tables(self):\n pass","def create_tables(self):\n for query in table_create_sql:\n self.cursor.execute(query)\n\n self.commit()","def on_doctype_update():\n\tif not frappe.db.sql(\"\"\"show index from `tabDefaultValue`\n\t\twhere Key_name=\"defaultvalue_parent_defkey_index\" \"\"\"):\n\t\tfrappe.db.commit()\n\t\tfrappe.db.sql(\"\"\"alter table `tabDefaultValue`\n\t\t\tadd index defaultvalue_parent_defkey_index(parent, defkey)\"\"\")\n\n\tif not frappe.db.sql(\"\"\"show index from `tabDefaultValue`\n\t\twhere Key_name=\"defaultvalue_parent_parenttype_index\" \"\"\"):\n\t\tfrappe.db.commit()\n\t\tfrappe.db.sql(\"\"\"alter table `tabDefaultValue`\n\t\t\tadd index defaultvalue_parent_parenttype_index(parent, parenttype)\"\"\")","def createTables(self,table=\"all\"):\n auto=\"\"\n\tif self.dbType==\"mysql\":\n\t auto=\"AUTO_INCREMENT\"\n\t \n\ttableName=\"FileID\"\n if table==\"all\" or table==tableName:\n\t # Drop/create FileID table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"CREATE TABLE %s (\n\t fileid %s %s PRIMARY KEY, \n\t fileName TEXT,\n\t typeid %s\n\t )\n\t \"\"\"%(tableName,self.long,auto,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"KeyFile\"\n\tif table==\"all\" or table==tableName: \n\t # Drop/create KeyFile table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t graphid %s NOT NULL, \n\t view VARCHAR(255) NOT NULL, \n\t run %s NOT NULL, \n\t uid %s, \n\t keyFileId %s NOT NULL, PRIMARY KEY(graphid,view,run,uid) )\n\t \"\"\"%(tableName,self.UINT,self.UINT,self.uid,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\t\n\ttableName=\"RunUID\"\n if table==\"all\" or table==tableName:\n\t # Drop/create RunUID table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t run %s NOT NULL,\n\t uid %s )\n\t \"\"\"%(tableName,self.UINT,self.uid)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"MaxMasterID\"\n if table==tableName:\n\t # Drop/create RunUID table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t masterMaxId %s NOT NULL,\n\t comment TEXT )\n\t \"\"\"%(tableName,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"Location\"\n if table==\"all\" or table==tableName:\n\t # Drop/create Localtion table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t id %s %s PRIMARY KEY,\n\t graphid %s NOT NULL, \n\t run %s NOT NULL, \n\t uid %s, \n\t locationFileId %s NOT NULL )\n\t \"\"\"%(tableName,self.long,auto,self.UINT,self.UINT,self.uid,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t query = \"CREATE INDEX LocationGroups ON Location(graphid,run,uid)\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"Version\"\n if table==\"all\" or table==tableName:\n\t # Drop/create Version table in SQLDB.EventStoreDB\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t id %s %s PRIMARY KEY,\n\t grade VARCHAR(255) NOT NULL, \n\t timeStamp %s NOT NULL, \n\t minRunNumber %s NOT NULL, \n\t maxRunNumber %s NOT NULL, \n\t graphid %s NOT NULL,\n\t state VARCHAR(10) ) \n\t \"\"\"%(tableName,self.long,auto,self.UINT,self.UINT,self.UINT,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"SpecificVersion\"\n if table==\"all\" or table==tableName:\n\t # Drop/create SpecificVersion table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t svName VARCHAR(255) NOT NULL PRIMARY KEY, \n\t svid %s NOT NULL )\n\t \"\"\"%(tableName,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"SpecificVersionComment\"\n if table==\"all\" or table==tableName:\n\t # Drop/create SpecificVersionComment table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t id %s %s NOT NULL PRIMARY KEY,\n\t svid %s NOT NULL,\n\t CommentDate %s,\n\t Comment TEXT )\n\t \"\"\"%(tableName,self.UINT,auto,self.UINT,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"GraphPath\"\n if table==\"all\" or table==tableName:\n\t # Drop/create GraphPath table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t graphid %s NOT NULL PRIMARY KEY, \n\t svid %s NOT NULL )\n\t \"\"\"%(tableName,self.UINT,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"PathDepend\"\n if table==\"all\" or table==tableName:\n\t # Drop/create GraphPath table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"\n\t CREATE TABLE %s (\n\t parentId %s, \n\t childId %s NOT NULL )\n\t \"\"\"%(tableName,self.UINT,self.UINT)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\n\ttableName=\"FileType\"\n if table==\"all\" or table==tableName: \n\t # Drop/create FileType table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"CREATE TABLE %s (\n\t id %s %s PRIMARY KEY, \n\t type VARCHAR(8) NOT NULL,\n\t description TEXT )\n\t \"\"\"%(tableName,self.UINT,auto)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query\n\t\n\ttableName=\"OrphanFileID\"\n if table==\"all\" or table==tableName:\n\t # Drop/create FileType table in SQLDB.EventStore\n\t self.dropTable(tableName)\n\t query = \"\"\"CREATE TABLE %s (\n\t id %s PRIMARY KEY, \n\t dateTime DATETIME,\n\t user VARCHAR(8) NOT NULL )\n\t \"\"\"%(tableName,self.long)\n\t if self.dbType==\"mysql\": query+=\" type=innodb\"\n\t self.updateDBAndLog(query)\n\t if not self.schemaDict.has_key(tableName):\n\t self.schemaDict[tableName]=query","def _create_tables_classic(self, engine, metadata):\n if engine and metadata:\n with (yield from engine) as conn:\n for x in self._models.values():\n try:\n yield from conn.execute(CreateTable(x))\n except ProgrammingError as error:\n if hasattr(self.app, 'log') and self.app.log:\n if self.app.debug:\n self.app.log.info(\"[PostgressPlugin] [ `{}` already exists]\".format(x))\n else:\n if self.app.debug:\n print(\"[PostgressPlugin] [ `{}` already exists]\".format(x))\n return","def create_table(self):\n pass","def touch(self, connection=None):\n self.create_marker_table()\n\n if connection is None:\n connection = self.connect()\n connection.autocommit = True # if connection created here, we commit it here\n\n connection.cursor().execute(\n \"\"\"INSERT INTO {marker_table} (update_id, target_table)\n VALUES (%s, %s)\n ON DUPLICATE KEY UPDATE\n update_id = VALUES(update_id)\n \"\"\".format(marker_table=self.marker_table),\n (self.update_id, self.table)\n )\n # make sure update is properly marked\n assert self.exists(connection)","def create_tables(self):\n for name, attribute in self.__dict__.items():\n if hasattr(attribute, 'create_table_in_sqlite_db'):\n attribute.create_table_in_sqlite_db()","def _create(self, tables, views, schema_name, config):\n if not isinstance(tables, dict):\n return False # Raise Exception That Tables Are In A Wrong Format???!!!\n success = True\n if schema_name is not None:\n self._create_schema(schema_name)\n for table_name_instance in tables.items():\n if self._create_table(table_name_instance[1]) is False:\n success = False\n break\n if isinstance(views, dict):\n for view_name_instance in views.items():\n if self._create_view(view_name_instance[1], schema_name, config) is False:\n success = False\n break\n return success","def create(self, overwrite_existing=False):\r\n\r\n #### Begin functionality here\r\n if debug: eprint(\"INFO: Creating database \" + self.filename)\r\n if os.path.exists(self.filename):\r\n os.remove(self.filename)\r\n engine = create_engine(\"sqlite:///\"+self.filename)\r\n Base.metadata.create_all(engine)\r\n self.connect()\r\n return()","def is_overwrite_all(self):\n return self._tag == 'overwrite_all'","def create_databases(self, overwrite = False):\r\n self.validate_config()\r\n self.template_runner.create_databases(overwrite)","def create_tables( self ) :\n return self._create_tables","def _create_schema(self):\n self._conn.executescript(self._db_schema)","async def _create_tables_declarative(self, base, engine):\n if hasattr(base, 'metadata'):\n base.metadata.create_all(bind=engine, checkfirst=True)\n return","def post_migrations(self):","def create_table_execute(self):\n self.execute(query=self.default_template.format(self.table_name), data=None)","def PreCreate(self, pre):\n pass","def PreCreate(self, pre):\n pass","def PreCreate(self, pre):\n pass","def PreCreate(self, pre):\n pass","def PreCreate(self, pre):\n pass","def init_tables(self) -> None:\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\n # it to be?\n # \"How to know that schema changes?\"\n # logger.warning(\"some message\")\n with self.table_access_condition:\n conn = self._get_connection()\n conn.execute(\"PRAGMA foreign_keys = 1\")\n with conn:\n c = conn.cursor()\n c.execute(CREATE_PROJECTS_TABLE)\n c.execute(CREATE_TASKS_TABLE)\n c.execute(CREATE_REQUESTERS_TABLE)\n c.execute(CREATE_TASK_RUNS_TABLE)\n c.execute(CREATE_ASSIGNMENTS_TABLE)\n c.execute(CREATE_UNITS_TABLE)\n c.execute(CREATE_WORKERS_TABLE)\n c.execute(CREATE_AGENTS_TABLE)\n c.execute(CREATE_QUALIFICATIONS_TABLE)\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)","def create_staging_schema(cursor,table_schema):\n create_schema = \"CREATE SCHEMA IF NOT EXISTS \" + table_schema + \";\"\n cursor.execute(create_schema)","def apply_patch():\n assert BaseDatabaseSchemaEditor is not None\n\n def _create_unique_sql(self, *args, **kwargs):\n from django.db.backends.ddl_references import IndexName\n\n statement = orig_create_unique_sql(self, *args, **kwargs)\n\n if statement is not None:\n index_name = statement.parts['name']\n\n if (isinstance(index_name, IndexName) and\n index_name.create_index_name == self._create_index_name):\n # The result will be unquoted. Let's quote it.\n index_name.create_index_name = lambda *args, **kwargs: \\\n self.quote_name(self._create_index_name(*args, **kwargs))\n\n return statement\n\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql","def __createFields(self):\n fields = self.updateFields\n for field in fields:\n self.__createField(field)","def create_triggers(self):\n triggers = self.get_source_triggers()\n if not triggers:\n self.create_insert_trigger()\n self.create_update_trigger()\n self.create_delete_trigger()\n self.commit()","def PreCreate(self, pre):\r\n pass","def PreCreate(self, pre):\r\n pass","def create_base_table(self, table_name):\n print('new')\n # Create table at first.\n select_stm = self.construct_base_table()\n exec_query('DROP TABLE IF EXISTS %s;' % table_name) \n sql = \"\"\"\n CREATE TABLE %s AS\n %s\n \"\"\" % (table_name, select_stm)\n exec_query(sql)","def begin_create(self):\n self.mdb.get().begin_create()","def create_db_execute(self):\n self.execute(query=self.db_create_schema.format(self.db_name))","def create_tables(c, drop_all = False):\n\tprint \"create_tables [status]: create tables triggered.\"\n\tautoincrement = \" autoincrement\"\n\tglobal Options, Database\n\tif drop_all:\n\t\tprint \"create_tables [status]: dropping tables initiated.\"\n\t\tif Database.type == DatabaseTypes.SQLITE:\n\t\t\tdrop_sql = open(mk_drop(\"sqlite\")).read()\n\t\telif Database.type == DatabaseTypes.MYSQL:\n\t\t\tdrop_sql = open(mk_drop(\"mysql\")).read()\n\t\telif Database.type == DatabaseTypes.POSTGRES:\n\t\t\tdrop_sql = open(mk_drop(\"postgres\")).read()\n\t\tdrop_list = drop_sql.split(\";\")\n\t\tfor line in drop_list:\n\t\t\tquery = line.strip()\n\t\t\tif query:\n\t\t\t\tc.execute(line)\n\t\tprint \"create_tables [status]: dropping tables complete.\"\n\tif Database.type == DatabaseTypes.SQLITE:\n\t\tdbf = open(mk_schema(\"sqlite\", Options.use_dict))\n\t\tquery_list = dbf.read()\n\t\tc.executescript(query_list)\n\telif Database.type == DatabaseTypes.MYSQL:\n\t\tdbf = open(mk_schema(\"mysql\", Options.use_dict))\n\t\texecutescript(c, dbf)\n\telif Database.type == DatabaseTypes.POSTGRES:\n\t\tdbf = open(mk_schema(\"postgres\", Options.use_dict))\n\t\texecutescript(c, dbf)","def __createTableIfNotExists(self):\n query = \"SELECT name FROM sqlite_master WHERE type='table'\"\n results = self._cursor.execute(query)\n name_list = [name for r in results for name in r]\n\n if self.table_name not in name_list:\n # Timestamp is for the time from pythons datetime.now() func\n table = \"\"\"CREATE TABLE {}\n (media TEXT PRIMARY KEY,\n thumbnail TEXT, regular TEXT, large TEXT,\n [timestamp] timestamp)\n \"\"\".format(self.table_name)\n self._cursor.execute(table)","def create_delta_table(self):\n self.execute_sql(\n sql.create_delta_table(\n self.delta_table_name,\n self.IDCOLNAME,\n self.DMLCOLNAME,\n self._old_table.engine,\n self.old_column_list,\n self._old_table.name,\n )\n )\n self.add_drop_table_entry(self.delta_table_name)\n # We will break table into chunks when calculate checksums using\n # old primary key. We need this index to skip verify the same row\n # for multiple time if it has been changed a lot\n if self._pk_for_filter_def and not self.is_full_table_dump:\n self.execute_sql(\n sql.create_idx_on_delta_table(\n self.delta_table_name,\n [col.name for col in self._pk_for_filter_def],\n )\n )","def fix_incremental(meta, bind):\n meta.create_all(bind=bind, checkfirst=True)\n ref = inspect(bind)\n for table in meta.sorted_tables:\n orm_cols = set(col.name for col in table.c)\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\n col_to_create = orm_cols - ref_cols\n col_to_delete = ref_cols - orm_cols\n if col_to_create:\n print table.name, 'has diff to create', col_to_create\n with bind.begin() as conn:\n for col_name in col_to_create:\n col = table.c.get(col_name)\n column_sql = CreateColumn(col).compile(bind).string\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\n if col.default:\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\n if not col.nullable:\n sql += ' NOT NULL'\n print 'executing sql: ' + sql\n conn.execute(sql)\n\n # Workaround to ensure updated DBs start with \"False\" in ignore column\n if list(col_to_create)[0] == 'ignore':\n sessionmaker = get_sessionmaker(bind.url.database)\n session = sessionmaker()\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\n items = session.query(query_object).all()\n for item in items:\n item.ignore = False\n session.flush()\n\n if col_to_delete:\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\n \"\"\"\n BEGIN TRANSACTION;\n CREATE TEMPORARY TABLE t1_backup(a,b);\n INSERT INTO t1_backup SELECT a,b FROM t1;\n DROP TABLE t1;\n CREATE TABLE t1(a,b);\n INSERT INTO t1 SELECT a,b FROM t1_backup;\n DROP TABLE t1_backup;\n COMMIT;\n \"\"\"","def create_tables():\n db.create_all()","def create_tables():\n db.create_all()","def pre_route_table_create(self, resource_dict):\n pass","def before_insert(mapper, conn, target):\n if target.sequence_id is None:\n sql = text(\n '''SELECT max(t_sequence_id)+1 FROM tables WHERE t_d_id = :did''')\n\n max_id, = conn.execute(sql, did=target.d_id).fetchone()\n\n if not max_id:\n max_id = 1\n\n target.sequence_id = max_id\n\n Table.before_update(mapper, conn, target)","def create_tables(self, tables=None):\n LOG.debug(f\"Creating table subset {tables}\")\n Base.metadata.create_all(self.engine, tables, checkfirst=False)","def create(self):\n c = self.cursor()\n byte_schema = pkgutil.get_data(__package__, 'schema.sql')\n c.executescript(byte_schema.decode('utf-8'))\n self.commit()","def ProcessDatasetOverwrite(ref, args, request):\n del ref\n dataset_id = request.dataset.datasetReference.datasetId\n project_id = request.projectId\n\n if args.overwrite:\n if _DatasetExists(dataset_id, project_id):\n _TryDeleteDataset(dataset_id, project_id)\n\n return request","def create_tables(self):\n if self.mock:\n mock_dynamodb2(self._create_tables())\n else:\n self._create_tables()","def _create_db(self, overwrite=False):\n current = list(self._cur.execute(\"select * from sqlite_master where type='table' and name='metrics'\"))\n if overwrite and len(current) >= 1:\n self._cur.execute('''DROP TABLE IF EXISTS metrics''')\n self._conn.commit()\n elif len(current) >= 1:\n self._fields = [x[1] for x in sorted(self._cur.execute('''PRAGMA table_info(metrics)'''))]\n return None\n self._cur.execute('''CREATE TABLE metrics (model_name text, operation_name text, metric_name text, metric_type text, metric_value real)''')\n self._fields = [\"model_name\", \"operation_name\", \"metric_name\", \"metric_type\", \"metric_value\"]\n self._conn.commit()","def _postprocess_arena(self):\n # Create tables\n for i, (offset, rot, half_size, friction, legs) in enumerate(\n zip(self.table_offsets, self.table_rots, self.table_half_sizes, self.table_frictions, self.has_legs)\n ):\n self._add_table(\n name=f\"table{i}\",\n offset=offset,\n rot=rot,\n half_size=half_size,\n friction=friction,\n has_legs=legs,\n )","def make_new_tbl(self):\n debug = False\n default_dd = getdata.get_default_db_dets()\n con, cur = default_dd.con, default_dd.cur\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\n tblname = self.tblname_lst[0]\n if debug: print(f'DBE in make_new_tbl is: {default_dd.dbe}')\n getdata.make_sofa_tbl(\n con, cur, tblname, oth_name_types, headless=False)\n wx.MessageBox(\n _('Your new table has been added to the default SOFA database'))","def pre_init_hook(cr):\n try:\n cr.execute(\n \"\"\"\n ALTER TABLE product_product\n ADD pricelist_id INTEGER REFERENCES product_pricelist(id),\n ADD currency_id INTEGER REFERENCES res_currency(id);\n ALTER TABLE product_template\n ADD currency_id INTEGER REFERENCES res_currency(id);\n \"\"\"\n )\n except psycopg2.ProgrammingError:\n cr.rollback()\n\n try:\n cr.execute(\n \"\"\"\n UPDATE product_product\n SET pricelist_id = 1,\n currency_id = 20\n \"\"\"\n )\n except psycopg2.ProgrammingError:\n cr.rollback()\n\n return True","def use_table(self):\n connection = self._get_connection()\n cursor = connection.cursor()\n cursor.execute(\n 'select exists(select * from information_schema.tables where table_name=%s)',\n (self.table,),\n )\n if cursor.fetchone()[0]:\n self.logger.info('Using existing table')\n else:\n try:\n cursor.execute(\n f'CREATE TABLE {self.table} ( \\\n ID VARCHAR PRIMARY KEY, \\\n DOC BYTEA);'\n )\n self.logger.info('Successfully created table')\n except (Exception, psycopg2.Error) as error:\n self.logger.error('Error while creating table!')\n connection.commit()\n self._close_connection(connection)","def recreate_non_unique_indexes(self):\n # Skip replaying changes for now, if don't have to recreate index\n if not self.droppable_indexes:\n return\n\n self.set_innodb_tmpdir(self.outfile_dir)\n # Execute alter table only if we have index to create\n if self.droppable_indexes:\n self.ddl_guard()\n log.info(\n \"Recreating indexes: {}\".format(\n \", \".join(col.name for col in self.droppable_indexes)\n )\n )\n self.execute_sql(sql.add_index(self.new_table_name, self.droppable_indexes))","def creates(f):\n f.creates = True\n return f","def no_overwrite_example():","def recreate():\n drop()\n create()","def recreate_db(self, run=False):\n if run:\n db_schema = open(self.db_schema_file).read().splitlines()\n for s in db_schema:\n t = s.strip()\n if len(t):\n self.cur.execute(t)","def create_all_schemas_and_tables(self):\n for schema, tables in self.schemas.items():\n self.create_schema(schema)\n for table in tables.keys():\n self.create_table(schema, table)","def create_all_tables():\n\tcommon_db.create_all_tables()","def markPartitionCreated(partitionTableName):\n global partitionCreationHistory\n partitionCreationHistory.add(partitionTableName)","def _auto_create(self):\n status = [\n os.path.exists(self.vertices_path),\n os.path.exists(self.edges_path),\n ]\n\n if not all(status):\n self._create_vertex_skel(self.path)\n self._create_edge_skel(self.path)","def create_gt_database_template_old(self):\n pass\n with self.connection as cursor:\n fn = os.path.join(os.path.dirname(__file__), 'gtlogold.sql')\n self.cursor.execute(open(fn, \"r\").read())","def on_ok(self, _event):\n dd = mg.DATADETS_OBJ\n if self.read_only:\n self.exiting = True\n self.Destroy()\n else:\n ## NB any changes defined in recode are already done\n new_tbl, tblname_changed, data_changed = self.get_change_status()\n if new_tbl or tblname_changed or data_changed:\n try:\n if not new_tbl:\n orig_tblname = self.tblname_lst[0]\n dd.set_tbl(tbl=orig_tblname)\n else:\n dd.set_tbl(tbl=None)\n self.make_changes()\n self.exiting = True\n self.Destroy()\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\n except FldMismatchException:\n wx.MessageBox(\n _('Unable to modify table. Some data does not match the'\n ' column type. Please edit and try again.'))\n return\n except Exception as e:\n wx.MessageBox(\n _(\"Unable to modify table.\\nCaused by error: %s\")\n % b.ue(e))\n return\n elif self.changes_made: ## not in tableconf. Must've been in recoding\n self.exiting = True\n self.Destroy()\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\n return\n else:\n wx.MessageBox(_('No changes to update.'))\n return","def create_marker_table(self):\n connection = self.connect(autocommit=True)\n cursor = connection.cursor()\n try:\n cursor.execute(\n \"\"\" CREATE TABLE {marker_table} (\n id BIGINT(20) NOT NULL AUTO_INCREMENT,\n update_id VARCHAR(128) NOT NULL,\n target_table VARCHAR(128),\n inserted TIMESTAMP DEFAULT NOW(),\n PRIMARY KEY (update_id),\n KEY id (id)\n )\n \"\"\"\n .format(marker_table=self.marker_table)\n )\n except mysql.connector.Error as e:\n if e.errno == errorcode.ER_TABLE_EXISTS_ERROR:\n pass\n else:\n raise\n connection.close()","def _apply(self):\n s = [(iptables_save, iptables_restore, self.ipv4)]\n if self.use_ipv6:\n s += [(ip6tables_save, ip6tables_restore, self.ipv6)]\n\n for save, restore, tables in s:\n all_tables, _err = save()\n all_lines = all_tables.split('\\n')\n for table_name, table in six.iteritems(tables):\n start, end = self._find_table(all_lines, table_name)\n all_lines[start:end] = self._modify_rules(\n all_lines[start:end], table, table_name)\n table.dirty = False\n restore('\\n'.join(all_lines))","def write(self):\n if not self._table: raise ValueError ( \"_table is Null\" )\n if self._isnew:\n for m in self._modified_values:\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\n \n try:\n rec = CFG.CX.insert ( CFG.DB.SCHEMA + \".\" + self._table.name,\n self._modified_values )\n #this will automatically re-read the data from the db, to take all changes\n #done by triggers and default values into account.\n self._objectid = rec['objectid']\n\n #print \"Record # {0} inserted into {1}.\".format(self._objectid, self._table.name)\n self.raiseEvent ( \"record_added\", self )\n \n except pg.DatabaseError, e:\n print \"Error inserting record.\"\n raise Record.DataManipulationError ( \"Inserting a new record into '{0}'\".format(self._table.name),\n str(self._modified_values),\n e)\n elif self._ismodified:\n \n for m in self._modified_values: \n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\n \n self._modified_values['objectid'] = self._objectid\n del self.TextCache[self._objectid]\n try:\n rec = CFG.CX.update ( CFG.DB.SCHEMA + \".\" + self._table.name,\n self._modified_values )\n self.read() \n self.raiseEvent ( \"record_saved\", self )\n except pg.DatabaseError, e:\n print \"Error updating record\"\n raise Record.DataManipulationError ( \"Updating record {1} of '{0}'\".format(self._table.name, self._objectid),\n str(self._modified_values),\n e)","def save_alter_sql(self, table_name):\n\t\talter_sql = ''\n\t\tscripted_alters = []\n\t\tcolNames,sql = self._generate_sql_parts(table_name)\n\t\tfor elem in self.joins:\n\t\t\tcolName = '{}.{}'.format(elem.Parent,elem.Column)\n\t\t\tprint(colName)\n\t\t\tif colName in colNames and colName not in scripted_alters:\n\t\t\t\tif colName == 'CommunityMart.dbo.PersonFact.SourceSystemClientID' and 'CommunityMart.dbo.PersonFact.SourceSystemClientID' not in scripted_alters:\n\t\t\t\t\tscripted_alters.append(colName)\n\t\t\t\t\talter = \"\\nUSE CommunityMart\\nGO\\n\\nIF NOT EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\nBEGIN\\n\\tALTER TABLE {} ADD {} {} NULL;\\n\\tPRINT '{}';\\nEND\\n\".format('PatientID',table_name.split('.')[2],table_name,'PatientID','int','PatientID')\n\t\t\t\t\talter = \"\\nUSE CommunityMart\\nGO\\n\\nIF EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\nBEGIN\\n\\tALTER TABLE {} ALTER COLUMN {} {} NULL;\\n\\tPRINT '{}';\\nEND\\n\".format('PatientID',table_name.split('.')[2],table_name,'PatientID','int','PatientID')\n\t\t\t\t\talter_sql += alter\n\t\t\t\tscripted_alters.append(colName)\n\t\t\t\talter = \"\\nUSE CommunityMart\\nGO\\n\\nIF NOT EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\nBEGIN\\n\\tALTER TABLE {} ADD {} {} NULL;\\n\\tPRINT '{}';\\nEND\\n\".format(elem.Column,table_name.split('.')[2],table_name,elem.Column,elem.Datatype,colName)\n\t\t\t\talter = \"\\nUSE CommunityMart\\nGO\\n\\nIF EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\nBEGIN\\n\\tALTER TABLE {} ALTER COLUMN {} {} NULL;\\n\\tPRINT '{}';\\nEND\\n\".format(elem.Column,table_name.split('.')[2],table_name,elem.Column,elem.Datatype,colName)\n\n\t\t\t\talter_sql += alter\n\t\t\t\tprint(alter)\n\t\twith open('Table/ALTER-{}.sql'.format(table_name),'w') as fout:\n\t\t\tself.altered_tables.append(table_name)\n\t\t\tfout.write(alter_sql)\n\t\treturn alter_sql","async def exec_post_create(self) -> int:\n stmt_count = 0\n for table in self._new_table_queue:\n sql = get_post_create(table)\n for stmt in sql:\n await self.conn.execute(stmt)\n stmt_count += len(sql)\n return stmt_count","def create_tables():\n db.create_all()","def create_table_statements() -> [str]:\n pass","def has_desired_schema(self):\n if self._new_table == self._old_table:\n if not self.rebuild:\n log.info(\"Table already has the desired schema. \")\n return True\n else:\n log.info(\n \"Table already has the desired schema. However \"\n \"--rebuild is specified, doing a rebuild instead\"\n )\n return False\n return False","def _remake_table(self, table_name, renames={}, deleted=[], altered={}):\r\n # Dry runs get skipped completely\r\n if self.dry_run:\r\n return\r\n # Temporary table's name\r\n temp_name = \"_south_new_\" + table_name\r\n # Work out the (possibly new) definitions of each column\r\n definitions = {}\r\n cursor = self._get_connection().cursor()\r\n for column_info in self._get_connection().introspection.get_table_description(cursor, table_name):\r\n name = column_info[0]\r\n type = column_info[1]\r\n # Deal with an alter (these happen before renames)\r\n if name in altered:\r\n type = altered[name]\r\n # Deal with a rename\r\n if name in renames:\r\n name = renames[name]\r\n # Add to the defs\r\n definitions[name] = type\r\n # Alright, Make the table\r\n self.execute(\"CREATE TABLE %s (%s)\" % (\r\n self.quote_name(temp_name),\r\n \", \".join([\"%s %s\" % (self.quote_name(cname), ctype) for cname, ctype in definitions.items()]),\r\n ))\r\n # Copy over the data\r\n self._copy_data(table_name, temp_name, renames)\r\n # Delete the old table, move our new one over it\r\n self.delete_table(table_name)\r\n self.rename_table(temp_name, table_name)","def abstract_write(self, *params): \n section = self.table_section_from_parameter(*params)\n row_args = self.table_row_args_from_parameter(*params)\n new_row = self.table_row_class(*row_args)\n # IMPORTANTE! ASUMO QUE UN BLOQUE INVALIDO ES IGUAL A UNO VACIO!\n # TO DO: PREGUNTAR EN ISSUE\n found_index = False\n for index, table_row in enumerate(section.copy()): \n if table_row is None or not table_row.valid:\n found_index = True\n overwrite_index = index\n break\n\n if not found_index:\n overwrite_index = self.next_replace(section)\n\n replace_index = self.index_mapping_from_parameter(overwrite_index, *params)\n\n\n old_line = self.table[replace_index]\n #print(f\"{self.__class__.__name__} Replace -> Index: {replace_index}\")\n\n # Perfom the actual write\n self.table[replace_index] = new_row","def setupAfterCreate( self, p, create_userfolder ):\n self.setupStorage( p, create_userfolder )","def create_new_index(self, dict_pg_info):\n # ! Setting if fun can use default setting\n ruler = Rules()\n str_conn = ruler.pg_info_rules(dict_pg_info)\n conn = psycopg2.connect(str_conn)\n\n with conn:\n with conn.cursor() as cur:\n str_create_table = \"CREATE TABLE \" + dict_pg_info['table'] + \" (path varchar PRIMARY KEY);\"\n # ! Check if table already exit\n cur.execute(str_create_table)\n cur.close()\n\n conn.close()","def _create_table_if_not_exists(self) -> None:\n COLUMN_DEFINITIONS = 'definitions'\n COLUMN_TYPE = 'type'\n\n KEY_REF = '$ref'\n\n TYPE_LOOKUP = {\n 'string': 'VARCHAR(255)',\n 'integer': 'INTEGER',\n 'boolean': 'BOOLEAN',\n 'number': 'INTEGER',\n }\n\n def ref_lookup(\n property: Dict[str, Any], fields: Dict[str, Any]\n ) -> Dict[str, Any]:\n ref = property[KEY_REF]\n property_lookup_name = ref[ref.rfind('/') + 1 :]\n return fields[COLUMN_DEFINITIONS][property_lookup_name]\n\n field_queries = []\n fields = json.loads(self.schema.schema_json())\n\n del fields[Keywords.Properties.value][\n Keywords.ID.value\n ] # Remove primary key field. It is handled with auto increment below.\n\n for property_name, property in fields[Keywords.Properties.value].items():\n if KEY_REF in property:\n property = ref_lookup(property, fields)\n field_queries.append(\n f'{property_name} {TYPE_LOOKUP[property[COLUMN_TYPE]]}'\n )\n table_columns = ', '.join(field_queries)\n\n with connect(**BaseModel.db_settings) as connection:\n cursor = connection.cursor()\n cursor.execute(\n f'CREATE TABLE IF NOT EXISTS {self.table_name} (ID INTEGER PRIMARY KEY AUTO_INCREMENT, {table_columns})'\n )\n self._table_created[self.table_name] = True","def create_tables(args):\n\n from bob.db.base.utils import create_engine_try_nolock\n\n engine = create_engine_try_nolock(args.type, args.files[0], echo=(args.verbose >= 2));\n Client.metadata.create_all(engine)\n File.metadata.create_all(engine) \n Annotation.metadata.create_all(engine)\n #Protocol_File_Association.metadata.create_all(engine)","def create(self, table, columns, types, primary_key_index=[], is_ifnotexists=True):\n\n self.lock.acquire()\n try:\n dblist = self.client.get_list_database()\n for dbdict in dblist:\n if self.dbname in dbdict[\"name\"]:\n self.lock.release()\n return True\n\n self.client.create_database(self.dbname)\n except Exception as e:\n raise Exception(\"Error in create statement; InfluxDb, DB=%s\\n\" % self.dbname)\n\n self.lock.release()\n\n return True","def fill_target_table(new_data, curs, conn, overwrite=False):\n for i in new_data:\n connect_database.add_target_to_database(list(i), curs, conn, overwrite_exsiting = overwrite)\n conn.commit()","def do_createuser(self, *args):\n self.connection_obj.initialize_table()\n print(\"UserTable Created Successful\")","def PreCreate(self, pre):\r\n \r\n pass","def process_IN_CREATE(self, event):","def createTables(self):\n metadata = Base.metadata\n metadata.create_all(self._engine)\n return","def setup_table(self):\n self.interface.start_transaction()\n self.interface.drop_table(_history_table)\n self.interface.drop_table(_history_stats_table)\n self.interface.create_table(_history_table)\n self.interface.create_index('index1', _history_table, [_history_table['timestamp']])\n self.interface.create_table(_history_stats_table)\n self.interface.create_index('index2', _history_stats_table, [_history_stats_table['benchmark']])\n self.interface.commit_transaction()","def _create_pre_commit(destination, template, context):\n # Is there already a hook?\n if isfile(destination) and not _pre_commit_has_hallmark(destination):\n raise PreCommitExists('{0} already exists'.format(destination))\n\n with open(destination, 'w') as fh:\n fh.write(template.format(**context))\n\n sinfo = stat(destination)\n mode = sinfo.st_mode | S_IXUSR | S_IXGRP | S_IXOTH\n\n # Make sure it's executable\n chmod(destination, mode)\n\n return destination","def _create_table(self) :\n\n cur = self.con.cursor()\n delete_sql = 'DROP TABLE IF EXISTS \"%s\"' % self.name\n cur.execute(delete_sql)\n\n col_sql = ','.join(['\"%s\" %s' % (self.cols[i], self.types[i])\n for i in range(len(self.cols))])\n create_sql = 'CREATE TABLE \"%s\" ( %s );' % (self.name, col_sql)\n cur.execute(create_sql)","def post_route_table_create(self, resource_dict):\n pass","def create_table(self, table_name: str) -> None:\n self._table_name = table_name\n meta_info = self._trip.get_meta_informations()\n\n # Check if event table already exists\n for event in meta_info.get_events_list():\n if event.get_name() == table_name:\n self._meta_event = event\n log.debug(f\"{table_name} table already exists in trip\")\n break\n else:\n log.debug(f\"Creating meta event {table_name}\")\n self._meta_event = MetaEvent()\n self._meta_event.set_name(table_name)\n # TODO Can't set isBase here because we're adding variables just below\n # meta_event.set_is_base(True)\n self._meta_event.set_comments(\"Imported from pynd's rec2trip\")\n # TODO How to set other metaevent values? (e.g. comment, etc.)\n self._trip.add_event(self._meta_event)","def create_tables(): \n \n pk_contraint = \"CONSTRAINT {}_pk PRIMARY KEY ({})\"\n uq_contraint = \"CONSTRAINT {}_uq UNIQUE ({})\"\n fk_query = \"\"\"CONSTRAINT {}_fk_{} \n FOREIGN KEY ({}) \n REFERENCES {}({}) \n ON UPDATE CASCADE \n ON DELETE RESTRICT\n \"\"\"\n \n create_dict = {}\n index = 1\n\n\n ############################## public SCHEMA ##############################\n \n schema = 'public'\n create_schema(schema)\n\n #################### site ####################\n table_name = 'site'\n pk_id = 'site_id'\n uq_list = ['site_code']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_code CHAR(3),\n purok VARCHAR,\n sitio VARCHAR,\n barangay VARCHAR,\n municipality VARCHAR,\n province VARCHAR,\n region VARCHAR,\n psgc INTEGER,\n active BOOLEAN NOT NULL DEFAULT TRUE,\n season SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################## spatial SCHEMA ##############################\n \n schema = 'spatial'\n create_schema(schema)\n \n #################### exposure ####################\n table_name = 'exposure'\n pk_id = 'exp_id'\n uq_list = ['exp_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n exp_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### site_exposure ####################\n table_name = 'site_exposure'\n pk_id = 'se_id'\n uq_list = ['site_id', 'exp_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n exp_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### feature ####################\n table_name = 'feature'\n pk_id = 'feat_id'\n uq_list = ['feat_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n feat_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_feature ####################\n table_name = 'site_feature'\n pk_id = 'sf_id'\n uq_list = ['site_id', 'feat_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n feat_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### hazard_zone ####################\n table_name = 'hazard_zone'\n pk_id = 'hz_id'\n uq_list = ['site_id, geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### monitoring ####################\n table_name = 'monitoring'\n pk_id = 'mon_id'\n uq_list = ['mon_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n mon_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_monitoring ####################\n table_name = 'site_monitoring'\n pk_id = 'sm_id'\n uq_list = ['site_id', 'mon_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n mon_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################### comm SCHEMA ###############################\n \n schema = 'comm'\n create_schema(schema)\n\n #################### gsm_server ####################\n table_name = 'gsm_server'\n pk_id = 'server_id'\n uq_list = ['server_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_name VARCHAR,\n platform_type VARCHAR,\n version SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### server_port ####################\n table_name = 'server_port'\n pk_id = 'port_id'\n uq_list = ['server_id', 'port']\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_id INTEGER,\n port BOOLEAN,\n ser_port VARCHAR,\n pwr_on_pin SMALLINT,\n ring_pin SMALLINT,\n module_type SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- left\n 1- right'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### network_type ####################\n table_name = 'network_type'\n pk_id = 'prefix'\n uq_list = ['prefix']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} VARCHAR(3), \n carrier SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '1- globe\n 2- smart\n 3- landline'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### gsm_module ####################\n table_name = 'gsm_module'\n pk_id = 'gsm_id'\n uq_list = ['prefix', 'num', 'activated']\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n prefix VARCHAR(3),\n num CHAR(7),\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n port_id INTEGER,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################# temporal SCHEMA #############################\n \n schema = 'temporal'\n create_schema(schema)\n\n #################### marker_observation ####################\n table_name = 'marker_observation'\n pk_id = 'mo_id'\n uq_list = ['site_id', 'ts']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n ts TIMESTAMP,\n meas_type VARCHAR(7),\n weather VARCHAR,\n observer_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_history ####################\n table_name = 'marker_history'\n pk_id = 'hist_id'\n uq_list = ['sm_id', 'ts', 'event']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n sm_id BIGINT,\n ts TIMESTAMP,\n event BOOLEAN,\n label_name VARCHAR,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- rename\n 1- reposition'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_data ####################\n table_name = 'marker_data'\n pk_id = 'data_id'\n uq_list = ['sm_id', 'mo_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n mo_id BIGINT,\n sm_id BIGINT,\n measurement NUMERIC(5,1),\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_alert ####################\n table_name = 'marker_alert'\n pk_id = 'alert_id'\n uq_list = ['data_id']\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n data_id BIGINT,\n displacement NUMERIC(4,1),\n time_delta FLOAT,\n alert_level SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger_model ####################\n table_name = 'logger_model'\n pk_id = 'model_id'\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n has_tilt BOOLEAN,\n has_rain BOOLEAN,\n has_piezo BOOLEAN,\n has_soms BOOLEAN,\n logger_type SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger ####################\n table_name = 'logger'\n pk_id = 'logger_id'\n uq_list = ['sm_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n sm_id BIGINT,\n model_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### logger_mobile ####################\n table_name = 'logger_mobile'\n pk_id = 'mobile_id'\n uq_list = ['logger_id', 'activated']\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n logger_id INTEGER,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n sim_num VARCHAR(12),\n gsm_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n #################### EXECUTE QUERY TO CREATE TABLES ####################\n for index in create_dict.keys():\n dct = create_dict[index]\n schema = dct['schema']\n table_name = dct['table_name']\n query = dct['query']\n pk_id = dct['pk_id']\n uq_list = dct['uq_list']\n fk_dict = dct['fk_dict']\n if len(fk_dict.keys()) == 0:\n fk_constraint = ''\n else:\n fk_constraint_list = ['']\n for fk_id in fk_dict.keys():\n ref_schema = fk_dict.get(fk_id)['ref_schema']\n ref_table = fk_dict.get(fk_id)['ref_table']\n fk_part = fk_query.format(table_name, ref_table, fk_id,\n \"{}.{}\".format(ref_schema, ref_table),\n fk_id)\n fk_constraint_list.append(fk_part)\n fk_constraint = ', '.join(fk_constraint_list)\n \n query = query.format(schema, table_name, pk_id, \n pk_contraint.format(table_name, pk_id),\n uq_contraint.format(table_name, ', '.join(uq_list)),\n \"{}\".format(fk_constraint))\n qdb.execute(query)","def check_db_schema(self):\n if not self.db.get_tables():\n self.create_db_schema()","def test_overwrites(self):\n\n extra_con = set([Constraint('fake', ['OVERWRITE'])])\n the_process_unit = ProcessUnit([self.a_pattern_ds], '/%fake%/%file%/%pattern%.txt',\n 'echo', extra_constraints=extra_con)\n\n ds_result = the_process_unit.execute(simulate=True)\n\n expected_in_cons = set([Constraint('fake', ['fake_1']),\n Constraint('file', ['file_1']),\n Constraint('pattern', ['pattern_1'])])\n expected_out_cons = set([Constraint('fake', ['OVERWRITE']),\n Constraint('file', ['file_1']),\n Constraint('pattern', ['pattern_1'])])\n\n self.assertEqual(expected_in_cons, self.a_pattern_ds.constraints)\n self.assertEqual(expected_out_cons, ds_result.constraints)","def pre_database_node_create(self, resource_dict):\n pass","def create_tables(self):\n if not self.is_enabled(Subsystem.database):\n raise RuntimeError(\"Database subsystem was not enabled\")\n\n Base.metadata.create_all(self.engine)"],"string":"[\n \"def create_tables_and_apply_patches(self):\\n\\n if self.authorized and not self.db_tables_initiated:\\n with self.connection.cursor() as cursor:\\n for statement in self.parse_mysql_sql_file():\\n cursor.execute(statement)\\n\\n PyFunceble.LOGGER.info(\\n \\\"Created the missing tables. Applied all patched\\\"\\n )\\n\\n self.db_tables_initiated = True\",\n \"def ProcessTableCopyOverwrite(ref, args, request):\\n del ref # Unused\\n if args.overwrite:\\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\\n return request\",\n \"def process(self):\\n try:\\n # self.alter_columns()\\n self.collect_drop_fk()\\n self.update_table()\\n self.create_tables()\\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\\n return True\\n except Exception as err:\\n logger.error(\\\"create_tables [error] -> %s\\\" % err)\",\n \"def process_overrides(self, db, dest, kvargs, lines):\\n logging.info(\\\"process_overrides db:{} dest:{} kvargs:{} \\\".format(db.name,dest,kvargs))\\n keyword = kvargs['keyword']\\n db.create_overrides(keyword)\\n return True\",\n \"def s3_table_set_before_write(cls, table):\\n\\n update_default = cls.s3_table_name_update_default\\n\\n table._before_insert.append(update_default)\\n table._before_update.append(lambda s, data: update_default(data))\",\n \"def __new_tables_statement(self):\\n new_tables = self.__new_tables()\\n for table in new_tables:\\n with open('./update/create_tables.sql', 'a') as f:\\n create_statement = self.source.query_create_table_statement(table.name)\\n f.write(create_statement)\\n f.write('\\\\n')\",\n \"def _do_action_tables_create(self):\\n\\n schema_shell = os.path.join(self.bento_home, \\\"schema-shell\\\", \\\"bin\\\", \\\"kiji-schema-shell\\\")\\n assert os.path.isfile(schema_shell), schema_shell\\n\\n # Delete the table first!\\n cmd = (\\n \\\"kiji delete --target={kiji_uri} --interactive=false; \\\" +\\n \\\"kiji install --kiji={kiji_uri}\\\" ).format(kiji_uri=self.kiji_uri)\\n self._run_kiji_job(cmd)\\n\\n for ddl in self.ddls:\\n ddl_full_path = os.path.join(self.movie_advisor_home, ddl)\\n assert os.path.isfile(ddl_full_path)\\n cmd = \\\"{schema_shell} --kiji={kiji_uri} --file={ddl_full_path}\\\".format(\\n schema_shell=schema_shell,\\n kiji_uri=self.kiji_uri,\\n ddl_full_path=ddl_full_path)\\n self._run_kiji_job(cmd)\",\n \"def test_database_object_overwrite_parameter_is_set(self):\\n database = generate_database_object(overwrite=True)\\n\\n self.assertEqual(\\n True,\\n database.overwrite == True,\\n \\\"Database object did not have an overwrite flag, despite being created with one.\\\"\\n )\",\n \"def touch(self):\\n if self.marker_table_bound is None:\\n self.create_marker_table()\\n\\n table = self.marker_table_bound\\n id_exists = self.exists()\\n with self.engine.begin() as conn:\\n if not id_exists:\\n ins = table.insert().values(\\n ParquetSource=self.parquet_source,\\n Environment=self.environment,\\n BackupDate=self.backup_date,\\n TargetTable=self.target_table,\\n InsertedDate=datetime.now())\\n else:\\n ins = table.update().where(sqlalchemy.and_(\\n table.c.ParquetSource == self.parquet_source,\\n table.c.Environment == self.environment,\\n table.c.TargetTable == self.target_table)).\\\\\\n values(ParquetSource=self.parquet_source,\\n Environment=self.environment,\\n BackupDate=self.backup_date,\\n TargetTable=self.target_table,\\n InsertedDate=datetime.now())\\n conn.execute(ins)\\n assert self.exists()\",\n \"def check_and_create_table(self) -> None:\\n table_ids = [t.table_id for t in self.instance.list_tables()]\\n\\n if not self.table_id in table_ids:\\n self.table.create()\\n f = self.table.column_family(self.family_id)\\n f.create()\\n\\n f_inc = self.table.column_family(self.incrementer_family_id,\\n gc_rule=MaxVersionsGCRule(1))\\n f_inc.create()\\n\\n f_log = self.table.column_family(self.log_family_id)\\n f_log.create()\\n\\n f_ce = self.table.column_family(self.cross_edge_family_id,\\n gc_rule=MaxVersionsGCRule(1))\\n f_ce.create()\\n\\n print(\\\"Table created\\\")\",\n \"def create_all_tables(self):\\n pass\",\n \"def create_tables(self):\\n for query in table_create_sql:\\n self.cursor.execute(query)\\n\\n self.commit()\",\n \"def on_doctype_update():\\n\\tif not frappe.db.sql(\\\"\\\"\\\"show index from `tabDefaultValue`\\n\\t\\twhere Key_name=\\\"defaultvalue_parent_defkey_index\\\" \\\"\\\"\\\"):\\n\\t\\tfrappe.db.commit()\\n\\t\\tfrappe.db.sql(\\\"\\\"\\\"alter table `tabDefaultValue`\\n\\t\\t\\tadd index defaultvalue_parent_defkey_index(parent, defkey)\\\"\\\"\\\")\\n\\n\\tif not frappe.db.sql(\\\"\\\"\\\"show index from `tabDefaultValue`\\n\\t\\twhere Key_name=\\\"defaultvalue_parent_parenttype_index\\\" \\\"\\\"\\\"):\\n\\t\\tfrappe.db.commit()\\n\\t\\tfrappe.db.sql(\\\"\\\"\\\"alter table `tabDefaultValue`\\n\\t\\t\\tadd index defaultvalue_parent_parenttype_index(parent, parenttype)\\\"\\\"\\\")\",\n \"def createTables(self,table=\\\"all\\\"):\\n auto=\\\"\\\"\\n\\tif self.dbType==\\\"mysql\\\":\\n\\t auto=\\\"AUTO_INCREMENT\\\"\\n\\t \\n\\ttableName=\\\"FileID\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create FileID table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"CREATE TABLE %s (\\n\\t fileid %s %s PRIMARY KEY, \\n\\t fileName TEXT,\\n\\t typeid %s\\n\\t )\\n\\t \\\"\\\"\\\"%(tableName,self.long,auto,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"KeyFile\\\"\\n\\tif table==\\\"all\\\" or table==tableName: \\n\\t # Drop/create KeyFile table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t graphid %s NOT NULL, \\n\\t view VARCHAR(255) NOT NULL, \\n\\t run %s NOT NULL, \\n\\t uid %s, \\n\\t keyFileId %s NOT NULL, PRIMARY KEY(graphid,view,run,uid) )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,self.UINT,self.uid,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\t\\n\\ttableName=\\\"RunUID\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create RunUID table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t run %s NOT NULL,\\n\\t uid %s )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,self.uid)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"MaxMasterID\\\"\\n if table==tableName:\\n\\t # Drop/create RunUID table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t masterMaxId %s NOT NULL,\\n\\t comment TEXT )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"Location\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create Localtion table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t id %s %s PRIMARY KEY,\\n\\t graphid %s NOT NULL, \\n\\t run %s NOT NULL, \\n\\t uid %s, \\n\\t locationFileId %s NOT NULL )\\n\\t \\\"\\\"\\\"%(tableName,self.long,auto,self.UINT,self.UINT,self.uid,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t query = \\\"CREATE INDEX LocationGroups ON Location(graphid,run,uid)\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"Version\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create Version table in SQLDB.EventStoreDB\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t id %s %s PRIMARY KEY,\\n\\t grade VARCHAR(255) NOT NULL, \\n\\t timeStamp %s NOT NULL, \\n\\t minRunNumber %s NOT NULL, \\n\\t maxRunNumber %s NOT NULL, \\n\\t graphid %s NOT NULL,\\n\\t state VARCHAR(10) ) \\n\\t \\\"\\\"\\\"%(tableName,self.long,auto,self.UINT,self.UINT,self.UINT,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"SpecificVersion\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create SpecificVersion table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t svName VARCHAR(255) NOT NULL PRIMARY KEY, \\n\\t svid %s NOT NULL )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"SpecificVersionComment\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create SpecificVersionComment table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t id %s %s NOT NULL PRIMARY KEY,\\n\\t svid %s NOT NULL,\\n\\t CommentDate %s,\\n\\t Comment TEXT )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,auto,self.UINT,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"GraphPath\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create GraphPath table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t graphid %s NOT NULL PRIMARY KEY, \\n\\t svid %s NOT NULL )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"PathDepend\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create GraphPath table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"\\n\\t CREATE TABLE %s (\\n\\t parentId %s, \\n\\t childId %s NOT NULL )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,self.UINT)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\n\\ttableName=\\\"FileType\\\"\\n if table==\\\"all\\\" or table==tableName: \\n\\t # Drop/create FileType table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"CREATE TABLE %s (\\n\\t id %s %s PRIMARY KEY, \\n\\t type VARCHAR(8) NOT NULL,\\n\\t description TEXT )\\n\\t \\\"\\\"\\\"%(tableName,self.UINT,auto)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\\n\\t\\n\\ttableName=\\\"OrphanFileID\\\"\\n if table==\\\"all\\\" or table==tableName:\\n\\t # Drop/create FileType table in SQLDB.EventStore\\n\\t self.dropTable(tableName)\\n\\t query = \\\"\\\"\\\"CREATE TABLE %s (\\n\\t id %s PRIMARY KEY, \\n\\t dateTime DATETIME,\\n\\t user VARCHAR(8) NOT NULL )\\n\\t \\\"\\\"\\\"%(tableName,self.long)\\n\\t if self.dbType==\\\"mysql\\\": query+=\\\" type=innodb\\\"\\n\\t self.updateDBAndLog(query)\\n\\t if not self.schemaDict.has_key(tableName):\\n\\t self.schemaDict[tableName]=query\",\n \"def _create_tables_classic(self, engine, metadata):\\n if engine and metadata:\\n with (yield from engine) as conn:\\n for x in self._models.values():\\n try:\\n yield from conn.execute(CreateTable(x))\\n except ProgrammingError as error:\\n if hasattr(self.app, 'log') and self.app.log:\\n if self.app.debug:\\n self.app.log.info(\\\"[PostgressPlugin] [ `{}` already exists]\\\".format(x))\\n else:\\n if self.app.debug:\\n print(\\\"[PostgressPlugin] [ `{}` already exists]\\\".format(x))\\n return\",\n \"def create_table(self):\\n pass\",\n \"def touch(self, connection=None):\\n self.create_marker_table()\\n\\n if connection is None:\\n connection = self.connect()\\n connection.autocommit = True # if connection created here, we commit it here\\n\\n connection.cursor().execute(\\n \\\"\\\"\\\"INSERT INTO {marker_table} (update_id, target_table)\\n VALUES (%s, %s)\\n ON DUPLICATE KEY UPDATE\\n update_id = VALUES(update_id)\\n \\\"\\\"\\\".format(marker_table=self.marker_table),\\n (self.update_id, self.table)\\n )\\n # make sure update is properly marked\\n assert self.exists(connection)\",\n \"def create_tables(self):\\n for name, attribute in self.__dict__.items():\\n if hasattr(attribute, 'create_table_in_sqlite_db'):\\n attribute.create_table_in_sqlite_db()\",\n \"def _create(self, tables, views, schema_name, config):\\n if not isinstance(tables, dict):\\n return False # Raise Exception That Tables Are In A Wrong Format???!!!\\n success = True\\n if schema_name is not None:\\n self._create_schema(schema_name)\\n for table_name_instance in tables.items():\\n if self._create_table(table_name_instance[1]) is False:\\n success = False\\n break\\n if isinstance(views, dict):\\n for view_name_instance in views.items():\\n if self._create_view(view_name_instance[1], schema_name, config) is False:\\n success = False\\n break\\n return success\",\n \"def create(self, overwrite_existing=False):\\r\\n\\r\\n #### Begin functionality here\\r\\n if debug: eprint(\\\"INFO: Creating database \\\" + self.filename)\\r\\n if os.path.exists(self.filename):\\r\\n os.remove(self.filename)\\r\\n engine = create_engine(\\\"sqlite:///\\\"+self.filename)\\r\\n Base.metadata.create_all(engine)\\r\\n self.connect()\\r\\n return()\",\n \"def is_overwrite_all(self):\\n return self._tag == 'overwrite_all'\",\n \"def create_databases(self, overwrite = False):\\r\\n self.validate_config()\\r\\n self.template_runner.create_databases(overwrite)\",\n \"def create_tables( self ) :\\n return self._create_tables\",\n \"def _create_schema(self):\\n self._conn.executescript(self._db_schema)\",\n \"async def _create_tables_declarative(self, base, engine):\\n if hasattr(base, 'metadata'):\\n base.metadata.create_all(bind=engine, checkfirst=True)\\n return\",\n \"def post_migrations(self):\",\n \"def create_table_execute(self):\\n self.execute(query=self.default_template.format(self.table_name), data=None)\",\n \"def PreCreate(self, pre):\\n pass\",\n \"def PreCreate(self, pre):\\n pass\",\n \"def PreCreate(self, pre):\\n pass\",\n \"def PreCreate(self, pre):\\n pass\",\n \"def PreCreate(self, pre):\\n pass\",\n \"def init_tables(self) -> None:\\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\\n # it to be?\\n # \\\"How to know that schema changes?\\\"\\n # logger.warning(\\\"some message\\\")\\n with self.table_access_condition:\\n conn = self._get_connection()\\n conn.execute(\\\"PRAGMA foreign_keys = 1\\\")\\n with conn:\\n c = conn.cursor()\\n c.execute(CREATE_PROJECTS_TABLE)\\n c.execute(CREATE_TASKS_TABLE)\\n c.execute(CREATE_REQUESTERS_TABLE)\\n c.execute(CREATE_TASK_RUNS_TABLE)\\n c.execute(CREATE_ASSIGNMENTS_TABLE)\\n c.execute(CREATE_UNITS_TABLE)\\n c.execute(CREATE_WORKERS_TABLE)\\n c.execute(CREATE_AGENTS_TABLE)\\n c.execute(CREATE_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)\",\n \"def create_staging_schema(cursor,table_schema):\\n create_schema = \\\"CREATE SCHEMA IF NOT EXISTS \\\" + table_schema + \\\";\\\"\\n cursor.execute(create_schema)\",\n \"def apply_patch():\\n assert BaseDatabaseSchemaEditor is not None\\n\\n def _create_unique_sql(self, *args, **kwargs):\\n from django.db.backends.ddl_references import IndexName\\n\\n statement = orig_create_unique_sql(self, *args, **kwargs)\\n\\n if statement is not None:\\n index_name = statement.parts['name']\\n\\n if (isinstance(index_name, IndexName) and\\n index_name.create_index_name == self._create_index_name):\\n # The result will be unquoted. Let's quote it.\\n index_name.create_index_name = lambda *args, **kwargs: \\\\\\n self.quote_name(self._create_index_name(*args, **kwargs))\\n\\n return statement\\n\\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql\",\n \"def __createFields(self):\\n fields = self.updateFields\\n for field in fields:\\n self.__createField(field)\",\n \"def create_triggers(self):\\n triggers = self.get_source_triggers()\\n if not triggers:\\n self.create_insert_trigger()\\n self.create_update_trigger()\\n self.create_delete_trigger()\\n self.commit()\",\n \"def PreCreate(self, pre):\\r\\n pass\",\n \"def PreCreate(self, pre):\\r\\n pass\",\n \"def create_base_table(self, table_name):\\n print('new')\\n # Create table at first.\\n select_stm = self.construct_base_table()\\n exec_query('DROP TABLE IF EXISTS %s;' % table_name) \\n sql = \\\"\\\"\\\"\\n CREATE TABLE %s AS\\n %s\\n \\\"\\\"\\\" % (table_name, select_stm)\\n exec_query(sql)\",\n \"def begin_create(self):\\n self.mdb.get().begin_create()\",\n \"def create_db_execute(self):\\n self.execute(query=self.db_create_schema.format(self.db_name))\",\n \"def create_tables(c, drop_all = False):\\n\\tprint \\\"create_tables [status]: create tables triggered.\\\"\\n\\tautoincrement = \\\" autoincrement\\\"\\n\\tglobal Options, Database\\n\\tif drop_all:\\n\\t\\tprint \\\"create_tables [status]: dropping tables initiated.\\\"\\n\\t\\tif Database.type == DatabaseTypes.SQLITE:\\n\\t\\t\\tdrop_sql = open(mk_drop(\\\"sqlite\\\")).read()\\n\\t\\telif Database.type == DatabaseTypes.MYSQL:\\n\\t\\t\\tdrop_sql = open(mk_drop(\\\"mysql\\\")).read()\\n\\t\\telif Database.type == DatabaseTypes.POSTGRES:\\n\\t\\t\\tdrop_sql = open(mk_drop(\\\"postgres\\\")).read()\\n\\t\\tdrop_list = drop_sql.split(\\\";\\\")\\n\\t\\tfor line in drop_list:\\n\\t\\t\\tquery = line.strip()\\n\\t\\t\\tif query:\\n\\t\\t\\t\\tc.execute(line)\\n\\t\\tprint \\\"create_tables [status]: dropping tables complete.\\\"\\n\\tif Database.type == DatabaseTypes.SQLITE:\\n\\t\\tdbf = open(mk_schema(\\\"sqlite\\\", Options.use_dict))\\n\\t\\tquery_list = dbf.read()\\n\\t\\tc.executescript(query_list)\\n\\telif Database.type == DatabaseTypes.MYSQL:\\n\\t\\tdbf = open(mk_schema(\\\"mysql\\\", Options.use_dict))\\n\\t\\texecutescript(c, dbf)\\n\\telif Database.type == DatabaseTypes.POSTGRES:\\n\\t\\tdbf = open(mk_schema(\\\"postgres\\\", Options.use_dict))\\n\\t\\texecutescript(c, dbf)\",\n \"def __createTableIfNotExists(self):\\n query = \\\"SELECT name FROM sqlite_master WHERE type='table'\\\"\\n results = self._cursor.execute(query)\\n name_list = [name for r in results for name in r]\\n\\n if self.table_name not in name_list:\\n # Timestamp is for the time from pythons datetime.now() func\\n table = \\\"\\\"\\\"CREATE TABLE {}\\n (media TEXT PRIMARY KEY,\\n thumbnail TEXT, regular TEXT, large TEXT,\\n [timestamp] timestamp)\\n \\\"\\\"\\\".format(self.table_name)\\n self._cursor.execute(table)\",\n \"def create_delta_table(self):\\n self.execute_sql(\\n sql.create_delta_table(\\n self.delta_table_name,\\n self.IDCOLNAME,\\n self.DMLCOLNAME,\\n self._old_table.engine,\\n self.old_column_list,\\n self._old_table.name,\\n )\\n )\\n self.add_drop_table_entry(self.delta_table_name)\\n # We will break table into chunks when calculate checksums using\\n # old primary key. We need this index to skip verify the same row\\n # for multiple time if it has been changed a lot\\n if self._pk_for_filter_def and not self.is_full_table_dump:\\n self.execute_sql(\\n sql.create_idx_on_delta_table(\\n self.delta_table_name,\\n [col.name for col in self._pk_for_filter_def],\\n )\\n )\",\n \"def fix_incremental(meta, bind):\\n meta.create_all(bind=bind, checkfirst=True)\\n ref = inspect(bind)\\n for table in meta.sorted_tables:\\n orm_cols = set(col.name for col in table.c)\\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\\n col_to_create = orm_cols - ref_cols\\n col_to_delete = ref_cols - orm_cols\\n if col_to_create:\\n print table.name, 'has diff to create', col_to_create\\n with bind.begin() as conn:\\n for col_name in col_to_create:\\n col = table.c.get(col_name)\\n column_sql = CreateColumn(col).compile(bind).string\\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\\n if col.default:\\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\\n if not col.nullable:\\n sql += ' NOT NULL'\\n print 'executing sql: ' + sql\\n conn.execute(sql)\\n\\n # Workaround to ensure updated DBs start with \\\"False\\\" in ignore column\\n if list(col_to_create)[0] == 'ignore':\\n sessionmaker = get_sessionmaker(bind.url.database)\\n session = sessionmaker()\\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\\n items = session.query(query_object).all()\\n for item in items:\\n item.ignore = False\\n session.flush()\\n\\n if col_to_delete:\\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\\n \\\"\\\"\\\"\\n BEGIN TRANSACTION;\\n CREATE TEMPORARY TABLE t1_backup(a,b);\\n INSERT INTO t1_backup SELECT a,b FROM t1;\\n DROP TABLE t1;\\n CREATE TABLE t1(a,b);\\n INSERT INTO t1 SELECT a,b FROM t1_backup;\\n DROP TABLE t1_backup;\\n COMMIT;\\n \\\"\\\"\\\"\",\n \"def create_tables():\\n db.create_all()\",\n \"def create_tables():\\n db.create_all()\",\n \"def pre_route_table_create(self, resource_dict):\\n pass\",\n \"def before_insert(mapper, conn, target):\\n if target.sequence_id is None:\\n sql = text(\\n '''SELECT max(t_sequence_id)+1 FROM tables WHERE t_d_id = :did''')\\n\\n max_id, = conn.execute(sql, did=target.d_id).fetchone()\\n\\n if not max_id:\\n max_id = 1\\n\\n target.sequence_id = max_id\\n\\n Table.before_update(mapper, conn, target)\",\n \"def create_tables(self, tables=None):\\n LOG.debug(f\\\"Creating table subset {tables}\\\")\\n Base.metadata.create_all(self.engine, tables, checkfirst=False)\",\n \"def create(self):\\n c = self.cursor()\\n byte_schema = pkgutil.get_data(__package__, 'schema.sql')\\n c.executescript(byte_schema.decode('utf-8'))\\n self.commit()\",\n \"def ProcessDatasetOverwrite(ref, args, request):\\n del ref\\n dataset_id = request.dataset.datasetReference.datasetId\\n project_id = request.projectId\\n\\n if args.overwrite:\\n if _DatasetExists(dataset_id, project_id):\\n _TryDeleteDataset(dataset_id, project_id)\\n\\n return request\",\n \"def create_tables(self):\\n if self.mock:\\n mock_dynamodb2(self._create_tables())\\n else:\\n self._create_tables()\",\n \"def _create_db(self, overwrite=False):\\n current = list(self._cur.execute(\\\"select * from sqlite_master where type='table' and name='metrics'\\\"))\\n if overwrite and len(current) >= 1:\\n self._cur.execute('''DROP TABLE IF EXISTS metrics''')\\n self._conn.commit()\\n elif len(current) >= 1:\\n self._fields = [x[1] for x in sorted(self._cur.execute('''PRAGMA table_info(metrics)'''))]\\n return None\\n self._cur.execute('''CREATE TABLE metrics (model_name text, operation_name text, metric_name text, metric_type text, metric_value real)''')\\n self._fields = [\\\"model_name\\\", \\\"operation_name\\\", \\\"metric_name\\\", \\\"metric_type\\\", \\\"metric_value\\\"]\\n self._conn.commit()\",\n \"def _postprocess_arena(self):\\n # Create tables\\n for i, (offset, rot, half_size, friction, legs) in enumerate(\\n zip(self.table_offsets, self.table_rots, self.table_half_sizes, self.table_frictions, self.has_legs)\\n ):\\n self._add_table(\\n name=f\\\"table{i}\\\",\\n offset=offset,\\n rot=rot,\\n half_size=half_size,\\n friction=friction,\\n has_legs=legs,\\n )\",\n \"def make_new_tbl(self):\\n debug = False\\n default_dd = getdata.get_default_db_dets()\\n con, cur = default_dd.con, default_dd.cur\\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\\n tblname = self.tblname_lst[0]\\n if debug: print(f'DBE in make_new_tbl is: {default_dd.dbe}')\\n getdata.make_sofa_tbl(\\n con, cur, tblname, oth_name_types, headless=False)\\n wx.MessageBox(\\n _('Your new table has been added to the default SOFA database'))\",\n \"def pre_init_hook(cr):\\n try:\\n cr.execute(\\n \\\"\\\"\\\"\\n ALTER TABLE product_product\\n ADD pricelist_id INTEGER REFERENCES product_pricelist(id),\\n ADD currency_id INTEGER REFERENCES res_currency(id);\\n ALTER TABLE product_template\\n ADD currency_id INTEGER REFERENCES res_currency(id);\\n \\\"\\\"\\\"\\n )\\n except psycopg2.ProgrammingError:\\n cr.rollback()\\n\\n try:\\n cr.execute(\\n \\\"\\\"\\\"\\n UPDATE product_product\\n SET pricelist_id = 1,\\n currency_id = 20\\n \\\"\\\"\\\"\\n )\\n except psycopg2.ProgrammingError:\\n cr.rollback()\\n\\n return True\",\n \"def use_table(self):\\n connection = self._get_connection()\\n cursor = connection.cursor()\\n cursor.execute(\\n 'select exists(select * from information_schema.tables where table_name=%s)',\\n (self.table,),\\n )\\n if cursor.fetchone()[0]:\\n self.logger.info('Using existing table')\\n else:\\n try:\\n cursor.execute(\\n f'CREATE TABLE {self.table} ( \\\\\\n ID VARCHAR PRIMARY KEY, \\\\\\n DOC BYTEA);'\\n )\\n self.logger.info('Successfully created table')\\n except (Exception, psycopg2.Error) as error:\\n self.logger.error('Error while creating table!')\\n connection.commit()\\n self._close_connection(connection)\",\n \"def recreate_non_unique_indexes(self):\\n # Skip replaying changes for now, if don't have to recreate index\\n if not self.droppable_indexes:\\n return\\n\\n self.set_innodb_tmpdir(self.outfile_dir)\\n # Execute alter table only if we have index to create\\n if self.droppable_indexes:\\n self.ddl_guard()\\n log.info(\\n \\\"Recreating indexes: {}\\\".format(\\n \\\", \\\".join(col.name for col in self.droppable_indexes)\\n )\\n )\\n self.execute_sql(sql.add_index(self.new_table_name, self.droppable_indexes))\",\n \"def creates(f):\\n f.creates = True\\n return f\",\n \"def no_overwrite_example():\",\n \"def recreate():\\n drop()\\n create()\",\n \"def recreate_db(self, run=False):\\n if run:\\n db_schema = open(self.db_schema_file).read().splitlines()\\n for s in db_schema:\\n t = s.strip()\\n if len(t):\\n self.cur.execute(t)\",\n \"def create_all_schemas_and_tables(self):\\n for schema, tables in self.schemas.items():\\n self.create_schema(schema)\\n for table in tables.keys():\\n self.create_table(schema, table)\",\n \"def create_all_tables():\\n\\tcommon_db.create_all_tables()\",\n \"def markPartitionCreated(partitionTableName):\\n global partitionCreationHistory\\n partitionCreationHistory.add(partitionTableName)\",\n \"def _auto_create(self):\\n status = [\\n os.path.exists(self.vertices_path),\\n os.path.exists(self.edges_path),\\n ]\\n\\n if not all(status):\\n self._create_vertex_skel(self.path)\\n self._create_edge_skel(self.path)\",\n \"def create_gt_database_template_old(self):\\n pass\\n with self.connection as cursor:\\n fn = os.path.join(os.path.dirname(__file__), 'gtlogold.sql')\\n self.cursor.execute(open(fn, \\\"r\\\").read())\",\n \"def on_ok(self, _event):\\n dd = mg.DATADETS_OBJ\\n if self.read_only:\\n self.exiting = True\\n self.Destroy()\\n else:\\n ## NB any changes defined in recode are already done\\n new_tbl, tblname_changed, data_changed = self.get_change_status()\\n if new_tbl or tblname_changed or data_changed:\\n try:\\n if not new_tbl:\\n orig_tblname = self.tblname_lst[0]\\n dd.set_tbl(tbl=orig_tblname)\\n else:\\n dd.set_tbl(tbl=None)\\n self.make_changes()\\n self.exiting = True\\n self.Destroy()\\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\\n except FldMismatchException:\\n wx.MessageBox(\\n _('Unable to modify table. Some data does not match the'\\n ' column type. Please edit and try again.'))\\n return\\n except Exception as e:\\n wx.MessageBox(\\n _(\\\"Unable to modify table.\\\\nCaused by error: %s\\\")\\n % b.ue(e))\\n return\\n elif self.changes_made: ## not in tableconf. Must've been in recoding\\n self.exiting = True\\n self.Destroy()\\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\\n return\\n else:\\n wx.MessageBox(_('No changes to update.'))\\n return\",\n \"def create_marker_table(self):\\n connection = self.connect(autocommit=True)\\n cursor = connection.cursor()\\n try:\\n cursor.execute(\\n \\\"\\\"\\\" CREATE TABLE {marker_table} (\\n id BIGINT(20) NOT NULL AUTO_INCREMENT,\\n update_id VARCHAR(128) NOT NULL,\\n target_table VARCHAR(128),\\n inserted TIMESTAMP DEFAULT NOW(),\\n PRIMARY KEY (update_id),\\n KEY id (id)\\n )\\n \\\"\\\"\\\"\\n .format(marker_table=self.marker_table)\\n )\\n except mysql.connector.Error as e:\\n if e.errno == errorcode.ER_TABLE_EXISTS_ERROR:\\n pass\\n else:\\n raise\\n connection.close()\",\n \"def _apply(self):\\n s = [(iptables_save, iptables_restore, self.ipv4)]\\n if self.use_ipv6:\\n s += [(ip6tables_save, ip6tables_restore, self.ipv6)]\\n\\n for save, restore, tables in s:\\n all_tables, _err = save()\\n all_lines = all_tables.split('\\\\n')\\n for table_name, table in six.iteritems(tables):\\n start, end = self._find_table(all_lines, table_name)\\n all_lines[start:end] = self._modify_rules(\\n all_lines[start:end], table, table_name)\\n table.dirty = False\\n restore('\\\\n'.join(all_lines))\",\n \"def write(self):\\n if not self._table: raise ValueError ( \\\"_table is Null\\\" )\\n if self._isnew:\\n for m in self._modified_values:\\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\\n \\n try:\\n rec = CFG.CX.insert ( CFG.DB.SCHEMA + \\\".\\\" + self._table.name,\\n self._modified_values )\\n #this will automatically re-read the data from the db, to take all changes\\n #done by triggers and default values into account.\\n self._objectid = rec['objectid']\\n\\n #print \\\"Record # {0} inserted into {1}.\\\".format(self._objectid, self._table.name)\\n self.raiseEvent ( \\\"record_added\\\", self )\\n \\n except pg.DatabaseError, e:\\n print \\\"Error inserting record.\\\"\\n raise Record.DataManipulationError ( \\\"Inserting a new record into '{0}'\\\".format(self._table.name),\\n str(self._modified_values),\\n e)\\n elif self._ismodified:\\n \\n for m in self._modified_values: \\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\\n \\n self._modified_values['objectid'] = self._objectid\\n del self.TextCache[self._objectid]\\n try:\\n rec = CFG.CX.update ( CFG.DB.SCHEMA + \\\".\\\" + self._table.name,\\n self._modified_values )\\n self.read() \\n self.raiseEvent ( \\\"record_saved\\\", self )\\n except pg.DatabaseError, e:\\n print \\\"Error updating record\\\"\\n raise Record.DataManipulationError ( \\\"Updating record {1} of '{0}'\\\".format(self._table.name, self._objectid),\\n str(self._modified_values),\\n e)\",\n \"def save_alter_sql(self, table_name):\\n\\t\\talter_sql = ''\\n\\t\\tscripted_alters = []\\n\\t\\tcolNames,sql = self._generate_sql_parts(table_name)\\n\\t\\tfor elem in self.joins:\\n\\t\\t\\tcolName = '{}.{}'.format(elem.Parent,elem.Column)\\n\\t\\t\\tprint(colName)\\n\\t\\t\\tif colName in colNames and colName not in scripted_alters:\\n\\t\\t\\t\\tif colName == 'CommunityMart.dbo.PersonFact.SourceSystemClientID' and 'CommunityMart.dbo.PersonFact.SourceSystemClientID' not in scripted_alters:\\n\\t\\t\\t\\t\\tscripted_alters.append(colName)\\n\\t\\t\\t\\t\\talter = \\\"\\\\nUSE CommunityMart\\\\nGO\\\\n\\\\nIF NOT EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\\\nBEGIN\\\\n\\\\tALTER TABLE {} ADD {} {} NULL;\\\\n\\\\tPRINT '{}';\\\\nEND\\\\n\\\".format('PatientID',table_name.split('.')[2],table_name,'PatientID','int','PatientID')\\n\\t\\t\\t\\t\\talter = \\\"\\\\nUSE CommunityMart\\\\nGO\\\\n\\\\nIF EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\\\nBEGIN\\\\n\\\\tALTER TABLE {} ALTER COLUMN {} {} NULL;\\\\n\\\\tPRINT '{}';\\\\nEND\\\\n\\\".format('PatientID',table_name.split('.')[2],table_name,'PatientID','int','PatientID')\\n\\t\\t\\t\\t\\talter_sql += alter\\n\\t\\t\\t\\tscripted_alters.append(colName)\\n\\t\\t\\t\\talter = \\\"\\\\nUSE CommunityMart\\\\nGO\\\\n\\\\nIF NOT EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\\\nBEGIN\\\\n\\\\tALTER TABLE {} ADD {} {} NULL;\\\\n\\\\tPRINT '{}';\\\\nEND\\\\n\\\".format(elem.Column,table_name.split('.')[2],table_name,elem.Column,elem.Datatype,colName)\\n\\t\\t\\t\\talter = \\\"\\\\nUSE CommunityMart\\\\nGO\\\\n\\\\nIF EXISTS(SELECT * FROM sys.columns AS col WHERE col.name = '{}' AND OBJECT_NAME(col.object_id) = '{}') \\\\nBEGIN\\\\n\\\\tALTER TABLE {} ALTER COLUMN {} {} NULL;\\\\n\\\\tPRINT '{}';\\\\nEND\\\\n\\\".format(elem.Column,table_name.split('.')[2],table_name,elem.Column,elem.Datatype,colName)\\n\\n\\t\\t\\t\\talter_sql += alter\\n\\t\\t\\t\\tprint(alter)\\n\\t\\twith open('Table/ALTER-{}.sql'.format(table_name),'w') as fout:\\n\\t\\t\\tself.altered_tables.append(table_name)\\n\\t\\t\\tfout.write(alter_sql)\\n\\t\\treturn alter_sql\",\n \"async def exec_post_create(self) -> int:\\n stmt_count = 0\\n for table in self._new_table_queue:\\n sql = get_post_create(table)\\n for stmt in sql:\\n await self.conn.execute(stmt)\\n stmt_count += len(sql)\\n return stmt_count\",\n \"def create_tables():\\n db.create_all()\",\n \"def create_table_statements() -> [str]:\\n pass\",\n \"def has_desired_schema(self):\\n if self._new_table == self._old_table:\\n if not self.rebuild:\\n log.info(\\\"Table already has the desired schema. \\\")\\n return True\\n else:\\n log.info(\\n \\\"Table already has the desired schema. However \\\"\\n \\\"--rebuild is specified, doing a rebuild instead\\\"\\n )\\n return False\\n return False\",\n \"def _remake_table(self, table_name, renames={}, deleted=[], altered={}):\\r\\n # Dry runs get skipped completely\\r\\n if self.dry_run:\\r\\n return\\r\\n # Temporary table's name\\r\\n temp_name = \\\"_south_new_\\\" + table_name\\r\\n # Work out the (possibly new) definitions of each column\\r\\n definitions = {}\\r\\n cursor = self._get_connection().cursor()\\r\\n for column_info in self._get_connection().introspection.get_table_description(cursor, table_name):\\r\\n name = column_info[0]\\r\\n type = column_info[1]\\r\\n # Deal with an alter (these happen before renames)\\r\\n if name in altered:\\r\\n type = altered[name]\\r\\n # Deal with a rename\\r\\n if name in renames:\\r\\n name = renames[name]\\r\\n # Add to the defs\\r\\n definitions[name] = type\\r\\n # Alright, Make the table\\r\\n self.execute(\\\"CREATE TABLE %s (%s)\\\" % (\\r\\n self.quote_name(temp_name),\\r\\n \\\", \\\".join([\\\"%s %s\\\" % (self.quote_name(cname), ctype) for cname, ctype in definitions.items()]),\\r\\n ))\\r\\n # Copy over the data\\r\\n self._copy_data(table_name, temp_name, renames)\\r\\n # Delete the old table, move our new one over it\\r\\n self.delete_table(table_name)\\r\\n self.rename_table(temp_name, table_name)\",\n \"def abstract_write(self, *params): \\n section = self.table_section_from_parameter(*params)\\n row_args = self.table_row_args_from_parameter(*params)\\n new_row = self.table_row_class(*row_args)\\n # IMPORTANTE! ASUMO QUE UN BLOQUE INVALIDO ES IGUAL A UNO VACIO!\\n # TO DO: PREGUNTAR EN ISSUE\\n found_index = False\\n for index, table_row in enumerate(section.copy()): \\n if table_row is None or not table_row.valid:\\n found_index = True\\n overwrite_index = index\\n break\\n\\n if not found_index:\\n overwrite_index = self.next_replace(section)\\n\\n replace_index = self.index_mapping_from_parameter(overwrite_index, *params)\\n\\n\\n old_line = self.table[replace_index]\\n #print(f\\\"{self.__class__.__name__} Replace -> Index: {replace_index}\\\")\\n\\n # Perfom the actual write\\n self.table[replace_index] = new_row\",\n \"def setupAfterCreate( self, p, create_userfolder ):\\n self.setupStorage( p, create_userfolder )\",\n \"def create_new_index(self, dict_pg_info):\\n # ! Setting if fun can use default setting\\n ruler = Rules()\\n str_conn = ruler.pg_info_rules(dict_pg_info)\\n conn = psycopg2.connect(str_conn)\\n\\n with conn:\\n with conn.cursor() as cur:\\n str_create_table = \\\"CREATE TABLE \\\" + dict_pg_info['table'] + \\\" (path varchar PRIMARY KEY);\\\"\\n # ! Check if table already exit\\n cur.execute(str_create_table)\\n cur.close()\\n\\n conn.close()\",\n \"def _create_table_if_not_exists(self) -> None:\\n COLUMN_DEFINITIONS = 'definitions'\\n COLUMN_TYPE = 'type'\\n\\n KEY_REF = '$ref'\\n\\n TYPE_LOOKUP = {\\n 'string': 'VARCHAR(255)',\\n 'integer': 'INTEGER',\\n 'boolean': 'BOOLEAN',\\n 'number': 'INTEGER',\\n }\\n\\n def ref_lookup(\\n property: Dict[str, Any], fields: Dict[str, Any]\\n ) -> Dict[str, Any]:\\n ref = property[KEY_REF]\\n property_lookup_name = ref[ref.rfind('/') + 1 :]\\n return fields[COLUMN_DEFINITIONS][property_lookup_name]\\n\\n field_queries = []\\n fields = json.loads(self.schema.schema_json())\\n\\n del fields[Keywords.Properties.value][\\n Keywords.ID.value\\n ] # Remove primary key field. It is handled with auto increment below.\\n\\n for property_name, property in fields[Keywords.Properties.value].items():\\n if KEY_REF in property:\\n property = ref_lookup(property, fields)\\n field_queries.append(\\n f'{property_name} {TYPE_LOOKUP[property[COLUMN_TYPE]]}'\\n )\\n table_columns = ', '.join(field_queries)\\n\\n with connect(**BaseModel.db_settings) as connection:\\n cursor = connection.cursor()\\n cursor.execute(\\n f'CREATE TABLE IF NOT EXISTS {self.table_name} (ID INTEGER PRIMARY KEY AUTO_INCREMENT, {table_columns})'\\n )\\n self._table_created[self.table_name] = True\",\n \"def create_tables(args):\\n\\n from bob.db.base.utils import create_engine_try_nolock\\n\\n engine = create_engine_try_nolock(args.type, args.files[0], echo=(args.verbose >= 2));\\n Client.metadata.create_all(engine)\\n File.metadata.create_all(engine) \\n Annotation.metadata.create_all(engine)\\n #Protocol_File_Association.metadata.create_all(engine)\",\n \"def create(self, table, columns, types, primary_key_index=[], is_ifnotexists=True):\\n\\n self.lock.acquire()\\n try:\\n dblist = self.client.get_list_database()\\n for dbdict in dblist:\\n if self.dbname in dbdict[\\\"name\\\"]:\\n self.lock.release()\\n return True\\n\\n self.client.create_database(self.dbname)\\n except Exception as e:\\n raise Exception(\\\"Error in create statement; InfluxDb, DB=%s\\\\n\\\" % self.dbname)\\n\\n self.lock.release()\\n\\n return True\",\n \"def fill_target_table(new_data, curs, conn, overwrite=False):\\n for i in new_data:\\n connect_database.add_target_to_database(list(i), curs, conn, overwrite_exsiting = overwrite)\\n conn.commit()\",\n \"def do_createuser(self, *args):\\n self.connection_obj.initialize_table()\\n print(\\\"UserTable Created Successful\\\")\",\n \"def PreCreate(self, pre):\\r\\n \\r\\n pass\",\n \"def process_IN_CREATE(self, event):\",\n \"def createTables(self):\\n metadata = Base.metadata\\n metadata.create_all(self._engine)\\n return\",\n \"def setup_table(self):\\n self.interface.start_transaction()\\n self.interface.drop_table(_history_table)\\n self.interface.drop_table(_history_stats_table)\\n self.interface.create_table(_history_table)\\n self.interface.create_index('index1', _history_table, [_history_table['timestamp']])\\n self.interface.create_table(_history_stats_table)\\n self.interface.create_index('index2', _history_stats_table, [_history_stats_table['benchmark']])\\n self.interface.commit_transaction()\",\n \"def _create_pre_commit(destination, template, context):\\n # Is there already a hook?\\n if isfile(destination) and not _pre_commit_has_hallmark(destination):\\n raise PreCommitExists('{0} already exists'.format(destination))\\n\\n with open(destination, 'w') as fh:\\n fh.write(template.format(**context))\\n\\n sinfo = stat(destination)\\n mode = sinfo.st_mode | S_IXUSR | S_IXGRP | S_IXOTH\\n\\n # Make sure it's executable\\n chmod(destination, mode)\\n\\n return destination\",\n \"def _create_table(self) :\\n\\n cur = self.con.cursor()\\n delete_sql = 'DROP TABLE IF EXISTS \\\"%s\\\"' % self.name\\n cur.execute(delete_sql)\\n\\n col_sql = ','.join(['\\\"%s\\\" %s' % (self.cols[i], self.types[i])\\n for i in range(len(self.cols))])\\n create_sql = 'CREATE TABLE \\\"%s\\\" ( %s );' % (self.name, col_sql)\\n cur.execute(create_sql)\",\n \"def post_route_table_create(self, resource_dict):\\n pass\",\n \"def create_table(self, table_name: str) -> None:\\n self._table_name = table_name\\n meta_info = self._trip.get_meta_informations()\\n\\n # Check if event table already exists\\n for event in meta_info.get_events_list():\\n if event.get_name() == table_name:\\n self._meta_event = event\\n log.debug(f\\\"{table_name} table already exists in trip\\\")\\n break\\n else:\\n log.debug(f\\\"Creating meta event {table_name}\\\")\\n self._meta_event = MetaEvent()\\n self._meta_event.set_name(table_name)\\n # TODO Can't set isBase here because we're adding variables just below\\n # meta_event.set_is_base(True)\\n self._meta_event.set_comments(\\\"Imported from pynd's rec2trip\\\")\\n # TODO How to set other metaevent values? (e.g. comment, etc.)\\n self._trip.add_event(self._meta_event)\",\n \"def create_tables(): \\n \\n pk_contraint = \\\"CONSTRAINT {}_pk PRIMARY KEY ({})\\\"\\n uq_contraint = \\\"CONSTRAINT {}_uq UNIQUE ({})\\\"\\n fk_query = \\\"\\\"\\\"CONSTRAINT {}_fk_{} \\n FOREIGN KEY ({}) \\n REFERENCES {}({}) \\n ON UPDATE CASCADE \\n ON DELETE RESTRICT\\n \\\"\\\"\\\"\\n \\n create_dict = {}\\n index = 1\\n\\n\\n ############################## public SCHEMA ##############################\\n \\n schema = 'public'\\n create_schema(schema)\\n\\n #################### site ####################\\n table_name = 'site'\\n pk_id = 'site_id'\\n uq_list = ['site_code']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_code CHAR(3),\\n purok VARCHAR,\\n sitio VARCHAR,\\n barangay VARCHAR,\\n municipality VARCHAR,\\n province VARCHAR,\\n region VARCHAR,\\n psgc INTEGER,\\n active BOOLEAN NOT NULL DEFAULT TRUE,\\n season SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################## spatial SCHEMA ##############################\\n \\n schema = 'spatial'\\n create_schema(schema)\\n \\n #################### exposure ####################\\n table_name = 'exposure'\\n pk_id = 'exp_id'\\n uq_list = ['exp_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n exp_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### site_exposure ####################\\n table_name = 'site_exposure'\\n pk_id = 'se_id'\\n uq_list = ['site_id', 'exp_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n exp_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### feature ####################\\n table_name = 'feature'\\n pk_id = 'feat_id'\\n uq_list = ['feat_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n feat_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_feature ####################\\n table_name = 'site_feature'\\n pk_id = 'sf_id'\\n uq_list = ['site_id', 'feat_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n feat_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### hazard_zone ####################\\n table_name = 'hazard_zone'\\n pk_id = 'hz_id'\\n uq_list = ['site_id, geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### monitoring ####################\\n table_name = 'monitoring'\\n pk_id = 'mon_id'\\n uq_list = ['mon_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n mon_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_monitoring ####################\\n table_name = 'site_monitoring'\\n pk_id = 'sm_id'\\n uq_list = ['site_id', 'mon_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n mon_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################### comm SCHEMA ###############################\\n \\n schema = 'comm'\\n create_schema(schema)\\n\\n #################### gsm_server ####################\\n table_name = 'gsm_server'\\n pk_id = 'server_id'\\n uq_list = ['server_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_name VARCHAR,\\n platform_type VARCHAR,\\n version SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### server_port ####################\\n table_name = 'server_port'\\n pk_id = 'port_id'\\n uq_list = ['server_id', 'port']\\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_id INTEGER,\\n port BOOLEAN,\\n ser_port VARCHAR,\\n pwr_on_pin SMALLINT,\\n ring_pin SMALLINT,\\n module_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- left\\n 1- right'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### network_type ####################\\n table_name = 'network_type'\\n pk_id = 'prefix'\\n uq_list = ['prefix']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} VARCHAR(3), \\n carrier SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '1- globe\\n 2- smart\\n 3- landline'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### gsm_module ####################\\n table_name = 'gsm_module'\\n pk_id = 'gsm_id'\\n uq_list = ['prefix', 'num', 'activated']\\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n prefix VARCHAR(3),\\n num CHAR(7),\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n port_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################# temporal SCHEMA #############################\\n \\n schema = 'temporal'\\n create_schema(schema)\\n\\n #################### marker_observation ####################\\n table_name = 'marker_observation'\\n pk_id = 'mo_id'\\n uq_list = ['site_id', 'ts']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n ts TIMESTAMP,\\n meas_type VARCHAR(7),\\n weather VARCHAR,\\n observer_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_history ####################\\n table_name = 'marker_history'\\n pk_id = 'hist_id'\\n uq_list = ['sm_id', 'ts', 'event']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n sm_id BIGINT,\\n ts TIMESTAMP,\\n event BOOLEAN,\\n label_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- rename\\n 1- reposition'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_data ####################\\n table_name = 'marker_data'\\n pk_id = 'data_id'\\n uq_list = ['sm_id', 'mo_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n mo_id BIGINT,\\n sm_id BIGINT,\\n measurement NUMERIC(5,1),\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_alert ####################\\n table_name = 'marker_alert'\\n pk_id = 'alert_id'\\n uq_list = ['data_id']\\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n data_id BIGINT,\\n displacement NUMERIC(4,1),\\n time_delta FLOAT,\\n alert_level SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger_model ####################\\n table_name = 'logger_model'\\n pk_id = 'model_id'\\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n has_tilt BOOLEAN,\\n has_rain BOOLEAN,\\n has_piezo BOOLEAN,\\n has_soms BOOLEAN,\\n logger_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger ####################\\n table_name = 'logger'\\n pk_id = 'logger_id'\\n uq_list = ['sm_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n sm_id BIGINT,\\n model_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### logger_mobile ####################\\n table_name = 'logger_mobile'\\n pk_id = 'mobile_id'\\n uq_list = ['logger_id', 'activated']\\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n logger_id INTEGER,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n sim_num VARCHAR(12),\\n gsm_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n #################### EXECUTE QUERY TO CREATE TABLES ####################\\n for index in create_dict.keys():\\n dct = create_dict[index]\\n schema = dct['schema']\\n table_name = dct['table_name']\\n query = dct['query']\\n pk_id = dct['pk_id']\\n uq_list = dct['uq_list']\\n fk_dict = dct['fk_dict']\\n if len(fk_dict.keys()) == 0:\\n fk_constraint = ''\\n else:\\n fk_constraint_list = ['']\\n for fk_id in fk_dict.keys():\\n ref_schema = fk_dict.get(fk_id)['ref_schema']\\n ref_table = fk_dict.get(fk_id)['ref_table']\\n fk_part = fk_query.format(table_name, ref_table, fk_id,\\n \\\"{}.{}\\\".format(ref_schema, ref_table),\\n fk_id)\\n fk_constraint_list.append(fk_part)\\n fk_constraint = ', '.join(fk_constraint_list)\\n \\n query = query.format(schema, table_name, pk_id, \\n pk_contraint.format(table_name, pk_id),\\n uq_contraint.format(table_name, ', '.join(uq_list)),\\n \\\"{}\\\".format(fk_constraint))\\n qdb.execute(query)\",\n \"def check_db_schema(self):\\n if not self.db.get_tables():\\n self.create_db_schema()\",\n \"def test_overwrites(self):\\n\\n extra_con = set([Constraint('fake', ['OVERWRITE'])])\\n the_process_unit = ProcessUnit([self.a_pattern_ds], '/%fake%/%file%/%pattern%.txt',\\n 'echo', extra_constraints=extra_con)\\n\\n ds_result = the_process_unit.execute(simulate=True)\\n\\n expected_in_cons = set([Constraint('fake', ['fake_1']),\\n Constraint('file', ['file_1']),\\n Constraint('pattern', ['pattern_1'])])\\n expected_out_cons = set([Constraint('fake', ['OVERWRITE']),\\n Constraint('file', ['file_1']),\\n Constraint('pattern', ['pattern_1'])])\\n\\n self.assertEqual(expected_in_cons, self.a_pattern_ds.constraints)\\n self.assertEqual(expected_out_cons, ds_result.constraints)\",\n \"def pre_database_node_create(self, resource_dict):\\n pass\",\n \"def create_tables(self):\\n if not self.is_enabled(Subsystem.database):\\n raise RuntimeError(\\\"Database subsystem was not enabled\\\")\\n\\n Base.metadata.create_all(self.engine)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6433206","0.6371944","0.6202041","0.61849165","0.60638314","0.5852797","0.580371","0.5792183","0.5743237","0.5713558","0.5528236","0.5432233","0.54164076","0.5352115","0.5333362","0.5304936","0.52447927","0.5226724","0.52159977","0.52028906","0.5177918","0.51768345","0.51553905","0.51210314","0.5118915","0.5118286","0.5114869","0.50867444","0.50867444","0.50867444","0.50867444","0.50867444","0.50833327","0.5080407","0.50796217","0.5064261","0.5053959","0.50513977","0.50513977","0.5047625","0.5044848","0.5031597","0.50238246","0.5020486","0.5012776","0.5011942","0.5009241","0.5009241","0.4990686","0.49874055","0.49873638","0.49861166","0.49819392","0.49803182","0.49643046","0.495394","0.49347922","0.49271744","0.4924157","0.4916718","0.49069428","0.4903045","0.48969543","0.4896464","0.48948598","0.48929358","0.4888368","0.48866692","0.48780018","0.4877153","0.48725364","0.48714048","0.4871308","0.48706442","0.4863335","0.48595682","0.4855364","0.48437744","0.483928","0.4839191","0.48301318","0.48292667","0.4828595","0.48168877","0.48140103","0.48131076","0.48108727","0.48098972","0.4808456","0.4808193","0.48070052","0.48069108","0.48049206","0.48037234","0.479842","0.47931126","0.4792066","0.47875252","0.47845593","0.47816607"],"string":"[\n \"0.6433206\",\n \"0.6371944\",\n \"0.6202041\",\n \"0.61849165\",\n \"0.60638314\",\n \"0.5852797\",\n \"0.580371\",\n \"0.5792183\",\n \"0.5743237\",\n \"0.5713558\",\n \"0.5528236\",\n \"0.5432233\",\n \"0.54164076\",\n \"0.5352115\",\n \"0.5333362\",\n \"0.5304936\",\n \"0.52447927\",\n \"0.5226724\",\n \"0.52159977\",\n \"0.52028906\",\n \"0.5177918\",\n \"0.51768345\",\n \"0.51553905\",\n \"0.51210314\",\n \"0.5118915\",\n \"0.5118286\",\n \"0.5114869\",\n \"0.50867444\",\n \"0.50867444\",\n \"0.50867444\",\n \"0.50867444\",\n \"0.50867444\",\n \"0.50833327\",\n \"0.5080407\",\n \"0.50796217\",\n \"0.5064261\",\n \"0.5053959\",\n \"0.50513977\",\n \"0.50513977\",\n \"0.5047625\",\n \"0.5044848\",\n \"0.5031597\",\n \"0.50238246\",\n \"0.5020486\",\n \"0.5012776\",\n \"0.5011942\",\n \"0.5009241\",\n \"0.5009241\",\n \"0.4990686\",\n \"0.49874055\",\n \"0.49873638\",\n \"0.49861166\",\n \"0.49819392\",\n \"0.49803182\",\n \"0.49643046\",\n \"0.495394\",\n \"0.49347922\",\n \"0.49271744\",\n \"0.4924157\",\n \"0.4916718\",\n \"0.49069428\",\n \"0.4903045\",\n \"0.48969543\",\n \"0.4896464\",\n \"0.48948598\",\n \"0.48929358\",\n \"0.4888368\",\n \"0.48866692\",\n \"0.48780018\",\n \"0.4877153\",\n \"0.48725364\",\n \"0.48714048\",\n \"0.4871308\",\n \"0.48706442\",\n \"0.4863335\",\n \"0.48595682\",\n \"0.4855364\",\n \"0.48437744\",\n \"0.483928\",\n \"0.4839191\",\n \"0.48301318\",\n \"0.48292667\",\n \"0.4828595\",\n \"0.48168877\",\n \"0.48140103\",\n \"0.48131076\",\n \"0.48108727\",\n \"0.48098972\",\n \"0.4808456\",\n \"0.4808193\",\n \"0.48070052\",\n \"0.48069108\",\n \"0.48049206\",\n \"0.48037234\",\n \"0.479842\",\n \"0.47931126\",\n \"0.4792066\",\n \"0.47875252\",\n \"0.47845593\",\n \"0.47816607\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6969729"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2285,"cells":{"query":{"kind":"string","value":"Process the overwrite flag on tables copy."},"document":{"kind":"string","value":"def ProcessTableCopyOverwrite(ref, args, request):\n del ref # Unused\n if args.overwrite:\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ProcessTableOverwrite(ref, args, request):\n dataset_id = ref.datasetId\n table_id = ref.Name()\n project_id = ref.projectId\n\n if args.overwrite:\n if _TableExists(dataset_id, table_id, project_id):\n _TryDeleteTable(dataset_id, table_id, project_id)\n\n return request","def process_overrides(self, db, dest, kvargs, lines):\n logging.info(\"process_overrides db:{} dest:{} kvargs:{} \".format(db.name,dest,kvargs))\n keyword = kvargs['keyword']\n db.create_overrides(keyword)\n return True","def is_overwrite_all(self):\n return self._tag == 'overwrite_all'","def test_overwrites(self):\n\n extra_con = set([Constraint('fake', ['OVERWRITE'])])\n the_process_unit = ProcessUnit([self.a_pattern_ds], '/%fake%/%file%/%pattern%.txt',\n 'echo', extra_constraints=extra_con)\n\n ds_result = the_process_unit.execute(simulate=True)\n\n expected_in_cons = set([Constraint('fake', ['fake_1']),\n Constraint('file', ['file_1']),\n Constraint('pattern', ['pattern_1'])])\n expected_out_cons = set([Constraint('fake', ['OVERWRITE']),\n Constraint('file', ['file_1']),\n Constraint('pattern', ['pattern_1'])])\n\n self.assertEqual(expected_in_cons, self.a_pattern_ds.constraints)\n self.assertEqual(expected_out_cons, ds_result.constraints)","def needPartitionTableUpdate(self):\n n_table=list()\n d_table=self.destination.getPartitionTable()\n s_table=self.source.getPartitionTable()\n for i in range(len(s_table)):\n n_table.append(re.sub(self.source.getDeviceName(), \\\n self.destination.getDeviceName(), \\\n s_table[i]))\n if d_table == n_table:\n return False\n else:\n return True","def no_overwrite_example():","def _apply(self):\n s = [(iptables_save, iptables_restore, self.ipv4)]\n if self.use_ipv6:\n s += [(ip6tables_save, ip6tables_restore, self.ipv6)]\n\n for save, restore, tables in s:\n all_tables, _err = save()\n all_lines = all_tables.split('\\n')\n for table_name, table in six.iteritems(tables):\n start, end = self._find_table(all_lines, table_name)\n all_lines[start:end] = self._modify_rules(\n all_lines[start:end], table, table_name)\n table.dirty = False\n restore('\\n'.join(all_lines))","def s3_table_set_before_write(cls, table):\n\n update_default = cls.s3_table_name_update_default\n\n table._before_insert.append(update_default)\n table._before_update.append(lambda s, data: update_default(data))","def ProcessDatasetOverwrite(ref, args, request):\n del ref\n dataset_id = request.dataset.datasetReference.datasetId\n project_id = request.projectId\n\n if args.overwrite:\n if _DatasetExists(dataset_id, project_id):\n _TryDeleteDataset(dataset_id, project_id)\n\n return request","def pre_osc_check(self):\n # Make sure temporary table we will use during copy doesn't exist\n self.table_check()\n self.decide_pk_for_filter()\n\n # Check if we can have indexes in new table to efficiently look up\n # current old pk combinations\n if not self.validate_post_alter_pk():\n self.table_size = self.get_table_size(self.table_name)\n if self.skip_pk_coverage_check:\n log.warning(\n \"Indexes on new table cannot cover current PK of \"\n \"the old schema, which will make binary logs replay \"\n \"in an inefficient way.\"\n )\n elif self.table_size < self.pk_coverage_size_threshold:\n log.warning(\n \"No index on new table can cover old pk. Since this is \"\n \"a small table: {}, we fallback to a full table dump\".format(\n self.table_size\n )\n )\n # All columns will be chosen if we are dumping table without\n # chunking, this means all columns will be used as a part of\n # the WHERE condition when replaying\n self.is_full_table_dump = True\n self._pk_for_filter = [col.name for col in self._old_table.column_list]\n self._pk_for_filter_def = self._old_table.column_list.copy()\n elif self.is_full_table_dump:\n log.warning(\n \"Skipping coverage index test, since we are doing \"\n \"full table dump\"\n )\n else:\n old_pk_names = \", \".join(\n \"`{}`\".format(col.name)\n for col in self._old_table.primary_key.column_list\n )\n raise OSCError(\"NO_INDEX_COVERAGE\", {\"pk_names\": old_pk_names})\n\n log.info(\n \"PK filter for replaying changes later: {}\".format(self._pk_for_filter)\n )\n\n self.foreign_key_check()\n self.trigger_check()\n self.init_range_variables()\n self.get_table_chunk_size()\n self.make_chunk_size_odd()\n self.check_disk_size()\n self.ts_bootstrap_check()\n self.drop_columns_check()","def test_merge_overwrite_traditional(self):\n mdict = copy.deepcopy(self.dict1)\n mdict[\"A\"] = \"b\"\n ret = dictupdate.merge_overwrite(copy.deepcopy(self.dict1), {\"A\": \"b\"})\n self.assertEqual(mdict, ret)","def test_merge_overwrite_missing_source_key(self):\n mdict = copy.deepcopy(self.dict1)\n mdict[\"D\"] = \"new\"\n ret = dictupdate.merge_overwrite(copy.deepcopy(self.dict1), {\"D\": \"new\"})\n self.assertEqual(mdict, ret)","def ProcessTableCopyConfiguration(ref, args, request):\n del ref # Unused\n source_ref = args.CONCEPTS.source.Parse()\n destination_ref = args.CONCEPTS.destination.Parse()\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.datasetId',\n destination_ref.Parent().Name())\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.projectId',\n destination_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.destinationTable.tableId',\n destination_ref.Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.datasetId',\n source_ref.Parent().Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.projectId',\n source_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.tableId',\n source_ref.Name())\n return request","def sectional_overwrite_check(self):\n\n for rule in self.options['sectional_overwrite']:\n if self.lineage_test(rule):\n return True\n return False","def run(self):\n if not (self.table and self.columns):\n raise Exception(\"table and columns need to be specified\")\n\n connection = self.output().connect()\n\n # attempt to copy the data into mysql\n # if it fails because the target table doesn't exist\n # try to create it by running self.create_table\n for attempt in range(2):\n try:\n cursor = connection.cursor()\n print(\"caling init copy...\")\n self.init_copy(connection)\n self.copy(cursor)\n self.post_copy(connection)\n if self.enable_metadata_columns:\n self.post_copy_metacolumns(cursor)\n except Error as err:\n if err.errno == errorcode.ER_NO_SUCH_TABLE and attempt == 0:\n # if first attempt fails with \"relation not found\", try creating table\n # logger.info(\"Creating table %s\", self.table)\n connection.reconnect()\n self.create_table(connection)\n else:\n raise\n else:\n break\n\n # mark as complete in same transaction\n self.output().touch(connection)\n connection.commit()\n connection.close()","def onUndo(self):\n pass","def overwrite_all ( self ):\n return self.value == self.OV_ALL","def undo(self):\n LOG.debug(\"In the undo method, will attempt to restore\")\n\n # validate detected nothing to do for this, nothing was done\n # for execute, so simply return\n if self.no_op:\n return\n\n if not self.source_dev or not self.target_dev:\n return\n LOG.debug(\"The source dictionary is: %s\", self.source_dict_restore)\n LOG.debug(\"The target dictionary is: %s\", self.target_dict_restore)\n\n # In scenario where no source IP Address...\n if self.source_dict_restore:\n self.commandex.send_ifcfg(self.source_dev,\n self.source_dict_restore)\n\n # May have failed because the ifcfg didn't even exist, nothing\n # to roll back then\n if self.target_dict_restore:\n self.commandex.send_ifcfg(self.target_dev,\n self.target_dict_restore)","def abstract_write(self, *params): \n section = self.table_section_from_parameter(*params)\n row_args = self.table_row_args_from_parameter(*params)\n new_row = self.table_row_class(*row_args)\n # IMPORTANTE! ASUMO QUE UN BLOQUE INVALIDO ES IGUAL A UNO VACIO!\n # TO DO: PREGUNTAR EN ISSUE\n found_index = False\n for index, table_row in enumerate(section.copy()): \n if table_row is None or not table_row.valid:\n found_index = True\n overwrite_index = index\n break\n\n if not found_index:\n overwrite_index = self.next_replace(section)\n\n replace_index = self.index_mapping_from_parameter(overwrite_index, *params)\n\n\n old_line = self.table[replace_index]\n #print(f\"{self.__class__.__name__} Replace -> Index: {replace_index}\")\n\n # Perfom the actual write\n self.table[replace_index] = new_row","def touch(self):\n if self.marker_table_bound is None:\n self.create_marker_table()\n\n table = self.marker_table_bound\n id_exists = self.exists()\n with self.engine.begin() as conn:\n if not id_exists:\n ins = table.insert().values(\n ParquetSource=self.parquet_source,\n Environment=self.environment,\n BackupDate=self.backup_date,\n TargetTable=self.target_table,\n InsertedDate=datetime.now())\n else:\n ins = table.update().where(sqlalchemy.and_(\n table.c.ParquetSource == self.parquet_source,\n table.c.Environment == self.environment,\n table.c.TargetTable == self.target_table)).\\\n values(ParquetSource=self.parquet_source,\n Environment=self.environment,\n BackupDate=self.backup_date,\n TargetTable=self.target_table,\n InsertedDate=datetime.now())\n conn.execute(ins)\n assert self.exists()","def process_dump_files(self):\n if not self.open_workbooks():\n exit()\n\n self.message('*****************************************************************************')\n self.message('Only columns that exist in both the dump and destination file will be synced.')\n self.message('They must also match exactly including spelling and capitalization.')\n self.message('*****************************************************************************')\n\n self.wb_destination.active = self.wb_destination['Hypercare Incidents']\n self.parse_dump_file(self.wb_incident.active, self.wb_destination.active, self.fn_incident)\n\n self.wb_destination.active = self.wb_destination['Hypercare Defects']\n self.parse_dump_file(self.wb_defect.active, self.wb_destination.active, self.fn_defect)\n\n self.wb_destination.active = self.wb_destination['Hypercare Enhancements']\n self.parse_dump_file(self.wb_enhancement.active, self.wb_destination.active, self.fn_enhancement)\n\n self.wb_destination.active = self.wb_destination['ALM Defects']\n self.parse_dump_file(self.wb_alm.active, self.wb_destination.active, self.fn_alm)","def process_overrides(recipes, args, production_cat, pkginfo_template):\n for recipe in recipes:\n print SEPARATOR\n\n if recipe in RECIPE_EXCLUSIONS:\n print_error(\"Not overriding %s because it is in the list of \"\n \"exclusions.\" % recipe)\n continue\n if recipe.startswith(\"local\"):\n print_error(\"Not overriding %s because it _is_ an override.\" %\n recipe)\n continue\n\n override_path = make_override(recipe, args.override_dir)\n if override_path is None:\n continue\n\n # Copy just-generated override's Input section to Input_Original.\n override = FoundationPlist.readPlist(override_path)\n override[\"Input_Original\"] = override[\"Input\"]\n override[\"Input\"] = {}\n override[\"Input\"][\"pkginfo\"] = {}\n\n current_version = get_current_production_version(\n production_cat, override, args)\n apply_current_or_orig_values(override, current_version, args)\n\n if not args.suppress_subdir:\n copy_package_path_to_input(override, current_version, args)\n\n if pkginfo_template:\n apply_pkginfo_template(override, pkginfo_template)\n\n FoundationPlist.writePlist(override, override_path)","def create_tables_and_apply_patches(self):\n\n if self.authorized and not self.db_tables_initiated:\n with self.connection.cursor() as cursor:\n for statement in self.parse_mysql_sql_file():\n cursor.execute(statement)\n\n PyFunceble.LOGGER.info(\n \"Created the missing tables. Applied all patched\"\n )\n\n self.db_tables_initiated = True","def copy_db(src=FRESHDB, dst=[APPDB]):\n for dest in dst:\n try:\n x = shutil.copy2(src, dest)\n print('File copied to {}'.format(x))\n except shutil.SameFileError:\n print('Both source and destination are identical.')","def test_database_object_overwrite_parameter_is_set(self):\n database = generate_database_object(overwrite=True)\n\n self.assertEqual(\n True,\n database.overwrite == True,\n \"Database object did not have an overwrite flag, despite being created with one.\"\n )","def copy_file_check(self):\n pass","def run_copy(self, src, dst):\n pass","def set_file_ingested(self, original_name, ingested, tablename):\n if ingested:\n prep_stmt = self.session.prepare(\n 'INSERT INTO {0} ({1}) VALUES (?, ?, ?)'.format(\n tablename, \",\".join(COLUMNS_META)\n ))\n bound = prep_stmt.bind([int(time.time()) * 1000, self.who, original_name])\n else:\n prep_stmt = self.session.prepare(\n 'DELETE FROM {0} WHERE {1}=?'.format(tablename, COLUMNS_META[2])\n )\n bound = prep_stmt.bind([original_name])\n # This is not asynchronous since this will be sent once per large file.\n self.session.execute(bound)","def load_into_staging_tables(cur, conn):\n for query in copy_table_queries:\n cur.execute(query)\n conn.commit()","def test_upload_overwrite(self):\n self.request.access.allow_overwrite = [\"everyone\"]\n name, filename = \"a\", \"a-1.tar.gz\"\n self.db.upload(filename, BytesIO(b\"old\"), name)\n self.db.upload(filename, BytesIO(b\"new\"), name)\n\n all_versions = self.db.all(name)\n self.assertEqual(len(all_versions), 1)","def test_overwrite_on_tape(overwrite_on_tape_topology, caches_mock):\n rse1_id, rse2_id, rse3_id, did1, did2 = overwrite_on_tape_topology(did1_corrupted=False, did2_corrupted=True)\n all_rses = [rse1_id, rse2_id, rse3_id]\n\n submitter(once=True, rses=[{'id': rse_id} for rse_id in all_rses], group_bulk=10, partition_wait_time=0, transfertype='single', filter_transfertool=None)\n\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\n assert request['state'] == RequestState.FAILED\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did2)\n assert request['state'] == RequestState.FAILED\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']","def _postprocess_staging_data(self):\n super()._postprocess_staging_data()\n with self._conn, self._conn.cursor() as cursor:\n cursor.execute(sql.SQL(\"\"\"UPDATE {0} SET rat_bitmask = translate_bands_to_rat_bitmask(bands)\"\"\")\n .format(self._staging_tbl_identifier))","def is_complete_overwrite(self) -> Optional[bool]:\n return pulumi.get(self, \"is_complete_overwrite\")","def test_overwrite_hops(overwrite_on_tape_topology, caches_mock, did_factory, file_factory):\n rse1_id, rse2_id, rse3_id, did1, did2 = overwrite_on_tape_topology(did1_corrupted=False, did2_corrupted=True)\n did_factory.upload_client.upload(\n [\n {\n 'path': file_factory.file_generator(size=3),\n 'rse': rse_core.get_rse_name(rse2_id),\n 'did_scope': did1['scope'].external,\n 'did_name': did1['name'],\n 'no_register': True,\n }\n ]\n )\n all_rses = [rse1_id, rse2_id, rse3_id]\n\n submitter(once=True, rses=[{'id': rse_id} for rse_id in all_rses], group_bulk=10, partition_wait_time=0, transfertype='single', filter_transfertool=None)\n\n fts_schema_version = FTS3Transfertool(external_host=TEST_FTS_HOST).version()['schema']['major']\n if fts_schema_version >= 8:\n # Newer fts version will honor the overwrite_hop\n request = __wait_for_state_transition(dst_rse_id=rse2_id, **did1)\n assert request['state'] == RequestState.DONE\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\n assert request['state'] == RequestState.FAILED\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\n else:\n # FTS only recently introduced the overwrite_hops parameter. It will be ignored on old\n # fts versions and the first hop will fail with the file exists error\n # TODO: remove this else after FTS 3.12 release and after updating rucio/fts container with the new release\n request = __wait_for_state_transition(dst_rse_id=rse2_id, **did1)\n assert request['state'] == RequestState.FAILED\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\n assert request['state'] == RequestState.FAILED\n assert 'Unused hop in multi-hop' in request['err_msg']","def update_mapping(self, flush=False, override_chunks=[]):\n\n # get set of filenames from File objects that have already been mapped\n already_mapped_inputs = set(map(lambda x: x.get_name(),self.get_inputs(flatten=True)))\n already_mapped_outputs = map(lambda x: x.get_index(),self.get_outputs())\n nextidx = 1\n if already_mapped_outputs:\n nextidx = max(already_mapped_outputs)+1\n original_nextidx = nextidx+0\n # if dataset is \"closed\" and we already have some inputs, then\n # don't bother doing get_files() again (wastes a DBS query)\n if (len(already_mapped_inputs) > 0 and not self.open_dataset):\n files = []\n else:\n files = [f for f in self.sample.get_files() if f.get_name() not in already_mapped_inputs]\n self.queried_nevents = self.sample.get_nevents()\n\n flush = (not self.open_dataset) or flush\n prefix, suffix = self.output_name.rsplit(\".\",1)\n if self.split_within_files:\n if self.total_nevents < 1 or self.events_per_output < 1:\n raise Exception(\"If splitting within files (presumably for LHE), need to specify total_nevents and events_per_output\")\n nchunks = int(self.total_nevents / self.events_per_output)\n chunks = [files for _ in range(nchunks)]\n leftoverchunk = []\n else:\n chunks, leftoverchunk = Utils.file_chunker(files, events_per_output=self.events_per_output, files_per_output=self.files_per_output, flush=flush)\n if len(override_chunks) > 0:\n self.logger.info(\"Manual override to have {0} chunks\".format(len(override_chunks)))\n chunks = override_chunks\n leftoverchunk = []\n for chunk in chunks:\n if not chunk: continue\n output_path = \"{0}/{1}_{2}.{3}\".format(self.get_outputdir(),prefix,nextidx,suffix)\n output_file = EventsFile(output_path)\n nevents_in_output = sum(map(lambda x: x.get_nevents(), chunk))\n output_file.set_nevents(nevents_in_output)\n self.io_mapping.append([chunk, output_file])\n nextidx += 1\n if (nextidx-original_nextidx > 0):\n self.logger.info(\"Updated mapping to have {0} more entries\".format(nextidx-original_nextidx))","def post_migrate_function(obj):\n obj.a = obj.a + u\"-modified\"\n return True","def update_table(table_name):\n for filename in table_name_to_funcs[table_name][\"filename\"]:\n choose_file_to_get(table_name_to_funcs[table_name][\"file_type\"], filename)\n\n for process_func in table_name_to_funcs[table_name][\"process\"]:\n process_func()\n for to_sql_func in table_name_to_funcs[table_name][\"to_sql\"]:\n to_sql_func(update=True)","async def test_cached_previous_overwrites(self):\n overwrite_json = (\n '{\"send_messages\": true, \"add_reactions\": false, \"create_private_threads\": true, '\n '\"create_public_threads\": false, \"send_messages_in_threads\": true}'\n )\n await self.cog._set_silence_overwrites(self.text_channel)\n self.cog.previous_overwrites.set.assert_awaited_once_with(self.text_channel.id, overwrite_json)","def create_copy_table(self):\n tmp_sql_obj = deepcopy(self._new_table)\n tmp_sql_obj.name = self.new_table_name\n if self.rm_partition:\n tmp_sql_obj.partition = self._old_table.partition\n tmp_sql_obj.partition_config = self._old_table.partition_config\n tmp_table_ddl = tmp_sql_obj.to_sql()\n log.info(\"Creating copy table using: {}\".format(tmp_table_ddl))\n self.execute_sql(tmp_table_ddl)\n self.partitions[self.new_table_name] = self.fetch_partitions(\n self.new_table_name\n )\n self.add_drop_table_entry(self.new_table_name)\n\n # Check whether the schema is consistent after execution to avoid\n # any implicit conversion\n if self.fail_for_implicit_conv:\n obj_after = self.fetch_table_schema(self.new_table_name)\n obj_after.name = self._new_table.name\n # Ignore partition difference, since there will be no implicit\n # conversion here\n obj_after.partition = self._new_table.partition\n obj_after.partition_config = self._new_table.partition_config\n self.populate_charset_collation(obj_after)\n if self.mysql_version.is_mysql8:\n # Remove 'USING HASH' in keys on 8.0, when present in 5.6, as 8.0\n # removes it by default\n self.remove_using_hash_for_80()\n if self.is_myrocks_table:\n log.warning(\n f\"Ignore BTREE indexes in table `{self._new_table.name}` on RocksDB\"\n )\n for idx in self._new_table.indexes:\n if idx.using == \"BTREE\":\n idx.using = None\n if obj_after != self._new_table:\n raise OSCError(\n \"IMPLICIT_CONVERSION_DETECTED\",\n {\"diff\": str(SchemaDiff(self._new_table, obj_after))},\n )","def update_table_in_file(table, source_file):\n with open(source_file, 'r') as source, \\\n tempfile.NamedTemporaryFile('w', delete=False) as temp:\n source_lines = source.readlines()\n\n table_start = index_tag_in_lines(source_lines, tag='Table Start')\n table_end = index_tag_in_lines(source_lines, tag='Table End')\n print(f'Found table_start tag at line no: {table_start}')\n print(f'Found table_end tag at line no: {table_end}')\n assert table_end > table_start, 'Table End must be after Table Start'\n\n table_written = False\n for line_no, line in enumerate(source_lines):\n if line_no <= table_start or line_no >= table_end:\n temp.write(line)\n elif not table_written: # write table once\n temp.writelines(table)\n table_written = True\n\n backup_file = source_file.with_suffix('.md.bkp')\n os.rename(source_file, backup_file)\n print(f'Original file backed up at: {backup_file}')\n\n shutil.copy(temp.name, source_file)","def overwrite_cmd(run, batch, source, lines, basename='xrb'):\n for i, line in enumerate(lines):\n if '\\n' not in line:\n lines[i] += '\\n'\n\n filepath = grid_strings.cmd_filepath(run, batch, source=source, basename=basename)\n print(f'Writing: {filepath}')\n with open(filepath, 'w') as f:\n f.writelines(lines)","def update_policy(self):\n self._sess.run(self._hard_copy_to_target_op);","def copy():\n copy2(per, per_old)","def makeOverrides(self):\n\t\tself.overridesWithValues = self.dataOverrides","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n cur.execute(query)\n conn.commit()","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n cur.execute(query)\n conn.commit()","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n cur.execute(query)\n conn.commit()","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n cur.execute(query)\n conn.commit()","def sync_table_partitions(self) -> None:\n log.info(\"== Stage 5.1: Check table partitions are up-to-date ==\")\n\n # we're using partitions in the ddl file, skip syncing anything\n if not self.rm_partition:\n return\n # not a partitioned table, nothing to do\n if not self.partitions:\n return\n\n # only apply this logic to RANGE partitioning, as other types\n # are usually static\n partition_method = self.get_partition_method(\n self._current_db, self.new_table_name\n )\n if partition_method != \"RANGE\":\n return\n\n try:\n new_tbl_parts = self.list_partition_names(self.new_table_name)\n orig_tbl_parts = self.list_partition_names(self.table_name)\n\n parts_to_drop = set(new_tbl_parts) - set(orig_tbl_parts)\n parts_to_add = set(orig_tbl_parts) - set(new_tbl_parts)\n\n # information schema literally has the string None for\n # non-partitioned tables. Previous checks *should* prevent us\n # from hitting this.\n if \"None\" in parts_to_add or \"None\" in parts_to_drop:\n log.warning(\n \"MySQL claims either %s or %s are not partitioned\",\n self.new_table_name,\n self.table_name,\n )\n return\n\n if parts_to_drop:\n log.info(\n \"Partitions missing from source table \"\n \"to drop from new table %s: %s\",\n self.new_table_name,\n \", \".join(parts_to_drop),\n )\n if parts_to_add:\n log.info(\n \"Partitions in source table to add to new table %s: %s\",\n self.new_table_name,\n \", \".join(parts_to_add),\n )\n self.apply_partition_differences(parts_to_drop, parts_to_add)\n except Exception:\n log.exception(\n \"Unable to sync new table %s with orig table %s partitions\",\n self.new_table_name,\n self.table_name,\n )","def _bmaction(old, new):\n if not old:\n return b'export'\n elif not new:\n return b'delete'\n return b'update'","def write(self):\n if not self._table: raise ValueError ( \"_table is Null\" )\n if self._isnew:\n for m in self._modified_values:\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\n \n try:\n rec = CFG.CX.insert ( CFG.DB.SCHEMA + \".\" + self._table.name,\n self._modified_values )\n #this will automatically re-read the data from the db, to take all changes\n #done by triggers and default values into account.\n self._objectid = rec['objectid']\n\n #print \"Record # {0} inserted into {1}.\".format(self._objectid, self._table.name)\n self.raiseEvent ( \"record_added\", self )\n \n except pg.DatabaseError, e:\n print \"Error inserting record.\"\n raise Record.DataManipulationError ( \"Inserting a new record into '{0}'\".format(self._table.name),\n str(self._modified_values),\n e)\n elif self._ismodified:\n \n for m in self._modified_values: \n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\n \n self._modified_values['objectid'] = self._objectid\n del self.TextCache[self._objectid]\n try:\n rec = CFG.CX.update ( CFG.DB.SCHEMA + \".\" + self._table.name,\n self._modified_values )\n self.read() \n self.raiseEvent ( \"record_saved\", self )\n except pg.DatabaseError, e:\n print \"Error updating record\"\n raise Record.DataManipulationError ( \"Updating record {1} of '{0}'\".format(self._table.name, self._objectid),\n str(self._modified_values),\n e)","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n print('staging', query)\n cur.execute(query)\n conn.commit()","def _batch_write(self):\n if self.to_put:\n db.put(self.to_put)\n self.to_put = []\n if self.to_delete:\n db.delete(self.to_delete)\n self.to_delete = []","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n try:\n cur.execute(query)\n conn.commit()\n \n except psycopg2.Error as e:\n print(e)","def test_setOverwrite(self):\n fp = FilePath(self.mktemp())\n fp.setContent(b\"I love contributing to Twisted!\")\n protocol = self.makeConnectedDccFileReceive(fp.path, overwrite=True)\n\n self.allDataReceivedForProtocol(protocol, b\"Twisted rocks!\")\n\n self.assertEqual(fp.getContent(), b\"Twisted rocks!\")","def need_checksum_for_changes(self):\n # We don't need to run checksum for changes, if we don't want checksum\n # at all\n if not self.need_checksum():\n return False\n if self.is_full_table_dump:\n log.warning(\n \"We're adding new primary key to the table. Skip running \"\n \"checksum for changes, because that's inefficient\"\n )\n return False\n return True","def overwrite(self, timestamp, write_data):\n\n if (self.data.dtype != write_data.dtype ):\n logger.error(\"Conflicting data types for overwrite\")\n raise SpatialDBError (\"Conflicting data types for overwrite\")\n \n self.data[timestamp,:] = overwriteDense_ctype(self.data[timestamp,:], write_data)","def _copy_output(src: Graph, dst: Graph):\n for n_src, n_dst in zip(src.nodes, dst.nodes):\n if n_src.op == 'output':\n n_dst.meta = n_src.meta","async def test_preserved_other_overwrites_voice(self):\n for overwrite_json in ('{\"connect\": true, \"speak\": true}', None):\n with self.subTest(overwrite_json=overwrite_json):\n self.cog.previous_overwrites.get.return_value = overwrite_json\n\n prev_overwrite_dict = dict(self.voice_overwrite)\n await self.cog._unsilence(self.voice_channel)\n new_overwrite_dict = dict(self.voice_overwrite)\n\n # Remove these keys because they were modified by the unsilence.\n del prev_overwrite_dict[\"connect\"]\n del prev_overwrite_dict[\"speak\"]\n del new_overwrite_dict[\"connect\"]\n del new_overwrite_dict[\"speak\"]\n\n self.assertDictEqual(prev_overwrite_dict, new_overwrite_dict)","def backup_overrides(overrides, action='debug'):\n backup_path = os.path.join(BACKUP_PATH, action)\n if not os.path.exists(backup_path):\n os.makedirs(backup_path)\n field = 'user_overrides'\n for chart in overrides:\n name = chart['name']\n if name not in oidc_charts:\n LOG.warning(\"oidc-auth-apps: mismatch chart name '%s'\", name)\n if chart[field]:\n document = yaml.safe_load(chart[field])\n if not document:\n LOG.debug(\"oidc-auth-apps: %s empty document\", name)\n continue\n backup_f = '_'.join([name, field])\n backup_f = '.'.join([backup_f, 'yaml'])\n backup_f = os.path.join(backup_path, backup_f)\n try:\n with open(backup_f, 'w') as file:\n yaml.dump(document, file, default_flow_style=False)\n except IOError as e:\n LOG.error(\"oidc-auth-apps: IOError: %s; file: %s\", e, backup_f)\n return 1\n LOG.info(\"oidc-auth-apps: user_overrides backed up to %s\", backup_path)\n return 0","def _undo_action(self):\n pass","def need_checksum(self):\n if self.skip_checksum:\n log.warning(\"Skip checksum because --skip-checksum is specified\")\n return False\n # There's no point running a checksum compare for selective dump\n if self.where:\n log.warning(\"Skip checksum because --where is given\")\n return False\n # If the collation of primary key column has been changed, then\n # it's high possible that the checksum will mis-match, because\n # the returning sequence after order by primary key may be vary\n # for different collations\n for pri_column in self._pk_for_filter:\n old_column_tmp = [\n col for col in self._old_table.column_list if col.name == pri_column\n ]\n if old_column_tmp:\n old_column = old_column_tmp[0]\n new_column_tmp = [\n col for col in self._new_table.column_list if col.name == pri_column\n ]\n if new_column_tmp:\n new_column = new_column_tmp[0]\n if old_column and new_column:\n if not is_equal(old_column.collate, new_column.collate):\n log.warning(\n \"Collation of primary key column {} has been \"\n \"changed. Skip checksum \".format(old_column.name)\n )\n return False\n # There's no way we can run checksum by chunk if the primary key cannot\n # be covered by any index of the new schema\n if not self.validate_post_alter_pk():\n if self.skip_pk_coverage_check:\n log.warning(\n \"Skipping checksuming because there's no unique index \"\n \"in new table schema can perfectly cover old primary key \"\n \"combination for search\".format(old_column.name)\n )\n return False\n else:\n # Though we have enough coverage for primary key doesn't\n # necessarily mean we can use it for checksum, it has to be an\n # unique index as well. Skip checksum if there's no such index\n if not self.find_coverage_index():\n log.warning(\n \"Skipping checksuming because there's no unique index \"\n \"in new table schema can perfectly cover old primary key \"\n \"combination for search\".format(old_column.name)\n )\n return False\n return True","def _maybe_copy_entry_to_image(instance):\n if instance.compo.is_imagefile_copied:\n name = str('th_' + os.path.basename(instance.entryfile.name))\n instance.imagefile_original.save(name, instance.entryfile)","def update_model_output(self):\n warnings.warn(\"Please ensure that the column names of the new file accurately corresponds to the relevant column names in the exisitng file\")\n column_names_new = self.new_data.head()\n column_names_old = self.existing_data.head()\n for column_name in column_names_new:\n if column_name in column_names_old:\n self.existing_data[column_name] = self.new_data[column_name]\n \n self.existing_data.to_csv(filename_main, index = False)","def overwrite_original_file(self):\n return self.__overwrite_original_file","def undo():","def do_before_dump(self):\n self.checksummer.prepare_checksums()","def scheduleTableAsyncCopy(self, hiveFilterDB, hiveFilterTable, copyDestination):\n\t\tlogging.debug(\"Executing copy_operations.scheduleTableAsyncCopy()\")\n\n\t\tif self.checkDBImportInstance(instance = copyDestination) == False:\n\t\t\tlogging.error(\"The specified remote DBImport instance does not exist.\")\n\t\t\tself.remove_temporary_files()\n\t\t\tsys.exit(1)\n\n\t\thiveFilterDB = hiveFilterDB.replace('*', '%').strip()\n\t\thiveFilterTable = hiveFilterTable.replace('*', '%').strip()\n\n\t\tlocalSession = self.configDBSession()\n\t\timportTables = aliased(configSchema.importTables)\n\t\tcopyASyncStatus = aliased(configSchema.copyASyncStatus)\n\n\t\t# Check if there are any tabled in this DAG that is marked for copy against the specified destination\n\t\tresult = (localSession.query(\n\t\t\t\tcopyASyncStatus\n\t\t\t)\n\t\t\t.filter(copyASyncStatus.hive_db.like(hiveFilterDB))\n\t\t\t.filter(copyASyncStatus.hive_table.like(hiveFilterTable))\n\t\t\t.filter(copyASyncStatus.destination == copyDestination)\n\t\t\t.count())\n\n\t\tif result > 0:\n\t\t\tlogging.error(\"There is already tables that matches this DAG's filter that is scheduled for copy against\")\n\t\t\tlogging.error(\"the specified destination. This operation cant continue until all the current copies are completed\")\n\t\t\tself.remove_temporary_files()\n\t\t\tsys.exit(1)\n\n\t\t# Calculate the source and target HDFS directories\n\t\tdbimportInstances = aliased(configSchema.dbimportInstances)\n\t\n\t\tsourceHDFSaddress = self.common_operations.hdfs_address \n\t\tsourceHDFSbasedir = self.common_operations.hdfs_basedir \n\n\t\trow = (localSession.query(\n\t\t\t\tdbimportInstances.hdfs_address,\n\t\t\t\tdbimportInstances.hdfs_basedir\n\t\t\t)\n\t\t\t.filter(dbimportInstances.name == copyDestination)\n\t\t\t.one())\n\t\t\n\t\ttargetHDFSaddress = row[0]\n\t\ttargetHDFSbasedir = row[1]\n\n\t\tlogging.debug(\"sourceHDFSaddress: %s\"%(sourceHDFSaddress))\n\t\tlogging.debug(\"sourceHDFSbasedir: %s\"%(sourceHDFSbasedir))\n\t\tlogging.debug(\"targetHDFSaddress: %s\"%(targetHDFSaddress))\n\t\tlogging.debug(\"targetHDFSbasedir: %s\"%(targetHDFSbasedir))\n\n\t\t# Fetch a list of tables that match the database and table filter\n\t\tresult = pd.DataFrame(localSession.query(\n\t\t\t\timportTables.table_id,\n\t\t\t\timportTables.hive_db,\n\t\t\t\timportTables.hive_table,\n\t\t\t\timportTables.dbalias\n\t\t\t)\n\t\t\t.filter(importTables.hive_db.like(hiveFilterDB))\n\t\t\t.filter(importTables.hive_table.like(hiveFilterTable))\n\t\t\t)\n\n\t\tfor index, row in result.iterrows():\n\t\t\tlogging.info(\"Schedule asynchronous copy for %s.%s\"%(row['hive_db'], row['hive_table']))\n\t\t\tself.import_config.Hive_DB = row['hive_db']\n\t\t\tself.import_config.Hive_Table = row['hive_table']\n\n\t\t\ttry:\n\t\t\t\tself.import_config.getImportConfig()\n\t\t\texcept invalidConfiguration as errMsg:\n\t\t\t\tlogging.error(errMsg)\n\t\t\t\tself.import_config.remove_temporary_files()\n\t\t\t\tsys.exit(1)\n\n\t\t\tlogging.debug(\"table_id: %s\"%(self.import_config.table_id))\n\t\t\tlogging.debug(\"import_is_incremental: %s\"%(self.import_config.import_is_incremental))\n\n\t\t\tif self.import_config.import_is_incremental == True and includeIncrImports == False:\n\t\t\t\tlogging.warning(\"Asynchronous copy for incremental table %s.%s skipped\"%(row['hive_db'], row['hive_table']))\n\t\t\t\tcontinue\n\n\t\t\tsourceHDFSdir = (sourceHDFSbasedir + \"/\"+ row['hive_db'] + \"/\" + row['hive_table']).replace('$', '').replace(' ', '')\n\t\t\ttargetHDFSdir = (targetHDFSbasedir + \"/\"+ row['hive_db'] + \"/\" + row['hive_table']).replace('$', '').replace(' ', '')\n\t\t\tlogging.debug(\"sourceHDFSdir: %s\"%(sourceHDFSdir))\n\t\t\tlogging.debug(\"targetHDFSdir: %s\"%(targetHDFSdir))\n\n\t\t\tresult = (localSession.query(\n\t\t\t\t\tcopyASyncStatus\n\t\t\t\t)\n\t\t\t\t.filter(copyASyncStatus.table_id == row['table_id'])\n\t\t\t\t.filter(copyASyncStatus.destination == copyDestination)\n\t\t\t\t.count())\n\n\t\t\tif result == 0:\n\t\t\t\tnewcopyASyncStatus = configSchema.copyASyncStatus(\n\t\t\t\t\ttable_id = row['table_id'],\n\t\t\t\t\thive_db = row['hive_db'],\n\t\t\t\t\thive_table = row['hive_table'],\n\t\t\t\t\tdestination = copyDestination,\n\t\t\t\t\thdfs_source_path = \"%s%s\"%(sourceHDFSaddress, sourceHDFSdir),\n\t\t\t\t\thdfs_target_path = \"%s%s\"%(targetHDFSaddress, targetHDFSdir),\n\t\t\t\t\tcopy_status = 0)\n\t\t\t\tlocalSession.add(newcopyASyncStatus)\n\t\t\t\tlocalSession.commit()\n\n\t\tlocalSession.close()\n\n\n\t\tlogging.debug(\"Executing copy_operations.scheduleTableAsyncCopy() - Finished\")","def copy_and_replace_keys(self, table, key_callback):\n client = self.bq_client\n t = client.get_table(table)\n\n cross_joins = []\n\n # begin query generation process\n q = f'CREATE OR REPLACE TABLE `{table}` AS (\\nSELECT \\n'\n for field in t.schema:\n q += process_field(field, None, key_callback)\n cross_joins.extend(process_cross_joins(field, \"copy_table\"))\n q = q.strip(\",\\n\")\n q += f\"\\nFROM\\n `{table}` copy_table\"\n\n for cross_join in cross_joins:\n q += cross_join\n q += \")\"\n\n return q","def swap_tables(self):\n if self.stop_before_swap:\n return True\n log.info(\"== Stage 6: Swap table ==\")\n self.stop_slave_sql()\n self.execute_sql(sql.set_session_variable(\"autocommit\"), (0,))\n self.start_transaction()\n stage_start_time = time.time()\n self.lock_tables((self.new_table_name, self.table_name, self.delta_table_name))\n log.info(\"Final round of replay before swap table\")\n self.checksum_required_for_replay = False\n self.replay_changes(single_trx=True, holding_locks=True)\n # We will not run delta checksum here, because there will be an error\n # like this, if we run a nested query using `NOT EXISTS`:\n # SQL execution error: [1100] Table 't' was not locked with LOCK TABLES\n if self.mysql_version.is_mysql8:\n # mysql 8.0 supports atomic rename inside WRITE locks\n self.execute_sql(\n sql.rename_all_tables(\n orig_name=self.table_name,\n old_name=self.renamed_table_name,\n new_name=self.new_table_name,\n )\n )\n self.table_swapped = True\n self.add_drop_table_entry(self.renamed_table_name)\n log.info(\n \"Renamed {} TO {}, {} TO {}\".format(\n self.table_name,\n self.renamed_table_name,\n self.new_table_name,\n self.table_name,\n )\n )\n else:\n self.execute_sql(sql.rename_table(self.table_name, self.renamed_table_name))\n log.info(\n \"Renamed {} TO {}\".format(self.table_name, self.renamed_table_name)\n )\n self.table_swapped = True\n self.add_drop_table_entry(self.renamed_table_name)\n self.execute_sql(sql.rename_table(self.new_table_name, self.table_name))\n log.info(\"Renamed {} TO {}\".format(self.new_table_name, self.table_name))\n\n log.info(\"Table has successfully swapped, new schema takes effect now\")\n self._cleanup_payload.remove_drop_table_entry(\n self._current_db, self.new_table_name\n )\n self.commit()\n self.unlock_tables()\n self.stats[\"time_in_lock\"] = self.stats.setdefault(\"time_in_lock\", 0) + (\n time.time() - stage_start_time\n )\n self.execute_sql(sql.set_session_variable(\"autocommit\"), (1,))\n self.start_slave_sql()\n self.stats[\"swap_table_progress\"] = \"Swap table finishes\"","def load_staging_tables(cur, conn):\n for query in copy_table_queries:\n try:\n cur.execute(query)\n conn.commit()\n except Exception as e:\n print(e)","def reset_data():\n shutil.copy2(\n 'data/one_producer_many_consumers.ORIG.json',\n 'data/one_producer_many_consumers.json'\n )","def copy_table_after(table, paragraph):\n\n\ttbl, p = table._tbl, paragraph._p\n\tnew_tbl = deepcopy(tbl)\n\tp.addnext(new_tbl)","def handle_copy_rows(request):\n\n request_body_json = json.loads(request.body)\n username = request_body_json['username']\n print(username)\n overwrite = request_body_json['overwrite']\n if overwrite == 'true':\n overwrite = True\n elif overwrite == 'false':\n overwrite = False\n\n usecases = UseCase.objects.all()\n uses = []\n json_resp = {'message':'Ok'}\n for el in usecases:\n if el.name not in uses:\n uses.append(el.name)\n if username is not None:\n try:\n for el in uses:\n copy_rows(el, username,request.session['username'],overwrite)\n\n except Exception as e:\n json_resp = {'error':'error'}\n return JsonResponse(json_resp,status=500)\n else:\n return JsonResponse(json_resp)","def copy_files(self, new_base_dir='.', overwrite=False,\n file_type='any', mode='copy', **kwargs ):\n #== retrieve query results\n file_list = self.bids_layout.get(**kwargs)\n #== select for reg/no-reg\n if file_type == 'reg':\n file_list = [file.filename for file in file_list if hasattr(file, 'registration')]\n elif file_type == 'noreg':\n file_list = [file.filename for file in file_list if (not hasattr(file, 'registration'))]\n else:\n file_list = [file.filename for file in file_list]\n\n if not file_type=='noreg':\n print(\"=== WARNING: directory structure for registered files is not handled correctly -- verify results!\")\n\n #== generate new paths\n for old_path in file_list:\n new_path_rel = self.bids_layout.build_path(old_path, self.bids_layout.path_patterns)\n new_path_abs = os.path.join(new_base_dir, new_path_rel)\n gt.ensure_dir_exists(new_path_abs)\n if mode=='copy':\n print(\"Preparing to copy '%s' to '%s'\"%(old_path, new_path_abs))\n elif mode=='move':\n print(\"Preparing to move '%s' to '%s'\" % (old_path, new_path_abs))\n if os.path.exists(new_path_abs):\n if overwrite:\n os.remove(new_path_abs)\n shutil.copy(old_path, new_path_abs)\n else:\n print(\"File '%s' already exists ... skipping.\"%(new_path_abs))\n else:\n shutil.copy(old_path, new_path_abs)\n if mode=='move':\n os.remove(old_path)\n try:\n os.rmdir(old_path)\n except:\n pass\n\n if not file_type=='noreg':\n print(\"=== WARNING: directory structure for registered files is not handled correctly -- verify results!\")","def merge_both_tables():\n old = Table.read('data/data_table_cartesian_including_tims_stars_with_bg_ols_and_component_overlaps.fits')\n wanted = Table.read('data/scocen_candidates_300k_only_spatial_cut.fits')\n additional = Table.read('data/scocen_candidates_300k_only_spatial_cut_200k_to_determine_bg_ols.fits')\n\n d_old = dict(zip(old['source_id'], old['background_log_overlap']))\n d_add = dict(zip(additional['source_id'], additional['background_log_overlap']))\n d_old.update(d_add)\n dct = d_old\n\n ln_bg_ols = [dct[source_id] for source_id in wanted['source_id']]\n print\n len(ln_bg_ols), len(wanted)\n\n wanted['background_log_overlap'] = ln_bg_ols\n print\n wanted\n\n wanted.write('data/scocen_candidates_300k_only_spatial_cut.fits', overwrite=True, format='fits')","def post_combine(self, target):\n target_extra_files = self.target_extra_files\n if target_extra_files:\n if self.disable_cleanup:\n self.stderr.write(\"Cleanup operations disabled by user.\\n\")\n else:\n self.stderr.write(\"Found extra files not part of source tree(s): \"\n f\"{len(target_extra_files)} files.\\n\")\n\n keep_existing = create_filtered_list(\"splunk\", default=False)\n # splglob_simple: Either full paths, or simple file-only match\n keep_existing.feedall(self.keep_existing, filter=splglob_simple)\n for dest_fn in target_extra_files:\n if keep_existing.match_path(dest_fn):\n self.stderr.write(f\"Keep existing file {dest_fn}\\n\")\n elif self.disable_cleanup:\n self.stderr.write(f\"Skip cleanup of unwanted file {dest_fn}\\n\")\n else:\n self.stderr.write(f\"Remove unwanted file {dest_fn}\\n\")\n os.unlink(os.path.join(target, dest_fn))","def copymode(src, dest):\n import shutil\n\n shutil.copymode(src, dest)","def copyBooks(self):\n skipMods = set(('Morrowind.esm',self.fileInfo.name))\n for id,(record,modName) in (self.srcBooks.items() + self.altBooks.items()):\n if modName not in skipMods:\n self.setRecord(copy.copy(record))","def update(self, mode=\"all\"):\n\n self._check_mode(mode)\n\n mode = [\"prod\", \"staging\"] if mode == \"all\" else [mode]\n for m in mode:\n\n try:\n table = self._get_table_obj(m)\n except google.api_core.exceptions.NotFound:\n continue\n\n # if m == \"staging\":\n\n table.description = self._render_template(\n Path(\"table/table_description.txt\"), self.table_config\n )\n\n # save table description\n with open(\n self.metadata_path\n / self.dataset_id\n / self.table_id\n / \"table_description.txt\",\n \"w\",\n encoding=\"utf-8\",\n ) as f:\n f.write(table.description)\n\n # when mode is staging the table schema already exists\n table.schema = self._load_schema(m)\n fields = [\"description\", \"schema\"] if m == \"prod\" else [\"description\"]\n self.client[f\"bigquery_{m}\"].update_table(table, fields=fields)\n\n logger.success(\n \" {object} {object_id} was {action}!\",\n object_id=self.table_id,\n object=\"Table\",\n action=\"updated\",\n )","def testOnOverwrite(self, widget):\n spy_signal = QtSignalSpy(widget, widget.modelModified)\n\n # check the default\n assert not widget.chkOverwrite.isChecked()\n\n # Change the state\n widget.chkOverwrite.setChecked(True)\n\n # Check the signal\n assert spy_signal.count() == 1\n\n # model dict updated\n assert widget.model['overwrite']","async def test_preserved_other_overwrites_text(self):\n for overwrite_json in ('{\"send_messages\": true, \"add_reactions\": null}', None):\n with self.subTest(overwrite_json=overwrite_json):\n self.cog.previous_overwrites.get.return_value = overwrite_json\n\n prev_overwrite_dict = dict(self.text_overwrite)\n await self.cog._unsilence(self.text_channel)\n new_overwrite_dict = dict(self.text_overwrite)\n\n # Remove these keys because they were modified by the unsilence.\n del prev_overwrite_dict[\"send_messages\"]\n del prev_overwrite_dict[\"add_reactions\"]\n del new_overwrite_dict[\"send_messages\"]\n del new_overwrite_dict[\"add_reactions\"]\n\n self.assertDictEqual(prev_overwrite_dict, new_overwrite_dict)","def _copy_all(entry_list: List[Path], target_dir: Path, on_duplicate: str):\n for entry in entry_list:\n target_entry = target_dir / entry.name\n if not target_entry.exists() or on_duplicate == 'overwrite':\n if entry.is_file():\n shutil.copy(entry, target_entry, follow_symlinks=False)\n else:\n shutil.copytree(entry, target_entry, symlinks=True)\n elif on_duplicate == 'exception':\n raise ValueError(f\"'{target_entry}' already exists (src {entry})\")\n else: # ignore\n continue","def restore_copy_tbl(orig_tblname):\n dd = mg.DATADETS_OBJ\n dd.con.commit()\n getdata.force_sofa_tbls_refresh(sofa_default_db_cur=dd.cur)\n SQL_rename_tbl = ('ALTER TABLE '\n f'{getdata.tblname_qtr(mg.DBE_SQLITE, mg.TMP_TBLNAME2)} RENAME TO '\n f'{getdata.tblname_qtr(mg.DBE_SQLITE, orig_tblname)}')\n dd.cur.execute(SQL_rename_tbl)","def update_tmp_table_location_changes(file_type, database_columns, unique_identifier, fiscal_year):\n le_loc_columns_distinct = \" OR \".join(\n [\n \"website.{column} IS DISTINCT FROM broker.{column}\".format(column=column)\n for column in database_columns\n if column[:12] == \"legal_entity\"\n ]\n )\n\n pop_loc_columns_distinct = \" OR \".join(\n [\n \"website.{column} IS DISTINCT FROM broker.{column}\".format(column=column)\n for column in database_columns\n if column[:13] == \"place_of_perf\"\n ]\n )\n\n sql_statement = \"\"\"\n -- Include columns to determine whether we need a place of performance change or recipient location\n ALTER TABLE {file_type}_transactions_to_update_{fiscal_year}\n ADD COLUMN place_of_performance_change boolean, add COLUMN recipient_change boolean;\n\n UPDATE {file_type}_transactions_to_update_{fiscal_year} broker\n SET\n recipient_change = (\n CASE WHEN\n {le_loc_columns_distinct}\n THEN TRUE ELSE FALSE END\n ),\n place_of_performance_change = (\n CASE WHEN\n {pop_loc_columns_distinct}\n THEN TRUE ELSE FALSE END\n )\n FROM transaction_{file_type} website\n WHERE broker.{unique_identifier} = website.{unique_identifier};\n\n\n -- Delete rows where there is no transaction in the table\n DELETE FROM {file_type}_transactions_to_update_{fiscal_year}\n WHERE place_of_performance_change IS NULL\n AND recipient_change IS NULL;\n\n -- Adding index to table to improve speed on update\n CREATE INDEX {file_type}_le_loc_idx ON {file_type}_transactions_to_update_{fiscal_year}(recipient_change);\n CREATE INDEX {file_type}_pop_idx ON\n {file_type}_transactions_to_update_{fiscal_year}(place_of_performance_change);\n ANALYZE {file_type}_transactions_to_update_{fiscal_year};\n \"\"\".format(\n file_type=file_type,\n unique_identifier=unique_identifier,\n fiscal_year=fiscal_year,\n le_loc_columns_distinct=le_loc_columns_distinct,\n pop_loc_columns_distinct=pop_loc_columns_distinct,\n )\n return sql_statement","def _copy_chunk(self, last_pk):\n self.execute(self.commands.copy_chunk(\n self.name,\n self._join_cols(self.intersection.dest_columns),\n self._qualify(self.source.name, self.intersection.origin_columns),\n self.source.name,\n self.primary_key_column,\n last_pk,\n self.chunk_size\n ))\n self.commit()","def flushUndo(*args, **kwargs)->None:\n pass","def touch(self, connection=None):\n self.create_marker_table()\n\n if connection is None:\n connection = self.connect()\n connection.autocommit = True # if connection created here, we commit it here\n\n connection.cursor().execute(\n \"\"\"INSERT INTO {marker_table} (update_id, target_table)\n VALUES (%s, %s)\n ON DUPLICATE KEY UPDATE\n update_id = VALUES(update_id)\n \"\"\".format(marker_table=self.marker_table),\n (self.update_id, self.table)\n )\n # make sure update is properly marked\n assert self.exists(connection)","def _do_action_tables_create(self):\n\n schema_shell = os.path.join(self.bento_home, \"schema-shell\", \"bin\", \"kiji-schema-shell\")\n assert os.path.isfile(schema_shell), schema_shell\n\n # Delete the table first!\n cmd = (\n \"kiji delete --target={kiji_uri} --interactive=false; \" +\n \"kiji install --kiji={kiji_uri}\" ).format(kiji_uri=self.kiji_uri)\n self._run_kiji_job(cmd)\n\n for ddl in self.ddls:\n ddl_full_path = os.path.join(self.movie_advisor_home, ddl)\n assert os.path.isfile(ddl_full_path)\n cmd = \"{schema_shell} --kiji={kiji_uri} --file={ddl_full_path}\".format(\n schema_shell=schema_shell,\n kiji_uri=self.kiji_uri,\n ddl_full_path=ddl_full_path)\n self._run_kiji_job(cmd)","def process(self):\n try:\n # self.alter_columns()\n self.collect_drop_fk()\n self.update_table()\n self.create_tables()\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\n return True\n except Exception as err:\n logger.error(\"create_tables [error] -> %s\" % err)","def pre_modify(self):\n return 0","def test_base_replica_repair_with_contention(self):\n self._base_replica_repair_test(fail_mv_lock=True)","def write_merged(self, content = '', table=''):\n\n if not os.path.isdir(self.out_dir):\n Path(self.out_dir).mkdir(parents=True, exist_ok=True) \n out_name = self.out_dir + '/' + self.station + '_CEUAS_merged_v0.nc' \n\n '''\n if os.path.isfile('dic_obstab_attributes.npy'):\n attrs_dic = np.load('dic_obstab_attributes.npy' , allow_pickle = True).item()\n else:\n attrs_dic = {}\n '''\n attrs_dic = {}\n\n \"\"\" Retrieving the attributes \"\"\"\n if content in ['observations_table','header_table','era5fb', 'station_configuration']:\n for var in table.keys():\n if var == 'comments':\n continue \n\n attrs_dic[var] = {}\n try:\n attrs_dic[var]['description'] = bytes( self.dic_type_attributes[content][var]['description'] , 'utf-8' )\n except:\n attrs_dic[var]['description'] = bytes( 'missing' , 'utf-8' )\n #print(' FFF FAILING WITH DESCRIPTION: ', var , ' ' , self.dic_type_attributes[content][var]['description']) # FFF CHECK WHY SOME ARE FAILING\n\n try:\n attrs_dic[var]['external_table'] = bytes( self.dic_type_attributes[content][var]['external_table'] , 'utf-8' )\n except:\n attrs_dic[var]['external_table'] = bytes( 'missing' , 'utf-8' )\n #print(' FFF FAILING WITH EXTERNAL TABLE : ', var ) # FFF CHECK WHY SOME ARE FAILING \n\n\n if content == 'recordindex': # writing the recordindex, recordtimestamp, dateindex\n #logging.info('Writing the merged record indices to the netCDF output ')\n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a')\n\n elif content == 'cdm_tables':\n for k in data['cdm_tables'].keys():\n table = data['cdm_tables'][k]\n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a', group = k)\n #logging.info('Writing the cdm table %s to the netCDF output ', k)\n \n elif content == 'source_configuration': \n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a', group = content)\n #logging.info('Writing the source_configuration table to the netCDF output ')\n\n elif content == 'station_configuration':\n for k in table.keys(): \n if k == 'station_name':\n print(0)\n var_type = self.dic_type_attributes[content][k]['type']\n\n ''' trying to convert the variable types to the correct types stored as attribute, read from the numpy dic file '''\n if type(table[k][0]) != var_type:\n try:\n table[k] = table[k].astype( var_type ) \n print('Done station_conf' , k )\n except:\n if k == 'secondary_id':\n table[k] = table[k].astype( bytes ) \n\n print ('FAILED converting column ' , k, ' type ', type(table[k][0]) , ' to type ', var_type )\n\n dic = {k:table[k]} \n write_dict_h5(out_name, dic , content, self.encodings[content], var_selection=[], mode='a', attrs = attrs_dic )\n \n \n # Writing the observations_table, header_table, era5fb \n elif content in ['observations_table', 'era5fb', 'header_table']: \n\n shape = ''\n for k in table.keys(): \n if k == 'index' or k == 'hdrlen' or 'string' in k :\n continue\n if k == 'station_name':\n print(0)\n \n var_type = self.dic_type_attributes[content][k]['type']\n\n ''' trying to convert the variable types to the correct types stored as attribute, read from the numpy dic file '''\n if type(table[k][0]) != var_type:\n\n if k == 'hdrlen': \n continue\n try:\n #table[k] = table[k].astype( bytes ) \n table[k] = table[k].astype( var_type ) \n \n except:\n print ('FAILED converting column ' , k, ' type ', type(table[k][0]) , ' to type ', var_type )\n\n #print('*** Writing the table ', content, ' variable ', k)\n #if k == 'duplicates':\n # table[k] = table[k].astype( bytes ) \n \n \n dic = {k:table[k]} # making a 1 colum dictionary\n shape = table[k].shape\n #print('SHAPE IS FFF ', table[k].shape )\n write_dict_h5(out_name, dic , content, self.encodings[content], var_selection=[], mode='a', attrs = attrs_dic )\n\n if content == 'observations_table' and not self.obstab_nans_filled :\n missing_cdm_var = [ v for v in self.dic_type_attributes[content].keys() if v not in self.observations_table_vars] # variables to be filled with nans \n for k in missing_cdm_var:\n if k not in ['advanced_assimilation_feedback']:\n var_type = self.dic_type_attributes[content][k]['type']\n if var_type == np.int32 :\n nan = np.int32(-2147483648)\n else:\n nan = np.float32(np.nan) \n logging.debug('Adding missing cdm colum with empty values: %s ' , k )\n dic={k:np.empty(shape,dtype=np.dtype(nan))}\n dic[k].fill(nan)\n write_dict_h5(out_name, dic, 'observations_table', self.encodings['observations_table'], var_selection=[], mode='a', attrs = attrs_dic ) ### TO DO\n self.obstab_nans_filled = True\n\n elif content == 'observations_table' and self.obstab_nans_filled:\n return","def before_update(mapper, conn, target):\n\n assert bool(target.ref), \"File.ref can't be null (before_update)\"","def begin_not_undoable_action(self):\n self.not_undoable_action = True","def modify_tbl(self):\n debug = False\n dd = mg.DATADETS_OBJ\n orig_tblname = dd.tbl\n ## other (i.e. not the sofa_id) field details\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\n if debug:\n print('oth_name_types to feed into '\n f'make_strict_typing_tbl {oth_name_types}')\n try: ## 1 way or other must do strict_cleanup()\n make_strict_typing_tbl(\n orig_tblname, oth_name_types, self.settings_data)\n except sqlite.IntegrityError as e: #@UndefinedVariable\n if debug: print(b.ue(e))\n strict_cleanup(restore_tblname=orig_tblname)\n raise FldMismatchException\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n raise Exception('Problem making strictly-typed table.'\n f'\\nCaused by error: {b.ue(e)}')\n copy_orig_tbl(orig_tblname)\n wipe_tbl(orig_tblname)\n final_name = self.tblname_lst[0] ## may have been renamed\n try:\n make_redesigned_tbl(final_name, oth_name_types)\n strict_cleanup(restore_tblname=final_name)\n dd.set_tbl(tbl=final_name)\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\n dd.set_tbl(tbl=orig_tblname)\n raise Exception('Problem making redesigned table.'\n f'\\nCaused by error: {b.ue(e)}')\n wipe_tbl(mg.TMP_TBLNAME2)","def _copy(self):\n for d in self._current_chunk:\n self.out.write(d)","def test_backup_merge_with_unmerged(self):\n gen = BlobGenerator(\"ent-backup\", \"ent-backup-\", self.value_size, end=self.num_items)\n self._load_all_buckets(self.master, gen, \"create\", 0)\n self.backup_create()\n self._take_n_backups(n=2)\n self.backupset.start = 1\n self.backupset.end = 2\n self.log.info(\"Merging existing incremental backups\")\n status, output, message = self.backup_merge()\n if not status:\n self.fail(message)\n self.log.info(\"Taking more backups\")\n self._take_n_backups(n=2)\n self.backupset.start = 1\n self.backupset.end = 3\n self.log.info(\"Merging new backups into already merged backup\")\n status, output, message = self.backup_merge()\n if not status:\n self.fail(message)\n self.log.info(\"Successfully merged new backups with already merged backup\")","def on_ok(self, _event):\n dd = mg.DATADETS_OBJ\n if self.read_only:\n self.exiting = True\n self.Destroy()\n else:\n ## NB any changes defined in recode are already done\n new_tbl, tblname_changed, data_changed = self.get_change_status()\n if new_tbl or tblname_changed or data_changed:\n try:\n if not new_tbl:\n orig_tblname = self.tblname_lst[0]\n dd.set_tbl(tbl=orig_tblname)\n else:\n dd.set_tbl(tbl=None)\n self.make_changes()\n self.exiting = True\n self.Destroy()\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\n except FldMismatchException:\n wx.MessageBox(\n _('Unable to modify table. Some data does not match the'\n ' column type. Please edit and try again.'))\n return\n except Exception as e:\n wx.MessageBox(\n _(\"Unable to modify table.\\nCaused by error: %s\")\n % b.ue(e))\n return\n elif self.changes_made: ## not in tableconf. Must've been in recoding\n self.exiting = True\n self.Destroy()\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\n return\n else:\n wx.MessageBox(_('No changes to update.'))\n return","def transfer_missing_elements(target_dict, source_dict, transfer_type=None):\r\n\r\n if transfer_type is None:\r\n transfer_type = source_dict.get(\"_transfer_type_\", \"recursive\")\r\n\r\n for key_, val_ in source_dict.items():\r\n # print(key_,isinstance(val_, dict), val_)\r\n if isinstance(val_, dict):\r\n if key_ not in target_dict:\r\n target_dict[key_] = EasyDict()\r\n if transfer_type is None:\r\n transfer_type = val_.get(\"_transfer_type_\", \"recursive\")\r\n # print(\"*********** \",transfer_type)\r\n\r\n if transfer_type == \"recursive\":\r\n transfer_missing_elements(target_dict[key_], val_, transfer_type)\r\n elif transfer_type == \"update\":\r\n target_dict[key_].update(val_)\r\n elif transfer_type == \"overwrite\":\r\n target_dict[key_] = copy.deepcopy(source_dict[key_])\r\n # target_dict[key_] = val_\r\n\r\n elif key_ not in target_dict:\r\n target_dict[key_] = copy.deepcopy(source_dict[key_])\r\n # target_dict[key_] = val_\r\n # else :\r\n # target_dict[key_] = val_\r\n # target_dict[key_] = copy.deepcopy(source_dict[key_])\r\n\r\n\r\n # if isinstance(source_dict[key_],list) and isinstance(source_dict[key_][0],dict):\r\n # if key_ not in target_dict:\r\n # target_dict[key_] = []\r\n # for src_ in source_dict[key_]:\r\n # if not isinstance(src_,dict):\r\n # continue\r\n # match = False\r\n # for tar_ in target_dict[key_]:\r\n # # TODO make a list of bool with ID keys loaded from odb and check if any(matches):\r\n # if key_matches(\"pth_full\", src_, tar_) or key_matches(\"pth_alias\", src_, tar_) :\r\n # match = True\r\n # if not match:\r\n # temp = EasyDict()\r\n # target_dict[key_].append(temp)\r\n # transfer_missing_elements(temp, src_)\r"],"string":"[\n \"def ProcessTableOverwrite(ref, args, request):\\n dataset_id = ref.datasetId\\n table_id = ref.Name()\\n project_id = ref.projectId\\n\\n if args.overwrite:\\n if _TableExists(dataset_id, table_id, project_id):\\n _TryDeleteTable(dataset_id, table_id, project_id)\\n\\n return request\",\n \"def process_overrides(self, db, dest, kvargs, lines):\\n logging.info(\\\"process_overrides db:{} dest:{} kvargs:{} \\\".format(db.name,dest,kvargs))\\n keyword = kvargs['keyword']\\n db.create_overrides(keyword)\\n return True\",\n \"def is_overwrite_all(self):\\n return self._tag == 'overwrite_all'\",\n \"def test_overwrites(self):\\n\\n extra_con = set([Constraint('fake', ['OVERWRITE'])])\\n the_process_unit = ProcessUnit([self.a_pattern_ds], '/%fake%/%file%/%pattern%.txt',\\n 'echo', extra_constraints=extra_con)\\n\\n ds_result = the_process_unit.execute(simulate=True)\\n\\n expected_in_cons = set([Constraint('fake', ['fake_1']),\\n Constraint('file', ['file_1']),\\n Constraint('pattern', ['pattern_1'])])\\n expected_out_cons = set([Constraint('fake', ['OVERWRITE']),\\n Constraint('file', ['file_1']),\\n Constraint('pattern', ['pattern_1'])])\\n\\n self.assertEqual(expected_in_cons, self.a_pattern_ds.constraints)\\n self.assertEqual(expected_out_cons, ds_result.constraints)\",\n \"def needPartitionTableUpdate(self):\\n n_table=list()\\n d_table=self.destination.getPartitionTable()\\n s_table=self.source.getPartitionTable()\\n for i in range(len(s_table)):\\n n_table.append(re.sub(self.source.getDeviceName(), \\\\\\n self.destination.getDeviceName(), \\\\\\n s_table[i]))\\n if d_table == n_table:\\n return False\\n else:\\n return True\",\n \"def no_overwrite_example():\",\n \"def _apply(self):\\n s = [(iptables_save, iptables_restore, self.ipv4)]\\n if self.use_ipv6:\\n s += [(ip6tables_save, ip6tables_restore, self.ipv6)]\\n\\n for save, restore, tables in s:\\n all_tables, _err = save()\\n all_lines = all_tables.split('\\\\n')\\n for table_name, table in six.iteritems(tables):\\n start, end = self._find_table(all_lines, table_name)\\n all_lines[start:end] = self._modify_rules(\\n all_lines[start:end], table, table_name)\\n table.dirty = False\\n restore('\\\\n'.join(all_lines))\",\n \"def s3_table_set_before_write(cls, table):\\n\\n update_default = cls.s3_table_name_update_default\\n\\n table._before_insert.append(update_default)\\n table._before_update.append(lambda s, data: update_default(data))\",\n \"def ProcessDatasetOverwrite(ref, args, request):\\n del ref\\n dataset_id = request.dataset.datasetReference.datasetId\\n project_id = request.projectId\\n\\n if args.overwrite:\\n if _DatasetExists(dataset_id, project_id):\\n _TryDeleteDataset(dataset_id, project_id)\\n\\n return request\",\n \"def pre_osc_check(self):\\n # Make sure temporary table we will use during copy doesn't exist\\n self.table_check()\\n self.decide_pk_for_filter()\\n\\n # Check if we can have indexes in new table to efficiently look up\\n # current old pk combinations\\n if not self.validate_post_alter_pk():\\n self.table_size = self.get_table_size(self.table_name)\\n if self.skip_pk_coverage_check:\\n log.warning(\\n \\\"Indexes on new table cannot cover current PK of \\\"\\n \\\"the old schema, which will make binary logs replay \\\"\\n \\\"in an inefficient way.\\\"\\n )\\n elif self.table_size < self.pk_coverage_size_threshold:\\n log.warning(\\n \\\"No index on new table can cover old pk. Since this is \\\"\\n \\\"a small table: {}, we fallback to a full table dump\\\".format(\\n self.table_size\\n )\\n )\\n # All columns will be chosen if we are dumping table without\\n # chunking, this means all columns will be used as a part of\\n # the WHERE condition when replaying\\n self.is_full_table_dump = True\\n self._pk_for_filter = [col.name for col in self._old_table.column_list]\\n self._pk_for_filter_def = self._old_table.column_list.copy()\\n elif self.is_full_table_dump:\\n log.warning(\\n \\\"Skipping coverage index test, since we are doing \\\"\\n \\\"full table dump\\\"\\n )\\n else:\\n old_pk_names = \\\", \\\".join(\\n \\\"`{}`\\\".format(col.name)\\n for col in self._old_table.primary_key.column_list\\n )\\n raise OSCError(\\\"NO_INDEX_COVERAGE\\\", {\\\"pk_names\\\": old_pk_names})\\n\\n log.info(\\n \\\"PK filter for replaying changes later: {}\\\".format(self._pk_for_filter)\\n )\\n\\n self.foreign_key_check()\\n self.trigger_check()\\n self.init_range_variables()\\n self.get_table_chunk_size()\\n self.make_chunk_size_odd()\\n self.check_disk_size()\\n self.ts_bootstrap_check()\\n self.drop_columns_check()\",\n \"def test_merge_overwrite_traditional(self):\\n mdict = copy.deepcopy(self.dict1)\\n mdict[\\\"A\\\"] = \\\"b\\\"\\n ret = dictupdate.merge_overwrite(copy.deepcopy(self.dict1), {\\\"A\\\": \\\"b\\\"})\\n self.assertEqual(mdict, ret)\",\n \"def test_merge_overwrite_missing_source_key(self):\\n mdict = copy.deepcopy(self.dict1)\\n mdict[\\\"D\\\"] = \\\"new\\\"\\n ret = dictupdate.merge_overwrite(copy.deepcopy(self.dict1), {\\\"D\\\": \\\"new\\\"})\\n self.assertEqual(mdict, ret)\",\n \"def ProcessTableCopyConfiguration(ref, args, request):\\n del ref # Unused\\n source_ref = args.CONCEPTS.source.Parse()\\n destination_ref = args.CONCEPTS.destination.Parse()\\n arg_utils.SetFieldInMessage(\\n request, 'job.configuration.copy.destinationTable.datasetId',\\n destination_ref.Parent().Name())\\n arg_utils.SetFieldInMessage(\\n request, 'job.configuration.copy.destinationTable.projectId',\\n destination_ref.projectId)\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.destinationTable.tableId',\\n destination_ref.Name())\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.datasetId',\\n source_ref.Parent().Name())\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.projectId',\\n source_ref.projectId)\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.tableId',\\n source_ref.Name())\\n return request\",\n \"def sectional_overwrite_check(self):\\n\\n for rule in self.options['sectional_overwrite']:\\n if self.lineage_test(rule):\\n return True\\n return False\",\n \"def run(self):\\n if not (self.table and self.columns):\\n raise Exception(\\\"table and columns need to be specified\\\")\\n\\n connection = self.output().connect()\\n\\n # attempt to copy the data into mysql\\n # if it fails because the target table doesn't exist\\n # try to create it by running self.create_table\\n for attempt in range(2):\\n try:\\n cursor = connection.cursor()\\n print(\\\"caling init copy...\\\")\\n self.init_copy(connection)\\n self.copy(cursor)\\n self.post_copy(connection)\\n if self.enable_metadata_columns:\\n self.post_copy_metacolumns(cursor)\\n except Error as err:\\n if err.errno == errorcode.ER_NO_SUCH_TABLE and attempt == 0:\\n # if first attempt fails with \\\"relation not found\\\", try creating table\\n # logger.info(\\\"Creating table %s\\\", self.table)\\n connection.reconnect()\\n self.create_table(connection)\\n else:\\n raise\\n else:\\n break\\n\\n # mark as complete in same transaction\\n self.output().touch(connection)\\n connection.commit()\\n connection.close()\",\n \"def onUndo(self):\\n pass\",\n \"def overwrite_all ( self ):\\n return self.value == self.OV_ALL\",\n \"def undo(self):\\n LOG.debug(\\\"In the undo method, will attempt to restore\\\")\\n\\n # validate detected nothing to do for this, nothing was done\\n # for execute, so simply return\\n if self.no_op:\\n return\\n\\n if not self.source_dev or not self.target_dev:\\n return\\n LOG.debug(\\\"The source dictionary is: %s\\\", self.source_dict_restore)\\n LOG.debug(\\\"The target dictionary is: %s\\\", self.target_dict_restore)\\n\\n # In scenario where no source IP Address...\\n if self.source_dict_restore:\\n self.commandex.send_ifcfg(self.source_dev,\\n self.source_dict_restore)\\n\\n # May have failed because the ifcfg didn't even exist, nothing\\n # to roll back then\\n if self.target_dict_restore:\\n self.commandex.send_ifcfg(self.target_dev,\\n self.target_dict_restore)\",\n \"def abstract_write(self, *params): \\n section = self.table_section_from_parameter(*params)\\n row_args = self.table_row_args_from_parameter(*params)\\n new_row = self.table_row_class(*row_args)\\n # IMPORTANTE! ASUMO QUE UN BLOQUE INVALIDO ES IGUAL A UNO VACIO!\\n # TO DO: PREGUNTAR EN ISSUE\\n found_index = False\\n for index, table_row in enumerate(section.copy()): \\n if table_row is None or not table_row.valid:\\n found_index = True\\n overwrite_index = index\\n break\\n\\n if not found_index:\\n overwrite_index = self.next_replace(section)\\n\\n replace_index = self.index_mapping_from_parameter(overwrite_index, *params)\\n\\n\\n old_line = self.table[replace_index]\\n #print(f\\\"{self.__class__.__name__} Replace -> Index: {replace_index}\\\")\\n\\n # Perfom the actual write\\n self.table[replace_index] = new_row\",\n \"def touch(self):\\n if self.marker_table_bound is None:\\n self.create_marker_table()\\n\\n table = self.marker_table_bound\\n id_exists = self.exists()\\n with self.engine.begin() as conn:\\n if not id_exists:\\n ins = table.insert().values(\\n ParquetSource=self.parquet_source,\\n Environment=self.environment,\\n BackupDate=self.backup_date,\\n TargetTable=self.target_table,\\n InsertedDate=datetime.now())\\n else:\\n ins = table.update().where(sqlalchemy.and_(\\n table.c.ParquetSource == self.parquet_source,\\n table.c.Environment == self.environment,\\n table.c.TargetTable == self.target_table)).\\\\\\n values(ParquetSource=self.parquet_source,\\n Environment=self.environment,\\n BackupDate=self.backup_date,\\n TargetTable=self.target_table,\\n InsertedDate=datetime.now())\\n conn.execute(ins)\\n assert self.exists()\",\n \"def process_dump_files(self):\\n if not self.open_workbooks():\\n exit()\\n\\n self.message('*****************************************************************************')\\n self.message('Only columns that exist in both the dump and destination file will be synced.')\\n self.message('They must also match exactly including spelling and capitalization.')\\n self.message('*****************************************************************************')\\n\\n self.wb_destination.active = self.wb_destination['Hypercare Incidents']\\n self.parse_dump_file(self.wb_incident.active, self.wb_destination.active, self.fn_incident)\\n\\n self.wb_destination.active = self.wb_destination['Hypercare Defects']\\n self.parse_dump_file(self.wb_defect.active, self.wb_destination.active, self.fn_defect)\\n\\n self.wb_destination.active = self.wb_destination['Hypercare Enhancements']\\n self.parse_dump_file(self.wb_enhancement.active, self.wb_destination.active, self.fn_enhancement)\\n\\n self.wb_destination.active = self.wb_destination['ALM Defects']\\n self.parse_dump_file(self.wb_alm.active, self.wb_destination.active, self.fn_alm)\",\n \"def process_overrides(recipes, args, production_cat, pkginfo_template):\\n for recipe in recipes:\\n print SEPARATOR\\n\\n if recipe in RECIPE_EXCLUSIONS:\\n print_error(\\\"Not overriding %s because it is in the list of \\\"\\n \\\"exclusions.\\\" % recipe)\\n continue\\n if recipe.startswith(\\\"local\\\"):\\n print_error(\\\"Not overriding %s because it _is_ an override.\\\" %\\n recipe)\\n continue\\n\\n override_path = make_override(recipe, args.override_dir)\\n if override_path is None:\\n continue\\n\\n # Copy just-generated override's Input section to Input_Original.\\n override = FoundationPlist.readPlist(override_path)\\n override[\\\"Input_Original\\\"] = override[\\\"Input\\\"]\\n override[\\\"Input\\\"] = {}\\n override[\\\"Input\\\"][\\\"pkginfo\\\"] = {}\\n\\n current_version = get_current_production_version(\\n production_cat, override, args)\\n apply_current_or_orig_values(override, current_version, args)\\n\\n if not args.suppress_subdir:\\n copy_package_path_to_input(override, current_version, args)\\n\\n if pkginfo_template:\\n apply_pkginfo_template(override, pkginfo_template)\\n\\n FoundationPlist.writePlist(override, override_path)\",\n \"def create_tables_and_apply_patches(self):\\n\\n if self.authorized and not self.db_tables_initiated:\\n with self.connection.cursor() as cursor:\\n for statement in self.parse_mysql_sql_file():\\n cursor.execute(statement)\\n\\n PyFunceble.LOGGER.info(\\n \\\"Created the missing tables. Applied all patched\\\"\\n )\\n\\n self.db_tables_initiated = True\",\n \"def copy_db(src=FRESHDB, dst=[APPDB]):\\n for dest in dst:\\n try:\\n x = shutil.copy2(src, dest)\\n print('File copied to {}'.format(x))\\n except shutil.SameFileError:\\n print('Both source and destination are identical.')\",\n \"def test_database_object_overwrite_parameter_is_set(self):\\n database = generate_database_object(overwrite=True)\\n\\n self.assertEqual(\\n True,\\n database.overwrite == True,\\n \\\"Database object did not have an overwrite flag, despite being created with one.\\\"\\n )\",\n \"def copy_file_check(self):\\n pass\",\n \"def run_copy(self, src, dst):\\n pass\",\n \"def set_file_ingested(self, original_name, ingested, tablename):\\n if ingested:\\n prep_stmt = self.session.prepare(\\n 'INSERT INTO {0} ({1}) VALUES (?, ?, ?)'.format(\\n tablename, \\\",\\\".join(COLUMNS_META)\\n ))\\n bound = prep_stmt.bind([int(time.time()) * 1000, self.who, original_name])\\n else:\\n prep_stmt = self.session.prepare(\\n 'DELETE FROM {0} WHERE {1}=?'.format(tablename, COLUMNS_META[2])\\n )\\n bound = prep_stmt.bind([original_name])\\n # This is not asynchronous since this will be sent once per large file.\\n self.session.execute(bound)\",\n \"def load_into_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n cur.execute(query)\\n conn.commit()\",\n \"def test_upload_overwrite(self):\\n self.request.access.allow_overwrite = [\\\"everyone\\\"]\\n name, filename = \\\"a\\\", \\\"a-1.tar.gz\\\"\\n self.db.upload(filename, BytesIO(b\\\"old\\\"), name)\\n self.db.upload(filename, BytesIO(b\\\"new\\\"), name)\\n\\n all_versions = self.db.all(name)\\n self.assertEqual(len(all_versions), 1)\",\n \"def test_overwrite_on_tape(overwrite_on_tape_topology, caches_mock):\\n rse1_id, rse2_id, rse3_id, did1, did2 = overwrite_on_tape_topology(did1_corrupted=False, did2_corrupted=True)\\n all_rses = [rse1_id, rse2_id, rse3_id]\\n\\n submitter(once=True, rses=[{'id': rse_id} for rse_id in all_rses], group_bulk=10, partition_wait_time=0, transfertype='single', filter_transfertool=None)\\n\\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\\n assert request['state'] == RequestState.FAILED\\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did2)\\n assert request['state'] == RequestState.FAILED\\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\",\n \"def _postprocess_staging_data(self):\\n super()._postprocess_staging_data()\\n with self._conn, self._conn.cursor() as cursor:\\n cursor.execute(sql.SQL(\\\"\\\"\\\"UPDATE {0} SET rat_bitmask = translate_bands_to_rat_bitmask(bands)\\\"\\\"\\\")\\n .format(self._staging_tbl_identifier))\",\n \"def is_complete_overwrite(self) -> Optional[bool]:\\n return pulumi.get(self, \\\"is_complete_overwrite\\\")\",\n \"def test_overwrite_hops(overwrite_on_tape_topology, caches_mock, did_factory, file_factory):\\n rse1_id, rse2_id, rse3_id, did1, did2 = overwrite_on_tape_topology(did1_corrupted=False, did2_corrupted=True)\\n did_factory.upload_client.upload(\\n [\\n {\\n 'path': file_factory.file_generator(size=3),\\n 'rse': rse_core.get_rse_name(rse2_id),\\n 'did_scope': did1['scope'].external,\\n 'did_name': did1['name'],\\n 'no_register': True,\\n }\\n ]\\n )\\n all_rses = [rse1_id, rse2_id, rse3_id]\\n\\n submitter(once=True, rses=[{'id': rse_id} for rse_id in all_rses], group_bulk=10, partition_wait_time=0, transfertype='single', filter_transfertool=None)\\n\\n fts_schema_version = FTS3Transfertool(external_host=TEST_FTS_HOST).version()['schema']['major']\\n if fts_schema_version >= 8:\\n # Newer fts version will honor the overwrite_hop\\n request = __wait_for_state_transition(dst_rse_id=rse2_id, **did1)\\n assert request['state'] == RequestState.DONE\\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\\n assert request['state'] == RequestState.FAILED\\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\\n else:\\n # FTS only recently introduced the overwrite_hops parameter. It will be ignored on old\\n # fts versions and the first hop will fail with the file exists error\\n # TODO: remove this else after FTS 3.12 release and after updating rucio/fts container with the new release\\n request = __wait_for_state_transition(dst_rse_id=rse2_id, **did1)\\n assert request['state'] == RequestState.FAILED\\n assert 'Destination file exists and overwrite is not enabled' in request['err_msg']\\n request = __wait_for_state_transition(dst_rse_id=rse3_id, **did1)\\n assert request['state'] == RequestState.FAILED\\n assert 'Unused hop in multi-hop' in request['err_msg']\",\n \"def update_mapping(self, flush=False, override_chunks=[]):\\n\\n # get set of filenames from File objects that have already been mapped\\n already_mapped_inputs = set(map(lambda x: x.get_name(),self.get_inputs(flatten=True)))\\n already_mapped_outputs = map(lambda x: x.get_index(),self.get_outputs())\\n nextidx = 1\\n if already_mapped_outputs:\\n nextidx = max(already_mapped_outputs)+1\\n original_nextidx = nextidx+0\\n # if dataset is \\\"closed\\\" and we already have some inputs, then\\n # don't bother doing get_files() again (wastes a DBS query)\\n if (len(already_mapped_inputs) > 0 and not self.open_dataset):\\n files = []\\n else:\\n files = [f for f in self.sample.get_files() if f.get_name() not in already_mapped_inputs]\\n self.queried_nevents = self.sample.get_nevents()\\n\\n flush = (not self.open_dataset) or flush\\n prefix, suffix = self.output_name.rsplit(\\\".\\\",1)\\n if self.split_within_files:\\n if self.total_nevents < 1 or self.events_per_output < 1:\\n raise Exception(\\\"If splitting within files (presumably for LHE), need to specify total_nevents and events_per_output\\\")\\n nchunks = int(self.total_nevents / self.events_per_output)\\n chunks = [files for _ in range(nchunks)]\\n leftoverchunk = []\\n else:\\n chunks, leftoverchunk = Utils.file_chunker(files, events_per_output=self.events_per_output, files_per_output=self.files_per_output, flush=flush)\\n if len(override_chunks) > 0:\\n self.logger.info(\\\"Manual override to have {0} chunks\\\".format(len(override_chunks)))\\n chunks = override_chunks\\n leftoverchunk = []\\n for chunk in chunks:\\n if not chunk: continue\\n output_path = \\\"{0}/{1}_{2}.{3}\\\".format(self.get_outputdir(),prefix,nextidx,suffix)\\n output_file = EventsFile(output_path)\\n nevents_in_output = sum(map(lambda x: x.get_nevents(), chunk))\\n output_file.set_nevents(nevents_in_output)\\n self.io_mapping.append([chunk, output_file])\\n nextidx += 1\\n if (nextidx-original_nextidx > 0):\\n self.logger.info(\\\"Updated mapping to have {0} more entries\\\".format(nextidx-original_nextidx))\",\n \"def post_migrate_function(obj):\\n obj.a = obj.a + u\\\"-modified\\\"\\n return True\",\n \"def update_table(table_name):\\n for filename in table_name_to_funcs[table_name][\\\"filename\\\"]:\\n choose_file_to_get(table_name_to_funcs[table_name][\\\"file_type\\\"], filename)\\n\\n for process_func in table_name_to_funcs[table_name][\\\"process\\\"]:\\n process_func()\\n for to_sql_func in table_name_to_funcs[table_name][\\\"to_sql\\\"]:\\n to_sql_func(update=True)\",\n \"async def test_cached_previous_overwrites(self):\\n overwrite_json = (\\n '{\\\"send_messages\\\": true, \\\"add_reactions\\\": false, \\\"create_private_threads\\\": true, '\\n '\\\"create_public_threads\\\": false, \\\"send_messages_in_threads\\\": true}'\\n )\\n await self.cog._set_silence_overwrites(self.text_channel)\\n self.cog.previous_overwrites.set.assert_awaited_once_with(self.text_channel.id, overwrite_json)\",\n \"def create_copy_table(self):\\n tmp_sql_obj = deepcopy(self._new_table)\\n tmp_sql_obj.name = self.new_table_name\\n if self.rm_partition:\\n tmp_sql_obj.partition = self._old_table.partition\\n tmp_sql_obj.partition_config = self._old_table.partition_config\\n tmp_table_ddl = tmp_sql_obj.to_sql()\\n log.info(\\\"Creating copy table using: {}\\\".format(tmp_table_ddl))\\n self.execute_sql(tmp_table_ddl)\\n self.partitions[self.new_table_name] = self.fetch_partitions(\\n self.new_table_name\\n )\\n self.add_drop_table_entry(self.new_table_name)\\n\\n # Check whether the schema is consistent after execution to avoid\\n # any implicit conversion\\n if self.fail_for_implicit_conv:\\n obj_after = self.fetch_table_schema(self.new_table_name)\\n obj_after.name = self._new_table.name\\n # Ignore partition difference, since there will be no implicit\\n # conversion here\\n obj_after.partition = self._new_table.partition\\n obj_after.partition_config = self._new_table.partition_config\\n self.populate_charset_collation(obj_after)\\n if self.mysql_version.is_mysql8:\\n # Remove 'USING HASH' in keys on 8.0, when present in 5.6, as 8.0\\n # removes it by default\\n self.remove_using_hash_for_80()\\n if self.is_myrocks_table:\\n log.warning(\\n f\\\"Ignore BTREE indexes in table `{self._new_table.name}` on RocksDB\\\"\\n )\\n for idx in self._new_table.indexes:\\n if idx.using == \\\"BTREE\\\":\\n idx.using = None\\n if obj_after != self._new_table:\\n raise OSCError(\\n \\\"IMPLICIT_CONVERSION_DETECTED\\\",\\n {\\\"diff\\\": str(SchemaDiff(self._new_table, obj_after))},\\n )\",\n \"def update_table_in_file(table, source_file):\\n with open(source_file, 'r') as source, \\\\\\n tempfile.NamedTemporaryFile('w', delete=False) as temp:\\n source_lines = source.readlines()\\n\\n table_start = index_tag_in_lines(source_lines, tag='Table Start')\\n table_end = index_tag_in_lines(source_lines, tag='Table End')\\n print(f'Found table_start tag at line no: {table_start}')\\n print(f'Found table_end tag at line no: {table_end}')\\n assert table_end > table_start, 'Table End must be after Table Start'\\n\\n table_written = False\\n for line_no, line in enumerate(source_lines):\\n if line_no <= table_start or line_no >= table_end:\\n temp.write(line)\\n elif not table_written: # write table once\\n temp.writelines(table)\\n table_written = True\\n\\n backup_file = source_file.with_suffix('.md.bkp')\\n os.rename(source_file, backup_file)\\n print(f'Original file backed up at: {backup_file}')\\n\\n shutil.copy(temp.name, source_file)\",\n \"def overwrite_cmd(run, batch, source, lines, basename='xrb'):\\n for i, line in enumerate(lines):\\n if '\\\\n' not in line:\\n lines[i] += '\\\\n'\\n\\n filepath = grid_strings.cmd_filepath(run, batch, source=source, basename=basename)\\n print(f'Writing: {filepath}')\\n with open(filepath, 'w') as f:\\n f.writelines(lines)\",\n \"def update_policy(self):\\n self._sess.run(self._hard_copy_to_target_op);\",\n \"def copy():\\n copy2(per, per_old)\",\n \"def makeOverrides(self):\\n\\t\\tself.overridesWithValues = self.dataOverrides\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n cur.execute(query)\\n conn.commit()\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n cur.execute(query)\\n conn.commit()\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n cur.execute(query)\\n conn.commit()\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n cur.execute(query)\\n conn.commit()\",\n \"def sync_table_partitions(self) -> None:\\n log.info(\\\"== Stage 5.1: Check table partitions are up-to-date ==\\\")\\n\\n # we're using partitions in the ddl file, skip syncing anything\\n if not self.rm_partition:\\n return\\n # not a partitioned table, nothing to do\\n if not self.partitions:\\n return\\n\\n # only apply this logic to RANGE partitioning, as other types\\n # are usually static\\n partition_method = self.get_partition_method(\\n self._current_db, self.new_table_name\\n )\\n if partition_method != \\\"RANGE\\\":\\n return\\n\\n try:\\n new_tbl_parts = self.list_partition_names(self.new_table_name)\\n orig_tbl_parts = self.list_partition_names(self.table_name)\\n\\n parts_to_drop = set(new_tbl_parts) - set(orig_tbl_parts)\\n parts_to_add = set(orig_tbl_parts) - set(new_tbl_parts)\\n\\n # information schema literally has the string None for\\n # non-partitioned tables. Previous checks *should* prevent us\\n # from hitting this.\\n if \\\"None\\\" in parts_to_add or \\\"None\\\" in parts_to_drop:\\n log.warning(\\n \\\"MySQL claims either %s or %s are not partitioned\\\",\\n self.new_table_name,\\n self.table_name,\\n )\\n return\\n\\n if parts_to_drop:\\n log.info(\\n \\\"Partitions missing from source table \\\"\\n \\\"to drop from new table %s: %s\\\",\\n self.new_table_name,\\n \\\", \\\".join(parts_to_drop),\\n )\\n if parts_to_add:\\n log.info(\\n \\\"Partitions in source table to add to new table %s: %s\\\",\\n self.new_table_name,\\n \\\", \\\".join(parts_to_add),\\n )\\n self.apply_partition_differences(parts_to_drop, parts_to_add)\\n except Exception:\\n log.exception(\\n \\\"Unable to sync new table %s with orig table %s partitions\\\",\\n self.new_table_name,\\n self.table_name,\\n )\",\n \"def _bmaction(old, new):\\n if not old:\\n return b'export'\\n elif not new:\\n return b'delete'\\n return b'update'\",\n \"def write(self):\\n if not self._table: raise ValueError ( \\\"_table is Null\\\" )\\n if self._isnew:\\n for m in self._modified_values:\\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\\n \\n try:\\n rec = CFG.CX.insert ( CFG.DB.SCHEMA + \\\".\\\" + self._table.name,\\n self._modified_values )\\n #this will automatically re-read the data from the db, to take all changes\\n #done by triggers and default values into account.\\n self._objectid = rec['objectid']\\n\\n #print \\\"Record # {0} inserted into {1}.\\\".format(self._objectid, self._table.name)\\n self.raiseEvent ( \\\"record_added\\\", self )\\n \\n except pg.DatabaseError, e:\\n print \\\"Error inserting record.\\\"\\n raise Record.DataManipulationError ( \\\"Inserting a new record into '{0}'\\\".format(self._table.name),\\n str(self._modified_values),\\n e)\\n elif self._ismodified:\\n \\n for m in self._modified_values: \\n self._modified_values[m] = self._table[m].val_py2sql(self._modified_values[m])\\n \\n self._modified_values['objectid'] = self._objectid\\n del self.TextCache[self._objectid]\\n try:\\n rec = CFG.CX.update ( CFG.DB.SCHEMA + \\\".\\\" + self._table.name,\\n self._modified_values )\\n self.read() \\n self.raiseEvent ( \\\"record_saved\\\", self )\\n except pg.DatabaseError, e:\\n print \\\"Error updating record\\\"\\n raise Record.DataManipulationError ( \\\"Updating record {1} of '{0}'\\\".format(self._table.name, self._objectid),\\n str(self._modified_values),\\n e)\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n print('staging', query)\\n cur.execute(query)\\n conn.commit()\",\n \"def _batch_write(self):\\n if self.to_put:\\n db.put(self.to_put)\\n self.to_put = []\\n if self.to_delete:\\n db.delete(self.to_delete)\\n self.to_delete = []\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n try:\\n cur.execute(query)\\n conn.commit()\\n \\n except psycopg2.Error as e:\\n print(e)\",\n \"def test_setOverwrite(self):\\n fp = FilePath(self.mktemp())\\n fp.setContent(b\\\"I love contributing to Twisted!\\\")\\n protocol = self.makeConnectedDccFileReceive(fp.path, overwrite=True)\\n\\n self.allDataReceivedForProtocol(protocol, b\\\"Twisted rocks!\\\")\\n\\n self.assertEqual(fp.getContent(), b\\\"Twisted rocks!\\\")\",\n \"def need_checksum_for_changes(self):\\n # We don't need to run checksum for changes, if we don't want checksum\\n # at all\\n if not self.need_checksum():\\n return False\\n if self.is_full_table_dump:\\n log.warning(\\n \\\"We're adding new primary key to the table. Skip running \\\"\\n \\\"checksum for changes, because that's inefficient\\\"\\n )\\n return False\\n return True\",\n \"def overwrite(self, timestamp, write_data):\\n\\n if (self.data.dtype != write_data.dtype ):\\n logger.error(\\\"Conflicting data types for overwrite\\\")\\n raise SpatialDBError (\\\"Conflicting data types for overwrite\\\")\\n \\n self.data[timestamp,:] = overwriteDense_ctype(self.data[timestamp,:], write_data)\",\n \"def _copy_output(src: Graph, dst: Graph):\\n for n_src, n_dst in zip(src.nodes, dst.nodes):\\n if n_src.op == 'output':\\n n_dst.meta = n_src.meta\",\n \"async def test_preserved_other_overwrites_voice(self):\\n for overwrite_json in ('{\\\"connect\\\": true, \\\"speak\\\": true}', None):\\n with self.subTest(overwrite_json=overwrite_json):\\n self.cog.previous_overwrites.get.return_value = overwrite_json\\n\\n prev_overwrite_dict = dict(self.voice_overwrite)\\n await self.cog._unsilence(self.voice_channel)\\n new_overwrite_dict = dict(self.voice_overwrite)\\n\\n # Remove these keys because they were modified by the unsilence.\\n del prev_overwrite_dict[\\\"connect\\\"]\\n del prev_overwrite_dict[\\\"speak\\\"]\\n del new_overwrite_dict[\\\"connect\\\"]\\n del new_overwrite_dict[\\\"speak\\\"]\\n\\n self.assertDictEqual(prev_overwrite_dict, new_overwrite_dict)\",\n \"def backup_overrides(overrides, action='debug'):\\n backup_path = os.path.join(BACKUP_PATH, action)\\n if not os.path.exists(backup_path):\\n os.makedirs(backup_path)\\n field = 'user_overrides'\\n for chart in overrides:\\n name = chart['name']\\n if name not in oidc_charts:\\n LOG.warning(\\\"oidc-auth-apps: mismatch chart name '%s'\\\", name)\\n if chart[field]:\\n document = yaml.safe_load(chart[field])\\n if not document:\\n LOG.debug(\\\"oidc-auth-apps: %s empty document\\\", name)\\n continue\\n backup_f = '_'.join([name, field])\\n backup_f = '.'.join([backup_f, 'yaml'])\\n backup_f = os.path.join(backup_path, backup_f)\\n try:\\n with open(backup_f, 'w') as file:\\n yaml.dump(document, file, default_flow_style=False)\\n except IOError as e:\\n LOG.error(\\\"oidc-auth-apps: IOError: %s; file: %s\\\", e, backup_f)\\n return 1\\n LOG.info(\\\"oidc-auth-apps: user_overrides backed up to %s\\\", backup_path)\\n return 0\",\n \"def _undo_action(self):\\n pass\",\n \"def need_checksum(self):\\n if self.skip_checksum:\\n log.warning(\\\"Skip checksum because --skip-checksum is specified\\\")\\n return False\\n # There's no point running a checksum compare for selective dump\\n if self.where:\\n log.warning(\\\"Skip checksum because --where is given\\\")\\n return False\\n # If the collation of primary key column has been changed, then\\n # it's high possible that the checksum will mis-match, because\\n # the returning sequence after order by primary key may be vary\\n # for different collations\\n for pri_column in self._pk_for_filter:\\n old_column_tmp = [\\n col for col in self._old_table.column_list if col.name == pri_column\\n ]\\n if old_column_tmp:\\n old_column = old_column_tmp[0]\\n new_column_tmp = [\\n col for col in self._new_table.column_list if col.name == pri_column\\n ]\\n if new_column_tmp:\\n new_column = new_column_tmp[0]\\n if old_column and new_column:\\n if not is_equal(old_column.collate, new_column.collate):\\n log.warning(\\n \\\"Collation of primary key column {} has been \\\"\\n \\\"changed. Skip checksum \\\".format(old_column.name)\\n )\\n return False\\n # There's no way we can run checksum by chunk if the primary key cannot\\n # be covered by any index of the new schema\\n if not self.validate_post_alter_pk():\\n if self.skip_pk_coverage_check:\\n log.warning(\\n \\\"Skipping checksuming because there's no unique index \\\"\\n \\\"in new table schema can perfectly cover old primary key \\\"\\n \\\"combination for search\\\".format(old_column.name)\\n )\\n return False\\n else:\\n # Though we have enough coverage for primary key doesn't\\n # necessarily mean we can use it for checksum, it has to be an\\n # unique index as well. Skip checksum if there's no such index\\n if not self.find_coverage_index():\\n log.warning(\\n \\\"Skipping checksuming because there's no unique index \\\"\\n \\\"in new table schema can perfectly cover old primary key \\\"\\n \\\"combination for search\\\".format(old_column.name)\\n )\\n return False\\n return True\",\n \"def _maybe_copy_entry_to_image(instance):\\n if instance.compo.is_imagefile_copied:\\n name = str('th_' + os.path.basename(instance.entryfile.name))\\n instance.imagefile_original.save(name, instance.entryfile)\",\n \"def update_model_output(self):\\n warnings.warn(\\\"Please ensure that the column names of the new file accurately corresponds to the relevant column names in the exisitng file\\\")\\n column_names_new = self.new_data.head()\\n column_names_old = self.existing_data.head()\\n for column_name in column_names_new:\\n if column_name in column_names_old:\\n self.existing_data[column_name] = self.new_data[column_name]\\n \\n self.existing_data.to_csv(filename_main, index = False)\",\n \"def overwrite_original_file(self):\\n return self.__overwrite_original_file\",\n \"def undo():\",\n \"def do_before_dump(self):\\n self.checksummer.prepare_checksums()\",\n \"def scheduleTableAsyncCopy(self, hiveFilterDB, hiveFilterTable, copyDestination):\\n\\t\\tlogging.debug(\\\"Executing copy_operations.scheduleTableAsyncCopy()\\\")\\n\\n\\t\\tif self.checkDBImportInstance(instance = copyDestination) == False:\\n\\t\\t\\tlogging.error(\\\"The specified remote DBImport instance does not exist.\\\")\\n\\t\\t\\tself.remove_temporary_files()\\n\\t\\t\\tsys.exit(1)\\n\\n\\t\\thiveFilterDB = hiveFilterDB.replace('*', '%').strip()\\n\\t\\thiveFilterTable = hiveFilterTable.replace('*', '%').strip()\\n\\n\\t\\tlocalSession = self.configDBSession()\\n\\t\\timportTables = aliased(configSchema.importTables)\\n\\t\\tcopyASyncStatus = aliased(configSchema.copyASyncStatus)\\n\\n\\t\\t# Check if there are any tabled in this DAG that is marked for copy against the specified destination\\n\\t\\tresult = (localSession.query(\\n\\t\\t\\t\\tcopyASyncStatus\\n\\t\\t\\t)\\n\\t\\t\\t.filter(copyASyncStatus.hive_db.like(hiveFilterDB))\\n\\t\\t\\t.filter(copyASyncStatus.hive_table.like(hiveFilterTable))\\n\\t\\t\\t.filter(copyASyncStatus.destination == copyDestination)\\n\\t\\t\\t.count())\\n\\n\\t\\tif result > 0:\\n\\t\\t\\tlogging.error(\\\"There is already tables that matches this DAG's filter that is scheduled for copy against\\\")\\n\\t\\t\\tlogging.error(\\\"the specified destination. This operation cant continue until all the current copies are completed\\\")\\n\\t\\t\\tself.remove_temporary_files()\\n\\t\\t\\tsys.exit(1)\\n\\n\\t\\t# Calculate the source and target HDFS directories\\n\\t\\tdbimportInstances = aliased(configSchema.dbimportInstances)\\n\\t\\n\\t\\tsourceHDFSaddress = self.common_operations.hdfs_address \\n\\t\\tsourceHDFSbasedir = self.common_operations.hdfs_basedir \\n\\n\\t\\trow = (localSession.query(\\n\\t\\t\\t\\tdbimportInstances.hdfs_address,\\n\\t\\t\\t\\tdbimportInstances.hdfs_basedir\\n\\t\\t\\t)\\n\\t\\t\\t.filter(dbimportInstances.name == copyDestination)\\n\\t\\t\\t.one())\\n\\t\\t\\n\\t\\ttargetHDFSaddress = row[0]\\n\\t\\ttargetHDFSbasedir = row[1]\\n\\n\\t\\tlogging.debug(\\\"sourceHDFSaddress: %s\\\"%(sourceHDFSaddress))\\n\\t\\tlogging.debug(\\\"sourceHDFSbasedir: %s\\\"%(sourceHDFSbasedir))\\n\\t\\tlogging.debug(\\\"targetHDFSaddress: %s\\\"%(targetHDFSaddress))\\n\\t\\tlogging.debug(\\\"targetHDFSbasedir: %s\\\"%(targetHDFSbasedir))\\n\\n\\t\\t# Fetch a list of tables that match the database and table filter\\n\\t\\tresult = pd.DataFrame(localSession.query(\\n\\t\\t\\t\\timportTables.table_id,\\n\\t\\t\\t\\timportTables.hive_db,\\n\\t\\t\\t\\timportTables.hive_table,\\n\\t\\t\\t\\timportTables.dbalias\\n\\t\\t\\t)\\n\\t\\t\\t.filter(importTables.hive_db.like(hiveFilterDB))\\n\\t\\t\\t.filter(importTables.hive_table.like(hiveFilterTable))\\n\\t\\t\\t)\\n\\n\\t\\tfor index, row in result.iterrows():\\n\\t\\t\\tlogging.info(\\\"Schedule asynchronous copy for %s.%s\\\"%(row['hive_db'], row['hive_table']))\\n\\t\\t\\tself.import_config.Hive_DB = row['hive_db']\\n\\t\\t\\tself.import_config.Hive_Table = row['hive_table']\\n\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.import_config.getImportConfig()\\n\\t\\t\\texcept invalidConfiguration as errMsg:\\n\\t\\t\\t\\tlogging.error(errMsg)\\n\\t\\t\\t\\tself.import_config.remove_temporary_files()\\n\\t\\t\\t\\tsys.exit(1)\\n\\n\\t\\t\\tlogging.debug(\\\"table_id: %s\\\"%(self.import_config.table_id))\\n\\t\\t\\tlogging.debug(\\\"import_is_incremental: %s\\\"%(self.import_config.import_is_incremental))\\n\\n\\t\\t\\tif self.import_config.import_is_incremental == True and includeIncrImports == False:\\n\\t\\t\\t\\tlogging.warning(\\\"Asynchronous copy for incremental table %s.%s skipped\\\"%(row['hive_db'], row['hive_table']))\\n\\t\\t\\t\\tcontinue\\n\\n\\t\\t\\tsourceHDFSdir = (sourceHDFSbasedir + \\\"/\\\"+ row['hive_db'] + \\\"/\\\" + row['hive_table']).replace('$', '').replace(' ', '')\\n\\t\\t\\ttargetHDFSdir = (targetHDFSbasedir + \\\"/\\\"+ row['hive_db'] + \\\"/\\\" + row['hive_table']).replace('$', '').replace(' ', '')\\n\\t\\t\\tlogging.debug(\\\"sourceHDFSdir: %s\\\"%(sourceHDFSdir))\\n\\t\\t\\tlogging.debug(\\\"targetHDFSdir: %s\\\"%(targetHDFSdir))\\n\\n\\t\\t\\tresult = (localSession.query(\\n\\t\\t\\t\\t\\tcopyASyncStatus\\n\\t\\t\\t\\t)\\n\\t\\t\\t\\t.filter(copyASyncStatus.table_id == row['table_id'])\\n\\t\\t\\t\\t.filter(copyASyncStatus.destination == copyDestination)\\n\\t\\t\\t\\t.count())\\n\\n\\t\\t\\tif result == 0:\\n\\t\\t\\t\\tnewcopyASyncStatus = configSchema.copyASyncStatus(\\n\\t\\t\\t\\t\\ttable_id = row['table_id'],\\n\\t\\t\\t\\t\\thive_db = row['hive_db'],\\n\\t\\t\\t\\t\\thive_table = row['hive_table'],\\n\\t\\t\\t\\t\\tdestination = copyDestination,\\n\\t\\t\\t\\t\\thdfs_source_path = \\\"%s%s\\\"%(sourceHDFSaddress, sourceHDFSdir),\\n\\t\\t\\t\\t\\thdfs_target_path = \\\"%s%s\\\"%(targetHDFSaddress, targetHDFSdir),\\n\\t\\t\\t\\t\\tcopy_status = 0)\\n\\t\\t\\t\\tlocalSession.add(newcopyASyncStatus)\\n\\t\\t\\t\\tlocalSession.commit()\\n\\n\\t\\tlocalSession.close()\\n\\n\\n\\t\\tlogging.debug(\\\"Executing copy_operations.scheduleTableAsyncCopy() - Finished\\\")\",\n \"def copy_and_replace_keys(self, table, key_callback):\\n client = self.bq_client\\n t = client.get_table(table)\\n\\n cross_joins = []\\n\\n # begin query generation process\\n q = f'CREATE OR REPLACE TABLE `{table}` AS (\\\\nSELECT \\\\n'\\n for field in t.schema:\\n q += process_field(field, None, key_callback)\\n cross_joins.extend(process_cross_joins(field, \\\"copy_table\\\"))\\n q = q.strip(\\\",\\\\n\\\")\\n q += f\\\"\\\\nFROM\\\\n `{table}` copy_table\\\"\\n\\n for cross_join in cross_joins:\\n q += cross_join\\n q += \\\")\\\"\\n\\n return q\",\n \"def swap_tables(self):\\n if self.stop_before_swap:\\n return True\\n log.info(\\\"== Stage 6: Swap table ==\\\")\\n self.stop_slave_sql()\\n self.execute_sql(sql.set_session_variable(\\\"autocommit\\\"), (0,))\\n self.start_transaction()\\n stage_start_time = time.time()\\n self.lock_tables((self.new_table_name, self.table_name, self.delta_table_name))\\n log.info(\\\"Final round of replay before swap table\\\")\\n self.checksum_required_for_replay = False\\n self.replay_changes(single_trx=True, holding_locks=True)\\n # We will not run delta checksum here, because there will be an error\\n # like this, if we run a nested query using `NOT EXISTS`:\\n # SQL execution error: [1100] Table 't' was not locked with LOCK TABLES\\n if self.mysql_version.is_mysql8:\\n # mysql 8.0 supports atomic rename inside WRITE locks\\n self.execute_sql(\\n sql.rename_all_tables(\\n orig_name=self.table_name,\\n old_name=self.renamed_table_name,\\n new_name=self.new_table_name,\\n )\\n )\\n self.table_swapped = True\\n self.add_drop_table_entry(self.renamed_table_name)\\n log.info(\\n \\\"Renamed {} TO {}, {} TO {}\\\".format(\\n self.table_name,\\n self.renamed_table_name,\\n self.new_table_name,\\n self.table_name,\\n )\\n )\\n else:\\n self.execute_sql(sql.rename_table(self.table_name, self.renamed_table_name))\\n log.info(\\n \\\"Renamed {} TO {}\\\".format(self.table_name, self.renamed_table_name)\\n )\\n self.table_swapped = True\\n self.add_drop_table_entry(self.renamed_table_name)\\n self.execute_sql(sql.rename_table(self.new_table_name, self.table_name))\\n log.info(\\\"Renamed {} TO {}\\\".format(self.new_table_name, self.table_name))\\n\\n log.info(\\\"Table has successfully swapped, new schema takes effect now\\\")\\n self._cleanup_payload.remove_drop_table_entry(\\n self._current_db, self.new_table_name\\n )\\n self.commit()\\n self.unlock_tables()\\n self.stats[\\\"time_in_lock\\\"] = self.stats.setdefault(\\\"time_in_lock\\\", 0) + (\\n time.time() - stage_start_time\\n )\\n self.execute_sql(sql.set_session_variable(\\\"autocommit\\\"), (1,))\\n self.start_slave_sql()\\n self.stats[\\\"swap_table_progress\\\"] = \\\"Swap table finishes\\\"\",\n \"def load_staging_tables(cur, conn):\\n for query in copy_table_queries:\\n try:\\n cur.execute(query)\\n conn.commit()\\n except Exception as e:\\n print(e)\",\n \"def reset_data():\\n shutil.copy2(\\n 'data/one_producer_many_consumers.ORIG.json',\\n 'data/one_producer_many_consumers.json'\\n )\",\n \"def copy_table_after(table, paragraph):\\n\\n\\ttbl, p = table._tbl, paragraph._p\\n\\tnew_tbl = deepcopy(tbl)\\n\\tp.addnext(new_tbl)\",\n \"def handle_copy_rows(request):\\n\\n request_body_json = json.loads(request.body)\\n username = request_body_json['username']\\n print(username)\\n overwrite = request_body_json['overwrite']\\n if overwrite == 'true':\\n overwrite = True\\n elif overwrite == 'false':\\n overwrite = False\\n\\n usecases = UseCase.objects.all()\\n uses = []\\n json_resp = {'message':'Ok'}\\n for el in usecases:\\n if el.name not in uses:\\n uses.append(el.name)\\n if username is not None:\\n try:\\n for el in uses:\\n copy_rows(el, username,request.session['username'],overwrite)\\n\\n except Exception as e:\\n json_resp = {'error':'error'}\\n return JsonResponse(json_resp,status=500)\\n else:\\n return JsonResponse(json_resp)\",\n \"def copy_files(self, new_base_dir='.', overwrite=False,\\n file_type='any', mode='copy', **kwargs ):\\n #== retrieve query results\\n file_list = self.bids_layout.get(**kwargs)\\n #== select for reg/no-reg\\n if file_type == 'reg':\\n file_list = [file.filename for file in file_list if hasattr(file, 'registration')]\\n elif file_type == 'noreg':\\n file_list = [file.filename for file in file_list if (not hasattr(file, 'registration'))]\\n else:\\n file_list = [file.filename for file in file_list]\\n\\n if not file_type=='noreg':\\n print(\\\"=== WARNING: directory structure for registered files is not handled correctly -- verify results!\\\")\\n\\n #== generate new paths\\n for old_path in file_list:\\n new_path_rel = self.bids_layout.build_path(old_path, self.bids_layout.path_patterns)\\n new_path_abs = os.path.join(new_base_dir, new_path_rel)\\n gt.ensure_dir_exists(new_path_abs)\\n if mode=='copy':\\n print(\\\"Preparing to copy '%s' to '%s'\\\"%(old_path, new_path_abs))\\n elif mode=='move':\\n print(\\\"Preparing to move '%s' to '%s'\\\" % (old_path, new_path_abs))\\n if os.path.exists(new_path_abs):\\n if overwrite:\\n os.remove(new_path_abs)\\n shutil.copy(old_path, new_path_abs)\\n else:\\n print(\\\"File '%s' already exists ... skipping.\\\"%(new_path_abs))\\n else:\\n shutil.copy(old_path, new_path_abs)\\n if mode=='move':\\n os.remove(old_path)\\n try:\\n os.rmdir(old_path)\\n except:\\n pass\\n\\n if not file_type=='noreg':\\n print(\\\"=== WARNING: directory structure for registered files is not handled correctly -- verify results!\\\")\",\n \"def merge_both_tables():\\n old = Table.read('data/data_table_cartesian_including_tims_stars_with_bg_ols_and_component_overlaps.fits')\\n wanted = Table.read('data/scocen_candidates_300k_only_spatial_cut.fits')\\n additional = Table.read('data/scocen_candidates_300k_only_spatial_cut_200k_to_determine_bg_ols.fits')\\n\\n d_old = dict(zip(old['source_id'], old['background_log_overlap']))\\n d_add = dict(zip(additional['source_id'], additional['background_log_overlap']))\\n d_old.update(d_add)\\n dct = d_old\\n\\n ln_bg_ols = [dct[source_id] for source_id in wanted['source_id']]\\n print\\n len(ln_bg_ols), len(wanted)\\n\\n wanted['background_log_overlap'] = ln_bg_ols\\n print\\n wanted\\n\\n wanted.write('data/scocen_candidates_300k_only_spatial_cut.fits', overwrite=True, format='fits')\",\n \"def post_combine(self, target):\\n target_extra_files = self.target_extra_files\\n if target_extra_files:\\n if self.disable_cleanup:\\n self.stderr.write(\\\"Cleanup operations disabled by user.\\\\n\\\")\\n else:\\n self.stderr.write(\\\"Found extra files not part of source tree(s): \\\"\\n f\\\"{len(target_extra_files)} files.\\\\n\\\")\\n\\n keep_existing = create_filtered_list(\\\"splunk\\\", default=False)\\n # splglob_simple: Either full paths, or simple file-only match\\n keep_existing.feedall(self.keep_existing, filter=splglob_simple)\\n for dest_fn in target_extra_files:\\n if keep_existing.match_path(dest_fn):\\n self.stderr.write(f\\\"Keep existing file {dest_fn}\\\\n\\\")\\n elif self.disable_cleanup:\\n self.stderr.write(f\\\"Skip cleanup of unwanted file {dest_fn}\\\\n\\\")\\n else:\\n self.stderr.write(f\\\"Remove unwanted file {dest_fn}\\\\n\\\")\\n os.unlink(os.path.join(target, dest_fn))\",\n \"def copymode(src, dest):\\n import shutil\\n\\n shutil.copymode(src, dest)\",\n \"def copyBooks(self):\\n skipMods = set(('Morrowind.esm',self.fileInfo.name))\\n for id,(record,modName) in (self.srcBooks.items() + self.altBooks.items()):\\n if modName not in skipMods:\\n self.setRecord(copy.copy(record))\",\n \"def update(self, mode=\\\"all\\\"):\\n\\n self._check_mode(mode)\\n\\n mode = [\\\"prod\\\", \\\"staging\\\"] if mode == \\\"all\\\" else [mode]\\n for m in mode:\\n\\n try:\\n table = self._get_table_obj(m)\\n except google.api_core.exceptions.NotFound:\\n continue\\n\\n # if m == \\\"staging\\\":\\n\\n table.description = self._render_template(\\n Path(\\\"table/table_description.txt\\\"), self.table_config\\n )\\n\\n # save table description\\n with open(\\n self.metadata_path\\n / self.dataset_id\\n / self.table_id\\n / \\\"table_description.txt\\\",\\n \\\"w\\\",\\n encoding=\\\"utf-8\\\",\\n ) as f:\\n f.write(table.description)\\n\\n # when mode is staging the table schema already exists\\n table.schema = self._load_schema(m)\\n fields = [\\\"description\\\", \\\"schema\\\"] if m == \\\"prod\\\" else [\\\"description\\\"]\\n self.client[f\\\"bigquery_{m}\\\"].update_table(table, fields=fields)\\n\\n logger.success(\\n \\\" {object} {object_id} was {action}!\\\",\\n object_id=self.table_id,\\n object=\\\"Table\\\",\\n action=\\\"updated\\\",\\n )\",\n \"def testOnOverwrite(self, widget):\\n spy_signal = QtSignalSpy(widget, widget.modelModified)\\n\\n # check the default\\n assert not widget.chkOverwrite.isChecked()\\n\\n # Change the state\\n widget.chkOverwrite.setChecked(True)\\n\\n # Check the signal\\n assert spy_signal.count() == 1\\n\\n # model dict updated\\n assert widget.model['overwrite']\",\n \"async def test_preserved_other_overwrites_text(self):\\n for overwrite_json in ('{\\\"send_messages\\\": true, \\\"add_reactions\\\": null}', None):\\n with self.subTest(overwrite_json=overwrite_json):\\n self.cog.previous_overwrites.get.return_value = overwrite_json\\n\\n prev_overwrite_dict = dict(self.text_overwrite)\\n await self.cog._unsilence(self.text_channel)\\n new_overwrite_dict = dict(self.text_overwrite)\\n\\n # Remove these keys because they were modified by the unsilence.\\n del prev_overwrite_dict[\\\"send_messages\\\"]\\n del prev_overwrite_dict[\\\"add_reactions\\\"]\\n del new_overwrite_dict[\\\"send_messages\\\"]\\n del new_overwrite_dict[\\\"add_reactions\\\"]\\n\\n self.assertDictEqual(prev_overwrite_dict, new_overwrite_dict)\",\n \"def _copy_all(entry_list: List[Path], target_dir: Path, on_duplicate: str):\\n for entry in entry_list:\\n target_entry = target_dir / entry.name\\n if not target_entry.exists() or on_duplicate == 'overwrite':\\n if entry.is_file():\\n shutil.copy(entry, target_entry, follow_symlinks=False)\\n else:\\n shutil.copytree(entry, target_entry, symlinks=True)\\n elif on_duplicate == 'exception':\\n raise ValueError(f\\\"'{target_entry}' already exists (src {entry})\\\")\\n else: # ignore\\n continue\",\n \"def restore_copy_tbl(orig_tblname):\\n dd = mg.DATADETS_OBJ\\n dd.con.commit()\\n getdata.force_sofa_tbls_refresh(sofa_default_db_cur=dd.cur)\\n SQL_rename_tbl = ('ALTER TABLE '\\n f'{getdata.tblname_qtr(mg.DBE_SQLITE, mg.TMP_TBLNAME2)} RENAME TO '\\n f'{getdata.tblname_qtr(mg.DBE_SQLITE, orig_tblname)}')\\n dd.cur.execute(SQL_rename_tbl)\",\n \"def update_tmp_table_location_changes(file_type, database_columns, unique_identifier, fiscal_year):\\n le_loc_columns_distinct = \\\" OR \\\".join(\\n [\\n \\\"website.{column} IS DISTINCT FROM broker.{column}\\\".format(column=column)\\n for column in database_columns\\n if column[:12] == \\\"legal_entity\\\"\\n ]\\n )\\n\\n pop_loc_columns_distinct = \\\" OR \\\".join(\\n [\\n \\\"website.{column} IS DISTINCT FROM broker.{column}\\\".format(column=column)\\n for column in database_columns\\n if column[:13] == \\\"place_of_perf\\\"\\n ]\\n )\\n\\n sql_statement = \\\"\\\"\\\"\\n -- Include columns to determine whether we need a place of performance change or recipient location\\n ALTER TABLE {file_type}_transactions_to_update_{fiscal_year}\\n ADD COLUMN place_of_performance_change boolean, add COLUMN recipient_change boolean;\\n\\n UPDATE {file_type}_transactions_to_update_{fiscal_year} broker\\n SET\\n recipient_change = (\\n CASE WHEN\\n {le_loc_columns_distinct}\\n THEN TRUE ELSE FALSE END\\n ),\\n place_of_performance_change = (\\n CASE WHEN\\n {pop_loc_columns_distinct}\\n THEN TRUE ELSE FALSE END\\n )\\n FROM transaction_{file_type} website\\n WHERE broker.{unique_identifier} = website.{unique_identifier};\\n\\n\\n -- Delete rows where there is no transaction in the table\\n DELETE FROM {file_type}_transactions_to_update_{fiscal_year}\\n WHERE place_of_performance_change IS NULL\\n AND recipient_change IS NULL;\\n\\n -- Adding index to table to improve speed on update\\n CREATE INDEX {file_type}_le_loc_idx ON {file_type}_transactions_to_update_{fiscal_year}(recipient_change);\\n CREATE INDEX {file_type}_pop_idx ON\\n {file_type}_transactions_to_update_{fiscal_year}(place_of_performance_change);\\n ANALYZE {file_type}_transactions_to_update_{fiscal_year};\\n \\\"\\\"\\\".format(\\n file_type=file_type,\\n unique_identifier=unique_identifier,\\n fiscal_year=fiscal_year,\\n le_loc_columns_distinct=le_loc_columns_distinct,\\n pop_loc_columns_distinct=pop_loc_columns_distinct,\\n )\\n return sql_statement\",\n \"def _copy_chunk(self, last_pk):\\n self.execute(self.commands.copy_chunk(\\n self.name,\\n self._join_cols(self.intersection.dest_columns),\\n self._qualify(self.source.name, self.intersection.origin_columns),\\n self.source.name,\\n self.primary_key_column,\\n last_pk,\\n self.chunk_size\\n ))\\n self.commit()\",\n \"def flushUndo(*args, **kwargs)->None:\\n pass\",\n \"def touch(self, connection=None):\\n self.create_marker_table()\\n\\n if connection is None:\\n connection = self.connect()\\n connection.autocommit = True # if connection created here, we commit it here\\n\\n connection.cursor().execute(\\n \\\"\\\"\\\"INSERT INTO {marker_table} (update_id, target_table)\\n VALUES (%s, %s)\\n ON DUPLICATE KEY UPDATE\\n update_id = VALUES(update_id)\\n \\\"\\\"\\\".format(marker_table=self.marker_table),\\n (self.update_id, self.table)\\n )\\n # make sure update is properly marked\\n assert self.exists(connection)\",\n \"def _do_action_tables_create(self):\\n\\n schema_shell = os.path.join(self.bento_home, \\\"schema-shell\\\", \\\"bin\\\", \\\"kiji-schema-shell\\\")\\n assert os.path.isfile(schema_shell), schema_shell\\n\\n # Delete the table first!\\n cmd = (\\n \\\"kiji delete --target={kiji_uri} --interactive=false; \\\" +\\n \\\"kiji install --kiji={kiji_uri}\\\" ).format(kiji_uri=self.kiji_uri)\\n self._run_kiji_job(cmd)\\n\\n for ddl in self.ddls:\\n ddl_full_path = os.path.join(self.movie_advisor_home, ddl)\\n assert os.path.isfile(ddl_full_path)\\n cmd = \\\"{schema_shell} --kiji={kiji_uri} --file={ddl_full_path}\\\".format(\\n schema_shell=schema_shell,\\n kiji_uri=self.kiji_uri,\\n ddl_full_path=ddl_full_path)\\n self._run_kiji_job(cmd)\",\n \"def process(self):\\n try:\\n # self.alter_columns()\\n self.collect_drop_fk()\\n self.update_table()\\n self.create_tables()\\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\\n return True\\n except Exception as err:\\n logger.error(\\\"create_tables [error] -> %s\\\" % err)\",\n \"def pre_modify(self):\\n return 0\",\n \"def test_base_replica_repair_with_contention(self):\\n self._base_replica_repair_test(fail_mv_lock=True)\",\n \"def write_merged(self, content = '', table=''):\\n\\n if not os.path.isdir(self.out_dir):\\n Path(self.out_dir).mkdir(parents=True, exist_ok=True) \\n out_name = self.out_dir + '/' + self.station + '_CEUAS_merged_v0.nc' \\n\\n '''\\n if os.path.isfile('dic_obstab_attributes.npy'):\\n attrs_dic = np.load('dic_obstab_attributes.npy' , allow_pickle = True).item()\\n else:\\n attrs_dic = {}\\n '''\\n attrs_dic = {}\\n\\n \\\"\\\"\\\" Retrieving the attributes \\\"\\\"\\\"\\n if content in ['observations_table','header_table','era5fb', 'station_configuration']:\\n for var in table.keys():\\n if var == 'comments':\\n continue \\n\\n attrs_dic[var] = {}\\n try:\\n attrs_dic[var]['description'] = bytes( self.dic_type_attributes[content][var]['description'] , 'utf-8' )\\n except:\\n attrs_dic[var]['description'] = bytes( 'missing' , 'utf-8' )\\n #print(' FFF FAILING WITH DESCRIPTION: ', var , ' ' , self.dic_type_attributes[content][var]['description']) # FFF CHECK WHY SOME ARE FAILING\\n\\n try:\\n attrs_dic[var]['external_table'] = bytes( self.dic_type_attributes[content][var]['external_table'] , 'utf-8' )\\n except:\\n attrs_dic[var]['external_table'] = bytes( 'missing' , 'utf-8' )\\n #print(' FFF FAILING WITH EXTERNAL TABLE : ', var ) # FFF CHECK WHY SOME ARE FAILING \\n\\n\\n if content == 'recordindex': # writing the recordindex, recordtimestamp, dateindex\\n #logging.info('Writing the merged record indices to the netCDF output ')\\n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a')\\n\\n elif content == 'cdm_tables':\\n for k in data['cdm_tables'].keys():\\n table = data['cdm_tables'][k]\\n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a', group = k)\\n #logging.info('Writing the cdm table %s to the netCDF output ', k)\\n \\n elif content == 'source_configuration': \\n table.to_netcdf(out_name, format='netCDF4', engine='h5netcdf', mode='a', group = content)\\n #logging.info('Writing the source_configuration table to the netCDF output ')\\n\\n elif content == 'station_configuration':\\n for k in table.keys(): \\n if k == 'station_name':\\n print(0)\\n var_type = self.dic_type_attributes[content][k]['type']\\n\\n ''' trying to convert the variable types to the correct types stored as attribute, read from the numpy dic file '''\\n if type(table[k][0]) != var_type:\\n try:\\n table[k] = table[k].astype( var_type ) \\n print('Done station_conf' , k )\\n except:\\n if k == 'secondary_id':\\n table[k] = table[k].astype( bytes ) \\n\\n print ('FAILED converting column ' , k, ' type ', type(table[k][0]) , ' to type ', var_type )\\n\\n dic = {k:table[k]} \\n write_dict_h5(out_name, dic , content, self.encodings[content], var_selection=[], mode='a', attrs = attrs_dic )\\n \\n \\n # Writing the observations_table, header_table, era5fb \\n elif content in ['observations_table', 'era5fb', 'header_table']: \\n\\n shape = ''\\n for k in table.keys(): \\n if k == 'index' or k == 'hdrlen' or 'string' in k :\\n continue\\n if k == 'station_name':\\n print(0)\\n \\n var_type = self.dic_type_attributes[content][k]['type']\\n\\n ''' trying to convert the variable types to the correct types stored as attribute, read from the numpy dic file '''\\n if type(table[k][0]) != var_type:\\n\\n if k == 'hdrlen': \\n continue\\n try:\\n #table[k] = table[k].astype( bytes ) \\n table[k] = table[k].astype( var_type ) \\n \\n except:\\n print ('FAILED converting column ' , k, ' type ', type(table[k][0]) , ' to type ', var_type )\\n\\n #print('*** Writing the table ', content, ' variable ', k)\\n #if k == 'duplicates':\\n # table[k] = table[k].astype( bytes ) \\n \\n \\n dic = {k:table[k]} # making a 1 colum dictionary\\n shape = table[k].shape\\n #print('SHAPE IS FFF ', table[k].shape )\\n write_dict_h5(out_name, dic , content, self.encodings[content], var_selection=[], mode='a', attrs = attrs_dic )\\n\\n if content == 'observations_table' and not self.obstab_nans_filled :\\n missing_cdm_var = [ v for v in self.dic_type_attributes[content].keys() if v not in self.observations_table_vars] # variables to be filled with nans \\n for k in missing_cdm_var:\\n if k not in ['advanced_assimilation_feedback']:\\n var_type = self.dic_type_attributes[content][k]['type']\\n if var_type == np.int32 :\\n nan = np.int32(-2147483648)\\n else:\\n nan = np.float32(np.nan) \\n logging.debug('Adding missing cdm colum with empty values: %s ' , k )\\n dic={k:np.empty(shape,dtype=np.dtype(nan))}\\n dic[k].fill(nan)\\n write_dict_h5(out_name, dic, 'observations_table', self.encodings['observations_table'], var_selection=[], mode='a', attrs = attrs_dic ) ### TO DO\\n self.obstab_nans_filled = True\\n\\n elif content == 'observations_table' and self.obstab_nans_filled:\\n return\",\n \"def before_update(mapper, conn, target):\\n\\n assert bool(target.ref), \\\"File.ref can't be null (before_update)\\\"\",\n \"def begin_not_undoable_action(self):\\n self.not_undoable_action = True\",\n \"def modify_tbl(self):\\n debug = False\\n dd = mg.DATADETS_OBJ\\n orig_tblname = dd.tbl\\n ## other (i.e. not the sofa_id) field details\\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\\n if debug:\\n print('oth_name_types to feed into '\\n f'make_strict_typing_tbl {oth_name_types}')\\n try: ## 1 way or other must do strict_cleanup()\\n make_strict_typing_tbl(\\n orig_tblname, oth_name_types, self.settings_data)\\n except sqlite.IntegrityError as e: #@UndefinedVariable\\n if debug: print(b.ue(e))\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise FldMismatchException\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise Exception('Problem making strictly-typed table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n copy_orig_tbl(orig_tblname)\\n wipe_tbl(orig_tblname)\\n final_name = self.tblname_lst[0] ## may have been renamed\\n try:\\n make_redesigned_tbl(final_name, oth_name_types)\\n strict_cleanup(restore_tblname=final_name)\\n dd.set_tbl(tbl=final_name)\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\\n dd.set_tbl(tbl=orig_tblname)\\n raise Exception('Problem making redesigned table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n wipe_tbl(mg.TMP_TBLNAME2)\",\n \"def _copy(self):\\n for d in self._current_chunk:\\n self.out.write(d)\",\n \"def test_backup_merge_with_unmerged(self):\\n gen = BlobGenerator(\\\"ent-backup\\\", \\\"ent-backup-\\\", self.value_size, end=self.num_items)\\n self._load_all_buckets(self.master, gen, \\\"create\\\", 0)\\n self.backup_create()\\n self._take_n_backups(n=2)\\n self.backupset.start = 1\\n self.backupset.end = 2\\n self.log.info(\\\"Merging existing incremental backups\\\")\\n status, output, message = self.backup_merge()\\n if not status:\\n self.fail(message)\\n self.log.info(\\\"Taking more backups\\\")\\n self._take_n_backups(n=2)\\n self.backupset.start = 1\\n self.backupset.end = 3\\n self.log.info(\\\"Merging new backups into already merged backup\\\")\\n status, output, message = self.backup_merge()\\n if not status:\\n self.fail(message)\\n self.log.info(\\\"Successfully merged new backups with already merged backup\\\")\",\n \"def on_ok(self, _event):\\n dd = mg.DATADETS_OBJ\\n if self.read_only:\\n self.exiting = True\\n self.Destroy()\\n else:\\n ## NB any changes defined in recode are already done\\n new_tbl, tblname_changed, data_changed = self.get_change_status()\\n if new_tbl or tblname_changed or data_changed:\\n try:\\n if not new_tbl:\\n orig_tblname = self.tblname_lst[0]\\n dd.set_tbl(tbl=orig_tblname)\\n else:\\n dd.set_tbl(tbl=None)\\n self.make_changes()\\n self.exiting = True\\n self.Destroy()\\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\\n except FldMismatchException:\\n wx.MessageBox(\\n _('Unable to modify table. Some data does not match the'\\n ' column type. Please edit and try again.'))\\n return\\n except Exception as e:\\n wx.MessageBox(\\n _(\\\"Unable to modify table.\\\\nCaused by error: %s\\\")\\n % b.ue(e))\\n return\\n elif self.changes_made: ## not in tableconf. Must've been in recoding\\n self.exiting = True\\n self.Destroy()\\n self.SetReturnCode(mg.RET_CHANGED_DESIGN)\\n return\\n else:\\n wx.MessageBox(_('No changes to update.'))\\n return\",\n \"def transfer_missing_elements(target_dict, source_dict, transfer_type=None):\\r\\n\\r\\n if transfer_type is None:\\r\\n transfer_type = source_dict.get(\\\"_transfer_type_\\\", \\\"recursive\\\")\\r\\n\\r\\n for key_, val_ in source_dict.items():\\r\\n # print(key_,isinstance(val_, dict), val_)\\r\\n if isinstance(val_, dict):\\r\\n if key_ not in target_dict:\\r\\n target_dict[key_] = EasyDict()\\r\\n if transfer_type is None:\\r\\n transfer_type = val_.get(\\\"_transfer_type_\\\", \\\"recursive\\\")\\r\\n # print(\\\"*********** \\\",transfer_type)\\r\\n\\r\\n if transfer_type == \\\"recursive\\\":\\r\\n transfer_missing_elements(target_dict[key_], val_, transfer_type)\\r\\n elif transfer_type == \\\"update\\\":\\r\\n target_dict[key_].update(val_)\\r\\n elif transfer_type == \\\"overwrite\\\":\\r\\n target_dict[key_] = copy.deepcopy(source_dict[key_])\\r\\n # target_dict[key_] = val_\\r\\n\\r\\n elif key_ not in target_dict:\\r\\n target_dict[key_] = copy.deepcopy(source_dict[key_])\\r\\n # target_dict[key_] = val_\\r\\n # else :\\r\\n # target_dict[key_] = val_\\r\\n # target_dict[key_] = copy.deepcopy(source_dict[key_])\\r\\n\\r\\n\\r\\n # if isinstance(source_dict[key_],list) and isinstance(source_dict[key_][0],dict):\\r\\n # if key_ not in target_dict:\\r\\n # target_dict[key_] = []\\r\\n # for src_ in source_dict[key_]:\\r\\n # if not isinstance(src_,dict):\\r\\n # continue\\r\\n # match = False\\r\\n # for tar_ in target_dict[key_]:\\r\\n # # TODO make a list of bool with ID keys loaded from odb and check if any(matches):\\r\\n # if key_matches(\\\"pth_full\\\", src_, tar_) or key_matches(\\\"pth_alias\\\", src_, tar_) :\\r\\n # match = True\\r\\n # if not match:\\r\\n # temp = EasyDict()\\r\\n # target_dict[key_].append(temp)\\r\\n # transfer_missing_elements(temp, src_)\\r\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67875683","0.5678444","0.5599842","0.55489415","0.53554213","0.52686346","0.52098215","0.5204137","0.51888007","0.51499987","0.5148369","0.5104553","0.5098129","0.5079654","0.50565994","0.50067544","0.49729812","0.4921561","0.49208447","0.49190444","0.49049547","0.4876093","0.48642325","0.48454264","0.48426992","0.4805531","0.47853872","0.47764587","0.47709787","0.47685695","0.47651505","0.47421384","0.4719523","0.47189656","0.46698436","0.46601954","0.46508545","0.4648953","0.4646259","0.46388894","0.46244058","0.46165442","0.4613741","0.4610374","0.46092814","0.46092814","0.46092814","0.46092814","0.46075898","0.46075276","0.46059236","0.46030006","0.45977128","0.4596791","0.45965713","0.45929635","0.45655447","0.45653617","0.45456892","0.45455638","0.45434755","0.45401084","0.45399258","0.45389456","0.45365837","0.45261776","0.45256174","0.45215175","0.4515388","0.45140523","0.4510521","0.45051414","0.45020434","0.45010355","0.44965118","0.44958654","0.44958392","0.44957772","0.44937748","0.44931486","0.44910946","0.44890088","0.4488855","0.44835627","0.4482444","0.44815952","0.44809628","0.4478462","0.4478174","0.44729036","0.44699356","0.4466202","0.44642127","0.44627175","0.44572547","0.44546086","0.44545653","0.4453769","0.44385532","0.4437149"],"string":"[\n \"0.67875683\",\n \"0.5678444\",\n \"0.5599842\",\n \"0.55489415\",\n \"0.53554213\",\n \"0.52686346\",\n \"0.52098215\",\n \"0.5204137\",\n \"0.51888007\",\n \"0.51499987\",\n \"0.5148369\",\n \"0.5104553\",\n \"0.5098129\",\n \"0.5079654\",\n \"0.50565994\",\n \"0.50067544\",\n \"0.49729812\",\n \"0.4921561\",\n \"0.49208447\",\n \"0.49190444\",\n \"0.49049547\",\n \"0.4876093\",\n \"0.48642325\",\n \"0.48454264\",\n \"0.48426992\",\n \"0.4805531\",\n \"0.47853872\",\n \"0.47764587\",\n \"0.47709787\",\n \"0.47685695\",\n \"0.47651505\",\n \"0.47421384\",\n \"0.4719523\",\n \"0.47189656\",\n \"0.46698436\",\n \"0.46601954\",\n \"0.46508545\",\n \"0.4648953\",\n \"0.4646259\",\n \"0.46388894\",\n \"0.46244058\",\n \"0.46165442\",\n \"0.4613741\",\n \"0.4610374\",\n \"0.46092814\",\n \"0.46092814\",\n \"0.46092814\",\n \"0.46092814\",\n \"0.46075898\",\n \"0.46075276\",\n \"0.46059236\",\n \"0.46030006\",\n \"0.45977128\",\n \"0.4596791\",\n \"0.45965713\",\n \"0.45929635\",\n \"0.45655447\",\n \"0.45653617\",\n \"0.45456892\",\n \"0.45455638\",\n \"0.45434755\",\n \"0.45401084\",\n \"0.45399258\",\n \"0.45389456\",\n \"0.45365837\",\n \"0.45261776\",\n \"0.45256174\",\n \"0.45215175\",\n \"0.4515388\",\n \"0.45140523\",\n \"0.4510521\",\n \"0.45051414\",\n \"0.45020434\",\n \"0.45010355\",\n \"0.44965118\",\n \"0.44958654\",\n \"0.44958392\",\n \"0.44957772\",\n \"0.44937748\",\n \"0.44931486\",\n \"0.44910946\",\n \"0.44890088\",\n \"0.4488855\",\n \"0.44835627\",\n \"0.4482444\",\n \"0.44815952\",\n \"0.44809628\",\n \"0.4478462\",\n \"0.4478174\",\n \"0.44729036\",\n \"0.44699356\",\n \"0.4466202\",\n \"0.44642127\",\n \"0.44627175\",\n \"0.44572547\",\n \"0.44546086\",\n \"0.44545653\",\n \"0.4453769\",\n \"0.44385532\",\n \"0.4437149\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8015918"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2286,"cells":{"query":{"kind":"string","value":"Build JobConfigurationTableCopy from request resource args."},"document":{"kind":"string","value":"def ProcessTableCopyConfiguration(ref, args, request):\n del ref # Unused\n source_ref = args.CONCEPTS.source.Parse()\n destination_ref = args.CONCEPTS.destination.Parse()\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.datasetId',\n destination_ref.Parent().Name())\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.projectId',\n destination_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.destinationTable.tableId',\n destination_ref.Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.datasetId',\n source_ref.Parent().Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.projectId',\n source_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.tableId',\n source_ref.Name())\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def GetTableCopyResourceArgs():\n table_spec_data = yaml_data.ResourceYAMLData.FromPath('bq.table')\n arg_specs = [\n resource_args.GetResourcePresentationSpec(\n verb='to copy from', name='source', required=True, prefixes=True,\n attribute_overrides={'table': 'source'}, positional=False,\n resource_data=table_spec_data.GetData()),\n resource_args.GetResourcePresentationSpec(\n verb='to copy to', name='destination',\n required=True, prefixes=True,\n attribute_overrides={'table': 'destination'}, positional=False,\n resource_data=table_spec_data.GetData())]\n fallthroughs = {\n '--source.dataset': ['--destination.dataset'],\n '--destination.dataset': ['--source.dataset']\n }\n return [concept_parsers.ConceptParser(arg_specs, fallthroughs)]","def _create_jobs_table_data(self, dist_src, sectors, \r\n building_types_and_ids_and_home_based): \r\n res_sample = []; jobs_table = []\r\n no_samples = []\r\n\r\n for key in sectors.keys():\r\n sector_num = key\r\n sector = sectors[key]\r\n for zone in sector.keys():\r\n for building_type, number_of_jobs in sector[zone]:\r\n for type, id, home_based in building_types_and_ids_and_home_based:\r\n if building_type == id: \r\n dist = dist_src[type]\r\n break\r\n else:\r\n raise TypeError, (\"Invalid building type: %s\" \r\n % building_type)\r\n \r\n try:\r\n samples = self._zip_and_sample(dist[zone], \r\n int(number_of_jobs))\r\n if samples is None: \r\n no_samples += [(zone, building_type)]\r\n raise\r\n \r\n except:\r\n pass\r\n \r\n else:\r\n for type, id, home_based in building_types_and_ids_and_home_based:\r\n if building_type == id and home_based == True:\r\n home = 1 \r\n else: home = 0 \r\n \r\n for grid_id in samples:\r\n jobs_table += [{'sector':sector_num, \r\n 'home':home, \r\n 'building':building_type, \r\n 'grid':grid_id}]\r\n \r\n if len(no_samples) > 0:\r\n print ('No job samples created for (zone, building_type): %s!' \r\n % no_samples)\r\n \r\n return jobs_table","def _copy_to_head_args(args: Namespace) -> Namespace:\n\n _head_args = copy.deepcopy(args)\n _head_args.polling = args.polling\n _head_args.port = args.port\n _head_args.host = args.host[0]\n _head_args.uses = args.uses\n _head_args.pod_role = PodRoleType.HEAD\n _head_args.runtime_cls = 'HeadRuntime'\n _head_args.replicas = 1\n\n if args.name:\n _head_args.name = f'{args.name}/head'\n else:\n _head_args.name = f'head'\n\n return _head_args","def ProcessTableCopyOverwrite(ref, args, request):\n del ref # Unused\n if args.overwrite:\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\n return request","def test_create_copy(self):\n\n config = {\n 'version': '2.0',\n 'input_files': {\n 'INPUT_1': [{\n 'id': 1234,\n 'type': 'PRODUCT',\n 'workspace_name': 'wksp-name',\n 'workspace_path': 'the/workspace/path/file.json',\n 'local_file_name': 'file_abcdfeg.json',\n 'is_deleted': False,\n }]\n },\n 'output_workspaces': {\n 'OUTPUT_1': 'WORKSPACE_1'\n },\n 'tasks': [\n {\n 'task_id': 'task-1234',\n 'type': 'main',\n 'resources': {'cpu': 1.0},\n 'args': 'foo ${INPUT_1} ${JOB_OUTPUT_DIR}',\n 'env_vars': {'ENV_VAR_NAME': 'ENV_VAR_VALUE'},\n 'workspaces': {'WORKSPACE_NAME': {'mode': 'ro'}},\n 'mounts': {'MOUNT_NAME': 'MOUNT_VOLUME_NAME'},\n 'settings': {'SETTING_NAME': 'SETTING_VALUE'},\n 'volumes': {\n 'VOLUME_NAME_1': {\n 'container_path': '/the/container/path',\n 'mode': 'ro',\n 'type': 'host',\n 'host_path': '/the/host/path'\n },\n 'VOLUME_NAME_2': {\n 'container_path': '/the/other/container/path',\n 'mode': 'rw',\n 'type': 'volume',\n 'driver': 'SUPER_DRIVER_5000',\n 'driver_opts': {'turbo': 'yes-pleez'}\n }\n },\n 'docker_params': [{'flag': 'hello', 'value': 'scale'}]\n }\n ]\n }\n exe_config = ExecutionConfiguration(config)\n\n copy = exe_config.create_copy()\n self.assertDictEqual(copy.get_dict(), config)","def _GetMigrationJob(\n self,\n source_ref,\n destination_ref,\n conversion_workspace_ref,\n cmek_key_ref,\n args,\n ):\n migration_job_type = self.messages.MigrationJob\n labels = labels_util.ParseCreateArgs(\n args, self.messages.MigrationJob.LabelsValue\n )\n type_value = self._GetType(migration_job_type, args.type)\n source = source_ref.RelativeName()\n destination = destination_ref.RelativeName()\n params = {}\n if args.IsSpecified('peer_vpc'):\n params['vpcPeeringConnectivity'] = self._GetVpcPeeringConnectivity(args)\n elif args.IsSpecified('vm_ip'):\n params['reverseSshConnectivity'] = self._GetReverseSshConnectivity(args)\n elif args.IsSpecified('static_ip'):\n params['staticIpConnectivity'] = self._GetStaticIpConnectivity()\n\n migration_job_obj = migration_job_type(\n labels=labels,\n displayName=args.display_name,\n state=migration_job_type.StateValueValuesEnum.CREATING,\n type=type_value,\n dumpPath=args.dump_path,\n source=source,\n destination=destination,\n **params)\n if conversion_workspace_ref is not None:\n migration_job_obj.conversionWorkspace = self._GetConversionWorkspaceInfo(\n conversion_workspace_ref, args\n )\n if cmek_key_ref is not None:\n migration_job_obj.cmekKeyName = cmek_key_ref.RelativeName()\n\n if args.IsKnownAndSpecified('filter'):\n args.filter, server_filter = filter_rewrite.Rewriter().Rewrite(\n args.filter\n )\n migration_job_obj.filter = server_filter\n\n if args.IsKnownAndSpecified('dump_parallel_level'):\n migration_job_obj.performanceConfig = self._GetPerformanceConfig(args)\n\n return migration_job_obj","def infocalypse_copy(ui_, repo, **opts):\n params, stored_cfg = get_config_info(ui_, opts)\n\n insert_uri = opts['inserturi']\n if insert_uri == '':\n # REDFLAG: fix parameter definition so that it is required?\n ui_.warn(\"Please set the insert URI with --inserturi.\\n\")\n return\n\n request_uri = opts['requesturi']\n if request_uri == '':\n request_uri = stored_cfg.get_request_uri(repo.root)\n if not request_uri:\n ui_.warn(\"There is no stored request URI for this repo.\\n\"\n \"Please set one with the --requesturi option.\\n\")\n return\n\n params['INSERT_URI'] = insert_uri\n params['REQUEST_URI'] = request_uri\n execute_copy(ui_, repo, params, stored_cfg)","def __get_datatables_args():\n\n table_args = dict()\n\n #\n # Common Arguments\n #\n\n table_args['column-count'] = 0\n table_args['sort-col-count'] = 0\n\n if request.args.get('draw'):\n table_args['sequence'] = request.args.get('draw')\n\n if request.args.get('start'):\n table_args['offset'] = int(request.args.get('start'))\n\n if request.args.get('length'):\n table_args['limit'] = int(request.args.get('length'))\n\n if request.args.get('search[value]'):\n table_args['filter'] = request.args.get('search[value]')\n\n if request.args.get('search[regex]'):\n table_args['filter-regex'] = request.args.get('search[regex]')\n\n #\n # Custom Arguments\n #\n\n if request.args.get('time_filter'):\n table_args['time_filter'] = request.args.get('time_filter')\n\n i = 0\n while True:\n if request.args.get('columns[%d][data]' % i):\n table_args['column-count'] += 1\n table_args['mDataProp_%d' % i] = request.args.get('columns[%d][data]' % i)\n else:\n break\n\n #\n # Column Search\n #\n\n if request.args.get('columns[%d][searchable]' % i):\n table_args['bSearchable_%d' % i] = request.args.get('columns[%d][searchable]' % i)\n\n if request.args.get('columns[%d][search][value]' % i):\n table_args['sSearch_%d' % i] = request.args.get('columns[%d][search][value]' % i)\n\n if request.args.get('columns[%d][search][regex]' % i):\n table_args['bRegex_%d' % i] = request.args.get('columns[%d][search][regex]' % i)\n\n #\n # Column Sort\n #\n\n if request.args.get('columns[%d][orderable]' % i):\n table_args['bSortable_%d' % i] = request.args.get('columns[%d][orderable]' % i)\n\n if request.args.get('order[%d][column]' % i):\n table_args['sort-col-count'] += 1\n table_args['iSortCol_%d' % i] = int(request.args.get('order[%d][column]' % i))\n\n if request.args.get('order[%d][dir]' % i):\n table_args['sSortDir_%d' % i] = request.args.get('order[%d][dir]' % i)\n\n i += 1\n\n return table_args","def initiate_build(self, config: Union[TableConfig, str, UUID],\n version: Union[str, UUID] = None) -> JobSubmissionResponse:\n if isinstance(config, TableConfig):\n if version is not None:\n logger.warning('Ignoring version {} since config object was provided.'\n .format(version))\n if config.version_number is None:\n raise ValueError('Cannot build table from config which has no version. '\n 'Try registering the config before building.')\n if config.config_uid is None:\n raise ValueError('Cannot build table from config which has no uid. '\n 'Try registering the config before building.')\n uid = config.config_uid\n version = config.version_number\n else:\n if version is None:\n raise ValueError('Version must be specified when building by config uid.')\n uid = config\n job_id = uuid4()\n logger.info('Building table from config {} version {} with job ID {}...'\n .format(uid, version, job_id))\n path = 'projects/{}/ara-definitions/{}/versions/{}/build'.format(\n self.project_id, uid, version\n )\n response = self.session.post_resource(\n path=path,\n json={},\n params={\n 'job_id': job_id\n }\n )\n submission = JobSubmissionResponse.build(response)\n logger.info('Build job submitted with job ID {}.'.format(submission.job_id))\n return submission","def __gen_datatable__(self):\n # | - __generate_data_table\n rows_list = []\n for Job_i in self.Job_list:\n # | - FOR LOOP BODY\n entry_param_dict = {}\n for prop, value in Job_i.job_params.items():\n entry_param_dict[prop] = value\n\n entry_param_dict[\"Job\"] = Job_i\n entry_param_dict[\"path\"] = Job_i.full_path\n entry_param_dict[\"max_revision\"] = Job_i.max_revision\n entry_param_dict[\"revision_number\"] = Job_i.revision_number\n\n rows_list.append(entry_param_dict)\n # __|\n\n data_frame = pd.DataFrame(rows_list)\n\n return(data_frame)\n # __|","def __init__(self, job_template_name, job_input, device_list,\n api_server_config, logger, amqp_client,\n transaction_id, transaction_descr, args):\n self._job_template_name = job_template_name\n self._job_input = job_input\n self._device_list = device_list\n self._api_server_config = api_server_config\n self._logger = logger\n self._job_id = None\n self._job_status = None\n self._amqp_client = amqp_client\n self._transaction_id = transaction_id\n self._transaction_descr = transaction_descr\n self._args = args\n super(JobHandler, self).__init__()","def get_merged_args(args):\n config_dict = load_config(args.config)\n\n args_dict = {\n \"cleaning_policy\": args.cleaning_policy,\n \"clear\": args.clear,\n \"content\": args.content,\n \"dry_run\": args.dry_run,\n \"force\": args.force,\n \"in_lines\": args.in_lines,\n \"max_size\": args.max_size,\n \"regex\": args.regex,\n \"restore\": args.restore,\n \"rmdir\": args.rmdir,\n \"short\": args.short,\n \"silent\": args.silent,\n \"storage_time\": args.storage_time,\n \"wastebasket_path\": args.wastebasket_path\n }\n\n for arg, value in args_dict.iteritems():\n if not value:\n args_dict[arg] = config_dict[arg]\n\n if args_dict[\"cleaning_policy\"] == POLICY:\n args_dict[\"cleaning_policy\"] = config_dict[\"cleaning_policy\"]\n\n if args_dict[\"storage_time\"] == STORAGE_TIME:\n args_dict[\"storage_time\"] = config_dict[\"storage_time\"]\n\n if args_dict[\"max_size\"] == MAX_SIZE:\n args_dict[\"max_size\"] = config_dict[\"max_size\"]\n\n return args_dict","def __copy__(self):\n from bn.distribs.distribution_builder import MultivariateTableBuilder\n builder = MultivariateTableBuilder()\n for assignment in self._table.keys():\n builder.add_row(copy(assignment), self._table[assignment])\n\n return builder.build()","def CopyTapSettings(self, *args, **kwargs):\n # type: (*Any, **Any) -> None\n payload = { \"Arg1\": self.href }\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\n for item in kwargs.items(): payload[item[0]] = item[1]\n return self._execute('copyTapSettings', payload=payload, response_object=None)","def __copy__(self):\n # prepare unnamed arguments\n args = [getattr(self, arg) for arg in self._copy_conf['args']]\n\n # prepare named arguments\n kwargs = {}\n for arg in self._copy_conf['kwargs']:\n # if arg is a tuple, the first entry will be the named kwargs, and\n # the second will be the name of the attribute to copy\n name = arg\n if isinstance(arg, tuple):\n name, arg = arg\n if hasattr(self, arg):\n kwargs[name] = getattr(self, arg)\n\n # create the new instance\n new_copy = self.__class__(*args, **kwargs)\n\n # then copy attributes\n for attr_name in self._copy_conf['attrs']:\n if hasattr(self, attr_name):\n setattr(new_copy, attr_name, getattr(self, attr_name))\n\n return new_copy","def visit_copy_command(element, compiler, **kw):\n qs = \"\"\"COPY {table}{columns} FROM :data_location\n WITH CREDENTIALS AS :credentials\n {format}\n {parameters}\"\"\"\n parameters = []\n bindparams = [\n sa.bindparam(\n 'data_location',\n value=element.data_location,\n type_=sa.String,\n ),\n sa.bindparam(\n 'credentials',\n value=element.credentials,\n type_=sa.String,\n ),\n ]\n\n if element.format == Format.csv:\n format_ = 'FORMAT AS CSV'\n if element.quote is not None:\n format_ += ' QUOTE AS :quote_character'\n bindparams.append(sa.bindparam(\n 'quote_character',\n value=element.quote,\n type_=sa.String,\n ))\n elif element.format == Format.json:\n format_ = 'FORMAT AS JSON AS :json_option'\n bindparams.append(sa.bindparam(\n 'json_option',\n value=element.path_file,\n type_=sa.String,\n ))\n elif element.format == Format.avro:\n format_ = 'FORMAT AS AVRO AS :avro_option'\n bindparams.append(sa.bindparam(\n 'avro_option',\n value=element.path_file,\n type_=sa.String,\n ))\n elif element.format == Format.orc:\n format_ = 'FORMAT AS ORC'\n elif element.format == Format.parquet:\n format_ = 'FORMAT AS PARQUET'\n elif element.format == Format.fixed_width and element.fixed_width is None:\n raise sa_exc.CompileError(\n \"'fixed_width' argument required for format 'FIXEDWIDTH'.\")\n else:\n format_ = ''\n\n if element.delimiter is not None:\n parameters.append('DELIMITER AS :delimiter_char')\n bindparams.append(sa.bindparam(\n 'delimiter_char',\n value=element.delimiter,\n type_=sa.String,\n ))\n\n if element.fixed_width is not None:\n parameters.append('FIXEDWIDTH AS :fixedwidth_spec')\n bindparams.append(sa.bindparam(\n 'fixedwidth_spec',\n value=_process_fixed_width(element.fixed_width),\n type_=sa.String,\n ))\n\n if element.compression is not None:\n parameters.append(Compression(element.compression).value)\n\n if element.manifest:\n parameters.append('MANIFEST')\n\n if element.accept_any_date:\n parameters.append('ACCEPTANYDATE')\n\n if element.accept_inv_chars is not None:\n parameters.append('ACCEPTINVCHARS AS :replacement_char')\n bindparams.append(sa.bindparam(\n 'replacement_char',\n value=element.accept_inv_chars,\n type_=sa.String\n ))\n\n if element.blanks_as_null:\n parameters.append('BLANKSASNULL')\n\n if element.date_format is not None:\n parameters.append('DATEFORMAT AS :dateformat_string')\n bindparams.append(sa.bindparam(\n 'dateformat_string',\n value=element.date_format,\n type_=sa.String,\n ))\n\n if element.empty_as_null:\n parameters.append('EMPTYASNULL')\n\n if element.encoding is not None:\n parameters.append('ENCODING AS ' + Encoding(element.encoding).value)\n\n if element.escape:\n parameters.append('ESCAPE')\n\n if element.explicit_ids:\n parameters.append('EXPLICIT_IDS')\n\n if element.fill_record:\n parameters.append('FILLRECORD')\n\n if element.ignore_blank_lines:\n parameters.append('IGNOREBLANKLINES')\n\n if element.ignore_header is not None:\n parameters.append('IGNOREHEADER AS :number_rows')\n bindparams.append(sa.bindparam(\n 'number_rows',\n value=element.ignore_header,\n type_=sa.Integer,\n ))\n\n if element.dangerous_null_delimiter is not None:\n parameters.append(\"NULL AS '%s'\" % element.dangerous_null_delimiter)\n\n if element.remove_quotes:\n parameters.append('REMOVEQUOTES')\n\n if element.roundec:\n parameters.append('ROUNDEC')\n\n if element.time_format is not None:\n parameters.append('TIMEFORMAT AS :timeformat_string')\n bindparams.append(sa.bindparam(\n 'timeformat_string',\n value=element.time_format,\n type_=sa.String,\n ))\n\n if element.trim_blanks:\n parameters.append('TRIMBLANKS')\n\n if element.truncate_columns:\n parameters.append('TRUNCATECOLUMNS')\n\n if element.comp_rows:\n parameters.append('COMPROWS :numrows')\n bindparams.append(sa.bindparam(\n 'numrows',\n value=element.comp_rows,\n type_=sa.Integer,\n ))\n\n if element.comp_update:\n parameters.append('COMPUPDATE ON')\n elif element.comp_update is not None:\n parameters.append('COMPUPDATE OFF')\n\n if element.max_error is not None:\n parameters.append('MAXERROR AS :error_count')\n bindparams.append(sa.bindparam(\n 'error_count',\n value=element.max_error,\n type_=sa.Integer,\n ))\n\n if element.no_load:\n parameters.append('NOLOAD')\n\n if element.stat_update:\n parameters.append('STATUPDATE ON')\n elif element.stat_update is not None:\n parameters.append('STATUPDATE OFF')\n\n if element.region is not None:\n parameters.append('REGION :region')\n bindparams.append(sa.bindparam(\n 'region',\n value=element.region,\n type_=sa.String\n ))\n\n columns = ' (%s)' % ', '.join(\n compiler.preparer.format_column(column) for column in element.columns\n ) if element.columns else ''\n\n qs = qs.format(\n table=compiler.preparer.format_table(element.table),\n columns=columns,\n format=format_,\n parameters='\\n'.join(parameters)\n )\n\n return compiler.process(sa.text(qs).bindparams(*bindparams), **kw)","def create_job_configuration(start_time: str) -> ItemsJobConfig:\n # Create job configuration\n config = {\n 'source_url': os.getenv(\"ITEMS_SOURCE_URL\", default=\"\"),\n 'dest_new_url': os.getenv(\"ITEMS_DEST_NEW_URL\", default=\"\"),\n 'dest_updates_url': os.getenv(\"ITEMS_DEST_UPDATES_URL\", default=\"\"),\n 'caiasoft_api_key': os.getenv('CAIASOFT_API_KEY', default=\"\"),\n 'storage_dir': os.getenv('ITEMS_STORAGE_DIR', default=\"\"),\n 'last_success_lookup': os.getenv('ITEMS_LAST_SUCCESS_LOOKUP', default=\"\")\n }\n\n job_id_prefix = \"caia.items\"\n\n job_config = ItemsJobConfig(config, job_id_prefix, start_time)\n logger.info(f\"Job Id: {job_config['job_id']}\")\n logger.debug(f\"job_config={job_config}\")\n\n return job_config","def __generate_data_table__(self):\n # | - __generate_data_table__\n rows_list = []\n for job in self.job_var_lst:\n revisions = self.job_revision_number(job)\n for revision in range(revisions + 1)[1:]:\n # | - FOR LOOP BODY\n entry_param_dict = {}\n for prop in job:\n entry_param_dict[prop[\"property\"]] = prop[\"value\"]\n\n entry_param_dict[\"variable_list\"] = job\n entry_param_dict[\"path\"] = self.var_lst_to_path(job)\n\n entry_param_dict[\"max_revision\"] = revisions\n entry_param_dict[\"revision_number\"] = revision\n\n rows_list.append(entry_param_dict)\n # __|\n\n data_frame = pd.DataFrame(rows_list)\n\n return(data_frame)\n # __|","def from_mapping(context: CreateCommandsContext, dry_run):\n if dry_run:\n logger.info(\"** Dry run, nothing will be sent to server **\")\n\n # Make sure no jobs are actually created\n context.client_tool.create_path_job = mock_create\n context.client_tool.create_pacs_job = mock_create\n\n job_sets = extract_job_sets(\n context.default_parameters(), context.get_mapping()\n )\n\n # inspect project name and destination to present the next question to the user\n project_names = set()\n destination_paths = set()\n for job_set in job_sets:\n project_names.add(job_set.get_param_by_type(Project).value)\n destination_paths.add(job_set.get_param_by_type(DestinationPath).value)\n\n question = (\n f\"This will create {len(job_sets)} jobs on \"\n f\"{context.get_active_server().name},\"\n f\" for projects '{list(project_names)}', writing data to \"\n f\"'{[str(x) for x in destination_paths]}'. Are you sure?\"\n )\n if not click.confirm(question):\n logger.info(\"Cancelled\")\n return\n\n created_job_ids = create_jobs(context, job_sets)\n\n if created_job_ids:\n context.add_to_batch(created_job_ids)\n\n logger.info(\"Done\")","def _prepare(self):\n logging.info('-> copy configuration...')\n path_cofig = self.params['path_config_bUnwarpJ']\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\n os.path.basename(path_cofig)))\n if 'path_config_IJ_SIFT' in self.params:\n path_cofig = self.params['path_config_IJ_SIFT']\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\n os.path.basename(path_cofig)))\n if 'path_config_IJ_MOPS' in self.params:\n path_cofig = self.params['path_config_IJ_MOPS']\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\n os.path.basename(path_cofig)))","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n copy: Optional[pulumi.Input[pulumi.InputType['JobCopyArgs']]] = None,\n extract: Optional[pulumi.Input[pulumi.InputType['JobExtractArgs']]] = None,\n job_id: Optional[pulumi.Input[str]] = None,\n job_timeout_ms: Optional[pulumi.Input[str]] = None,\n labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n load: Optional[pulumi.Input[pulumi.InputType['JobLoadArgs']]] = None,\n location: Optional[pulumi.Input[str]] = None,\n project: Optional[pulumi.Input[str]] = None,\n query: Optional[pulumi.Input[pulumi.InputType['JobQueryArgs']]] = None,\n __props__=None,\n __name__=None,\n __opts__=None):\n if __name__ is not None:\n warnings.warn(\"explicit use of __name__ is deprecated\", DeprecationWarning)\n resource_name = __name__\n if __opts__ is not None:\n warnings.warn(\"explicit use of __opts__ is deprecated, use 'opts' instead\", DeprecationWarning)\n opts = __opts__\n if opts is None:\n opts = pulumi.ResourceOptions()\n if not isinstance(opts, pulumi.ResourceOptions):\n raise TypeError('Expected resource options to be a ResourceOptions instance')\n if opts.version is None:\n opts.version = _utilities.get_version()\n if opts.id is None:\n if __props__ is not None:\n raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')\n __props__ = dict()\n\n __props__['copy'] = copy\n __props__['extract'] = extract\n if job_id is None:\n raise TypeError(\"Missing required property 'job_id'\")\n __props__['job_id'] = job_id\n __props__['job_timeout_ms'] = job_timeout_ms\n __props__['labels'] = labels\n __props__['load'] = load\n __props__['location'] = location\n __props__['project'] = project\n __props__['query'] = query\n __props__['job_type'] = None\n __props__['user_email'] = None\n super(Job, __self__).__init__(\n 'gcp:bigquery/job:Job',\n resource_name,\n __props__,\n opts)","def build_from_config(self, config: Union[TableConfig, str, UUID], *,\n version: Union[str, int] = None,\n timeout: float = 15 * 60) -> GemTable:\n job = self.initiate_build(config, version)\n return self.get_by_build_job(job, timeout=timeout)","def _GetUpdatedMigrationJob(\n self, migration_job, source_ref, destination_ref, args):\n update_fields = self._GetUpdateMask(args)\n if args.IsSpecified('display_name'):\n migration_job.displayName = args.display_name\n if args.IsSpecified('type'):\n migration_job.type = self._GetType(self.messages.MigrationJob, args.type)\n if args.IsSpecified('dump_path'):\n migration_job.dumpPath = args.dump_path\n if args.IsSpecified('source'):\n migration_job.source = source_ref.RelativeName()\n if args.IsSpecified('destination'):\n migration_job.destination = destination_ref.RelativeName()\n if args.IsKnownAndSpecified('dump_parallel_level'):\n migration_job.performanceConfig = self._GetPerformanceConfig(args)\n self._UpdateConnectivity(migration_job, args)\n self._UpdateLabels(args, migration_job, update_fields)\n return migration_job, update_fields","def __init__(self, job_spec: JobSpec):\n self.job_spec = job_spec\n \n self.merge_rules = spark.read.csv(job_spec.mapping_document_path, header='true').toPandas()\n\n self.join_map = JoinMap()\n \n # defined externally\n self.merge_action_map = merge_action_map","def _init_from_config(self):\n self.arch = self.job_config.get('arch', 'x86_64')\n self.os_type = self.job_config.get(\"os_type\")\n self.flavor = self.job_config.get(\"flavor\")\n self.codename = self.job_config.get(\"codename\")\n self.os_version = self._get_version()\n # if os_version is given, prefer version/codename derived from it\n if self.os_version:\n self.os_version, self.codename = \\\n OS.version_codename(self.os_type, self.os_version)\n self.branch = self.job_config.get(\"branch\")\n self.tag = self.job_config.get(\"tag\")\n self.ref = self.job_config.get(\"ref\")\n self.distro = self._get_distro(\n distro=self.os_type,\n version=self.os_version,\n codename=self.codename,\n )\n self.pkg_type = \"deb\" if self.os_type.lower() in (\n \"ubuntu\",\n \"debian\",\n ) else \"rpm\"\n\n if not getattr(self, 'flavor'):\n # avoiding circular imports\n from teuthology.suite.util import get_install_task_flavor\n # when we're initializing from a full teuthology config, not just a\n # task config we need to make sure we're looking at the flavor for\n # the install task\n self.flavor = get_install_task_flavor(self.job_config)","def table_creater(self, tablename, columnnames, entries):\n createrurl = self.casjobsurl + '/contexts/MyDB/query'","def create_compilation_job(CompilationJobName=None, RoleArn=None, InputConfig=None, OutputConfig=None, StoppingCondition=None):\n pass","def prepare_pr_condor_job(self, pool_type, pool_address, number_of_jobs, subtask_index, data_files, rank='0', extraArgs=''):\n ############\n copasi_file = 'auto_copasi_%d.$(Process).cps' % subtask_index\n output_file = 'output_%d.$(Process).txt' % subtask_index\n \n \n \n if pool_type == 'ec2':\n binary_dir = '/usr/local/bin'\n transfer_executable = 'NO'\n else:\n binary_dir, binary = os.path.split(settings.COPASI_LOCAL_BINARY)\n transfer_executable = 'YES'\n \n input_files_string = ', '\n for data_file in data_files:\n input_files_string += (data_file + ', ')\n input_files_string = input_files_string.rstrip(', ')\n\n condor_job_string = Template(condor_spec.raw_condor_job_string).substitute(copasiFile=copasi_file, \n otherFiles=input_files_string,\n rank=rank,\n binary_dir = binary_dir,\n transfer_executable = transfer_executable,\n pool_type = pool_type,\n pool_address = pool_address,\n subtask=str(subtask_index),\n n = number_of_jobs,\n outputFile = output_file,\n extraArgs='',\n )\n \n condor_job_filename = 'auto_condor_%d.job'%subtask_index\n condor_job_full_filename = os.path.join(self.path, condor_job_filename)\n condor_file = open(condor_job_full_filename, 'w')\n condor_file.write(condor_job_string)\n condor_file.close()\n\n return condor_job_filename","def configure_queued_job(self, job):\n\n config = ExecutionConfiguration()\n data = job.get_job_data()\n\n # Add input file meta-data\n input_files_dict = self._create_input_file_dict(data)\n config.set_input_files(input_files_dict)\n\n # Set up env vars for job's input data\n input_values = data.get_injected_input_values(input_files_dict)\n interface = job.job_type_rev.get_input_interface()\n\n env_vars = {}\n if isinstance(data, JobData):\n # call job.data.job_data.JobData.get_injected_env_vars\n env_vars = data.get_injected_env_vars(input_files_dict, interface)\n else:\n # call old job.configuration.data.job_data.get_injected_env_vars\n # TODO: remove once old JobData class is no longer used\n env_vars = data.get_injected_env_vars(input_files_dict)\n\n task_workspaces = {}\n if job.job_type.is_system:\n # Add any workspaces needed for this system job\n task_workspaces = QueuedExecutionConfigurator._system_job_workspaces(job)\n else:\n # Set any output workspaces needed\n output_workspaces = {}\n if job.input and 'version' in job.input and job.input['version'] == '1.0':\n # Set output workspaces using legacy job data\n self._cache_workspace_names(data.get_output_workspace_ids())\n output_workspaces = {}\n for output, workspace_id in data.get_output_workspaces().items():\n output_workspaces[output] = self._cached_workspace_names[workspace_id]\n config.set_output_workspaces(output_workspaces)\n if not output_workspaces:\n # Set output workspaces from job configuration\n output_workspaces = {}\n job_config = job.get_job_configuration()\n interface = SeedManifest(job.job_type_rev.manifest, do_validate=False)\n for output_name in interface.get_file_output_names():\n output_workspace = job_config.get_output_workspace(output_name)\n if output_workspace:\n output_workspaces[output_name] = output_workspace\n config.set_output_workspaces(output_workspaces)\n\n # Create main task with fields populated from input data\n args = job.get_job_interface().get_injected_command_args(input_values, env_vars)\n config.create_tasks(['main'])\n config.add_to_task('main', args=args, env_vars=env_vars, workspaces=task_workspaces)\n return config","def copy(self) -> pulumi.Output[Optional['outputs.JobCopy']]:\n return pulumi.get(self, \"copy\")","def get_template_args(csv_directory, id_field, address_field, zone_field, upload_bucket, results_bucket, upload=True):\n job_csvs = [f for f in listdir(csv_directory) if isfile(join(csv_directory, f))]\n job_template_args = []\n for job_num, job_csv in enumerate(job_csvs):\n if upload:\n upload_blob(UPLOAD_BUCKET, join(csv_directory, job_csv), job_csv)\n print(job_csv, 'uploaded')\n job_template_args.append({\n 'job_number': job_num,\n 'csv_name': job_csv,\n 'id_field': id_field,\n 'address_field': address_field,\n 'zone_field': zone_field,\n 'upload_bucket': upload_bucket,\n 'results_bucket': results_bucket\n })\n return job_template_args","def __init__(self, settings, ui_id, job_id):\n # Call the original constructor\n super().__init__(settings, ui_id, job_id)\n\n # Set the local template\n self.local_template = 'settings/bilby_local.sh'\n # Set our job parameter path\n self.job_parameter_file = os.path.join(self.get_working_directory(), 'json_params.json')\n # Set the job output directory\n self.job_output_directory = os.path.join(self.get_working_directory(), 'output')","def build_job_configs(self, args):\n job_configs = {}\n\n ttype = args['ttype']\n (targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)\n if sim is not None:\n raise ValueError(\"Found 'sim' argument on AnalyzeExtension_SG config.\")\n if targets_yaml is None:\n return job_configs\n\n targets = load_yaml(targets_yaml)\n config_yaml = 'config.yaml'\n\n base_config = dict(roi_baseline=args['roi_baseline'],\n make_plots=args['make_plots'])\n\n for target_name, target_list in targets.items():\n name_keys = dict(target_type=ttype,\n target_name=target_name,\n fullpath=True)\n target_dir = NAME_FACTORY.targetdir(**name_keys)\n config_path = os.path.join(target_dir, config_yaml)\n logfile = make_nfs_path(os.path.join(\n target_dir, \"%s_%s.log\" % (self.linkname, target_name)))\n job_config = base_config.copy()\n job_config.update(dict(config=config_path,\n logfile=logfile))\n job_configs[target_name] = job_config\n\n return job_configs","def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data):\n super().__init__(cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data)\n if input_cfg_json_data:\n self._read_custom_pars()\n else:\n self._combine_conditions()\n\n # Mike's new stuff\n self.outpars = self._flatten_dict(self.outpars, '', {})","def create_arg_config(environment, region, template, parameters):\r\n raw_config = {\r\n 'Environment': environment,\r\n 'Region': region\r\n }\r\n if template:\r\n raw_config['Template'] = template\r\n if parameters:\r\n raw_config['Parameters'] = dict(parameters)\r\n return Config(raw_config)","def deploy_features_table():\n\n logging.info(\"copy table\")\n target_dataset_ref = bigquery.DatasetReference(GCP_PROJECT, BQ_TARGET_DATASET)\n target_table_ref = bigquery.TableReference(target_dataset_ref, 'features')\n copyjob_config = bigquery.CopyJobConfig()\n copyjob_config.create_disposition = bigquery.CreateDisposition.CREATE_IF_NEEDED\n copyjob_config.write_disposition = bigquery.WriteDisposition.WRITE_TRUNCATE\n bq.copy_table(temp_table_ref, target_table_ref, job_config=copyjob_config)","def _create_job_spec(\n self,\n job_id: Text,\n training_input: Dict[Text, Any],\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\n pass","def test_copy_options_from_config_file(self):\n tempfile = self.get_temp_file()\n self.prepare(nodes=1)\n\n logger.debug('Running stress')\n stress_table = 'keyspace1.standard1'\n self.node1.stress(['write', 'n=1K', 'no-warmup', '-rate', 'threads=50'])\n\n def create_config_file(config_lines):\n config_file = self.get_temp_file()\n logger.debug('Creating config file {}'.format(config_file.name))\n\n with open(config_file.name, 'w') as config:\n for line in config_lines:\n config.write(line + os.linesep)\n config.close()\n\n return config_file.name\n\n def extract_options(out):\n prefix = 'Using options: '\n for l in out.split('\\n'):\n if l.startswith(prefix):\n return l[len(prefix):].strip().strip(\"'\").replace(\"'\", \"\\\"\")\n return ''\n\n def check_options(out, expected_options):\n opts = extract_options(out)\n logger.debug('Options: {}'.format(opts))\n d = json.loads(opts)\n for k, v in expected_options:\n assert v == d[k]\n\n def do_test(config_lines, expected_options):\n config_file = create_config_file(config_lines)\n\n cmd = \"COPY {} {} '{}'\".format(stress_table, direction, tempfile.name)\n if not use_default:\n cmd += \" WITH CONFIGFILE = '{}'\".format(config_file)\n\n cqlsh_options = []\n if use_default:\n cqlsh_options.append('--cqlshrc={}'.format(config_file))\n\n logger.debug('{} with options {}'.format(cmd, cqlsh_options))\n out, _, _ = self.run_cqlsh(cmds=cmd, cqlsh_options=cqlsh_options, skip_cqlshrc=True)\n logger.debug(out)\n check_options(out, expected_options)\n\n for use_default in [True, False]:\n for direction in ['TO', 'FROM']:\n do_test(['[copy]', 'header = True', 'maxattempts = 10'],\n [('header', 'True'), ('maxattempts', '10')])\n\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\n '[copy:{}]'.format(stress_table), 'maxattempts = 9'],\n [('header', 'True'), ('maxattempts', '9')])\n\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\n '[copy-from]', 'maxattempts = 9',\n '[copy-to]', 'maxattempts = 8'],\n [('header', 'True'), ('maxattempts', '8' if direction == 'TO' else '9')])\n\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\n '[copy-from]', 'maxattempts = 9',\n '[copy-to]', 'maxattempts = 8',\n '[copy:{}]'.format(stress_table), 'maxattempts = 7'],\n [('header', 'True'), ('maxattempts', '7')])\n\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\n '[copy-from]', 'maxattempts = 9',\n '[copy-to]', 'maxattempts = 8',\n '[copy:{}]'.format(stress_table), 'maxattempts = 7',\n '[copy-from:{}]'.format(stress_table), 'maxattempts = 6',\n '[copy-to:{}]'.format(stress_table), 'maxattempts = 5'],\n [('header', 'True'), ('maxattempts', '5' if direction == 'TO' else '6')])","def get(resource_name: str,\n id: pulumi.Input[str],\n opts: Optional[pulumi.ResourceOptions] = None,\n copy: Optional[pulumi.Input[pulumi.InputType['JobCopyArgs']]] = None,\n extract: Optional[pulumi.Input[pulumi.InputType['JobExtractArgs']]] = None,\n job_id: Optional[pulumi.Input[str]] = None,\n job_timeout_ms: Optional[pulumi.Input[str]] = None,\n job_type: Optional[pulumi.Input[str]] = None,\n labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n load: Optional[pulumi.Input[pulumi.InputType['JobLoadArgs']]] = None,\n location: Optional[pulumi.Input[str]] = None,\n project: Optional[pulumi.Input[str]] = None,\n query: Optional[pulumi.Input[pulumi.InputType['JobQueryArgs']]] = None,\n user_email: Optional[pulumi.Input[str]] = None) -> 'Job':\n opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))\n\n __props__ = dict()\n\n __props__[\"copy\"] = copy\n __props__[\"extract\"] = extract\n __props__[\"job_id\"] = job_id\n __props__[\"job_timeout_ms\"] = job_timeout_ms\n __props__[\"job_type\"] = job_type\n __props__[\"labels\"] = labels\n __props__[\"load\"] = load\n __props__[\"location\"] = location\n __props__[\"project\"] = project\n __props__[\"query\"] = query\n __props__[\"user_email\"] = user_email\n return Job(resource_name, opts=opts, __props__=__props__)","def generate_template_dict(self):\n # Get the existing parameters\n params = super().generate_template_dict()\n\n # Add our custom parameters\n params['job_parameter_file'] = self.job_parameter_file\n params['job_output_directory'] = self.job_output_directory\n\n # Return the updated params\n return params","def main(args):\n try:\n config_path = project_path + \"/\" + args.config\n input_data_path = project_path + \"/\" + args.input\n output_data_path = project_path + \"/\" + args.output\n\n config = load_config(config_path)\n df = read_csv(input_data_path)\n product = product_dim(df, **config['product_dim'])\n\n # Write to output file\n save_csv(product, output_data_path)\n except Exception as e:\n logger.error(\"Unexpected error occurred when creating object table for products: \" + str(e))","def constructObjectJob(self, xml_node):\n name = os.path.join(self.dir, xml_node.find(\"name\").text)\n output_name = name + \".o\"\n object_job = CopyFile(name, output_name, self.dir)\n object_job.output = output_name\n return object_job","def __init__(\n self,\n workspace=None,\n profile=None,\n extend_path=None,\n devel_layout=None,\n install=False,\n isolate_install=False,\n cmake_args=None,\n make_args=None,\n jobs_args=None,\n use_internal_make_jobserver=True,\n use_env_cache=False,\n catkin_make_args=None,\n space_suffix=None,\n buildlist=None,\n skiplist=None,\n authors=None,\n maintainers=None,\n licenses=None,\n extends=None,\n key_origins={},\n **kwargs\n ):\n self.__locked = False\n\n # Handle deprecated arguments\n if 'whitelist' in kwargs:\n buildlist = kwargs['whitelist']\n del kwargs['whitelist']\n if 'blacklist' in kwargs:\n skiplist = kwargs['blacklist']\n del kwargs['blacklist']\n\n # Validation is done on assignment\n self.workspace = workspace\n\n self.extend_path = extend_path if extend_path else None\n self.key_origins = key_origins\n\n self.profile = profile\n\n # Handle *space assignment and defaults\n for space, space_dict in Context.SPACES.items():\n key_name = space + '_space'\n default = space_dict['default']\n value = kwargs.pop(key_name, default)\n if value == default and space_suffix and space != 'source':\n value += space_suffix\n setattr(self, key_name, value)\n\n # Check for unhandled context options\n if len(kwargs) > 0:\n print('Warning: Unhandled config context options: {}'.format(kwargs), file=sys.stderr)\n\n self.destdir = os.environ.get('DESTDIR', None)\n\n # Handle package buildlist/skiplist\n self.buildlist = buildlist or []\n self.skiplist = skiplist or []\n\n # Handle default authors/maintainers\n self.authors = authors or []\n self.maintainers = maintainers or []\n self.licenses = licenses or ['TODO']\n\n # Handle build options\n self.devel_layout = devel_layout if devel_layout else 'linked'\n self.install = install\n self.isolate_install = isolate_install\n\n # Handle additional cmake and make arguments\n self.cmake_args = cmake_args or []\n self.make_args = make_args or []\n self.jobs_args = jobs_args or []\n self.use_internal_make_jobserver = use_internal_make_jobserver\n self.use_env_cache = use_env_cache\n self.catkin_make_args = catkin_make_args or []\n\n # List of packages in the workspace is set externally\n self.packages = []\n\n # List of warnings about the workspace is set internally\n self.warnings = []\n\n # Initialize environment settings set by load_env\n self.manual_cmake_prefix_path = None\n self.cached_cmake_prefix_path = None\n self.env_cmake_prefix_path = None\n self.cmake_prefix_path = None\n\n self.extends = extends","def build_job_configs(self, args):\n job_configs = {}\n\n ttype = args['ttype']\n (targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(\n args, require_sim_name=True)\n if targets_yaml is None:\n return job_configs\n\n specconfig = NAME_FACTORY.resolve_specconfig(args)\n\n astro_priors = args['astro_priors']\n write_full = args.get('write_full', False)\n\n targets = load_yaml(targets_yaml)\n base_config = dict(nsims=args['nsims'],\n seed=args['seed'],\n specconfig=specconfig)\n\n for target_name, profile_list in list(targets.items()):\n for profile in profile_list:\n for astro_prior in astro_priors:\n if is_null(astro_prior):\n astro_prior = 'none'\n full_key = \"%s:%s:%s:%s\" % (\n target_name, profile, sim, astro_prior)\n name_keys = dict(target_type=ttype,\n target_name=target_name,\n sim_name=sim,\n profile=profile,\n astro_prior=astro_prior,\n fullpath=True)\n limitfile = NAME_FACTORY.sim_dmlimitsfile(**name_keys)\n first = args['seed']\n last = first + args['nsims'] - 1\n outfile = limitfile.replace(\n '_SEED.fits', '_collected_%06i_%06i.fits' %\n (first, last))\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\n if not write_full:\n outfile = None\n summaryfile = limitfile.replace(\n '_SEED.fits', '_summary_%06i_%06i.fits' %\n (first, last))\n job_config = base_config.copy()\n job_config.update(dict(limitfile=limitfile,\n astro_prior=astro_prior,\n outfile=outfile,\n summaryfile=summaryfile,\n logfile=logfile))\n job_configs[full_key] = job_config\n\n return job_configs","def copyPetscArguments(jobdir, argsfile):\n shutil.copyfile(argsfile, os.path.join(jobdir, \"petsc_commandline_arg\"))","def _create_job_spec(\n self,\n job_id: Text,\n training_input: Dict[Text, Any],\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\n\n job_spec = {\n 'display_name': job_id,\n 'job_spec': training_input,\n 'labels': job_labels,\n }\n return job_spec","def build_input_table(cls, name='inputTableName', input_name='input'):\n obj = cls(name)\n obj.exporter = 'get_input_table_name'\n obj.input_name = input_name\n return obj","def __init__(__self__, *,\n include_cluster_scope_resources: pulumi.Input[bool],\n object_type: pulumi.Input[str],\n snapshot_volumes: pulumi.Input[bool],\n excluded_namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n excluded_resource_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n included_namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n included_resource_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n label_selectors: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"include_cluster_scope_resources\", include_cluster_scope_resources)\n pulumi.set(__self__, \"object_type\", 'KubernetesClusterBackupDatasourceParameters')\n pulumi.set(__self__, \"snapshot_volumes\", snapshot_volumes)\n if excluded_namespaces is not None:\n pulumi.set(__self__, \"excluded_namespaces\", excluded_namespaces)\n if excluded_resource_types is not None:\n pulumi.set(__self__, \"excluded_resource_types\", excluded_resource_types)\n if included_namespaces is not None:\n pulumi.set(__self__, \"included_namespaces\", included_namespaces)\n if included_resource_types is not None:\n pulumi.set(__self__, \"included_resource_types\", included_resource_types)\n if label_selectors is not None:\n pulumi.set(__self__, \"label_selectors\", label_selectors)","def input_config_to_job_input(input_batch_id, job_name, job_level, input_config):\n JobInput = namedtuple(\n \"JobInput\",\n [\"input_manifest_s3_uri\", \"label_attribute_name\", \"label_category_s3_uri\"],\n )\n\n input_manifest_s3_uri = input_config.get(\"inputManifestS3Uri\")\n if input_manifest_s3_uri is not None:\n return JobInput(\n input_manifest_s3_uri=input_manifest_s3_uri,\n label_attribute_name=None,\n label_category_s3_uri=None,\n )\n\n chain_to_job_name = job_name\n chain_from_job_name = input_config[\"chainFromJobName\"]\n\n # Only support jobs within the current batch for now.\n if job_level == 1:\n raise Exception(\"can't chain in job_level 1\")\n\n batches = chainable_batches(input_batch_id, job_level)\n if len(batches) == 0:\n raise Exception(\"no chainable batches found\")\n\n processed_job_level_batch = next(\n iter(\n db.get_batch_metadata_by_labeling_job_name(\n chain_to_job_name, BatchMetadataType.PROCESS_LEVEL\n )\n ),\n None,\n )\n\n prev_level_jobs = []\n for batch in batches:\n prev_level_jobs += db.get_child_batch_metadata(\n batch[\"BatchId\"], BatchMetadataType.JOB_LEVEL\n )\n\n for job in prev_level_jobs:\n if job[BatchMetadataTableAttributes.LABELING_JOB_NAME] == chain_from_job_name:\n # If available, use the downsampled manifest file as input to the new job\n if processed_job_level_batch:\n processed_data_location = processed_job_level_batch[\n BatchMetadataTableAttributes.JOB_INPUT_LOCATION\n ]\n else:\n processed_data_location = None\n\n batch_output_location = (\n processed_data_location or job[BatchMetadataTableAttributes.JOB_OUTPUT_LOCATION]\n )\n\n return JobInput(\n input_manifest_s3_uri=batch_output_location,\n label_attribute_name=job[BatchMetadataTableAttributes.LABEL_ATTRIBUTE_NAME],\n label_category_s3_uri=job[BatchMetadataTableAttributes.LABEL_CATEGORY_CONFIG],\n )\n\n raise Exception(f\"chain job {chain_from_job_name} not found\")","def _create_job_spec(\n self,\n job_id: Text,\n training_input: Dict[Text, Any],\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\n\n job_spec = {\n 'jobId': job_id,\n 'trainingInput': training_input,\n 'labels': job_labels,\n }\n return job_spec","def svn_client_copy4(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def _deep_copy_arg_dict(input_arg_dict):\n output_arg_dict = {}\n for name, param in input_arg_dict.items():\n output_arg_dict[name] = param.copy()\n return output_arg_dict","def test_args_copy():\n args = cli.parse_args(['-c'])\n assert args.copy\n args = cli.parse_args(['--copy'])\n assert args.copy","def svn_client_copy5(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, svn_boolean_t_ignore_externals, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def copy(self):\n r = PredictionJobRequest()\n r.__dict__.update(self.__dict__)\n\n return r","def synthesize_employment_data(self, config):\r\n jobs_by_zone_by_sector_table_name = config['jobs_by_zone_by_sector']\r\n gridcells_table_name = config['gridcells']\r\n jobs_table_name = config['jobs']\r\n gridcells_output_table_name = config['gridcells_output']\r\n jobs_output_table_name = config['jobs_output']\r\n \r\n input_db_name = config['db_config'].database_name\r\n output_db_name = config['output_database_name']\r\n \r\n sectors = config['sector_names_and_ids']\r\n building_types_and_ids_and_home_based = config[\r\n 'building_type_column_names_and_ids_and_home_based']\r\n \r\n building_types = []\r\n building_ids = []\r\n home_based = [] \r\n for type, id, home in building_types_and_ids_and_home_based:\r\n building_types += [type]\r\n building_ids += [id]\r\n home_based += [home]\r\n \r\n \r\n from_database_configuration = ScenarioDatabaseConfiguration(\r\n database_name = input_db_name,\r\n host_name = config['db_config'].host_name,\r\n user_name = config['db_config'].user_name,\r\n password = config['db_config'].password \r\n )\r\n to_database_configuration = ScenarioDatabaseConfiguration(\r\n database_name = output_db_name,\r\n host_name = config['db_config'].host_name,\r\n user_name = config['db_config'].user_name,\r\n password = config['db_config'].password \r\n )\r\n\r\n FlattenScenarioDatabaseChain().copy_scenario_database(\r\n from_database_configuration = from_database_configuration, \r\n to_database_configuration = to_database_configuration,\r\n tables_to_copy = [gridcells_table_name, jobs_table_name])\r\n \r\n db_server = DatabaseServer(to_database_configuration) \r\n output_database = db_server.get_database(output_db_name)\r\n \r\n sector_name = 0; sector_id = 1\r\n \r\n sector = {}\r\n for entry in sectors:\r\n name = entry[sector_name]\r\n id = entry[sector_id]\r\n sector[id] = self._get_jobs_per_building_type_in_sector_by_zone(\r\n output_database, jobs_by_zone_by_sector_table_name, \r\n jobs_table_name, name, id)\r\n\r\n results = self._get_building_type_proportion_by_zone(output_database, \r\n gridcells_table_name)\r\n \r\n grid_id = 0; zone_id = 1\r\n dist = {}\r\n \r\n type_index = {}\r\n \r\n for name in building_types:\r\n for i in range(len(results[0])):\r\n column_name = results[0][i]\r\n if name == column_name:\r\n type_index[name] = i\r\n break;\r\n else:\r\n raise KeyError, ('No column by the name of \\'%s\\' found in '\r\n 'the database.' % name) \r\n\r\n for name in building_types:\r\n dist[name] = {}\r\n \r\n for row in results[1:]:\r\n for name in building_types:\r\n dist[name][row[zone_id]] = []\r\n \r\n for row in results[1:]:\r\n for name in building_types:\r\n dist[name][row[zone_id]] += [(row[grid_id], \r\n row[type_index[name]])]\r\n \r\n jobs_table_data = self._create_jobs_table_data(dist, sector,\r\n building_types_and_ids_and_home_based)\r\n \r\n output_database.execute('USE %(out_db)s' % {'out_db':output_db_name})\r\n \r\n output_database.execute(\"\"\"\r\n CREATE TABLE %(jobs_out)s (\r\n JOB_ID INT AUTO_INCREMENT, PRIMARY KEY(JOB_ID),\r\n GRID_ID INT, HOME_BASED INT, SECTOR_ID INT, BUILDING_TYPE INT);\r\n \"\"\" % {'jobs_out':jobs_output_table_name})\r\n \r\n if len(jobs_table_data) > 0:\r\n output_prefix = (\r\n \"\"\"INSERT INTO %(jobs_out)s \r\n (GRID_ID, HOME_BASED, SECTOR_ID, BUILDING_TYPE) VALUES\r\n \"\"\" % {'jobs_out':jobs_output_table_name})\r\n output_postfix = ';'\r\n \r\n step = 1000\r\n length = len(jobs_table_data)\r\n iterations = int(length/step) + 1\r\n \r\n for i in range(iterations):\r\n low = i*step\r\n high = (i+1)*step\r\n \r\n if high > length: high = length\r\n \r\n output_body = \"\"\r\n \r\n for j in range(low, high):\r\n output_body += (\r\n '(%(grid)s, %(home)s, %(sector)s, %(building)s),\\n' \r\n % jobs_table_data[j])\r\n \r\n output_query = \"%s%s%s\" % (output_prefix, \r\n output_body[:-2], \r\n output_postfix)\r\n\r\n output_database.execute(output_query)\r\n \r\n \r\n ### TODO: \r","def _map_arguments(self, args):\n config_yaml = args['config']\n config_dict = load_yaml(config_yaml)\n\n dry_run = args.get('dry_run', False)\n\n data = config_dict.get('data')\n comp = config_dict.get('comp')\n library = config_dict.get('library')\n models = config_dict.get('models')\n scratch = config_dict.get('scratch')\n\n self._set_link('prepare', SplitAndBinChain,\n comp=comp, data=data,\n ft1file=config_dict.get('ft1file'),\n hpx_order_ccube=config_dict.get('hpx_order_ccube'),\n hpx_order_expcube=config_dict.get('hpx_order_expcube'),\n scratch=scratch,\n dry_run=dry_run)\n\n self._set_link('diffuse-comp', DiffuseCompChain,\n comp=comp, data=data,\n library=library,\n make_xml=config_dict.get('make_diffuse_comp_xml', False),\n outdir=config_dict.get('merged_gasmap_dir', 'merged_gasmap'),\n dry_run=dry_run)\n\n self._set_link('catalog-comp', CatalogCompChain,\n comp=comp, data=data,\n library=library,\n make_xml=config_dict.get('make_catalog_comp_xml', False),\n nsrc=config_dict.get('catalog_nsrc', 500),\n dry_run=dry_run)\n \n self._set_link('assemble-model', AssembleModelChain,\n comp=comp, data=data,\n library=library,\n models=models,\n hpx_order=config_dict.get('hpx_order_fitting'),\n dry_run=dry_run)","def build_parms(args):\r\n readDir=args.dir\r\n #target_date=args.target_date\r\n target_date=args.target_date\r\n outdir=args.outdir \r\n parms = {\"readDir\":readDir,\r\n \"target_date\":target_date,\r\n \"outdir\":outdir}\r\n \r\n return(parms)","def build(self, data: dict) -> GemTable:\n table = GemTable.build(data)\n table.project_id = self.project_id\n table.session = self.session\n return table","def from_dict(data: Dict) -> 'JobConfig':\n job_name = list(data.keys())[0]\n return JobConfig(job_name=job_name,\n job_type=data[job_name].get('job_type', None),\n properties=data[job_name].get('properties', {}))","def build_job_configs(self, args):\n job_configs = {}\n\n ttype = args['ttype']\n (roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(\n args, require_sim_name=True)\n if roster_yaml is None:\n return job_configs\n\n specconfig = NAME_FACTORY.resolve_specconfig(args)\n\n astro_priors = args['astro_priors']\n write_full = args['write_full']\n first = args['seed']\n last = first + args['nsims'] - 1\n\n base_config = dict(nsims=args['nsims'],\n seed=args['seed'])\n\n roster_dict = load_yaml(roster_yaml)\n for roster_name in list(roster_dict.keys()):\n for astro_prior in astro_priors:\n if is_null(astro_prior):\n astro_prior = 'none'\n full_key = \"%s:%s:%s\" % (roster_name, sim, astro_prior)\n name_keys = dict(target_type=ttype,\n roster_name=roster_name,\n sim_name=sim,\n astro_prior=astro_prior,\n fullpath=True)\n\n limitfile = NAME_FACTORY.sim_stackedlimitsfile(**name_keys)\n outfile = limitfile.replace(\n '_SEED.fits', '_collected_%06i_%06i.fits' %\n (first, last))\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\n if not write_full:\n outfile = None\n summaryfile = limitfile.replace('_SEED.fits', '_summary.fits')\n\n job_config = base_config.copy()\n job_config.update(dict(limitfile=limitfile,\n specconfig=specconfig,\n astro_prior=astro_prior,\n outfile=outfile,\n summaryfile=summaryfile,\n logfile=logfile))\n job_configs[full_key] = job_config\n\n return job_configs","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n column_names: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\n column_wildcard: Optional[pulumi.Input[pulumi.InputType['DataCellsFilterColumnWildcardArgs']]] = None,\n database_name: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n row_filter: Optional[pulumi.Input[pulumi.InputType['DataCellsFilterRowFilterArgs']]] = None,\n table_catalog_id: Optional[pulumi.Input[str]] = None,\n table_name: Optional[pulumi.Input[str]] = None,\n __props__=None):\n ...","def svn_client_copy(svn_client_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def Copy(self, name, **kargs):\n if \"TOOLCHAIN\" in kargs and not kargs[\"TOOLCHAIN\"] is None:\n self.set_toolchain(kargs[\"TOOLCHAIN\"])\n if \"STATIC\" in kargs:\n self.static = kargs[\"STATIC\"]\n else:\n self.static = 0\n if \"TESTENV\" in kargs:\n self.testenv = kargs[\"TESTENV\"]\n else:\n self.testenv = 0\n \n new_self = Environment.Copy(self, **kargs)\n new_self.libs = copy.copy(self.libs)\n new_self.apps = copy.copy(self.apps)\n new_self.cpp_path = copy.copy(self.cpp_path)\n new_self.files = copy.copy(self.files)\n new_self.name = name\n #new_self.build_libs(*libs)\n return new_self","def getCloneArgs(self):\n\n values = {\n \"dest\": self.subnode_dest.makeClone()\n if self.subnode_dest is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def copy_config(cfg):\n res= dict(cfg)\n #model_param = dict(cfg['model_param'])\n model_param = dict(cfg.get('model_param', {}))\n res['model_param'] = model_param\n return res","def copy_unified_job(self, _eager_fields=None, **new_prompts):\n unified_job_class = self.__class__\n unified_jt_class = self._get_unified_job_template_class()\n parent_field_name = self._get_parent_field_name()\n fields = unified_jt_class._get_unified_job_field_names() | set([parent_field_name])\n\n create_data = {}\n if _eager_fields:\n create_data = _eager_fields.copy()\n create_data[\"launch_type\"] = \"relaunch\"\n\n prompts = self.launch_prompts()\n if self.unified_job_template and (prompts is not None):\n prompts.update(new_prompts)\n prompts['_eager_fields'] = create_data\n unified_job = self.unified_job_template.create_unified_job(**prompts)\n else:\n unified_job = copy_model_by_class(self, unified_job_class, fields, {})\n for fd, val in create_data.items():\n setattr(unified_job, fd, val)\n unified_job.save()\n\n # Labels copied here\n from awx.main.signals import disable_activity_stream\n\n with disable_activity_stream():\n copy_m2m_relationships(self, unified_job, fields)\n\n return unified_job","def parse_args(args):\n parser = argparse.ArgumentParser(description='Parse Mysql Copy account you want',add_help=False)\n connect_setting = parser.add_argument_group('connect setting')\n connect_setting.add_argument('-h','--host',dest='host',type=str,help='Host the MySQL database server located',default='127.0.0.1')\n connect_setting.add_argument('-u','--user',dest='user',type=str,help='MySQL Username to log in as',default='root')\n connect_setting.add_argument('-p','--password',dest='password',type=str,help='MySQL Password to use', default='')\n connect_setting.add_argument('-P', '--port', dest='port', type=int,help='MySQL port to use', default=3306)\n copy_user = parser.add_argument_group('copy user')\n copy_user.add_argument('--src-user',dest='srcuser',type=str,help='copy from the user',nargs='*',default='*')\n copy_user.add_argument('--src-host',dest='srchost',type=str,help='copy from the host',nargs='*',default='*')\n copy_user.add_argument('--dest-user',dest='destuser',type=str,help='copy to the user',nargs='*',default='')\n copy_user.add_argument('--dest-host',dest='desthost',type=str,help='copy to the host',nargs='*',default='')\n\n parser.add_argument('--help', dest='help', action='store_true', help='help infomation', default=False)\n\n return parser","def _generate_ipt_args_settings_in_construct(ipt_args_in_construct, settings):\n if settings and settings.op_ipt_type:\n input_type = settings.op_ipt_type\n if input_type == InputType.TENSOR.value:\n ipt_args_settings_in_construct = ipt_args_in_construct\n elif input_type == InputType.LIST.value:\n ipt_args_settings_in_construct = f\"({ipt_args_in_construct},)\"\n else:\n raise NodeInputTypeNotSupportError(f\"Input type[{input_type}] is not supported now.\")\n else:\n ipt_args_settings_in_construct = ipt_args_in_construct\n\n if settings and settings.op_extra_input:\n settings_value = settings.op_extra_input\n if settings_value:\n settings_in_construct = ', '.join([f\"{setting_val}\" for _, setting_val in settings_value.items()])\n ipt_args_settings_in_construct = ', '.join((ipt_args_settings_in_construct, settings_in_construct))\n\n return ipt_args_settings_in_construct","def __init__(self, *args, **kwargs):\n super(ColumnShiftTable, self).__init__(*args, **kwargs)\n # Override default template\n if hasattr(self, \"template_name\"):\n self.template_name = self.shifter_template\n else:\n self.template = self.shifter_template","def prepare_pr_optimal_model_condor_job(self, pool_type, pool_address, number_of_jobs, subtask_index, data_files, rank='0', extraArgs=''):\n ############\n copasi_file = 'auto_copasi_%d.$(Process).cps' % subtask_index\n output_file = ''\n \n \n \n if pool_type == 'ec2':\n binary_dir = '/usr/local/bin'\n transfer_executable = 'NO'\n else:\n binary_dir, binary = os.path.split(settings.COPASI_LOCAL_BINARY)\n transfer_executable = 'YES'\n \n input_files_string = ', '\n for data_file in data_files:\n input_files_string += (data_file + ', ')\n input_files_string = input_files_string.rstrip(', ')\n\n condor_job_string = Template(condor_spec.raw_condor_job_string).substitute(copasiFile=copasi_file, \n otherFiles=input_files_string,\n rank=rank,\n binary_dir = binary_dir,\n transfer_executable = transfer_executable,\n pool_type = pool_type,\n pool_address = pool_address,\n subtask=str(subtask_index),\n n = number_of_jobs,\n outputFile = output_file,\n extraArgs='',\n )\n \n condor_job_filename = 'auto_condor_%d.job'%subtask_index\n condor_job_full_filename = os.path.join(self.path, condor_job_filename)\n condor_file = open(condor_job_full_filename, 'w')\n condor_file.write(condor_job_string)\n condor_file.close()\n\n return condor_job_filename","def templateargs(self, target_jar, confs=None):\r\n raise NotImplementedError()","def load_params():\n # start arg parser\n parser = argparse.ArgumentParser(description='Apero Copy')\n # add arguments\n parser.add_argument('yaml', help='yaml file to use', type=str,\n default=None)\n parser.add_argument('--overwrite', help='overwrite existing files',\n action='store_true', default=False)\n parser.add_argument('--test', help='run in test mode (no copy or remove)',\n action='store_true', default=False)\n parser.add_argument('--symlinks', action='store_true', default=False,\n help='Copy in symlink mode (not recommended)')\n # get arguments\n args = vars(parser.parse_args())\n # ------------------------------------------------------------------\n # deal with getting yaml file\n # ------------------------------------------------------------------\n # deal with no yaml file set\n if args['yaml'] is None:\n emsg = 'yaml file must be set'\n raise AperoCopyError(emsg)\n # deal with bad path\n if not os.path.exists(args['yaml']):\n emsg = 'yaml file {0} does not exist'\n eargs = [args['yaml']]\n raise AperoCopyError(emsg.format(*eargs))\n # otherwise we read the yaml file\n params = read_yaml(args['yaml'])\n # add args to params\n for arg in args:\n if arg not in params:\n params[arg] = args[arg]\n # ------------------------------------------------------------------\n # return the parameters\n return params","def prepare_row(task, full):\n\n # Would like to include the Job ID in the default set of columns, but\n # it is a long value and would leave little room for status and update time.\n\n row_spec = collections.namedtuple('row_spec',\n ['key', 'optional', 'default_value'])\n\n # pyformat: disable\n default_columns = [\n row_spec('job-name', False, None),\n row_spec('task-id', True, None),\n row_spec('last-update', False, None)\n ]\n short_columns = default_columns + [\n row_spec('status-message', False, None),\n ]\n full_columns = default_columns + [\n row_spec('job-id', False, None),\n row_spec('user-id', False, None),\n row_spec('status', False, None),\n row_spec('status-detail', False, None),\n row_spec('create-time', False, None),\n row_spec('end-time', False, 'NA'),\n row_spec('internal-id', False, None),\n row_spec('logging', False, None),\n row_spec('inputs', False, {}),\n row_spec('outputs', False, {}),\n row_spec('envs', False, {}),\n row_spec('labels', False, {}),\n ]\n # pyformat: enable\n\n columns = full_columns if full else short_columns\n\n row = {}\n for col in columns:\n key, optional, default = col\n\n value = task.get_field(key, default)\n if not optional or value:\n row[key] = value\n\n return row","def init_jobs(self):\n self.jobsTableWidget.clear()\n self.jobsTableWidget.setColumnCount(6)\n self.jobsTableWidget.setHorizontalHeaderLabels(['Job Id', 'Description/Error', 'Submission Date', 'Status',\n 'Execute', 'Display'])\n header = self.jobsTableWidget.horizontalHeader()\n header.setSectionResizeMode(0, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(1, QtWidgets.QHeaderView.Stretch)\n header.setSectionResizeMode(2, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(3, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(4, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(5, QtWidgets.QHeaderView.ResizeToContents)","def from_dict(cls, dikt) -> 'JobOutputRequest':\n return util.deserialize_model(dikt, cls)","def load_raw_to_bq(event, context):\n\n import os\n\n\n print(f\"Processing .....\")\n\n file = event\n project = os.environ.get('ENV_PROJECT')\n dataset = os.environ.get('ENV_DATASET')\n bucket = file.get(\"bucket\")\n tableCsv = file.get(\"name\")\n tableDestList = tableCsv.split(\".\")\n tableDest = tableDestList[0]\n table_id = f'{project}.{dataset}.{tableDest}'\n\n from Configuration import Configuration\n\n Configuration(tableCsv,bucket,table_id)\n\n\n print(f\"End Process.\")","def __init__(__self__,\n resource_name: str,\n args: Optional[TransferConfigArgs] = None,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def clone(source, destination):\n\t\treturn \"CREATE DATABASE {0} WITH TEMPLATE {1};\".format(destination, source)","def __init__(self, table_name='casbin_rule', **kwargs):\n self.table_name = table_name\n self.dynamodb = boto3.client('dynamodb', **kwargs)\n try:\n\n self.dynamodb.create_table(\n TableName=self.table_name,\n\n AttributeDefinitions=[\n {\n 'AttributeName': 'id',\n 'AttributeType': 'S'\n }\n ],\n KeySchema=[\n {\n 'AttributeName': 'id',\n 'KeyType': 'HASH'\n },\n ],\n ProvisionedThroughput={\n 'ReadCapacityUnits': 10,\n 'WriteCapacityUnits': 10\n }\n )\n except self.dynamodb.exceptions.ResourceInUseException:\n pass","def __init__(self, postgresRunner, tablename, table_columns):\n self.postgresRunner = postgresRunner\n self.tablename = tablename\n self.table_config = table_columns\n self.table_keys = [column.get(\"name\") for column in table_columns]\n self.__run(\n _PostgresCrud__create_table_command(tablename, table_columns)\n )","def build_data(cmd, rel_new_path, new_md5, founded_path=None):\n data = {'cmd': cmd}\n if cmd == 'copy':\n data['file'] = {'src': founded_path,\n 'dst': rel_new_path,\n 'md5': new_md5,\n }\n else:\n data['file'] = {'filepath': rel_new_path,\n 'md5': new_md5,\n }\n return data","def __init__(self, jobArgs):\n logging.info(\"Constructing job with args %r\" % jobArgs)\n self.args = jobArgs\n\n self._setup()","def __init__(self, job_id=None, version=None, status=None, exit_status=None, exit_message=None, create_time=None, start_time=None, end_time=None, last_updated=None):\n self.swagger_types = {\n 'job_id': str,\n 'version': str,\n 'status': str,\n 'exit_status': str,\n 'exit_message': str,\n 'create_time': datetime,\n 'start_time': datetime,\n 'end_time': datetime,\n 'last_updated': datetime\n }\n\n self.attribute_map = {\n 'job_id': 'job_id',\n 'version': 'version',\n 'status': 'status',\n 'exit_status': 'exit_status',\n 'exit_message': 'exit_message',\n 'create_time': 'create_time',\n 'start_time': 'start_time',\n 'end_time': 'end_time',\n 'last_updated': 'last_updated'\n }\n\n self._job_id = job_id\n self._version = version\n self._status = status\n self._exit_status = exit_status\n self._exit_message = exit_message\n self._create_time = create_time\n self._start_time = start_time\n self._end_time = end_time\n self._last_updated = last_updated","def constructBundleJob(self, xml_node):\n name = os.path.join(self.dir, xml_node.find(\"name\").text)\n output_name = name + \".o\"\n xar_job = BitcodeBundle(self.arch, name, output_name)\n return xar_job","async def copy(self, _id: str, dst_id: str, *,\n rev: Optional[str] = None,\n dst_rev: Optional[str] = None,\n batch: Optional[bool] = None) -> dict:\n\n headers = dict(\n Destination=f'{dst_id}?rev={dst_rev}' if dst_rev else dst_id\n )\n\n params = dict(\n rev=rev,\n batch=\"ok\" if batch else None,\n )\n\n return await self.__connection.query('COPY', self._get_path(_id), params=params, headers=headers)","def make_job_config_json(self, job_description):\n bench_name = job_description[0]\n bench_type = job_description[1]\n bench_preference = job_description[2]\n config_file = self._node_mgr_path / f'{bench_name}_{bench_type}_{bench_preference}' / 'job.json'\n\n # FIXME: hard coded\n # Dict[str, Dict[str, Any]]\n output = dict()\n config = dict()\n config[\"name\"] = bench_name\n config[\"type\"] = bench_type\n config[\"num_of_threads\"] = 2\n if self._node_type == NodeType.IntegratedGPU:\n config[\"binding_cores\"] = \"0,3-5\"\n elif self._node_type == NodeType.CPU:\n config[\"binding_cores\"] = \"0-3\"\n config[\"numa_nodes\"] = \"0\"\n config[\"cpu_freq\"] = 2.1\n config[\"cpu_percent\"] = 100\n if self._node_type == NodeType.IntegratedGPU:\n config[\"gpu_freq\"] = 1300500000\n\n output[\"workloads\"] = config\n\n with config_file.open('w') as fp:\n fp.seek(0)\n json.dump(output, fp, indent=4)\n return config_file","def AddJobResourceArg(parser):\n\n return concept_parsers.ConceptParser.ForResource(\n 'job_name',\n GetJobResourceSpec(),\n 'Transcoder Job name',\n required=True).AddToParser(parser)","def getCloneArgs(self):\n\n values = {\n \"condition\": self.subnode_condition.makeClone(),\n \"yes_branch\": self.subnode_yes_branch.makeClone()\n if self.subnode_yes_branch is not None\n else None,\n \"no_branch\": self.subnode_no_branch.makeClone()\n if self.subnode_no_branch is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def build_job_configs(self, args):\n job_configs = {}\n\n components = Component.build_from_yamlfile(args['comp'])\n\n datafile = args['data']\n if datafile is None or datafile == 'None':\n return job_configs\n NAME_FACTORY.update_base_dict(args['data'])\n outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'], 'counts_cubes')\n\n inputfiles = create_inputlist(args['ft1file'])\n num_files = len(inputfiles)\n\n for comp in components:\n zcut = \"zmax%i\" % comp.zmax\n\n mktimelist = copy.copy(comp.mktimefilters)\n if not mktimelist:\n mktimelist.append('none')\n evtclasslist_keys = copy.copy(comp.evtclasses)\n if not evtclasslist_keys:\n evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]\n else:\n evtclasslist_vals = copy.copy(evtclasslist_keys)\n\n for mktimekey in mktimelist:\n for evtclassval in evtclasslist_vals:\n fullkey = comp.make_key(\n '%s_%s_{ebin_name}_%s_{evtype_name}' %\n (evtclassval, zcut, mktimekey))\n\n name_keys = dict(zcut=zcut,\n ebin=comp.ebin_name,\n psftype=comp.evtype_name,\n coordsys=comp.coordsys,\n irf_ver=NAME_FACTORY.irf_ver(),\n mktime=mktimekey,\n evclass=evtclassval,\n fullpath=True)\n\n ccube_name = os.path.basename(NAME_FACTORY.ccube(**name_keys))\n outfile = os.path.join(outdir_base, ccube_name)\n infiles = _make_input_file_list(outfile, num_files)\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\n job_configs[fullkey] = dict(args=infiles,\n output=outfile,\n logfile=logfile)\n\n return job_configs","def layout_copycat(source_network, target_network, source_column='name', target_column='name',\n grid_unmapped=True, select_unmapped=True, base_url=DEFAULT_BASE_URL):\n source_network = networks.get_network_name(source_network)\n target_network = networks.get_network_name(target_network)\n res = commands.commands_post(\n 'layout copycat sourceNetwork=\"' + source_network + '\" targetNetwork=\"' + target_network +\n '\" sourceColumn=\"' + source_column + '\" targetColumn=\"' + target_column +\n '\" gridUnmapped=\"' + str(grid_unmapped) + '\" selectUnmapped=\"' + str(select_unmapped),\n base_url=base_url)\n return res","def defaultconfig(self):\r\n\r\n config_data = {\r\n \"path_to_database\": \"FUDB/FOLLOWUP.DB\",\r\n \"path_to_frontend\": \"FUDB/\",\r\n \"path_to_dcs_info\": \"FUDB/\",\r\n \"path_to_bin\": \"bin/\",\r\n \"path_to_excels_exported_from_database\": \"excels exported/\",\r\n \"path_to_excels_to_be_imported_in_database\": \"excels to be imported/\",\r\n \"path_to_new_opfiles\": \"DC BATCHES IN WORK/0 NEW/\",\r\n \"path_to_batches_unassigned\": \"DC BATCHES IN WORK/1 UNASSIGNED/\",\r\n \"path_to_batches_prepfiles\": \"DC BATCHES IN WORK/2 PREPARED FILES/\",\r\n \"path_to_batches_assigned\": \"DC BATCHES IN WORK/3 ASSIGNED/\",\r\n \"path_to_batches_tobechecked\": \"DC BATCHES IN WORK/4 TO BE CHECKED/\",\r\n \"path_to_batches_tbimported\": \"DC BATCHES IN WORK/5 TO BE IMPORTED/\",\r\n \"path_to_batches_finished\": \"DC BATCHES IN WORK/6 FINISHED/\",\r\n \"path_to_batches_instandby\": \"DC BATCHES IN WORK/7 IN STANDBY/\",\r\n \"path_to_batches_unrecordable\": \"DC BATCHES IN WORK/8 UNRECORDABLE/\",\r\n \"batch_status_options_responsible\": \"PREP. OP FILE, IMPORTATION & SPLIT FILE, RELIABILITY & DATA UPGRADE, CHECK OP FILE, CHECK SPLIT FILE, CHECK FRONT END, **TO BE CHECKED\",\r\n \"batch_status_options_proofreader\": \"OP FILE OK, SPLIT FILE OK, FRONT END OK, **TO BE IMPORTED, **FINISHED, **REWORK, **STANDBY, **UNRECORDABLE\",\r\n \"batch_status_options_overall\": \"ONGOING, STANDBY, FINISHED, UNRECORDABLE\",\r\n \"aircrafts\": \"A300, A300-600, A310, A320, A330, A340, A350, A380\",\r\n \"split_batch_factor\": \"2, 3, 4, 5, 6, 7, 8, 9\",\r\n \"IDlentgh\": \"6\",\r\n \"port\": \"5000\"\r\n }\r\n \r\n if not os.path.isfile(os.path.join(self.cwd, \"config.json\")):\r\n self.func.write_json(config_data, self.cwd, fname=\"config.json\")","def copy(CopySource=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, SourceClient=None, Config=None):\n pass","def _kwargs(self):\n dict = DAG._kwargs(self) \n if (self.job): \n dict[\"inputpaths\"] = self.job.inputpaths\n dict[\"outputpath\"] = self.job.outputpath\n dict[\"job\"] = \"%s()\" % self.job.__class__.__name__\n return dict","def setup_jobs(self):\n transfer_args = [\"analysis_type\", \"perturbation\", \"num_permutations\", \"permutation_test_statistic\", \"loss_function\",\n \"importance_significance_level\", \"window_search_algorithm\", \"window_effect_size_threshold\"]\n jobs = [None] * self.num_jobs\n for idx in range(self.num_jobs):\n # Create and launch condor job\n features_filename = constants.INPUT_FEATURES_FILENAME.format(self.args.output_dir, idx)\n input_files = [features_filename, self.args.model_filename, self.args.model_loader_filename, self.args.data_filename]\n job_dir = f\"{self.args.output_dir}/outputs_{idx}\"\n cmd = f\"python3 -m anamod.core.worker -worker_idx {idx}\"\n for arg in transfer_args:\n if hasattr(self.args, arg):\n cmd += f\" -{arg} {getattr(self.args, arg)}\"\n # Relative file paths for non-shared FS, absolute for shared FS\n for name, path in dict(output_dir=job_dir, features_filename=features_filename, model_filename=self.args.model_filename,\n model_loader_filename=self.args.model_loader_filename, data_filename=self.args.data_filename).items():\n cmd += f\" -{name} {os.path.abspath(path)}\" if self.args.shared_filesystem else f\" -{name} {os.path.basename(path)}\"\n job = CondorJobWrapper(cmd, input_files, job_dir, shared_filesystem=self.args.shared_filesystem,\n memory=f\"{self.args.memory_requirement}GB\", disk=f\"{self.args.disk_requirement}GB\",\n avoid_bad_hosts=self.args.avoid_bad_hosts, retry_arbitrary_failures=self.args.retry_arbitrary_failures,\n cleanup=self.args.cleanup)\n jobs[idx] = job\n return jobs","def assert_task_args(cls, args: \"DictConfig\", shared_state: \"SharedTaskState\") -> None:\n assert isinstance(\n shared_state, SharedStaticTaskState\n ), \"Cannot assert args on a non-static state\"\n super().assert_task_args(args, shared_state)\n\n found_task_source = args.blueprint.task_source\n assert (\n found_task_source is not None\n ), \"Must provide a path to a javascript bundle in `task_source`\"\n\n found_task_path = os.path.expanduser(found_task_source)\n assert os.path.exists(\n found_task_path\n ), f\"Provided task source {found_task_path} does not exist.\"\n\n link_task_source = args.blueprint.link_task_source\n current_architect = args.architect._architect_type\n allowed_architects = [\"local\"]\n assert link_task_source == False or (\n link_task_source == True and current_architect in allowed_architects\n ), f\"`link_task_source={link_task_source}` is not compatible with architect type: {args.architect._architect_type}. Please check your task configuration.\"\n\n if link_task_source == False and current_architect in allowed_architects:\n logger.info(\n \"If you want your server to update on reload whenever you make changes to your webapp, then make sure to set \\n\\nlink_task_source: [blue]true[/blue]\\n\\nin your task's hydra configuration and run \\n\\n[purple]cd[/purple] webapp [red]&&[/red] [green]npm[/green] run dev:watch\\n\\nin a separate terminal window. For more information check out:\\nhttps://mephisto.ai/docs/guides/tutorials/custom_react/#12-launching-the-task\\n\",\n extra={\"markup\": True},\n )","def prepare_jobs_data(self, ecosystem, package, version):\n return \\\n {\n \"flow_arguments\": [\n {\n \"ecosystem\": ecosystem,\n \"name\": package,\n \"version\": version,\n \"force\": True,\n \"force_graph_sync\": True,\n \"recursive_limit\": 0\n }\n ],\n \"flow_name\": \"bayesianApiFlow\"\n }","def main(conn, label_config, table_name, start_date, end_date,\r\n preprocessing_prefix):\r\n label_sql = label_config['query']\r\n label_sql = label_sql.replace('{prefix}', preprocessing_prefix)\r\n label_sql = label_sql.replace('{start_date}', start_date)\r\n label_sql = label_sql.replace('{end_date}', end_date)\r\n drop_sql = f'drop table if exists {table_name};'\r\n create_sql = f'create table {table_name} as ({label_sql});'\r\n sql.run_sql_from_string(conn, drop_sql)\r\n sql.run_sql_from_string(conn, create_sql)","def Copy(self, copy):\n return _table.Table_Copy(self, copy)","def __prepare_job(self, job_wrapper, job_destination):\n command_line = None\n client = None\n remote_job_config = None\n compute_environment = None\n try:\n client = self.get_client_from_wrapper(job_wrapper)\n tool = job_wrapper.tool\n remote_job_config = client.setup(tool.id, tool.version)\n rewrite_parameters = LwrJobRunner.__rewrite_parameters( client )\n prepare_kwds = {}\n if rewrite_parameters:\n compute_environment = LwrComputeEnvironment( client, job_wrapper, remote_job_config )\n prepare_kwds[ 'compute_environment' ] = compute_environment\n job_wrapper.prepare( **prepare_kwds )\n self.__prepare_input_files_locally(job_wrapper)\n remote_metadata = LwrJobRunner.__remote_metadata( client )\n dependency_resolution = LwrJobRunner.__dependency_resolution( client )\n metadata_kwds = self.__build_metadata_configuration(client, job_wrapper, remote_metadata, remote_job_config)\n remote_command_params = dict(\n working_directory=remote_job_config['working_directory'],\n metadata_kwds=metadata_kwds,\n dependency_resolution=dependency_resolution,\n )\n remote_working_directory = remote_job_config['working_directory']\n # TODO: Following defs work for LWR, always worked for LWR but should be\n # calculated at some other level.\n remote_job_directory = os.path.abspath(os.path.join(remote_working_directory, os.path.pardir))\n remote_tool_directory = os.path.abspath(os.path.join(remote_job_directory, \"tool_files\"))\n container = self._find_container(\n job_wrapper,\n compute_working_directory=remote_working_directory,\n compute_tool_directory=remote_tool_directory,\n compute_job_directory=remote_job_directory,\n )\n command_line = build_command(\n self,\n job_wrapper=job_wrapper,\n container=container,\n include_metadata=remote_metadata,\n include_work_dir_outputs=False,\n remote_command_params=remote_command_params,\n )\n except Exception:\n job_wrapper.fail( \"failure preparing job\", exception=True )\n log.exception(\"failure running job %d\" % job_wrapper.job_id)\n\n # If we were able to get a command line, run the job\n if not command_line:\n job_wrapper.finish( '', '' )\n\n return command_line, client, remote_job_config, compute_environment"],"string":"[\n \"def GetTableCopyResourceArgs():\\n table_spec_data = yaml_data.ResourceYAMLData.FromPath('bq.table')\\n arg_specs = [\\n resource_args.GetResourcePresentationSpec(\\n verb='to copy from', name='source', required=True, prefixes=True,\\n attribute_overrides={'table': 'source'}, positional=False,\\n resource_data=table_spec_data.GetData()),\\n resource_args.GetResourcePresentationSpec(\\n verb='to copy to', name='destination',\\n required=True, prefixes=True,\\n attribute_overrides={'table': 'destination'}, positional=False,\\n resource_data=table_spec_data.GetData())]\\n fallthroughs = {\\n '--source.dataset': ['--destination.dataset'],\\n '--destination.dataset': ['--source.dataset']\\n }\\n return [concept_parsers.ConceptParser(arg_specs, fallthroughs)]\",\n \"def _create_jobs_table_data(self, dist_src, sectors, \\r\\n building_types_and_ids_and_home_based): \\r\\n res_sample = []; jobs_table = []\\r\\n no_samples = []\\r\\n\\r\\n for key in sectors.keys():\\r\\n sector_num = key\\r\\n sector = sectors[key]\\r\\n for zone in sector.keys():\\r\\n for building_type, number_of_jobs in sector[zone]:\\r\\n for type, id, home_based in building_types_and_ids_and_home_based:\\r\\n if building_type == id: \\r\\n dist = dist_src[type]\\r\\n break\\r\\n else:\\r\\n raise TypeError, (\\\"Invalid building type: %s\\\" \\r\\n % building_type)\\r\\n \\r\\n try:\\r\\n samples = self._zip_and_sample(dist[zone], \\r\\n int(number_of_jobs))\\r\\n if samples is None: \\r\\n no_samples += [(zone, building_type)]\\r\\n raise\\r\\n \\r\\n except:\\r\\n pass\\r\\n \\r\\n else:\\r\\n for type, id, home_based in building_types_and_ids_and_home_based:\\r\\n if building_type == id and home_based == True:\\r\\n home = 1 \\r\\n else: home = 0 \\r\\n \\r\\n for grid_id in samples:\\r\\n jobs_table += [{'sector':sector_num, \\r\\n 'home':home, \\r\\n 'building':building_type, \\r\\n 'grid':grid_id}]\\r\\n \\r\\n if len(no_samples) > 0:\\r\\n print ('No job samples created for (zone, building_type): %s!' \\r\\n % no_samples)\\r\\n \\r\\n return jobs_table\",\n \"def _copy_to_head_args(args: Namespace) -> Namespace:\\n\\n _head_args = copy.deepcopy(args)\\n _head_args.polling = args.polling\\n _head_args.port = args.port\\n _head_args.host = args.host[0]\\n _head_args.uses = args.uses\\n _head_args.pod_role = PodRoleType.HEAD\\n _head_args.runtime_cls = 'HeadRuntime'\\n _head_args.replicas = 1\\n\\n if args.name:\\n _head_args.name = f'{args.name}/head'\\n else:\\n _head_args.name = f'head'\\n\\n return _head_args\",\n \"def ProcessTableCopyOverwrite(ref, args, request):\\n del ref # Unused\\n if args.overwrite:\\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\\n return request\",\n \"def test_create_copy(self):\\n\\n config = {\\n 'version': '2.0',\\n 'input_files': {\\n 'INPUT_1': [{\\n 'id': 1234,\\n 'type': 'PRODUCT',\\n 'workspace_name': 'wksp-name',\\n 'workspace_path': 'the/workspace/path/file.json',\\n 'local_file_name': 'file_abcdfeg.json',\\n 'is_deleted': False,\\n }]\\n },\\n 'output_workspaces': {\\n 'OUTPUT_1': 'WORKSPACE_1'\\n },\\n 'tasks': [\\n {\\n 'task_id': 'task-1234',\\n 'type': 'main',\\n 'resources': {'cpu': 1.0},\\n 'args': 'foo ${INPUT_1} ${JOB_OUTPUT_DIR}',\\n 'env_vars': {'ENV_VAR_NAME': 'ENV_VAR_VALUE'},\\n 'workspaces': {'WORKSPACE_NAME': {'mode': 'ro'}},\\n 'mounts': {'MOUNT_NAME': 'MOUNT_VOLUME_NAME'},\\n 'settings': {'SETTING_NAME': 'SETTING_VALUE'},\\n 'volumes': {\\n 'VOLUME_NAME_1': {\\n 'container_path': '/the/container/path',\\n 'mode': 'ro',\\n 'type': 'host',\\n 'host_path': '/the/host/path'\\n },\\n 'VOLUME_NAME_2': {\\n 'container_path': '/the/other/container/path',\\n 'mode': 'rw',\\n 'type': 'volume',\\n 'driver': 'SUPER_DRIVER_5000',\\n 'driver_opts': {'turbo': 'yes-pleez'}\\n }\\n },\\n 'docker_params': [{'flag': 'hello', 'value': 'scale'}]\\n }\\n ]\\n }\\n exe_config = ExecutionConfiguration(config)\\n\\n copy = exe_config.create_copy()\\n self.assertDictEqual(copy.get_dict(), config)\",\n \"def _GetMigrationJob(\\n self,\\n source_ref,\\n destination_ref,\\n conversion_workspace_ref,\\n cmek_key_ref,\\n args,\\n ):\\n migration_job_type = self.messages.MigrationJob\\n labels = labels_util.ParseCreateArgs(\\n args, self.messages.MigrationJob.LabelsValue\\n )\\n type_value = self._GetType(migration_job_type, args.type)\\n source = source_ref.RelativeName()\\n destination = destination_ref.RelativeName()\\n params = {}\\n if args.IsSpecified('peer_vpc'):\\n params['vpcPeeringConnectivity'] = self._GetVpcPeeringConnectivity(args)\\n elif args.IsSpecified('vm_ip'):\\n params['reverseSshConnectivity'] = self._GetReverseSshConnectivity(args)\\n elif args.IsSpecified('static_ip'):\\n params['staticIpConnectivity'] = self._GetStaticIpConnectivity()\\n\\n migration_job_obj = migration_job_type(\\n labels=labels,\\n displayName=args.display_name,\\n state=migration_job_type.StateValueValuesEnum.CREATING,\\n type=type_value,\\n dumpPath=args.dump_path,\\n source=source,\\n destination=destination,\\n **params)\\n if conversion_workspace_ref is not None:\\n migration_job_obj.conversionWorkspace = self._GetConversionWorkspaceInfo(\\n conversion_workspace_ref, args\\n )\\n if cmek_key_ref is not None:\\n migration_job_obj.cmekKeyName = cmek_key_ref.RelativeName()\\n\\n if args.IsKnownAndSpecified('filter'):\\n args.filter, server_filter = filter_rewrite.Rewriter().Rewrite(\\n args.filter\\n )\\n migration_job_obj.filter = server_filter\\n\\n if args.IsKnownAndSpecified('dump_parallel_level'):\\n migration_job_obj.performanceConfig = self._GetPerformanceConfig(args)\\n\\n return migration_job_obj\",\n \"def infocalypse_copy(ui_, repo, **opts):\\n params, stored_cfg = get_config_info(ui_, opts)\\n\\n insert_uri = opts['inserturi']\\n if insert_uri == '':\\n # REDFLAG: fix parameter definition so that it is required?\\n ui_.warn(\\\"Please set the insert URI with --inserturi.\\\\n\\\")\\n return\\n\\n request_uri = opts['requesturi']\\n if request_uri == '':\\n request_uri = stored_cfg.get_request_uri(repo.root)\\n if not request_uri:\\n ui_.warn(\\\"There is no stored request URI for this repo.\\\\n\\\"\\n \\\"Please set one with the --requesturi option.\\\\n\\\")\\n return\\n\\n params['INSERT_URI'] = insert_uri\\n params['REQUEST_URI'] = request_uri\\n execute_copy(ui_, repo, params, stored_cfg)\",\n \"def __get_datatables_args():\\n\\n table_args = dict()\\n\\n #\\n # Common Arguments\\n #\\n\\n table_args['column-count'] = 0\\n table_args['sort-col-count'] = 0\\n\\n if request.args.get('draw'):\\n table_args['sequence'] = request.args.get('draw')\\n\\n if request.args.get('start'):\\n table_args['offset'] = int(request.args.get('start'))\\n\\n if request.args.get('length'):\\n table_args['limit'] = int(request.args.get('length'))\\n\\n if request.args.get('search[value]'):\\n table_args['filter'] = request.args.get('search[value]')\\n\\n if request.args.get('search[regex]'):\\n table_args['filter-regex'] = request.args.get('search[regex]')\\n\\n #\\n # Custom Arguments\\n #\\n\\n if request.args.get('time_filter'):\\n table_args['time_filter'] = request.args.get('time_filter')\\n\\n i = 0\\n while True:\\n if request.args.get('columns[%d][data]' % i):\\n table_args['column-count'] += 1\\n table_args['mDataProp_%d' % i] = request.args.get('columns[%d][data]' % i)\\n else:\\n break\\n\\n #\\n # Column Search\\n #\\n\\n if request.args.get('columns[%d][searchable]' % i):\\n table_args['bSearchable_%d' % i] = request.args.get('columns[%d][searchable]' % i)\\n\\n if request.args.get('columns[%d][search][value]' % i):\\n table_args['sSearch_%d' % i] = request.args.get('columns[%d][search][value]' % i)\\n\\n if request.args.get('columns[%d][search][regex]' % i):\\n table_args['bRegex_%d' % i] = request.args.get('columns[%d][search][regex]' % i)\\n\\n #\\n # Column Sort\\n #\\n\\n if request.args.get('columns[%d][orderable]' % i):\\n table_args['bSortable_%d' % i] = request.args.get('columns[%d][orderable]' % i)\\n\\n if request.args.get('order[%d][column]' % i):\\n table_args['sort-col-count'] += 1\\n table_args['iSortCol_%d' % i] = int(request.args.get('order[%d][column]' % i))\\n\\n if request.args.get('order[%d][dir]' % i):\\n table_args['sSortDir_%d' % i] = request.args.get('order[%d][dir]' % i)\\n\\n i += 1\\n\\n return table_args\",\n \"def initiate_build(self, config: Union[TableConfig, str, UUID],\\n version: Union[str, UUID] = None) -> JobSubmissionResponse:\\n if isinstance(config, TableConfig):\\n if version is not None:\\n logger.warning('Ignoring version {} since config object was provided.'\\n .format(version))\\n if config.version_number is None:\\n raise ValueError('Cannot build table from config which has no version. '\\n 'Try registering the config before building.')\\n if config.config_uid is None:\\n raise ValueError('Cannot build table from config which has no uid. '\\n 'Try registering the config before building.')\\n uid = config.config_uid\\n version = config.version_number\\n else:\\n if version is None:\\n raise ValueError('Version must be specified when building by config uid.')\\n uid = config\\n job_id = uuid4()\\n logger.info('Building table from config {} version {} with job ID {}...'\\n .format(uid, version, job_id))\\n path = 'projects/{}/ara-definitions/{}/versions/{}/build'.format(\\n self.project_id, uid, version\\n )\\n response = self.session.post_resource(\\n path=path,\\n json={},\\n params={\\n 'job_id': job_id\\n }\\n )\\n submission = JobSubmissionResponse.build(response)\\n logger.info('Build job submitted with job ID {}.'.format(submission.job_id))\\n return submission\",\n \"def __gen_datatable__(self):\\n # | - __generate_data_table\\n rows_list = []\\n for Job_i in self.Job_list:\\n # | - FOR LOOP BODY\\n entry_param_dict = {}\\n for prop, value in Job_i.job_params.items():\\n entry_param_dict[prop] = value\\n\\n entry_param_dict[\\\"Job\\\"] = Job_i\\n entry_param_dict[\\\"path\\\"] = Job_i.full_path\\n entry_param_dict[\\\"max_revision\\\"] = Job_i.max_revision\\n entry_param_dict[\\\"revision_number\\\"] = Job_i.revision_number\\n\\n rows_list.append(entry_param_dict)\\n # __|\\n\\n data_frame = pd.DataFrame(rows_list)\\n\\n return(data_frame)\\n # __|\",\n \"def __init__(self, job_template_name, job_input, device_list,\\n api_server_config, logger, amqp_client,\\n transaction_id, transaction_descr, args):\\n self._job_template_name = job_template_name\\n self._job_input = job_input\\n self._device_list = device_list\\n self._api_server_config = api_server_config\\n self._logger = logger\\n self._job_id = None\\n self._job_status = None\\n self._amqp_client = amqp_client\\n self._transaction_id = transaction_id\\n self._transaction_descr = transaction_descr\\n self._args = args\\n super(JobHandler, self).__init__()\",\n \"def get_merged_args(args):\\n config_dict = load_config(args.config)\\n\\n args_dict = {\\n \\\"cleaning_policy\\\": args.cleaning_policy,\\n \\\"clear\\\": args.clear,\\n \\\"content\\\": args.content,\\n \\\"dry_run\\\": args.dry_run,\\n \\\"force\\\": args.force,\\n \\\"in_lines\\\": args.in_lines,\\n \\\"max_size\\\": args.max_size,\\n \\\"regex\\\": args.regex,\\n \\\"restore\\\": args.restore,\\n \\\"rmdir\\\": args.rmdir,\\n \\\"short\\\": args.short,\\n \\\"silent\\\": args.silent,\\n \\\"storage_time\\\": args.storage_time,\\n \\\"wastebasket_path\\\": args.wastebasket_path\\n }\\n\\n for arg, value in args_dict.iteritems():\\n if not value:\\n args_dict[arg] = config_dict[arg]\\n\\n if args_dict[\\\"cleaning_policy\\\"] == POLICY:\\n args_dict[\\\"cleaning_policy\\\"] = config_dict[\\\"cleaning_policy\\\"]\\n\\n if args_dict[\\\"storage_time\\\"] == STORAGE_TIME:\\n args_dict[\\\"storage_time\\\"] = config_dict[\\\"storage_time\\\"]\\n\\n if args_dict[\\\"max_size\\\"] == MAX_SIZE:\\n args_dict[\\\"max_size\\\"] = config_dict[\\\"max_size\\\"]\\n\\n return args_dict\",\n \"def __copy__(self):\\n from bn.distribs.distribution_builder import MultivariateTableBuilder\\n builder = MultivariateTableBuilder()\\n for assignment in self._table.keys():\\n builder.add_row(copy(assignment), self._table[assignment])\\n\\n return builder.build()\",\n \"def CopyTapSettings(self, *args, **kwargs):\\n # type: (*Any, **Any) -> None\\n payload = { \\\"Arg1\\\": self.href }\\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\\n for item in kwargs.items(): payload[item[0]] = item[1]\\n return self._execute('copyTapSettings', payload=payload, response_object=None)\",\n \"def __copy__(self):\\n # prepare unnamed arguments\\n args = [getattr(self, arg) for arg in self._copy_conf['args']]\\n\\n # prepare named arguments\\n kwargs = {}\\n for arg in self._copy_conf['kwargs']:\\n # if arg is a tuple, the first entry will be the named kwargs, and\\n # the second will be the name of the attribute to copy\\n name = arg\\n if isinstance(arg, tuple):\\n name, arg = arg\\n if hasattr(self, arg):\\n kwargs[name] = getattr(self, arg)\\n\\n # create the new instance\\n new_copy = self.__class__(*args, **kwargs)\\n\\n # then copy attributes\\n for attr_name in self._copy_conf['attrs']:\\n if hasattr(self, attr_name):\\n setattr(new_copy, attr_name, getattr(self, attr_name))\\n\\n return new_copy\",\n \"def visit_copy_command(element, compiler, **kw):\\n qs = \\\"\\\"\\\"COPY {table}{columns} FROM :data_location\\n WITH CREDENTIALS AS :credentials\\n {format}\\n {parameters}\\\"\\\"\\\"\\n parameters = []\\n bindparams = [\\n sa.bindparam(\\n 'data_location',\\n value=element.data_location,\\n type_=sa.String,\\n ),\\n sa.bindparam(\\n 'credentials',\\n value=element.credentials,\\n type_=sa.String,\\n ),\\n ]\\n\\n if element.format == Format.csv:\\n format_ = 'FORMAT AS CSV'\\n if element.quote is not None:\\n format_ += ' QUOTE AS :quote_character'\\n bindparams.append(sa.bindparam(\\n 'quote_character',\\n value=element.quote,\\n type_=sa.String,\\n ))\\n elif element.format == Format.json:\\n format_ = 'FORMAT AS JSON AS :json_option'\\n bindparams.append(sa.bindparam(\\n 'json_option',\\n value=element.path_file,\\n type_=sa.String,\\n ))\\n elif element.format == Format.avro:\\n format_ = 'FORMAT AS AVRO AS :avro_option'\\n bindparams.append(sa.bindparam(\\n 'avro_option',\\n value=element.path_file,\\n type_=sa.String,\\n ))\\n elif element.format == Format.orc:\\n format_ = 'FORMAT AS ORC'\\n elif element.format == Format.parquet:\\n format_ = 'FORMAT AS PARQUET'\\n elif element.format == Format.fixed_width and element.fixed_width is None:\\n raise sa_exc.CompileError(\\n \\\"'fixed_width' argument required for format 'FIXEDWIDTH'.\\\")\\n else:\\n format_ = ''\\n\\n if element.delimiter is not None:\\n parameters.append('DELIMITER AS :delimiter_char')\\n bindparams.append(sa.bindparam(\\n 'delimiter_char',\\n value=element.delimiter,\\n type_=sa.String,\\n ))\\n\\n if element.fixed_width is not None:\\n parameters.append('FIXEDWIDTH AS :fixedwidth_spec')\\n bindparams.append(sa.bindparam(\\n 'fixedwidth_spec',\\n value=_process_fixed_width(element.fixed_width),\\n type_=sa.String,\\n ))\\n\\n if element.compression is not None:\\n parameters.append(Compression(element.compression).value)\\n\\n if element.manifest:\\n parameters.append('MANIFEST')\\n\\n if element.accept_any_date:\\n parameters.append('ACCEPTANYDATE')\\n\\n if element.accept_inv_chars is not None:\\n parameters.append('ACCEPTINVCHARS AS :replacement_char')\\n bindparams.append(sa.bindparam(\\n 'replacement_char',\\n value=element.accept_inv_chars,\\n type_=sa.String\\n ))\\n\\n if element.blanks_as_null:\\n parameters.append('BLANKSASNULL')\\n\\n if element.date_format is not None:\\n parameters.append('DATEFORMAT AS :dateformat_string')\\n bindparams.append(sa.bindparam(\\n 'dateformat_string',\\n value=element.date_format,\\n type_=sa.String,\\n ))\\n\\n if element.empty_as_null:\\n parameters.append('EMPTYASNULL')\\n\\n if element.encoding is not None:\\n parameters.append('ENCODING AS ' + Encoding(element.encoding).value)\\n\\n if element.escape:\\n parameters.append('ESCAPE')\\n\\n if element.explicit_ids:\\n parameters.append('EXPLICIT_IDS')\\n\\n if element.fill_record:\\n parameters.append('FILLRECORD')\\n\\n if element.ignore_blank_lines:\\n parameters.append('IGNOREBLANKLINES')\\n\\n if element.ignore_header is not None:\\n parameters.append('IGNOREHEADER AS :number_rows')\\n bindparams.append(sa.bindparam(\\n 'number_rows',\\n value=element.ignore_header,\\n type_=sa.Integer,\\n ))\\n\\n if element.dangerous_null_delimiter is not None:\\n parameters.append(\\\"NULL AS '%s'\\\" % element.dangerous_null_delimiter)\\n\\n if element.remove_quotes:\\n parameters.append('REMOVEQUOTES')\\n\\n if element.roundec:\\n parameters.append('ROUNDEC')\\n\\n if element.time_format is not None:\\n parameters.append('TIMEFORMAT AS :timeformat_string')\\n bindparams.append(sa.bindparam(\\n 'timeformat_string',\\n value=element.time_format,\\n type_=sa.String,\\n ))\\n\\n if element.trim_blanks:\\n parameters.append('TRIMBLANKS')\\n\\n if element.truncate_columns:\\n parameters.append('TRUNCATECOLUMNS')\\n\\n if element.comp_rows:\\n parameters.append('COMPROWS :numrows')\\n bindparams.append(sa.bindparam(\\n 'numrows',\\n value=element.comp_rows,\\n type_=sa.Integer,\\n ))\\n\\n if element.comp_update:\\n parameters.append('COMPUPDATE ON')\\n elif element.comp_update is not None:\\n parameters.append('COMPUPDATE OFF')\\n\\n if element.max_error is not None:\\n parameters.append('MAXERROR AS :error_count')\\n bindparams.append(sa.bindparam(\\n 'error_count',\\n value=element.max_error,\\n type_=sa.Integer,\\n ))\\n\\n if element.no_load:\\n parameters.append('NOLOAD')\\n\\n if element.stat_update:\\n parameters.append('STATUPDATE ON')\\n elif element.stat_update is not None:\\n parameters.append('STATUPDATE OFF')\\n\\n if element.region is not None:\\n parameters.append('REGION :region')\\n bindparams.append(sa.bindparam(\\n 'region',\\n value=element.region,\\n type_=sa.String\\n ))\\n\\n columns = ' (%s)' % ', '.join(\\n compiler.preparer.format_column(column) for column in element.columns\\n ) if element.columns else ''\\n\\n qs = qs.format(\\n table=compiler.preparer.format_table(element.table),\\n columns=columns,\\n format=format_,\\n parameters='\\\\n'.join(parameters)\\n )\\n\\n return compiler.process(sa.text(qs).bindparams(*bindparams), **kw)\",\n \"def create_job_configuration(start_time: str) -> ItemsJobConfig:\\n # Create job configuration\\n config = {\\n 'source_url': os.getenv(\\\"ITEMS_SOURCE_URL\\\", default=\\\"\\\"),\\n 'dest_new_url': os.getenv(\\\"ITEMS_DEST_NEW_URL\\\", default=\\\"\\\"),\\n 'dest_updates_url': os.getenv(\\\"ITEMS_DEST_UPDATES_URL\\\", default=\\\"\\\"),\\n 'caiasoft_api_key': os.getenv('CAIASOFT_API_KEY', default=\\\"\\\"),\\n 'storage_dir': os.getenv('ITEMS_STORAGE_DIR', default=\\\"\\\"),\\n 'last_success_lookup': os.getenv('ITEMS_LAST_SUCCESS_LOOKUP', default=\\\"\\\")\\n }\\n\\n job_id_prefix = \\\"caia.items\\\"\\n\\n job_config = ItemsJobConfig(config, job_id_prefix, start_time)\\n logger.info(f\\\"Job Id: {job_config['job_id']}\\\")\\n logger.debug(f\\\"job_config={job_config}\\\")\\n\\n return job_config\",\n \"def __generate_data_table__(self):\\n # | - __generate_data_table__\\n rows_list = []\\n for job in self.job_var_lst:\\n revisions = self.job_revision_number(job)\\n for revision in range(revisions + 1)[1:]:\\n # | - FOR LOOP BODY\\n entry_param_dict = {}\\n for prop in job:\\n entry_param_dict[prop[\\\"property\\\"]] = prop[\\\"value\\\"]\\n\\n entry_param_dict[\\\"variable_list\\\"] = job\\n entry_param_dict[\\\"path\\\"] = self.var_lst_to_path(job)\\n\\n entry_param_dict[\\\"max_revision\\\"] = revisions\\n entry_param_dict[\\\"revision_number\\\"] = revision\\n\\n rows_list.append(entry_param_dict)\\n # __|\\n\\n data_frame = pd.DataFrame(rows_list)\\n\\n return(data_frame)\\n # __|\",\n \"def from_mapping(context: CreateCommandsContext, dry_run):\\n if dry_run:\\n logger.info(\\\"** Dry run, nothing will be sent to server **\\\")\\n\\n # Make sure no jobs are actually created\\n context.client_tool.create_path_job = mock_create\\n context.client_tool.create_pacs_job = mock_create\\n\\n job_sets = extract_job_sets(\\n context.default_parameters(), context.get_mapping()\\n )\\n\\n # inspect project name and destination to present the next question to the user\\n project_names = set()\\n destination_paths = set()\\n for job_set in job_sets:\\n project_names.add(job_set.get_param_by_type(Project).value)\\n destination_paths.add(job_set.get_param_by_type(DestinationPath).value)\\n\\n question = (\\n f\\\"This will create {len(job_sets)} jobs on \\\"\\n f\\\"{context.get_active_server().name},\\\"\\n f\\\" for projects '{list(project_names)}', writing data to \\\"\\n f\\\"'{[str(x) for x in destination_paths]}'. Are you sure?\\\"\\n )\\n if not click.confirm(question):\\n logger.info(\\\"Cancelled\\\")\\n return\\n\\n created_job_ids = create_jobs(context, job_sets)\\n\\n if created_job_ids:\\n context.add_to_batch(created_job_ids)\\n\\n logger.info(\\\"Done\\\")\",\n \"def _prepare(self):\\n logging.info('-> copy configuration...')\\n path_cofig = self.params['path_config_bUnwarpJ']\\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\\n os.path.basename(path_cofig)))\\n if 'path_config_IJ_SIFT' in self.params:\\n path_cofig = self.params['path_config_IJ_SIFT']\\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\\n os.path.basename(path_cofig)))\\n if 'path_config_IJ_MOPS' in self.params:\\n path_cofig = self.params['path_config_IJ_MOPS']\\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\\n os.path.basename(path_cofig)))\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n copy: Optional[pulumi.Input[pulumi.InputType['JobCopyArgs']]] = None,\\n extract: Optional[pulumi.Input[pulumi.InputType['JobExtractArgs']]] = None,\\n job_id: Optional[pulumi.Input[str]] = None,\\n job_timeout_ms: Optional[pulumi.Input[str]] = None,\\n labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n load: Optional[pulumi.Input[pulumi.InputType['JobLoadArgs']]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n project: Optional[pulumi.Input[str]] = None,\\n query: Optional[pulumi.Input[pulumi.InputType['JobQueryArgs']]] = None,\\n __props__=None,\\n __name__=None,\\n __opts__=None):\\n if __name__ is not None:\\n warnings.warn(\\\"explicit use of __name__ is deprecated\\\", DeprecationWarning)\\n resource_name = __name__\\n if __opts__ is not None:\\n warnings.warn(\\\"explicit use of __opts__ is deprecated, use 'opts' instead\\\", DeprecationWarning)\\n opts = __opts__\\n if opts is None:\\n opts = pulumi.ResourceOptions()\\n if not isinstance(opts, pulumi.ResourceOptions):\\n raise TypeError('Expected resource options to be a ResourceOptions instance')\\n if opts.version is None:\\n opts.version = _utilities.get_version()\\n if opts.id is None:\\n if __props__ is not None:\\n raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')\\n __props__ = dict()\\n\\n __props__['copy'] = copy\\n __props__['extract'] = extract\\n if job_id is None:\\n raise TypeError(\\\"Missing required property 'job_id'\\\")\\n __props__['job_id'] = job_id\\n __props__['job_timeout_ms'] = job_timeout_ms\\n __props__['labels'] = labels\\n __props__['load'] = load\\n __props__['location'] = location\\n __props__['project'] = project\\n __props__['query'] = query\\n __props__['job_type'] = None\\n __props__['user_email'] = None\\n super(Job, __self__).__init__(\\n 'gcp:bigquery/job:Job',\\n resource_name,\\n __props__,\\n opts)\",\n \"def build_from_config(self, config: Union[TableConfig, str, UUID], *,\\n version: Union[str, int] = None,\\n timeout: float = 15 * 60) -> GemTable:\\n job = self.initiate_build(config, version)\\n return self.get_by_build_job(job, timeout=timeout)\",\n \"def _GetUpdatedMigrationJob(\\n self, migration_job, source_ref, destination_ref, args):\\n update_fields = self._GetUpdateMask(args)\\n if args.IsSpecified('display_name'):\\n migration_job.displayName = args.display_name\\n if args.IsSpecified('type'):\\n migration_job.type = self._GetType(self.messages.MigrationJob, args.type)\\n if args.IsSpecified('dump_path'):\\n migration_job.dumpPath = args.dump_path\\n if args.IsSpecified('source'):\\n migration_job.source = source_ref.RelativeName()\\n if args.IsSpecified('destination'):\\n migration_job.destination = destination_ref.RelativeName()\\n if args.IsKnownAndSpecified('dump_parallel_level'):\\n migration_job.performanceConfig = self._GetPerformanceConfig(args)\\n self._UpdateConnectivity(migration_job, args)\\n self._UpdateLabels(args, migration_job, update_fields)\\n return migration_job, update_fields\",\n \"def __init__(self, job_spec: JobSpec):\\n self.job_spec = job_spec\\n \\n self.merge_rules = spark.read.csv(job_spec.mapping_document_path, header='true').toPandas()\\n\\n self.join_map = JoinMap()\\n \\n # defined externally\\n self.merge_action_map = merge_action_map\",\n \"def _init_from_config(self):\\n self.arch = self.job_config.get('arch', 'x86_64')\\n self.os_type = self.job_config.get(\\\"os_type\\\")\\n self.flavor = self.job_config.get(\\\"flavor\\\")\\n self.codename = self.job_config.get(\\\"codename\\\")\\n self.os_version = self._get_version()\\n # if os_version is given, prefer version/codename derived from it\\n if self.os_version:\\n self.os_version, self.codename = \\\\\\n OS.version_codename(self.os_type, self.os_version)\\n self.branch = self.job_config.get(\\\"branch\\\")\\n self.tag = self.job_config.get(\\\"tag\\\")\\n self.ref = self.job_config.get(\\\"ref\\\")\\n self.distro = self._get_distro(\\n distro=self.os_type,\\n version=self.os_version,\\n codename=self.codename,\\n )\\n self.pkg_type = \\\"deb\\\" if self.os_type.lower() in (\\n \\\"ubuntu\\\",\\n \\\"debian\\\",\\n ) else \\\"rpm\\\"\\n\\n if not getattr(self, 'flavor'):\\n # avoiding circular imports\\n from teuthology.suite.util import get_install_task_flavor\\n # when we're initializing from a full teuthology config, not just a\\n # task config we need to make sure we're looking at the flavor for\\n # the install task\\n self.flavor = get_install_task_flavor(self.job_config)\",\n \"def table_creater(self, tablename, columnnames, entries):\\n createrurl = self.casjobsurl + '/contexts/MyDB/query'\",\n \"def create_compilation_job(CompilationJobName=None, RoleArn=None, InputConfig=None, OutputConfig=None, StoppingCondition=None):\\n pass\",\n \"def prepare_pr_condor_job(self, pool_type, pool_address, number_of_jobs, subtask_index, data_files, rank='0', extraArgs=''):\\n ############\\n copasi_file = 'auto_copasi_%d.$(Process).cps' % subtask_index\\n output_file = 'output_%d.$(Process).txt' % subtask_index\\n \\n \\n \\n if pool_type == 'ec2':\\n binary_dir = '/usr/local/bin'\\n transfer_executable = 'NO'\\n else:\\n binary_dir, binary = os.path.split(settings.COPASI_LOCAL_BINARY)\\n transfer_executable = 'YES'\\n \\n input_files_string = ', '\\n for data_file in data_files:\\n input_files_string += (data_file + ', ')\\n input_files_string = input_files_string.rstrip(', ')\\n\\n condor_job_string = Template(condor_spec.raw_condor_job_string).substitute(copasiFile=copasi_file, \\n otherFiles=input_files_string,\\n rank=rank,\\n binary_dir = binary_dir,\\n transfer_executable = transfer_executable,\\n pool_type = pool_type,\\n pool_address = pool_address,\\n subtask=str(subtask_index),\\n n = number_of_jobs,\\n outputFile = output_file,\\n extraArgs='',\\n )\\n \\n condor_job_filename = 'auto_condor_%d.job'%subtask_index\\n condor_job_full_filename = os.path.join(self.path, condor_job_filename)\\n condor_file = open(condor_job_full_filename, 'w')\\n condor_file.write(condor_job_string)\\n condor_file.close()\\n\\n return condor_job_filename\",\n \"def configure_queued_job(self, job):\\n\\n config = ExecutionConfiguration()\\n data = job.get_job_data()\\n\\n # Add input file meta-data\\n input_files_dict = self._create_input_file_dict(data)\\n config.set_input_files(input_files_dict)\\n\\n # Set up env vars for job's input data\\n input_values = data.get_injected_input_values(input_files_dict)\\n interface = job.job_type_rev.get_input_interface()\\n\\n env_vars = {}\\n if isinstance(data, JobData):\\n # call job.data.job_data.JobData.get_injected_env_vars\\n env_vars = data.get_injected_env_vars(input_files_dict, interface)\\n else:\\n # call old job.configuration.data.job_data.get_injected_env_vars\\n # TODO: remove once old JobData class is no longer used\\n env_vars = data.get_injected_env_vars(input_files_dict)\\n\\n task_workspaces = {}\\n if job.job_type.is_system:\\n # Add any workspaces needed for this system job\\n task_workspaces = QueuedExecutionConfigurator._system_job_workspaces(job)\\n else:\\n # Set any output workspaces needed\\n output_workspaces = {}\\n if job.input and 'version' in job.input and job.input['version'] == '1.0':\\n # Set output workspaces using legacy job data\\n self._cache_workspace_names(data.get_output_workspace_ids())\\n output_workspaces = {}\\n for output, workspace_id in data.get_output_workspaces().items():\\n output_workspaces[output] = self._cached_workspace_names[workspace_id]\\n config.set_output_workspaces(output_workspaces)\\n if not output_workspaces:\\n # Set output workspaces from job configuration\\n output_workspaces = {}\\n job_config = job.get_job_configuration()\\n interface = SeedManifest(job.job_type_rev.manifest, do_validate=False)\\n for output_name in interface.get_file_output_names():\\n output_workspace = job_config.get_output_workspace(output_name)\\n if output_workspace:\\n output_workspaces[output_name] = output_workspace\\n config.set_output_workspaces(output_workspaces)\\n\\n # Create main task with fields populated from input data\\n args = job.get_job_interface().get_injected_command_args(input_values, env_vars)\\n config.create_tasks(['main'])\\n config.add_to_task('main', args=args, env_vars=env_vars, workspaces=task_workspaces)\\n return config\",\n \"def copy(self) -> pulumi.Output[Optional['outputs.JobCopy']]:\\n return pulumi.get(self, \\\"copy\\\")\",\n \"def get_template_args(csv_directory, id_field, address_field, zone_field, upload_bucket, results_bucket, upload=True):\\n job_csvs = [f for f in listdir(csv_directory) if isfile(join(csv_directory, f))]\\n job_template_args = []\\n for job_num, job_csv in enumerate(job_csvs):\\n if upload:\\n upload_blob(UPLOAD_BUCKET, join(csv_directory, job_csv), job_csv)\\n print(job_csv, 'uploaded')\\n job_template_args.append({\\n 'job_number': job_num,\\n 'csv_name': job_csv,\\n 'id_field': id_field,\\n 'address_field': address_field,\\n 'zone_field': zone_field,\\n 'upload_bucket': upload_bucket,\\n 'results_bucket': results_bucket\\n })\\n return job_template_args\",\n \"def __init__(self, settings, ui_id, job_id):\\n # Call the original constructor\\n super().__init__(settings, ui_id, job_id)\\n\\n # Set the local template\\n self.local_template = 'settings/bilby_local.sh'\\n # Set our job parameter path\\n self.job_parameter_file = os.path.join(self.get_working_directory(), 'json_params.json')\\n # Set the job output directory\\n self.job_output_directory = os.path.join(self.get_working_directory(), 'output')\",\n \"def build_job_configs(self, args):\\n job_configs = {}\\n\\n ttype = args['ttype']\\n (targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(args)\\n if sim is not None:\\n raise ValueError(\\\"Found 'sim' argument on AnalyzeExtension_SG config.\\\")\\n if targets_yaml is None:\\n return job_configs\\n\\n targets = load_yaml(targets_yaml)\\n config_yaml = 'config.yaml'\\n\\n base_config = dict(roi_baseline=args['roi_baseline'],\\n make_plots=args['make_plots'])\\n\\n for target_name, target_list in targets.items():\\n name_keys = dict(target_type=ttype,\\n target_name=target_name,\\n fullpath=True)\\n target_dir = NAME_FACTORY.targetdir(**name_keys)\\n config_path = os.path.join(target_dir, config_yaml)\\n logfile = make_nfs_path(os.path.join(\\n target_dir, \\\"%s_%s.log\\\" % (self.linkname, target_name)))\\n job_config = base_config.copy()\\n job_config.update(dict(config=config_path,\\n logfile=logfile))\\n job_configs[target_name] = job_config\\n\\n return job_configs\",\n \"def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data):\\n super().__init__(cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data)\\n if input_cfg_json_data:\\n self._read_custom_pars()\\n else:\\n self._combine_conditions()\\n\\n # Mike's new stuff\\n self.outpars = self._flatten_dict(self.outpars, '', {})\",\n \"def create_arg_config(environment, region, template, parameters):\\r\\n raw_config = {\\r\\n 'Environment': environment,\\r\\n 'Region': region\\r\\n }\\r\\n if template:\\r\\n raw_config['Template'] = template\\r\\n if parameters:\\r\\n raw_config['Parameters'] = dict(parameters)\\r\\n return Config(raw_config)\",\n \"def deploy_features_table():\\n\\n logging.info(\\\"copy table\\\")\\n target_dataset_ref = bigquery.DatasetReference(GCP_PROJECT, BQ_TARGET_DATASET)\\n target_table_ref = bigquery.TableReference(target_dataset_ref, 'features')\\n copyjob_config = bigquery.CopyJobConfig()\\n copyjob_config.create_disposition = bigquery.CreateDisposition.CREATE_IF_NEEDED\\n copyjob_config.write_disposition = bigquery.WriteDisposition.WRITE_TRUNCATE\\n bq.copy_table(temp_table_ref, target_table_ref, job_config=copyjob_config)\",\n \"def _create_job_spec(\\n self,\\n job_id: Text,\\n training_input: Dict[Text, Any],\\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\\n pass\",\n \"def test_copy_options_from_config_file(self):\\n tempfile = self.get_temp_file()\\n self.prepare(nodes=1)\\n\\n logger.debug('Running stress')\\n stress_table = 'keyspace1.standard1'\\n self.node1.stress(['write', 'n=1K', 'no-warmup', '-rate', 'threads=50'])\\n\\n def create_config_file(config_lines):\\n config_file = self.get_temp_file()\\n logger.debug('Creating config file {}'.format(config_file.name))\\n\\n with open(config_file.name, 'w') as config:\\n for line in config_lines:\\n config.write(line + os.linesep)\\n config.close()\\n\\n return config_file.name\\n\\n def extract_options(out):\\n prefix = 'Using options: '\\n for l in out.split('\\\\n'):\\n if l.startswith(prefix):\\n return l[len(prefix):].strip().strip(\\\"'\\\").replace(\\\"'\\\", \\\"\\\\\\\"\\\")\\n return ''\\n\\n def check_options(out, expected_options):\\n opts = extract_options(out)\\n logger.debug('Options: {}'.format(opts))\\n d = json.loads(opts)\\n for k, v in expected_options:\\n assert v == d[k]\\n\\n def do_test(config_lines, expected_options):\\n config_file = create_config_file(config_lines)\\n\\n cmd = \\\"COPY {} {} '{}'\\\".format(stress_table, direction, tempfile.name)\\n if not use_default:\\n cmd += \\\" WITH CONFIGFILE = '{}'\\\".format(config_file)\\n\\n cqlsh_options = []\\n if use_default:\\n cqlsh_options.append('--cqlshrc={}'.format(config_file))\\n\\n logger.debug('{} with options {}'.format(cmd, cqlsh_options))\\n out, _, _ = self.run_cqlsh(cmds=cmd, cqlsh_options=cqlsh_options, skip_cqlshrc=True)\\n logger.debug(out)\\n check_options(out, expected_options)\\n\\n for use_default in [True, False]:\\n for direction in ['TO', 'FROM']:\\n do_test(['[copy]', 'header = True', 'maxattempts = 10'],\\n [('header', 'True'), ('maxattempts', '10')])\\n\\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\\n '[copy:{}]'.format(stress_table), 'maxattempts = 9'],\\n [('header', 'True'), ('maxattempts', '9')])\\n\\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\\n '[copy-from]', 'maxattempts = 9',\\n '[copy-to]', 'maxattempts = 8'],\\n [('header', 'True'), ('maxattempts', '8' if direction == 'TO' else '9')])\\n\\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\\n '[copy-from]', 'maxattempts = 9',\\n '[copy-to]', 'maxattempts = 8',\\n '[copy:{}]'.format(stress_table), 'maxattempts = 7'],\\n [('header', 'True'), ('maxattempts', '7')])\\n\\n do_test(['[copy]', 'header = True', 'maxattempts = 10',\\n '[copy-from]', 'maxattempts = 9',\\n '[copy-to]', 'maxattempts = 8',\\n '[copy:{}]'.format(stress_table), 'maxattempts = 7',\\n '[copy-from:{}]'.format(stress_table), 'maxattempts = 6',\\n '[copy-to:{}]'.format(stress_table), 'maxattempts = 5'],\\n [('header', 'True'), ('maxattempts', '5' if direction == 'TO' else '6')])\",\n \"def get(resource_name: str,\\n id: pulumi.Input[str],\\n opts: Optional[pulumi.ResourceOptions] = None,\\n copy: Optional[pulumi.Input[pulumi.InputType['JobCopyArgs']]] = None,\\n extract: Optional[pulumi.Input[pulumi.InputType['JobExtractArgs']]] = None,\\n job_id: Optional[pulumi.Input[str]] = None,\\n job_timeout_ms: Optional[pulumi.Input[str]] = None,\\n job_type: Optional[pulumi.Input[str]] = None,\\n labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n load: Optional[pulumi.Input[pulumi.InputType['JobLoadArgs']]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n project: Optional[pulumi.Input[str]] = None,\\n query: Optional[pulumi.Input[pulumi.InputType['JobQueryArgs']]] = None,\\n user_email: Optional[pulumi.Input[str]] = None) -> 'Job':\\n opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))\\n\\n __props__ = dict()\\n\\n __props__[\\\"copy\\\"] = copy\\n __props__[\\\"extract\\\"] = extract\\n __props__[\\\"job_id\\\"] = job_id\\n __props__[\\\"job_timeout_ms\\\"] = job_timeout_ms\\n __props__[\\\"job_type\\\"] = job_type\\n __props__[\\\"labels\\\"] = labels\\n __props__[\\\"load\\\"] = load\\n __props__[\\\"location\\\"] = location\\n __props__[\\\"project\\\"] = project\\n __props__[\\\"query\\\"] = query\\n __props__[\\\"user_email\\\"] = user_email\\n return Job(resource_name, opts=opts, __props__=__props__)\",\n \"def generate_template_dict(self):\\n # Get the existing parameters\\n params = super().generate_template_dict()\\n\\n # Add our custom parameters\\n params['job_parameter_file'] = self.job_parameter_file\\n params['job_output_directory'] = self.job_output_directory\\n\\n # Return the updated params\\n return params\",\n \"def main(args):\\n try:\\n config_path = project_path + \\\"/\\\" + args.config\\n input_data_path = project_path + \\\"/\\\" + args.input\\n output_data_path = project_path + \\\"/\\\" + args.output\\n\\n config = load_config(config_path)\\n df = read_csv(input_data_path)\\n product = product_dim(df, **config['product_dim'])\\n\\n # Write to output file\\n save_csv(product, output_data_path)\\n except Exception as e:\\n logger.error(\\\"Unexpected error occurred when creating object table for products: \\\" + str(e))\",\n \"def constructObjectJob(self, xml_node):\\n name = os.path.join(self.dir, xml_node.find(\\\"name\\\").text)\\n output_name = name + \\\".o\\\"\\n object_job = CopyFile(name, output_name, self.dir)\\n object_job.output = output_name\\n return object_job\",\n \"def __init__(\\n self,\\n workspace=None,\\n profile=None,\\n extend_path=None,\\n devel_layout=None,\\n install=False,\\n isolate_install=False,\\n cmake_args=None,\\n make_args=None,\\n jobs_args=None,\\n use_internal_make_jobserver=True,\\n use_env_cache=False,\\n catkin_make_args=None,\\n space_suffix=None,\\n buildlist=None,\\n skiplist=None,\\n authors=None,\\n maintainers=None,\\n licenses=None,\\n extends=None,\\n key_origins={},\\n **kwargs\\n ):\\n self.__locked = False\\n\\n # Handle deprecated arguments\\n if 'whitelist' in kwargs:\\n buildlist = kwargs['whitelist']\\n del kwargs['whitelist']\\n if 'blacklist' in kwargs:\\n skiplist = kwargs['blacklist']\\n del kwargs['blacklist']\\n\\n # Validation is done on assignment\\n self.workspace = workspace\\n\\n self.extend_path = extend_path if extend_path else None\\n self.key_origins = key_origins\\n\\n self.profile = profile\\n\\n # Handle *space assignment and defaults\\n for space, space_dict in Context.SPACES.items():\\n key_name = space + '_space'\\n default = space_dict['default']\\n value = kwargs.pop(key_name, default)\\n if value == default and space_suffix and space != 'source':\\n value += space_suffix\\n setattr(self, key_name, value)\\n\\n # Check for unhandled context options\\n if len(kwargs) > 0:\\n print('Warning: Unhandled config context options: {}'.format(kwargs), file=sys.stderr)\\n\\n self.destdir = os.environ.get('DESTDIR', None)\\n\\n # Handle package buildlist/skiplist\\n self.buildlist = buildlist or []\\n self.skiplist = skiplist or []\\n\\n # Handle default authors/maintainers\\n self.authors = authors or []\\n self.maintainers = maintainers or []\\n self.licenses = licenses or ['TODO']\\n\\n # Handle build options\\n self.devel_layout = devel_layout if devel_layout else 'linked'\\n self.install = install\\n self.isolate_install = isolate_install\\n\\n # Handle additional cmake and make arguments\\n self.cmake_args = cmake_args or []\\n self.make_args = make_args or []\\n self.jobs_args = jobs_args or []\\n self.use_internal_make_jobserver = use_internal_make_jobserver\\n self.use_env_cache = use_env_cache\\n self.catkin_make_args = catkin_make_args or []\\n\\n # List of packages in the workspace is set externally\\n self.packages = []\\n\\n # List of warnings about the workspace is set internally\\n self.warnings = []\\n\\n # Initialize environment settings set by load_env\\n self.manual_cmake_prefix_path = None\\n self.cached_cmake_prefix_path = None\\n self.env_cmake_prefix_path = None\\n self.cmake_prefix_path = None\\n\\n self.extends = extends\",\n \"def build_job_configs(self, args):\\n job_configs = {}\\n\\n ttype = args['ttype']\\n (targets_yaml, sim) = NAME_FACTORY.resolve_targetfile(\\n args, require_sim_name=True)\\n if targets_yaml is None:\\n return job_configs\\n\\n specconfig = NAME_FACTORY.resolve_specconfig(args)\\n\\n astro_priors = args['astro_priors']\\n write_full = args.get('write_full', False)\\n\\n targets = load_yaml(targets_yaml)\\n base_config = dict(nsims=args['nsims'],\\n seed=args['seed'],\\n specconfig=specconfig)\\n\\n for target_name, profile_list in list(targets.items()):\\n for profile in profile_list:\\n for astro_prior in astro_priors:\\n if is_null(astro_prior):\\n astro_prior = 'none'\\n full_key = \\\"%s:%s:%s:%s\\\" % (\\n target_name, profile, sim, astro_prior)\\n name_keys = dict(target_type=ttype,\\n target_name=target_name,\\n sim_name=sim,\\n profile=profile,\\n astro_prior=astro_prior,\\n fullpath=True)\\n limitfile = NAME_FACTORY.sim_dmlimitsfile(**name_keys)\\n first = args['seed']\\n last = first + args['nsims'] - 1\\n outfile = limitfile.replace(\\n '_SEED.fits', '_collected_%06i_%06i.fits' %\\n (first, last))\\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\\n if not write_full:\\n outfile = None\\n summaryfile = limitfile.replace(\\n '_SEED.fits', '_summary_%06i_%06i.fits' %\\n (first, last))\\n job_config = base_config.copy()\\n job_config.update(dict(limitfile=limitfile,\\n astro_prior=astro_prior,\\n outfile=outfile,\\n summaryfile=summaryfile,\\n logfile=logfile))\\n job_configs[full_key] = job_config\\n\\n return job_configs\",\n \"def copyPetscArguments(jobdir, argsfile):\\n shutil.copyfile(argsfile, os.path.join(jobdir, \\\"petsc_commandline_arg\\\"))\",\n \"def _create_job_spec(\\n self,\\n job_id: Text,\\n training_input: Dict[Text, Any],\\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\\n\\n job_spec = {\\n 'display_name': job_id,\\n 'job_spec': training_input,\\n 'labels': job_labels,\\n }\\n return job_spec\",\n \"def build_input_table(cls, name='inputTableName', input_name='input'):\\n obj = cls(name)\\n obj.exporter = 'get_input_table_name'\\n obj.input_name = input_name\\n return obj\",\n \"def __init__(__self__, *,\\n include_cluster_scope_resources: pulumi.Input[bool],\\n object_type: pulumi.Input[str],\\n snapshot_volumes: pulumi.Input[bool],\\n excluded_namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n excluded_resource_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n included_namespaces: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n included_resource_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n label_selectors: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"include_cluster_scope_resources\\\", include_cluster_scope_resources)\\n pulumi.set(__self__, \\\"object_type\\\", 'KubernetesClusterBackupDatasourceParameters')\\n pulumi.set(__self__, \\\"snapshot_volumes\\\", snapshot_volumes)\\n if excluded_namespaces is not None:\\n pulumi.set(__self__, \\\"excluded_namespaces\\\", excluded_namespaces)\\n if excluded_resource_types is not None:\\n pulumi.set(__self__, \\\"excluded_resource_types\\\", excluded_resource_types)\\n if included_namespaces is not None:\\n pulumi.set(__self__, \\\"included_namespaces\\\", included_namespaces)\\n if included_resource_types is not None:\\n pulumi.set(__self__, \\\"included_resource_types\\\", included_resource_types)\\n if label_selectors is not None:\\n pulumi.set(__self__, \\\"label_selectors\\\", label_selectors)\",\n \"def input_config_to_job_input(input_batch_id, job_name, job_level, input_config):\\n JobInput = namedtuple(\\n \\\"JobInput\\\",\\n [\\\"input_manifest_s3_uri\\\", \\\"label_attribute_name\\\", \\\"label_category_s3_uri\\\"],\\n )\\n\\n input_manifest_s3_uri = input_config.get(\\\"inputManifestS3Uri\\\")\\n if input_manifest_s3_uri is not None:\\n return JobInput(\\n input_manifest_s3_uri=input_manifest_s3_uri,\\n label_attribute_name=None,\\n label_category_s3_uri=None,\\n )\\n\\n chain_to_job_name = job_name\\n chain_from_job_name = input_config[\\\"chainFromJobName\\\"]\\n\\n # Only support jobs within the current batch for now.\\n if job_level == 1:\\n raise Exception(\\\"can't chain in job_level 1\\\")\\n\\n batches = chainable_batches(input_batch_id, job_level)\\n if len(batches) == 0:\\n raise Exception(\\\"no chainable batches found\\\")\\n\\n processed_job_level_batch = next(\\n iter(\\n db.get_batch_metadata_by_labeling_job_name(\\n chain_to_job_name, BatchMetadataType.PROCESS_LEVEL\\n )\\n ),\\n None,\\n )\\n\\n prev_level_jobs = []\\n for batch in batches:\\n prev_level_jobs += db.get_child_batch_metadata(\\n batch[\\\"BatchId\\\"], BatchMetadataType.JOB_LEVEL\\n )\\n\\n for job in prev_level_jobs:\\n if job[BatchMetadataTableAttributes.LABELING_JOB_NAME] == chain_from_job_name:\\n # If available, use the downsampled manifest file as input to the new job\\n if processed_job_level_batch:\\n processed_data_location = processed_job_level_batch[\\n BatchMetadataTableAttributes.JOB_INPUT_LOCATION\\n ]\\n else:\\n processed_data_location = None\\n\\n batch_output_location = (\\n processed_data_location or job[BatchMetadataTableAttributes.JOB_OUTPUT_LOCATION]\\n )\\n\\n return JobInput(\\n input_manifest_s3_uri=batch_output_location,\\n label_attribute_name=job[BatchMetadataTableAttributes.LABEL_ATTRIBUTE_NAME],\\n label_category_s3_uri=job[BatchMetadataTableAttributes.LABEL_CATEGORY_CONFIG],\\n )\\n\\n raise Exception(f\\\"chain job {chain_from_job_name} not found\\\")\",\n \"def _create_job_spec(\\n self,\\n job_id: Text,\\n training_input: Dict[Text, Any],\\n job_labels: Optional[Dict[Text, Text]] = None) -> Dict[Text, Any]:\\n\\n job_spec = {\\n 'jobId': job_id,\\n 'trainingInput': training_input,\\n 'labels': job_labels,\\n }\\n return job_spec\",\n \"def svn_client_copy4(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def _deep_copy_arg_dict(input_arg_dict):\\n output_arg_dict = {}\\n for name, param in input_arg_dict.items():\\n output_arg_dict[name] = param.copy()\\n return output_arg_dict\",\n \"def test_args_copy():\\n args = cli.parse_args(['-c'])\\n assert args.copy\\n args = cli.parse_args(['--copy'])\\n assert args.copy\",\n \"def svn_client_copy5(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, svn_boolean_t_ignore_externals, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def copy(self):\\n r = PredictionJobRequest()\\n r.__dict__.update(self.__dict__)\\n\\n return r\",\n \"def synthesize_employment_data(self, config):\\r\\n jobs_by_zone_by_sector_table_name = config['jobs_by_zone_by_sector']\\r\\n gridcells_table_name = config['gridcells']\\r\\n jobs_table_name = config['jobs']\\r\\n gridcells_output_table_name = config['gridcells_output']\\r\\n jobs_output_table_name = config['jobs_output']\\r\\n \\r\\n input_db_name = config['db_config'].database_name\\r\\n output_db_name = config['output_database_name']\\r\\n \\r\\n sectors = config['sector_names_and_ids']\\r\\n building_types_and_ids_and_home_based = config[\\r\\n 'building_type_column_names_and_ids_and_home_based']\\r\\n \\r\\n building_types = []\\r\\n building_ids = []\\r\\n home_based = [] \\r\\n for type, id, home in building_types_and_ids_and_home_based:\\r\\n building_types += [type]\\r\\n building_ids += [id]\\r\\n home_based += [home]\\r\\n \\r\\n \\r\\n from_database_configuration = ScenarioDatabaseConfiguration(\\r\\n database_name = input_db_name,\\r\\n host_name = config['db_config'].host_name,\\r\\n user_name = config['db_config'].user_name,\\r\\n password = config['db_config'].password \\r\\n )\\r\\n to_database_configuration = ScenarioDatabaseConfiguration(\\r\\n database_name = output_db_name,\\r\\n host_name = config['db_config'].host_name,\\r\\n user_name = config['db_config'].user_name,\\r\\n password = config['db_config'].password \\r\\n )\\r\\n\\r\\n FlattenScenarioDatabaseChain().copy_scenario_database(\\r\\n from_database_configuration = from_database_configuration, \\r\\n to_database_configuration = to_database_configuration,\\r\\n tables_to_copy = [gridcells_table_name, jobs_table_name])\\r\\n \\r\\n db_server = DatabaseServer(to_database_configuration) \\r\\n output_database = db_server.get_database(output_db_name)\\r\\n \\r\\n sector_name = 0; sector_id = 1\\r\\n \\r\\n sector = {}\\r\\n for entry in sectors:\\r\\n name = entry[sector_name]\\r\\n id = entry[sector_id]\\r\\n sector[id] = self._get_jobs_per_building_type_in_sector_by_zone(\\r\\n output_database, jobs_by_zone_by_sector_table_name, \\r\\n jobs_table_name, name, id)\\r\\n\\r\\n results = self._get_building_type_proportion_by_zone(output_database, \\r\\n gridcells_table_name)\\r\\n \\r\\n grid_id = 0; zone_id = 1\\r\\n dist = {}\\r\\n \\r\\n type_index = {}\\r\\n \\r\\n for name in building_types:\\r\\n for i in range(len(results[0])):\\r\\n column_name = results[0][i]\\r\\n if name == column_name:\\r\\n type_index[name] = i\\r\\n break;\\r\\n else:\\r\\n raise KeyError, ('No column by the name of \\\\'%s\\\\' found in '\\r\\n 'the database.' % name) \\r\\n\\r\\n for name in building_types:\\r\\n dist[name] = {}\\r\\n \\r\\n for row in results[1:]:\\r\\n for name in building_types:\\r\\n dist[name][row[zone_id]] = []\\r\\n \\r\\n for row in results[1:]:\\r\\n for name in building_types:\\r\\n dist[name][row[zone_id]] += [(row[grid_id], \\r\\n row[type_index[name]])]\\r\\n \\r\\n jobs_table_data = self._create_jobs_table_data(dist, sector,\\r\\n building_types_and_ids_and_home_based)\\r\\n \\r\\n output_database.execute('USE %(out_db)s' % {'out_db':output_db_name})\\r\\n \\r\\n output_database.execute(\\\"\\\"\\\"\\r\\n CREATE TABLE %(jobs_out)s (\\r\\n JOB_ID INT AUTO_INCREMENT, PRIMARY KEY(JOB_ID),\\r\\n GRID_ID INT, HOME_BASED INT, SECTOR_ID INT, BUILDING_TYPE INT);\\r\\n \\\"\\\"\\\" % {'jobs_out':jobs_output_table_name})\\r\\n \\r\\n if len(jobs_table_data) > 0:\\r\\n output_prefix = (\\r\\n \\\"\\\"\\\"INSERT INTO %(jobs_out)s \\r\\n (GRID_ID, HOME_BASED, SECTOR_ID, BUILDING_TYPE) VALUES\\r\\n \\\"\\\"\\\" % {'jobs_out':jobs_output_table_name})\\r\\n output_postfix = ';'\\r\\n \\r\\n step = 1000\\r\\n length = len(jobs_table_data)\\r\\n iterations = int(length/step) + 1\\r\\n \\r\\n for i in range(iterations):\\r\\n low = i*step\\r\\n high = (i+1)*step\\r\\n \\r\\n if high > length: high = length\\r\\n \\r\\n output_body = \\\"\\\"\\r\\n \\r\\n for j in range(low, high):\\r\\n output_body += (\\r\\n '(%(grid)s, %(home)s, %(sector)s, %(building)s),\\\\n' \\r\\n % jobs_table_data[j])\\r\\n \\r\\n output_query = \\\"%s%s%s\\\" % (output_prefix, \\r\\n output_body[:-2], \\r\\n output_postfix)\\r\\n\\r\\n output_database.execute(output_query)\\r\\n \\r\\n \\r\\n ### TODO: \\r\",\n \"def _map_arguments(self, args):\\n config_yaml = args['config']\\n config_dict = load_yaml(config_yaml)\\n\\n dry_run = args.get('dry_run', False)\\n\\n data = config_dict.get('data')\\n comp = config_dict.get('comp')\\n library = config_dict.get('library')\\n models = config_dict.get('models')\\n scratch = config_dict.get('scratch')\\n\\n self._set_link('prepare', SplitAndBinChain,\\n comp=comp, data=data,\\n ft1file=config_dict.get('ft1file'),\\n hpx_order_ccube=config_dict.get('hpx_order_ccube'),\\n hpx_order_expcube=config_dict.get('hpx_order_expcube'),\\n scratch=scratch,\\n dry_run=dry_run)\\n\\n self._set_link('diffuse-comp', DiffuseCompChain,\\n comp=comp, data=data,\\n library=library,\\n make_xml=config_dict.get('make_diffuse_comp_xml', False),\\n outdir=config_dict.get('merged_gasmap_dir', 'merged_gasmap'),\\n dry_run=dry_run)\\n\\n self._set_link('catalog-comp', CatalogCompChain,\\n comp=comp, data=data,\\n library=library,\\n make_xml=config_dict.get('make_catalog_comp_xml', False),\\n nsrc=config_dict.get('catalog_nsrc', 500),\\n dry_run=dry_run)\\n \\n self._set_link('assemble-model', AssembleModelChain,\\n comp=comp, data=data,\\n library=library,\\n models=models,\\n hpx_order=config_dict.get('hpx_order_fitting'),\\n dry_run=dry_run)\",\n \"def build_parms(args):\\r\\n readDir=args.dir\\r\\n #target_date=args.target_date\\r\\n target_date=args.target_date\\r\\n outdir=args.outdir \\r\\n parms = {\\\"readDir\\\":readDir,\\r\\n \\\"target_date\\\":target_date,\\r\\n \\\"outdir\\\":outdir}\\r\\n \\r\\n return(parms)\",\n \"def build(self, data: dict) -> GemTable:\\n table = GemTable.build(data)\\n table.project_id = self.project_id\\n table.session = self.session\\n return table\",\n \"def from_dict(data: Dict) -> 'JobConfig':\\n job_name = list(data.keys())[0]\\n return JobConfig(job_name=job_name,\\n job_type=data[job_name].get('job_type', None),\\n properties=data[job_name].get('properties', {}))\",\n \"def build_job_configs(self, args):\\n job_configs = {}\\n\\n ttype = args['ttype']\\n (roster_yaml, sim) = NAME_FACTORY.resolve_rosterfile(\\n args, require_sim_name=True)\\n if roster_yaml is None:\\n return job_configs\\n\\n specconfig = NAME_FACTORY.resolve_specconfig(args)\\n\\n astro_priors = args['astro_priors']\\n write_full = args['write_full']\\n first = args['seed']\\n last = first + args['nsims'] - 1\\n\\n base_config = dict(nsims=args['nsims'],\\n seed=args['seed'])\\n\\n roster_dict = load_yaml(roster_yaml)\\n for roster_name in list(roster_dict.keys()):\\n for astro_prior in astro_priors:\\n if is_null(astro_prior):\\n astro_prior = 'none'\\n full_key = \\\"%s:%s:%s\\\" % (roster_name, sim, astro_prior)\\n name_keys = dict(target_type=ttype,\\n roster_name=roster_name,\\n sim_name=sim,\\n astro_prior=astro_prior,\\n fullpath=True)\\n\\n limitfile = NAME_FACTORY.sim_stackedlimitsfile(**name_keys)\\n outfile = limitfile.replace(\\n '_SEED.fits', '_collected_%06i_%06i.fits' %\\n (first, last))\\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\\n if not write_full:\\n outfile = None\\n summaryfile = limitfile.replace('_SEED.fits', '_summary.fits')\\n\\n job_config = base_config.copy()\\n job_config.update(dict(limitfile=limitfile,\\n specconfig=specconfig,\\n astro_prior=astro_prior,\\n outfile=outfile,\\n summaryfile=summaryfile,\\n logfile=logfile))\\n job_configs[full_key] = job_config\\n\\n return job_configs\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n column_names: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,\\n column_wildcard: Optional[pulumi.Input[pulumi.InputType['DataCellsFilterColumnWildcardArgs']]] = None,\\n database_name: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n row_filter: Optional[pulumi.Input[pulumi.InputType['DataCellsFilterRowFilterArgs']]] = None,\\n table_catalog_id: Optional[pulumi.Input[str]] = None,\\n table_name: Optional[pulumi.Input[str]] = None,\\n __props__=None):\\n ...\",\n \"def svn_client_copy(svn_client_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def Copy(self, name, **kargs):\\n if \\\"TOOLCHAIN\\\" in kargs and not kargs[\\\"TOOLCHAIN\\\"] is None:\\n self.set_toolchain(kargs[\\\"TOOLCHAIN\\\"])\\n if \\\"STATIC\\\" in kargs:\\n self.static = kargs[\\\"STATIC\\\"]\\n else:\\n self.static = 0\\n if \\\"TESTENV\\\" in kargs:\\n self.testenv = kargs[\\\"TESTENV\\\"]\\n else:\\n self.testenv = 0\\n \\n new_self = Environment.Copy(self, **kargs)\\n new_self.libs = copy.copy(self.libs)\\n new_self.apps = copy.copy(self.apps)\\n new_self.cpp_path = copy.copy(self.cpp_path)\\n new_self.files = copy.copy(self.files)\\n new_self.name = name\\n #new_self.build_libs(*libs)\\n return new_self\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"dest\\\": self.subnode_dest.makeClone()\\n if self.subnode_dest is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def copy_config(cfg):\\n res= dict(cfg)\\n #model_param = dict(cfg['model_param'])\\n model_param = dict(cfg.get('model_param', {}))\\n res['model_param'] = model_param\\n return res\",\n \"def copy_unified_job(self, _eager_fields=None, **new_prompts):\\n unified_job_class = self.__class__\\n unified_jt_class = self._get_unified_job_template_class()\\n parent_field_name = self._get_parent_field_name()\\n fields = unified_jt_class._get_unified_job_field_names() | set([parent_field_name])\\n\\n create_data = {}\\n if _eager_fields:\\n create_data = _eager_fields.copy()\\n create_data[\\\"launch_type\\\"] = \\\"relaunch\\\"\\n\\n prompts = self.launch_prompts()\\n if self.unified_job_template and (prompts is not None):\\n prompts.update(new_prompts)\\n prompts['_eager_fields'] = create_data\\n unified_job = self.unified_job_template.create_unified_job(**prompts)\\n else:\\n unified_job = copy_model_by_class(self, unified_job_class, fields, {})\\n for fd, val in create_data.items():\\n setattr(unified_job, fd, val)\\n unified_job.save()\\n\\n # Labels copied here\\n from awx.main.signals import disable_activity_stream\\n\\n with disable_activity_stream():\\n copy_m2m_relationships(self, unified_job, fields)\\n\\n return unified_job\",\n \"def parse_args(args):\\n parser = argparse.ArgumentParser(description='Parse Mysql Copy account you want',add_help=False)\\n connect_setting = parser.add_argument_group('connect setting')\\n connect_setting.add_argument('-h','--host',dest='host',type=str,help='Host the MySQL database server located',default='127.0.0.1')\\n connect_setting.add_argument('-u','--user',dest='user',type=str,help='MySQL Username to log in as',default='root')\\n connect_setting.add_argument('-p','--password',dest='password',type=str,help='MySQL Password to use', default='')\\n connect_setting.add_argument('-P', '--port', dest='port', type=int,help='MySQL port to use', default=3306)\\n copy_user = parser.add_argument_group('copy user')\\n copy_user.add_argument('--src-user',dest='srcuser',type=str,help='copy from the user',nargs='*',default='*')\\n copy_user.add_argument('--src-host',dest='srchost',type=str,help='copy from the host',nargs='*',default='*')\\n copy_user.add_argument('--dest-user',dest='destuser',type=str,help='copy to the user',nargs='*',default='')\\n copy_user.add_argument('--dest-host',dest='desthost',type=str,help='copy to the host',nargs='*',default='')\\n\\n parser.add_argument('--help', dest='help', action='store_true', help='help infomation', default=False)\\n\\n return parser\",\n \"def _generate_ipt_args_settings_in_construct(ipt_args_in_construct, settings):\\n if settings and settings.op_ipt_type:\\n input_type = settings.op_ipt_type\\n if input_type == InputType.TENSOR.value:\\n ipt_args_settings_in_construct = ipt_args_in_construct\\n elif input_type == InputType.LIST.value:\\n ipt_args_settings_in_construct = f\\\"({ipt_args_in_construct},)\\\"\\n else:\\n raise NodeInputTypeNotSupportError(f\\\"Input type[{input_type}] is not supported now.\\\")\\n else:\\n ipt_args_settings_in_construct = ipt_args_in_construct\\n\\n if settings and settings.op_extra_input:\\n settings_value = settings.op_extra_input\\n if settings_value:\\n settings_in_construct = ', '.join([f\\\"{setting_val}\\\" for _, setting_val in settings_value.items()])\\n ipt_args_settings_in_construct = ', '.join((ipt_args_settings_in_construct, settings_in_construct))\\n\\n return ipt_args_settings_in_construct\",\n \"def __init__(self, *args, **kwargs):\\n super(ColumnShiftTable, self).__init__(*args, **kwargs)\\n # Override default template\\n if hasattr(self, \\\"template_name\\\"):\\n self.template_name = self.shifter_template\\n else:\\n self.template = self.shifter_template\",\n \"def prepare_pr_optimal_model_condor_job(self, pool_type, pool_address, number_of_jobs, subtask_index, data_files, rank='0', extraArgs=''):\\n ############\\n copasi_file = 'auto_copasi_%d.$(Process).cps' % subtask_index\\n output_file = ''\\n \\n \\n \\n if pool_type == 'ec2':\\n binary_dir = '/usr/local/bin'\\n transfer_executable = 'NO'\\n else:\\n binary_dir, binary = os.path.split(settings.COPASI_LOCAL_BINARY)\\n transfer_executable = 'YES'\\n \\n input_files_string = ', '\\n for data_file in data_files:\\n input_files_string += (data_file + ', ')\\n input_files_string = input_files_string.rstrip(', ')\\n\\n condor_job_string = Template(condor_spec.raw_condor_job_string).substitute(copasiFile=copasi_file, \\n otherFiles=input_files_string,\\n rank=rank,\\n binary_dir = binary_dir,\\n transfer_executable = transfer_executable,\\n pool_type = pool_type,\\n pool_address = pool_address,\\n subtask=str(subtask_index),\\n n = number_of_jobs,\\n outputFile = output_file,\\n extraArgs='',\\n )\\n \\n condor_job_filename = 'auto_condor_%d.job'%subtask_index\\n condor_job_full_filename = os.path.join(self.path, condor_job_filename)\\n condor_file = open(condor_job_full_filename, 'w')\\n condor_file.write(condor_job_string)\\n condor_file.close()\\n\\n return condor_job_filename\",\n \"def templateargs(self, target_jar, confs=None):\\r\\n raise NotImplementedError()\",\n \"def load_params():\\n # start arg parser\\n parser = argparse.ArgumentParser(description='Apero Copy')\\n # add arguments\\n parser.add_argument('yaml', help='yaml file to use', type=str,\\n default=None)\\n parser.add_argument('--overwrite', help='overwrite existing files',\\n action='store_true', default=False)\\n parser.add_argument('--test', help='run in test mode (no copy or remove)',\\n action='store_true', default=False)\\n parser.add_argument('--symlinks', action='store_true', default=False,\\n help='Copy in symlink mode (not recommended)')\\n # get arguments\\n args = vars(parser.parse_args())\\n # ------------------------------------------------------------------\\n # deal with getting yaml file\\n # ------------------------------------------------------------------\\n # deal with no yaml file set\\n if args['yaml'] is None:\\n emsg = 'yaml file must be set'\\n raise AperoCopyError(emsg)\\n # deal with bad path\\n if not os.path.exists(args['yaml']):\\n emsg = 'yaml file {0} does not exist'\\n eargs = [args['yaml']]\\n raise AperoCopyError(emsg.format(*eargs))\\n # otherwise we read the yaml file\\n params = read_yaml(args['yaml'])\\n # add args to params\\n for arg in args:\\n if arg not in params:\\n params[arg] = args[arg]\\n # ------------------------------------------------------------------\\n # return the parameters\\n return params\",\n \"def prepare_row(task, full):\\n\\n # Would like to include the Job ID in the default set of columns, but\\n # it is a long value and would leave little room for status and update time.\\n\\n row_spec = collections.namedtuple('row_spec',\\n ['key', 'optional', 'default_value'])\\n\\n # pyformat: disable\\n default_columns = [\\n row_spec('job-name', False, None),\\n row_spec('task-id', True, None),\\n row_spec('last-update', False, None)\\n ]\\n short_columns = default_columns + [\\n row_spec('status-message', False, None),\\n ]\\n full_columns = default_columns + [\\n row_spec('job-id', False, None),\\n row_spec('user-id', False, None),\\n row_spec('status', False, None),\\n row_spec('status-detail', False, None),\\n row_spec('create-time', False, None),\\n row_spec('end-time', False, 'NA'),\\n row_spec('internal-id', False, None),\\n row_spec('logging', False, None),\\n row_spec('inputs', False, {}),\\n row_spec('outputs', False, {}),\\n row_spec('envs', False, {}),\\n row_spec('labels', False, {}),\\n ]\\n # pyformat: enable\\n\\n columns = full_columns if full else short_columns\\n\\n row = {}\\n for col in columns:\\n key, optional, default = col\\n\\n value = task.get_field(key, default)\\n if not optional or value:\\n row[key] = value\\n\\n return row\",\n \"def init_jobs(self):\\n self.jobsTableWidget.clear()\\n self.jobsTableWidget.setColumnCount(6)\\n self.jobsTableWidget.setHorizontalHeaderLabels(['Job Id', 'Description/Error', 'Submission Date', 'Status',\\n 'Execute', 'Display'])\\n header = self.jobsTableWidget.horizontalHeader()\\n header.setSectionResizeMode(0, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(1, QtWidgets.QHeaderView.Stretch)\\n header.setSectionResizeMode(2, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(3, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(4, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(5, QtWidgets.QHeaderView.ResizeToContents)\",\n \"def from_dict(cls, dikt) -> 'JobOutputRequest':\\n return util.deserialize_model(dikt, cls)\",\n \"def load_raw_to_bq(event, context):\\n\\n import os\\n\\n\\n print(f\\\"Processing .....\\\")\\n\\n file = event\\n project = os.environ.get('ENV_PROJECT')\\n dataset = os.environ.get('ENV_DATASET')\\n bucket = file.get(\\\"bucket\\\")\\n tableCsv = file.get(\\\"name\\\")\\n tableDestList = tableCsv.split(\\\".\\\")\\n tableDest = tableDestList[0]\\n table_id = f'{project}.{dataset}.{tableDest}'\\n\\n from Configuration import Configuration\\n\\n Configuration(tableCsv,bucket,table_id)\\n\\n\\n print(f\\\"End Process.\\\")\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: Optional[TransferConfigArgs] = None,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def clone(source, destination):\\n\\t\\treturn \\\"CREATE DATABASE {0} WITH TEMPLATE {1};\\\".format(destination, source)\",\n \"def __init__(self, table_name='casbin_rule', **kwargs):\\n self.table_name = table_name\\n self.dynamodb = boto3.client('dynamodb', **kwargs)\\n try:\\n\\n self.dynamodb.create_table(\\n TableName=self.table_name,\\n\\n AttributeDefinitions=[\\n {\\n 'AttributeName': 'id',\\n 'AttributeType': 'S'\\n }\\n ],\\n KeySchema=[\\n {\\n 'AttributeName': 'id',\\n 'KeyType': 'HASH'\\n },\\n ],\\n ProvisionedThroughput={\\n 'ReadCapacityUnits': 10,\\n 'WriteCapacityUnits': 10\\n }\\n )\\n except self.dynamodb.exceptions.ResourceInUseException:\\n pass\",\n \"def __init__(self, postgresRunner, tablename, table_columns):\\n self.postgresRunner = postgresRunner\\n self.tablename = tablename\\n self.table_config = table_columns\\n self.table_keys = [column.get(\\\"name\\\") for column in table_columns]\\n self.__run(\\n _PostgresCrud__create_table_command(tablename, table_columns)\\n )\",\n \"def build_data(cmd, rel_new_path, new_md5, founded_path=None):\\n data = {'cmd': cmd}\\n if cmd == 'copy':\\n data['file'] = {'src': founded_path,\\n 'dst': rel_new_path,\\n 'md5': new_md5,\\n }\\n else:\\n data['file'] = {'filepath': rel_new_path,\\n 'md5': new_md5,\\n }\\n return data\",\n \"def __init__(self, jobArgs):\\n logging.info(\\\"Constructing job with args %r\\\" % jobArgs)\\n self.args = jobArgs\\n\\n self._setup()\",\n \"def __init__(self, job_id=None, version=None, status=None, exit_status=None, exit_message=None, create_time=None, start_time=None, end_time=None, last_updated=None):\\n self.swagger_types = {\\n 'job_id': str,\\n 'version': str,\\n 'status': str,\\n 'exit_status': str,\\n 'exit_message': str,\\n 'create_time': datetime,\\n 'start_time': datetime,\\n 'end_time': datetime,\\n 'last_updated': datetime\\n }\\n\\n self.attribute_map = {\\n 'job_id': 'job_id',\\n 'version': 'version',\\n 'status': 'status',\\n 'exit_status': 'exit_status',\\n 'exit_message': 'exit_message',\\n 'create_time': 'create_time',\\n 'start_time': 'start_time',\\n 'end_time': 'end_time',\\n 'last_updated': 'last_updated'\\n }\\n\\n self._job_id = job_id\\n self._version = version\\n self._status = status\\n self._exit_status = exit_status\\n self._exit_message = exit_message\\n self._create_time = create_time\\n self._start_time = start_time\\n self._end_time = end_time\\n self._last_updated = last_updated\",\n \"def constructBundleJob(self, xml_node):\\n name = os.path.join(self.dir, xml_node.find(\\\"name\\\").text)\\n output_name = name + \\\".o\\\"\\n xar_job = BitcodeBundle(self.arch, name, output_name)\\n return xar_job\",\n \"async def copy(self, _id: str, dst_id: str, *,\\n rev: Optional[str] = None,\\n dst_rev: Optional[str] = None,\\n batch: Optional[bool] = None) -> dict:\\n\\n headers = dict(\\n Destination=f'{dst_id}?rev={dst_rev}' if dst_rev else dst_id\\n )\\n\\n params = dict(\\n rev=rev,\\n batch=\\\"ok\\\" if batch else None,\\n )\\n\\n return await self.__connection.query('COPY', self._get_path(_id), params=params, headers=headers)\",\n \"def make_job_config_json(self, job_description):\\n bench_name = job_description[0]\\n bench_type = job_description[1]\\n bench_preference = job_description[2]\\n config_file = self._node_mgr_path / f'{bench_name}_{bench_type}_{bench_preference}' / 'job.json'\\n\\n # FIXME: hard coded\\n # Dict[str, Dict[str, Any]]\\n output = dict()\\n config = dict()\\n config[\\\"name\\\"] = bench_name\\n config[\\\"type\\\"] = bench_type\\n config[\\\"num_of_threads\\\"] = 2\\n if self._node_type == NodeType.IntegratedGPU:\\n config[\\\"binding_cores\\\"] = \\\"0,3-5\\\"\\n elif self._node_type == NodeType.CPU:\\n config[\\\"binding_cores\\\"] = \\\"0-3\\\"\\n config[\\\"numa_nodes\\\"] = \\\"0\\\"\\n config[\\\"cpu_freq\\\"] = 2.1\\n config[\\\"cpu_percent\\\"] = 100\\n if self._node_type == NodeType.IntegratedGPU:\\n config[\\\"gpu_freq\\\"] = 1300500000\\n\\n output[\\\"workloads\\\"] = config\\n\\n with config_file.open('w') as fp:\\n fp.seek(0)\\n json.dump(output, fp, indent=4)\\n return config_file\",\n \"def AddJobResourceArg(parser):\\n\\n return concept_parsers.ConceptParser.ForResource(\\n 'job_name',\\n GetJobResourceSpec(),\\n 'Transcoder Job name',\\n required=True).AddToParser(parser)\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"condition\\\": self.subnode_condition.makeClone(),\\n \\\"yes_branch\\\": self.subnode_yes_branch.makeClone()\\n if self.subnode_yes_branch is not None\\n else None,\\n \\\"no_branch\\\": self.subnode_no_branch.makeClone()\\n if self.subnode_no_branch is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def build_job_configs(self, args):\\n job_configs = {}\\n\\n components = Component.build_from_yamlfile(args['comp'])\\n\\n datafile = args['data']\\n if datafile is None or datafile == 'None':\\n return job_configs\\n NAME_FACTORY.update_base_dict(args['data'])\\n outdir_base = os.path.join(NAME_FACTORY.base_dict['basedir'], 'counts_cubes')\\n\\n inputfiles = create_inputlist(args['ft1file'])\\n num_files = len(inputfiles)\\n\\n for comp in components:\\n zcut = \\\"zmax%i\\\" % comp.zmax\\n\\n mktimelist = copy.copy(comp.mktimefilters)\\n if not mktimelist:\\n mktimelist.append('none')\\n evtclasslist_keys = copy.copy(comp.evtclasses)\\n if not evtclasslist_keys:\\n evtclasslist_vals = [NAME_FACTORY.base_dict['evclass']]\\n else:\\n evtclasslist_vals = copy.copy(evtclasslist_keys)\\n\\n for mktimekey in mktimelist:\\n for evtclassval in evtclasslist_vals:\\n fullkey = comp.make_key(\\n '%s_%s_{ebin_name}_%s_{evtype_name}' %\\n (evtclassval, zcut, mktimekey))\\n\\n name_keys = dict(zcut=zcut,\\n ebin=comp.ebin_name,\\n psftype=comp.evtype_name,\\n coordsys=comp.coordsys,\\n irf_ver=NAME_FACTORY.irf_ver(),\\n mktime=mktimekey,\\n evclass=evtclassval,\\n fullpath=True)\\n\\n ccube_name = os.path.basename(NAME_FACTORY.ccube(**name_keys))\\n outfile = os.path.join(outdir_base, ccube_name)\\n infiles = _make_input_file_list(outfile, num_files)\\n logfile = make_nfs_path(outfile.replace('.fits', '.log'))\\n job_configs[fullkey] = dict(args=infiles,\\n output=outfile,\\n logfile=logfile)\\n\\n return job_configs\",\n \"def layout_copycat(source_network, target_network, source_column='name', target_column='name',\\n grid_unmapped=True, select_unmapped=True, base_url=DEFAULT_BASE_URL):\\n source_network = networks.get_network_name(source_network)\\n target_network = networks.get_network_name(target_network)\\n res = commands.commands_post(\\n 'layout copycat sourceNetwork=\\\"' + source_network + '\\\" targetNetwork=\\\"' + target_network +\\n '\\\" sourceColumn=\\\"' + source_column + '\\\" targetColumn=\\\"' + target_column +\\n '\\\" gridUnmapped=\\\"' + str(grid_unmapped) + '\\\" selectUnmapped=\\\"' + str(select_unmapped),\\n base_url=base_url)\\n return res\",\n \"def defaultconfig(self):\\r\\n\\r\\n config_data = {\\r\\n \\\"path_to_database\\\": \\\"FUDB/FOLLOWUP.DB\\\",\\r\\n \\\"path_to_frontend\\\": \\\"FUDB/\\\",\\r\\n \\\"path_to_dcs_info\\\": \\\"FUDB/\\\",\\r\\n \\\"path_to_bin\\\": \\\"bin/\\\",\\r\\n \\\"path_to_excels_exported_from_database\\\": \\\"excels exported/\\\",\\r\\n \\\"path_to_excels_to_be_imported_in_database\\\": \\\"excels to be imported/\\\",\\r\\n \\\"path_to_new_opfiles\\\": \\\"DC BATCHES IN WORK/0 NEW/\\\",\\r\\n \\\"path_to_batches_unassigned\\\": \\\"DC BATCHES IN WORK/1 UNASSIGNED/\\\",\\r\\n \\\"path_to_batches_prepfiles\\\": \\\"DC BATCHES IN WORK/2 PREPARED FILES/\\\",\\r\\n \\\"path_to_batches_assigned\\\": \\\"DC BATCHES IN WORK/3 ASSIGNED/\\\",\\r\\n \\\"path_to_batches_tobechecked\\\": \\\"DC BATCHES IN WORK/4 TO BE CHECKED/\\\",\\r\\n \\\"path_to_batches_tbimported\\\": \\\"DC BATCHES IN WORK/5 TO BE IMPORTED/\\\",\\r\\n \\\"path_to_batches_finished\\\": \\\"DC BATCHES IN WORK/6 FINISHED/\\\",\\r\\n \\\"path_to_batches_instandby\\\": \\\"DC BATCHES IN WORK/7 IN STANDBY/\\\",\\r\\n \\\"path_to_batches_unrecordable\\\": \\\"DC BATCHES IN WORK/8 UNRECORDABLE/\\\",\\r\\n \\\"batch_status_options_responsible\\\": \\\"PREP. OP FILE, IMPORTATION & SPLIT FILE, RELIABILITY & DATA UPGRADE, CHECK OP FILE, CHECK SPLIT FILE, CHECK FRONT END, **TO BE CHECKED\\\",\\r\\n \\\"batch_status_options_proofreader\\\": \\\"OP FILE OK, SPLIT FILE OK, FRONT END OK, **TO BE IMPORTED, **FINISHED, **REWORK, **STANDBY, **UNRECORDABLE\\\",\\r\\n \\\"batch_status_options_overall\\\": \\\"ONGOING, STANDBY, FINISHED, UNRECORDABLE\\\",\\r\\n \\\"aircrafts\\\": \\\"A300, A300-600, A310, A320, A330, A340, A350, A380\\\",\\r\\n \\\"split_batch_factor\\\": \\\"2, 3, 4, 5, 6, 7, 8, 9\\\",\\r\\n \\\"IDlentgh\\\": \\\"6\\\",\\r\\n \\\"port\\\": \\\"5000\\\"\\r\\n }\\r\\n \\r\\n if not os.path.isfile(os.path.join(self.cwd, \\\"config.json\\\")):\\r\\n self.func.write_json(config_data, self.cwd, fname=\\\"config.json\\\")\",\n \"def copy(CopySource=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, SourceClient=None, Config=None):\\n pass\",\n \"def _kwargs(self):\\n dict = DAG._kwargs(self) \\n if (self.job): \\n dict[\\\"inputpaths\\\"] = self.job.inputpaths\\n dict[\\\"outputpath\\\"] = self.job.outputpath\\n dict[\\\"job\\\"] = \\\"%s()\\\" % self.job.__class__.__name__\\n return dict\",\n \"def setup_jobs(self):\\n transfer_args = [\\\"analysis_type\\\", \\\"perturbation\\\", \\\"num_permutations\\\", \\\"permutation_test_statistic\\\", \\\"loss_function\\\",\\n \\\"importance_significance_level\\\", \\\"window_search_algorithm\\\", \\\"window_effect_size_threshold\\\"]\\n jobs = [None] * self.num_jobs\\n for idx in range(self.num_jobs):\\n # Create and launch condor job\\n features_filename = constants.INPUT_FEATURES_FILENAME.format(self.args.output_dir, idx)\\n input_files = [features_filename, self.args.model_filename, self.args.model_loader_filename, self.args.data_filename]\\n job_dir = f\\\"{self.args.output_dir}/outputs_{idx}\\\"\\n cmd = f\\\"python3 -m anamod.core.worker -worker_idx {idx}\\\"\\n for arg in transfer_args:\\n if hasattr(self.args, arg):\\n cmd += f\\\" -{arg} {getattr(self.args, arg)}\\\"\\n # Relative file paths for non-shared FS, absolute for shared FS\\n for name, path in dict(output_dir=job_dir, features_filename=features_filename, model_filename=self.args.model_filename,\\n model_loader_filename=self.args.model_loader_filename, data_filename=self.args.data_filename).items():\\n cmd += f\\\" -{name} {os.path.abspath(path)}\\\" if self.args.shared_filesystem else f\\\" -{name} {os.path.basename(path)}\\\"\\n job = CondorJobWrapper(cmd, input_files, job_dir, shared_filesystem=self.args.shared_filesystem,\\n memory=f\\\"{self.args.memory_requirement}GB\\\", disk=f\\\"{self.args.disk_requirement}GB\\\",\\n avoid_bad_hosts=self.args.avoid_bad_hosts, retry_arbitrary_failures=self.args.retry_arbitrary_failures,\\n cleanup=self.args.cleanup)\\n jobs[idx] = job\\n return jobs\",\n \"def assert_task_args(cls, args: \\\"DictConfig\\\", shared_state: \\\"SharedTaskState\\\") -> None:\\n assert isinstance(\\n shared_state, SharedStaticTaskState\\n ), \\\"Cannot assert args on a non-static state\\\"\\n super().assert_task_args(args, shared_state)\\n\\n found_task_source = args.blueprint.task_source\\n assert (\\n found_task_source is not None\\n ), \\\"Must provide a path to a javascript bundle in `task_source`\\\"\\n\\n found_task_path = os.path.expanduser(found_task_source)\\n assert os.path.exists(\\n found_task_path\\n ), f\\\"Provided task source {found_task_path} does not exist.\\\"\\n\\n link_task_source = args.blueprint.link_task_source\\n current_architect = args.architect._architect_type\\n allowed_architects = [\\\"local\\\"]\\n assert link_task_source == False or (\\n link_task_source == True and current_architect in allowed_architects\\n ), f\\\"`link_task_source={link_task_source}` is not compatible with architect type: {args.architect._architect_type}. Please check your task configuration.\\\"\\n\\n if link_task_source == False and current_architect in allowed_architects:\\n logger.info(\\n \\\"If you want your server to update on reload whenever you make changes to your webapp, then make sure to set \\\\n\\\\nlink_task_source: [blue]true[/blue]\\\\n\\\\nin your task's hydra configuration and run \\\\n\\\\n[purple]cd[/purple] webapp [red]&&[/red] [green]npm[/green] run dev:watch\\\\n\\\\nin a separate terminal window. For more information check out:\\\\nhttps://mephisto.ai/docs/guides/tutorials/custom_react/#12-launching-the-task\\\\n\\\",\\n extra={\\\"markup\\\": True},\\n )\",\n \"def prepare_jobs_data(self, ecosystem, package, version):\\n return \\\\\\n {\\n \\\"flow_arguments\\\": [\\n {\\n \\\"ecosystem\\\": ecosystem,\\n \\\"name\\\": package,\\n \\\"version\\\": version,\\n \\\"force\\\": True,\\n \\\"force_graph_sync\\\": True,\\n \\\"recursive_limit\\\": 0\\n }\\n ],\\n \\\"flow_name\\\": \\\"bayesianApiFlow\\\"\\n }\",\n \"def main(conn, label_config, table_name, start_date, end_date,\\r\\n preprocessing_prefix):\\r\\n label_sql = label_config['query']\\r\\n label_sql = label_sql.replace('{prefix}', preprocessing_prefix)\\r\\n label_sql = label_sql.replace('{start_date}', start_date)\\r\\n label_sql = label_sql.replace('{end_date}', end_date)\\r\\n drop_sql = f'drop table if exists {table_name};'\\r\\n create_sql = f'create table {table_name} as ({label_sql});'\\r\\n sql.run_sql_from_string(conn, drop_sql)\\r\\n sql.run_sql_from_string(conn, create_sql)\",\n \"def Copy(self, copy):\\n return _table.Table_Copy(self, copy)\",\n \"def __prepare_job(self, job_wrapper, job_destination):\\n command_line = None\\n client = None\\n remote_job_config = None\\n compute_environment = None\\n try:\\n client = self.get_client_from_wrapper(job_wrapper)\\n tool = job_wrapper.tool\\n remote_job_config = client.setup(tool.id, tool.version)\\n rewrite_parameters = LwrJobRunner.__rewrite_parameters( client )\\n prepare_kwds = {}\\n if rewrite_parameters:\\n compute_environment = LwrComputeEnvironment( client, job_wrapper, remote_job_config )\\n prepare_kwds[ 'compute_environment' ] = compute_environment\\n job_wrapper.prepare( **prepare_kwds )\\n self.__prepare_input_files_locally(job_wrapper)\\n remote_metadata = LwrJobRunner.__remote_metadata( client )\\n dependency_resolution = LwrJobRunner.__dependency_resolution( client )\\n metadata_kwds = self.__build_metadata_configuration(client, job_wrapper, remote_metadata, remote_job_config)\\n remote_command_params = dict(\\n working_directory=remote_job_config['working_directory'],\\n metadata_kwds=metadata_kwds,\\n dependency_resolution=dependency_resolution,\\n )\\n remote_working_directory = remote_job_config['working_directory']\\n # TODO: Following defs work for LWR, always worked for LWR but should be\\n # calculated at some other level.\\n remote_job_directory = os.path.abspath(os.path.join(remote_working_directory, os.path.pardir))\\n remote_tool_directory = os.path.abspath(os.path.join(remote_job_directory, \\\"tool_files\\\"))\\n container = self._find_container(\\n job_wrapper,\\n compute_working_directory=remote_working_directory,\\n compute_tool_directory=remote_tool_directory,\\n compute_job_directory=remote_job_directory,\\n )\\n command_line = build_command(\\n self,\\n job_wrapper=job_wrapper,\\n container=container,\\n include_metadata=remote_metadata,\\n include_work_dir_outputs=False,\\n remote_command_params=remote_command_params,\\n )\\n except Exception:\\n job_wrapper.fail( \\\"failure preparing job\\\", exception=True )\\n log.exception(\\\"failure running job %d\\\" % job_wrapper.job_id)\\n\\n # If we were able to get a command line, run the job\\n if not command_line:\\n job_wrapper.finish( '', '' )\\n\\n return command_line, client, remote_job_config, compute_environment\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6806518","0.51471066","0.5135233","0.5034788","0.4957393","0.49131292","0.483293","0.4809419","0.47891185","0.47865072","0.4757659","0.46871853","0.46683812","0.46534342","0.46357578","0.46097738","0.45914286","0.45865327","0.457555","0.45609608","0.45531315","0.4541542","0.45230606","0.45217237","0.45121175","0.44751364","0.44724846","0.44585148","0.44583514","0.44578895","0.44328374","0.4430723","0.44290823","0.4424437","0.43942782","0.43902308","0.4380478","0.43767503","0.4376245","0.43692726","0.43640503","0.43627232","0.43527898","0.43488112","0.4348266","0.43480918","0.43472457","0.43357152","0.43352816","0.4329406","0.43147004","0.42907143","0.42858192","0.4280023","0.42786917","0.4275506","0.42655027","0.4262821","0.42623588","0.426164","0.42548752","0.42503175","0.42485717","0.42431003","0.42278922","0.42273858","0.42170283","0.42044568","0.41984707","0.4198079","0.4197644","0.41960672","0.41902086","0.41797945","0.4178592","0.41717142","0.4162135","0.4161416","0.41609934","0.4154808","0.41535458","0.4153215","0.4151624","0.41487232","0.4144681","0.41438156","0.41397274","0.41393596","0.41336727","0.4129702","0.41267553","0.4119714","0.4118392","0.41181016","0.4117269","0.41152474","0.41130465","0.41129538","0.4112596","0.41043875"],"string":"[\n \"0.6806518\",\n \"0.51471066\",\n \"0.5135233\",\n \"0.5034788\",\n \"0.4957393\",\n \"0.49131292\",\n \"0.483293\",\n \"0.4809419\",\n \"0.47891185\",\n \"0.47865072\",\n \"0.4757659\",\n \"0.46871853\",\n \"0.46683812\",\n \"0.46534342\",\n \"0.46357578\",\n \"0.46097738\",\n \"0.45914286\",\n \"0.45865327\",\n \"0.457555\",\n \"0.45609608\",\n \"0.45531315\",\n \"0.4541542\",\n \"0.45230606\",\n \"0.45217237\",\n \"0.45121175\",\n \"0.44751364\",\n \"0.44724846\",\n \"0.44585148\",\n \"0.44583514\",\n \"0.44578895\",\n \"0.44328374\",\n \"0.4430723\",\n \"0.44290823\",\n \"0.4424437\",\n \"0.43942782\",\n \"0.43902308\",\n \"0.4380478\",\n \"0.43767503\",\n \"0.4376245\",\n \"0.43692726\",\n \"0.43640503\",\n \"0.43627232\",\n \"0.43527898\",\n \"0.43488112\",\n \"0.4348266\",\n \"0.43480918\",\n \"0.43472457\",\n \"0.43357152\",\n \"0.43352816\",\n \"0.4329406\",\n \"0.43147004\",\n \"0.42907143\",\n \"0.42858192\",\n \"0.4280023\",\n \"0.42786917\",\n \"0.4275506\",\n \"0.42655027\",\n \"0.4262821\",\n \"0.42623588\",\n \"0.426164\",\n \"0.42548752\",\n \"0.42503175\",\n \"0.42485717\",\n \"0.42431003\",\n \"0.42278922\",\n \"0.42273858\",\n \"0.42170283\",\n \"0.42044568\",\n \"0.41984707\",\n \"0.4198079\",\n \"0.4197644\",\n \"0.41960672\",\n \"0.41902086\",\n \"0.41797945\",\n \"0.4178592\",\n \"0.41717142\",\n \"0.4162135\",\n \"0.4161416\",\n \"0.41609934\",\n \"0.4154808\",\n \"0.41535458\",\n \"0.4153215\",\n \"0.4151624\",\n \"0.41487232\",\n \"0.4144681\",\n \"0.41438156\",\n \"0.41397274\",\n \"0.41393596\",\n \"0.41336727\",\n \"0.4129702\",\n \"0.41267553\",\n \"0.4119714\",\n \"0.4118392\",\n \"0.41181016\",\n \"0.4117269\",\n \"0.41152474\",\n \"0.41130465\",\n \"0.41129538\",\n \"0.4112596\",\n \"0.41043875\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.73063713"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2287,"cells":{"query":{"kind":"string","value":"Process schema Updates (additions/mode changes) for the request. Retrieves the current table schema for ref and attempts to merge in the schema provided in the requests. This is necessary since the API backend does not handle PATCH semantics for schema updates (e.g. process the deltas) so we must always send the fully updated schema in the requests."},"document":{"kind":"string","value":"def ProcessSchemaUpdate(ref, args, request):\n table = request.table\n relaxed_columns = args.relax_columns\n if not table.schema and not relaxed_columns: # if not updating schema,\n return request # then just return.\n\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\n ref.Name(),\n ref.projectId)\n\n new_schema_columns = table.schema\n updated_fields = _GetUpdatedSchema(original_schema,\n new_schema_columns,\n relaxed_columns)\n\n table_schema_type = GetApiMessage('TableSchema')\n request.table.schema = table_schema_type(fields=updated_fields)\n\n return request"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def compute_schema_updates(self):\n data = self.client._perform_json(\n \"GET\", \"/projects/%s/recipes/%s/schema-update\" % (self.project_key, self.recipe_name))\n return RequiredSchemaUpdates(self, data)","async def upgradeSchema(self) -> None:","def merge_schema_entry(\n self,\n old_schema_entry,\n new_schema_entry,\n base_path=None,\n ):\n if not old_schema_entry:\n return new_schema_entry\n\n # If the new schema is None, return immediately.\n if not new_schema_entry:\n return new_schema_entry\n\n # If a field value is missing, permanently set 'filled' to False.\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\n old_schema_entry['filled'] = False\n new_schema_entry['filled'] = False\n\n old_status = old_schema_entry['status']\n new_status = new_schema_entry['status']\n\n # new 'soft' does not clobber old 'hard'\n if old_status == 'hard' and new_status == 'soft':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n old_schema_entry['info']['mode'] = mode\n return old_schema_entry\n\n # new 'hard' clobbers old 'soft'\n if old_status == 'soft' and new_status == 'hard':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n new_schema_entry['info']['mode'] = mode\n return new_schema_entry\n\n # Verify that it's soft->soft or hard->hard\n if old_status != new_status:\n raise Exception(\n f'Unexpected schema_entry type, this should never happen: '\n f'old ({old_status}); new ({new_status})'\n )\n\n old_info = old_schema_entry['info']\n old_name = old_info['name']\n old_type = old_info['type']\n old_mode = old_info['mode']\n new_info = new_schema_entry['info']\n new_name = new_info['name']\n new_type = new_info['type']\n new_mode = new_info['mode']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # Defensive check, names should always be the same.\n if old_name != new_name:\n if old_name.lower() != new_name.lower():\n raise Exception(\n 'Unexpected difference in name, should never happen:'\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\n )\n else:\n # preserve old name if case is different\n new_info['name'] = old_info['name']\n\n # Recursively merge in the subfields of a RECORD, allowing\n # NULLABLE to become REPEATED (because 'bq load' allows it).\n if old_type == 'RECORD' and new_type == 'RECORD':\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\n # 'bq load' allows it.\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\n old_info['mode'] = 'REPEATED'\n self.log_error(\n f'Converting schema for \"{full_old_name}\" from '\n 'NULLABLE RECORD into REPEATED RECORD'\n )\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\n # TODO: Maybe remove this warning output. It was helpful during\n # development, but maybe it's just natural.\n self.log_error(\n f'Leaving schema for \"{full_old_name}\" as REPEATED RECORD'\n )\n\n # RECORD type needs a recursive merging of sub-fields. We merge into\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\n # can be modified in situ.\n old_fields = old_info['fields']\n new_fields = new_info['fields']\n for key, new_entry in new_fields.items():\n old_entry = old_fields.get(key)\n new_base_path = json_full_path(base_path, old_name)\n old_fields[key] = self.merge_schema_entry(\n old_schema_entry=old_entry,\n new_schema_entry=new_entry,\n base_path=new_base_path,\n )\n return old_schema_entry\n\n new_mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if new_mode is None:\n return None\n new_schema_entry['info']['mode'] = new_mode\n\n # For all other types...\n if old_type != new_type:\n # Check that the converted types are compatible.\n candidate_type = convert_type(old_type, new_type)\n if not candidate_type:\n self.log_error(\n f'Ignoring field with mismatched type: '\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\n )\n return None\n\n new_info['type'] = candidate_type\n return new_schema_entry","def resolve_schema_in_request_body(self, request_body):\n content = request_body[\"content\"]\n for content_type in content:\n schema = content[content_type][\"schema\"]\n content[content_type][\"schema\"] = self.openapi.resolve_schema_dict(schema)","def process(*, schemas: types.Schemas) -> None:\n # Retrieve back references\n backrefs = process_helper.get_artifacts(\n schemas=schemas, get_schema_artifacts=_get_schema_backrefs\n )\n # Map to a schema for each grouped back references\n backref_schemas = process_helper.calculate_outputs(\n artifacts=backrefs, calculate_output=_backrefs_to_schema\n )\n # Convert to list to resolve iterator\n backref_schema_list = list(backref_schemas)\n # Add backreferences to schemas\n for name, backref_schema in backref_schema_list:\n schemas[name] = {\"allOf\": [schemas[name], backref_schema]}","def _GetUpdatedSchema(\n original_schema,\n new_columns=None,\n relaxed_columns=None):\n orig_field_map = (\n {f.name: f for f in original_schema.fields} if original_schema else {})\n\n if relaxed_columns:\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\n\n if new_columns:\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\n\n return sorted(orig_field_map.values(), key=lambda x: x.name)","def resolve_schema(self, data):\n if not isinstance(data, dict):\n return\n\n # OAS 2 component or OAS 3 header\n if \"schema\" in data:\n data[\"schema\"] = self.openapi.resolve_schema_dict(data[\"schema\"])\n # OAS 3 component except header\n if self.openapi_version.major >= 3:\n if \"content\" in data:\n for content_type in data[\"content\"]:\n schema = data[\"content\"][content_type][\"schema\"]\n data[\"content\"][content_type][\n \"schema\"\n ] = self.openapi.resolve_schema_dict(schema)","def update_schema(self, new_schema):\n return self.conn.update_schema(new_schema)","def upgrade_schema():\n\n db_version = get_db_version()\n try:\n while db_version < CURRENT_DATABASE_VERSION:\n db_version += 1\n upgrade_script = 'upgrade_to_'+str(db_version)\n globals()[upgrade_script]()\n except KeyError as e:\n logging.exception('Attempted to upgrade using script that does not exist: {}'.format(e))\n sys.exit(1)\n except Exception as e:\n logging.exception('Incremental upgrade of db failed')\n sys.exit(1)\n else:\n config.db.singletons.update_one({'_id': 'version'}, {'$set': {'database': CURRENT_DATABASE_VERSION}})\n sys.exit(0)","def update_schema(self, engine_name, schema):\n endpoint = \"engines/{}/schema\".format(engine_name)\n data = json.dumps(schema)\n return self.swiftype_session.request('post', endpoint, data=data)","def merge_schema(self, schema):\n for _, attr_schema in schema.iter_attributes():\n self.merge_attribute_schema(attr_schema)","def test_compare_schemas_happypath(self):\n status = schema_utils.compare_schemas(\n self.base_schema,\n self.base_schema\n )\n\n assert status == schema_utils.Update.no_update","def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\n old_info = old_schema_entry['info']\n new_info = new_schema_entry['info']\n old_mode = old_info['mode']\n old_name = old_info['name']\n old_type = old_info['type']\n old_status = old_schema_entry['status']\n new_mode = new_info['mode']\n new_name = new_info['name']\n new_type = new_info['type']\n new_status = new_schema_entry['status']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # If the old field is a REQUIRED primitive (which could only have come\n # from an existing schema), the new field can be either a\n # NULLABLE(filled) or a NULLABLE(unfilled).\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\n # If the new field is filled, then retain the REQUIRED.\n if new_schema_entry['filled']:\n return old_mode\n else:\n # The new field is not filled (i.e. an empty or null field).\n # If --infer_mode is active, then we allow the REQUIRED to\n # revert back to NULLABLE.\n if self.infer_mode:\n return new_mode\n else:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode.'\n ' cannot convert to NULLABLE because infer_schema not'\n ' set:'\n f' old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n elif old_mode != new_mode:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode: '\n f'old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n return old_mode","def _patch_schema(self):\n fields = get_json()['data']['attributes'].keys()\n return make_entity_schema(\n self.SCHEMA, self.RESOURCE_NAME,\n make_data_schema(\n self.SCHEMA, id_required=True,\n only=fields, partial=True\n )\n )","def _update(self, schema: 'Schema'):\n for method in schema._get_methods():\n if method.id in self:\n raise ValueError(\n f\"Duplicate method id for {method.method} id: {method.id}\"\n )\n\n for combinator in schema._get_combinators():\n if combinator.id in self:\n raise ValueError(\n f\"Duplicate combinator id for {combinator.predicate} \" +\n f\"id: {combinator.id}\"\n )\n\n self.constructors += schema.constructors\n self.functions += schema.functions\n\n self._build_schema_data()","def preprocess_schema(schema, imported_schemas, elements, xsd_uri, dialect, http, cache, force_download, wsdl_basedir, global_namespaces=None, qualified=False):\n\n from .simplexml import SimpleXMLElement # here to avoid recursive imports\n\n # analyze the namespaces used in this schema\n local_namespaces = {}\n for k, v in schema[:]:\n if k.startswith(\"xmlns\"):\n local_namespaces[get_local_name(k)] = v\n if k == 'targetNamespace':\n # URI namespace reference for this schema\n if v == \"urn:DefaultNamespace\":\n v = global_namespaces[None]\n local_namespaces[None] = v\n if k == 'elementFormDefault':\n qualified = (v == \"qualified\")\n # add schema namespaces to the global namespace dict = {URI: ns prefix}\n for ns in local_namespaces.values():\n if ns not in global_namespaces:\n global_namespaces[ns] = 'ns%s' % len(global_namespaces)\n \n for element in schema.children() or []:\n if element.get_local_name() in ('import', 'include',):\n schema_namespace = element['namespace']\n schema_location = element['schemaLocation']\n if schema_location is None:\n log.debug('Schema location not provided for %s!' % schema_namespace)\n continue\n if schema_location in imported_schemas:\n log.debug('Schema %s already imported!' % schema_location)\n continue\n imported_schemas[schema_location] = schema_namespace\n log.debug('Importing schema %s from %s' % (schema_namespace, schema_location))\n # Open uri and read xml:\n xml = fetch(schema_location, http, cache, force_download, wsdl_basedir)\n\n # Parse imported XML schema (recursively):\n imported_schema = SimpleXMLElement(xml, namespace=xsd_uri)\n preprocess_schema(imported_schema, imported_schemas, elements, xsd_uri, dialect, http, cache, force_download, wsdl_basedir, global_namespaces, qualified)\n\n element_type = element.get_local_name()\n if element_type in ('element', 'complexType', \"simpleType\"):\n namespace = local_namespaces[None] # get targetNamespace\n element_ns = global_namespaces[ns] # get the prefix\n element_name = element['name']\n log.debug(\"Parsing Element %s: %s\" % (element_type, element_name))\n if element.get_local_name() == 'complexType':\n children = element.children()\n elif element.get_local_name() == 'simpleType':\n children = element('restriction', ns=xsd_uri)\n elif element.get_local_name() == 'element' and element['type']:\n children = element\n else:\n children = element.children()\n if children:\n children = children.children()\n elif element.get_local_name() == 'element':\n children = element\n if children:\n process_element(elements, element_name, children, element_type, xsd_uri, dialect, namespace, qualified)","def modify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\n\n return provision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)","def modify_bigquery_schema(self, schema, info_keys):\n # type: (bigquery.TableSchema, Set[str]) -> None","async def update_db(appname, schema, table, action):\n loop = asyncio.get_event_loop()\n if args.action == 'info':\n await schema_info(args.appname, args.schema)\n sys.exit()\n\n dbstate = await schema_state(args.appname, args.schema, args.table)\n modstate = model_state(args.appname, args.schema, args.table)\n updiff, downdiff = compare_state(args.appname, args.schema, args.table,\n dbstate, modstate)\n if args.action == 'upgrade':\n await set_state(args.appname, updiff)\n elif args.action == 'downgrade':\n await set_state(args.appname, downdiff)\n else:\n print(\"upgrade diff looks like\")\n print(updiff)\n print(\"downgrade diff looks like\")\n print(downdiff)","def _Dynamic_GetSchema(self, req, schema, request_id=None):\n # This is not used, but it is required for the method signature.\n del request_id\n\n app_str = req.app()\n self.__ValidateAppId(app_str)\n schema.set_more_results(False)","def status_changes_schema():\n schema = endpoint_schema(\"status_changes\")\n items = schema[\"properties\"][\"data\"][\"properties\"][\"status_changes\"][\"items\"]\n\n # merge the state machine definitions and transition combinations rule\n state_machine_defs, transitions = common.vehicle_state_machine(\"vehicle_state\", \"event_types\")\n schema[\"definitions\"].update(state_machine_defs)\n items[\"allOf\"].append(transitions)\n\n trip_id_ref = common.load_definitions(\"trip_id_reference\")\n items[\"allOf\"].append(trip_id_ref)\n\n # verify and return\n return common.check_schema(schema)","def update(self, schema: 'Schema'):\n self._update(schema)","def test_schema_updates(self):\n with patch(\"openedx.core.djangoapps.content_libraries.libraries_index.ContentLibraryIndexer.SCHEMA_VERSION\",\n new=0):\n result = self._create_library(slug=\"test-lib-schemaupdates-1\", title=\"Title 1\", description=\"Description\")\n library_key = LibraryLocatorV2.from_string(result['id'])\n assert len(ContentLibraryIndexer.get_items([library_key])) == 1\n\n with patch(\"openedx.core.djangoapps.content_libraries.libraries_index.ContentLibraryIndexer.SCHEMA_VERSION\",\n new=1):\n assert len(ContentLibraryIndexer.get_items([library_key])) == 0\n\n call_command(\"reindex_content_library\", all=True, force=True)\n\n assert len(ContentLibraryIndexer.get_items([library_key])) == 1","def process_updates():\n print \"[{x}] Processing Requests\".format(x=dates.now())\n WorkflowApi.process_requests()\n WorkflowApi.process_enhancements()","def fetch_schema(self) -> None:\n if self.schema_file:\n logger.info(\"Loaded schema from file '%s'\", self.schema_file)\n self._schema = load_schema_file(self.schema_file)\n else:\n url = self.schema_url or urljoin(self.base_url, \"schema/openapi.yaml\")\n logger.info(\"Fetching schema at '%s'\", url)\n self._schema = schema_fetcher.fetch(url, {\"v\": \"3\"})","def ensure_internal_schema_updated(self):\n if self._internal_schema_updated:\n return\n if internalmigrations.needs_upgrading(self):\n assert not self._in_transaction\n with self.lock():\n internalmigrations.upgrade(self)\n self.connection.commit()\n self._internal_schema_updated = True","def rebuild(self, dframe, overwrite=False):\n current_schema = self\n new_schema = schema_from_dframe(dframe, self)\n\n if current_schema and not overwrite:\n # merge new schema with existing schema\n current_schema.update(new_schema)\n new_schema = current_schema\n\n return new_schema","def test_schema_updates(self):\n lib = self._create_library(slug=\"test-lib--block-schemaupdates-1\", title=\"Title 1\", description=\"Description\")\n with patch(\"openedx.core.djangoapps.content_libraries.libraries_index.LibraryBlockIndexer.SCHEMA_VERSION\",\n new=0):\n block = self._add_block_to_library(lib['id'], \"problem\", \"problem1\")\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 1\n\n with patch(\"openedx.core.djangoapps.content_libraries.libraries_index.LibraryBlockIndexer.SCHEMA_VERSION\",\n new=1):\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 0\n\n call_command(\"reindex_content_library\", all=True, force=True)\n\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 1","def test_compare_schemas_major(self):\n status = schema_utils.compare_schemas(\n self.base_schema,\n self.major_removed_value\n )\n\n assert status == schema_utils.Update.major","def _load_schema(self, mode=\"staging\"):\n\n self._check_mode(mode)\n\n json_path = self.table_folder / f\"schema-{mode}.json\"\n columns = self.table_config[\"columns\"]\n\n if mode == \"staging\":\n new_columns = []\n for c in columns:\n # case is_in_staging are None then must be True\n is_in_staging = (\n True if c.get(\"is_in_staging\") is None else c[\"is_in_staging\"]\n )\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\n if is_in_staging and not c.get(\"is_partition\"):\n c[\"type\"] = \"STRING\"\n new_columns.append(c)\n\n del columns\n columns = new_columns\n\n elif mode == \"prod\":\n schema = self._get_table_obj(mode).schema\n\n # get field names for fields at schema and at table_config.yaml\n column_names = [c[\"name\"] for c in columns]\n schema_names = [s.name for s in schema]\n\n # check if there are mismatched fields\n not_in_columns = [name for name in schema_names if name not in column_names]\n not_in_schema = [name for name in column_names if name not in schema_names]\n\n # raise if field is not in table_config\n if not_in_columns:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in table_config.yaml. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_columns,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # raise if field is not in schema\n if not_in_schema:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in publish.sql. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_schema,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # if field is in schema, get field_type and field_mode\n for c in columns:\n for s in schema:\n if c[\"name\"] == s.name:\n c[\"type\"] = s.field_type\n c[\"mode\"] = s.mode\n break\n ## force utf-8, write schema_{mode}.json\n json.dump(columns, (json_path).open(\"w\", encoding=\"utf-8\"))\n\n # load new created schema\n return self.client[f\"bigquery_{mode}\"].schema_from_json(str(json_path))","async def schemas(\n self,\n *,\n query_params: Optional[Dict[str, any]] = None,\n headers: Optional[Dict[str, str]] = None,\n ) -> AuditLogsResponse:\n return await self.api_call(\n path=\"schemas\",\n query_params=query_params,\n headers=headers,\n )","def parse_schema(schemaurl, schema_dir=None):\n if schema_dir:\n try:\n # attempts to open .schema file in directory schema_dir\n local_schema_path = schema_dir + \"/\" + \\\n schemaurl[schemaurl.rfind('/') + 1:-1] + \".schema\"\n print \"Looking for schema in file %s\" % (local_schema_path)\n schema = json.load(open(local_schema_path))\n except Exception as e:\n print \"Couldn't load schema %s from file %s\\n%s\" % (\n schemaurl, schema_dir, str(e))\n return None\n else:\n # load the schema directly from schemaurl, i.e., from the web\n try:\n schema = json.load(urllib2.urlopen(schemaurl))\n except Exception as e:\n print \"Couldn't load schema %s\\n%s\" % (schemaurl, str(e))\n return None\n\n if 'extends' in schema and '$ref' in schema['extends']:\n\n parent_schema = json.load(urllib2.urlopen(schema['extends']['$ref']))\n while (True): # exits loop when no additional extensions (break below)\n for key in sorted(parent_schema.keys()):\n if key not in schema:\n schema[key] = parent_schema[key]\n # need to merge these keys individually\n if key == 'properties':\n for key in sorted(parent_schema['properties'].keys()):\n if key not in schema['properties']:\n schema['properties'][key] = parent_schema[\n 'properties'][key]\n if 'extends' in parent_schema:\n parent_schema = json.load(\n urllib2.urlopen(parent_schema['extends']['$ref']))\n else:\n break\n # essentially a do while loop (exit condition)\n\n return schema","def deduce_schema_for_record(self, json_object, schema_map, base_path=None):\n for key, value in json_object.items():\n # The canonical key is the lower-cased version of the sanitized key\n # so that the case of the field name is preserved when generating\n # the schema but we don't create invalid, duplicate, fields since\n # BigQuery is case insensitive\n canonical_key = self.sanitize_name(key).lower()\n schema_entry = schema_map.get(canonical_key)\n new_schema_entry = self.get_schema_entry(\n key=key,\n value=value,\n base_path=base_path\n )\n schema_map[canonical_key] = self.merge_schema_entry(\n old_schema_entry=schema_entry,\n new_schema_entry=new_schema_entry,\n base_path=base_path\n )","def update_all():\n req_data = request.get_json()\n jobs = JobModel.get_one_job(job_id)\n if not jobs:\n return custom_response({'Error': 'Job Not Found'}, 404)\n\n data, error = job_schema.load(req_data, partial=True)\n if error:\n return custom_response(error, 400)\n\n for job in jobs:\n job.update(data)\n job_message = job_schema.dump(job)\n\n return custom_response(job_message, 200)","def test_json_merge_patch():\n schemas = {}\n\n basenames = (\n 'record-package-schema.json',\n 'release-package-schema.json',\n 'release-schema.json',\n 'versioned-release-validation-schema.json',\n )\n\n if ocds_version or not use_development_version:\n url_pattern = ocds_schema_base_url + ocds_tag + '/{}'\n else:\n url_pattern = development_base_url + '/{}'\n\n for basename in basenames:\n schemas[basename] = http_get(url_pattern.format(basename)).json()\n\n if basename == 'release-schema.json':\n path = os.path.join(extensiondir, 'extension.json')\n with open(path) as f:\n metadata = json.load(f, object_pairs_hook=rejecting_dict)\n schemas[basename] = extend_schema(basename, schemas[basename], metadata, codelists=external_codelists)\n\n # This loop is somewhat unnecessary, as repositories contain at most one of each schema file.\n for path, name, text, data in walk_json_data(patch):\n if is_json_merge_patch(data):\n if name in basenames:\n unpatched = deepcopy(schemas[name])\n try:\n patched = merge(unpatched, data)\n except Exception as e:\n assert False, f'Exception: {e} {path}'\n\n # All metadata should be present.\n validate_json_schema(path, name, patched, metaschemas()['metaschema'], full_schema=True)\n\n # Empty patches aren't allowed. json_merge_patch mutates `unpatched`, so `schemas[name]` is tested.\n assert patched != schemas[name]","def forwards_func(apps, schema_editor):\n judge_file = apps.get_model(\"judges\", \"JudgeFile\")\n db_alias = schema_editor.connection.alias\n judge_file.objects.using(db_alias).filter(\n file_type='ruling').update(file_type='rulings')\n judge_file.objects.using(db_alias).filter(\n file_type='verdict').update(file_type='verdicts')\n judge_file.objects.using(db_alias).filter(\n file_type='transcript').update(file_type='transcripts')\n judge_file.objects.using(db_alias).filter(\n file_type='image').update(file_type='campaigns')","def update_all(self, request):\n\n schema = self.session.info['schema']\n\n for item in self.query().filter_by(schema=schema):\n self.session.delete(item)\n\n for item in ElectionCollection(self.session).query():\n self.update(item, request)\n\n for item in ElectionCompoundCollection(self.session).query():\n self.update(item, request)\n\n for item in VoteCollection(self.session).query():\n self.update(item, request)","def _get_and_validate_schema_mapping(schema1, schema2, strict=False):\n\n len_schema1 = len(schema1)\n len_schema2 = len(schema2)\n\n # If both non-empty, must be same length\n if 0 < len_schema1 != len_schema2 > 0:\n raise ValueError(\"Attempted to merge profiles with different \"\n \"numbers of columns\")\n\n # In the case of __add__ with one of the schemas not initialized\n if strict and (len_schema1 == 0 or len_schema2 == 0):\n raise ValueError(\"Cannot merge empty profiles.\")\n\n # In the case of _update_from_chunk with uninitialized schema\n if not strict and len_schema2 == 0:\n return {col_ind: col_ind for col_ind_list in schema1.values()\n for col_ind in col_ind_list}\n\n # Map indices in schema1 to indices in schema2\n schema_mapping = dict()\n\n for key in schema1:\n # Pandas columns are int by default, but need to fuzzy match strs\n if isinstance(key, str):\n key = key.lower()\n if key not in schema2:\n raise ValueError(\"Columns do not match, cannot update \"\n \"or merge profiles.\")\n\n elif len(schema1[key]) != len(schema2[key]):\n raise ValueError(f\"Different number of columns detected for \"\n f\"'{key}', cannot update or merge profiles.\")\n\n is_duplicate_col = len(schema1[key]) > 1\n for schema1_col_ind, schema2_col_ind in zip(schema1[key],\n schema2[key]):\n if is_duplicate_col and (schema1_col_ind != schema2_col_ind):\n raise ValueError(f\"Different column indices under \"\n f\"duplicate name '{key}', cannot update \"\n f\"or merge unless schema is identical.\")\n schema_mapping[schema1_col_ind] = schema2_col_ind\n\n return schema_mapping","def _process_json(self, json_content):\n if self._ns_sqlcon.connection is None:\n LOG.error(f'failed to open connection to DB')\n return\n entries = [entry for entry in json_content]\n LOG.info('started updating DB')\n num_of_entries = len(entries)\n for x in range(num_of_entries):\n entry = entries[x]\n try:\n self._ns_sqlcon.update_plugins_table(entry['_source'])\n except AttributeError:\n LOG.exception(f'malformed entry: {entry}')\n if x % 2000 != 0:\n continue\n LOG.info(f'Updated {x} records')\n\n LOG.info(f'Updated {num_of_entries} records')\n try:\n LOG.info('Commit started')\n self._ns_sqlcon.session.commit()\n LOG.info('Commit finished')\n except sqlalchemy.exc.IntegrityError:\n LOG.exception('failed committing updates to DB')\n self._ns_sqlcon.session.rollback()\n\n LOG.info('Finished updating DB')","def formatSchema(self):\n schema = json.loads(self.schemaSource)\n stack = [schema]\n # Strip out all the docs\n while len(stack) > 0:\n elm = stack.pop()\n if \"doc\" in elm:\n elm[\"doc\"] = \"\"\n for value in elm.values():\n if isinstance(value, dict):\n stack.append(value)\n elif isinstance(value, list):\n for dic in value:\n if isinstance(dic, dict):\n stack.append(dic)\n jsonData = json.dumps(schema)\n output = \"\\n\".join(textwrap.wrap(jsonData)) + \"\\n\"\n return output","def schema_helper(self, name, _, schema=None, **kwargs):\n if schema is None:\n return None\n\n schema_instance = resolve_schema_instance(schema)\n\n schema_key = make_schema_key(schema_instance)\n self.warn_if_schema_already_in_spec(schema_key)\n self.openapi.refs[schema_key] = name\n\n json_schema = self.openapi.schema2jsonschema(schema_instance)\n\n return json_schema","def _TryGetCurrentSchema(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\n get_request = get_request_type(datasetId=dataset_id,\n tableId=table_id,\n projectId=project_id)\n try:\n table = service.Get(get_request)\n if not table or table.type != 'TABLE':\n raise SchemaUpdateError('Schema modifications only supported '\n 'on TABLE objects received [{}]'.format(\n table))\n except apitools_exceptions.HttpNotFoundError:\n raise SchemaUpdateError('Table with id [{}:{}:{}] not found.'.format(\n project_id, dataset_id, table_id))\n\n return table.schema","def generate_update(stmt, schema, path, rpc=None):\n if path:\n path_params = get_input_path_parameters(path)\n put = {}\n generate_api_header(stmt, put, 'Update', path)\n # Input parameters\n if path:\n put['parameters'] = create_parameter_list(path_params)\n else:\n put['parameters'] = []\n put['parameters'].append(create_body_dict(stmt.arg, schema))\n # Responses\n if rpc:\n response = create_responses(stmt.arg, rpc)\n else:\n response = create_responses(stmt.arg)\n put['responses'] = response\n return put","def update(self, mode=\"all\"):\n\n self._check_mode(mode)\n\n mode = [\"prod\", \"staging\"] if mode == \"all\" else [mode]\n for m in mode:\n\n try:\n table = self._get_table_obj(m)\n except google.api_core.exceptions.NotFound:\n continue\n\n # if m == \"staging\":\n\n table.description = self._render_template(\n Path(\"table/table_description.txt\"), self.table_config\n )\n\n # save table description\n with open(\n self.metadata_path\n / self.dataset_id\n / self.table_id\n / \"table_description.txt\",\n \"w\",\n encoding=\"utf-8\",\n ) as f:\n f.write(table.description)\n\n # when mode is staging the table schema already exists\n table.schema = self._load_schema(m)\n fields = [\"description\", \"schema\"] if m == \"prod\" else [\"description\"]\n self.client[f\"bigquery_{m}\"].update_table(table, fields=fields)\n\n logger.success(\n \" {object} {object_id} was {action}!\",\n object_id=self.table_id,\n object=\"Table\",\n action=\"updated\",\n )","def deduce_schema(self, input_data, *, schema_map=None):\n\n if self.input_format == 'csv':\n if self.csv_dialect:\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\n else:\n reader = csv.DictReader(input_data)\n elif self.input_format == 'json' or self.input_format is None:\n reader = json_reader(input_data)\n elif self.input_format == 'dict':\n reader = input_data\n else:\n raise Exception(f\"Unknown input_format '{self.input_format}'\")\n\n if schema_map is None:\n schema_map = OrderedDict()\n\n try:\n for json_object in reader:\n\n # Print a progress message periodically.\n self.line_number += 1\n if self.line_number % self.debugging_interval == 0:\n logging.info(f'Processing line {self.line_number}')\n\n # Deduce the schema from this given data record.\n if isinstance(json_object, dict):\n self.deduce_schema_for_record(\n json_object=json_object,\n schema_map=schema_map,\n )\n elif isinstance(json_object, Exception):\n self.log_error(\n f'Record could not be parsed: Exception: {json_object}'\n )\n if not self.ignore_invalid_lines:\n raise json_object\n else:\n self.log_error(\n 'Record should be a JSON Object '\n f'but was a {type(json_object)}'\n )\n if not self.ignore_invalid_lines:\n raise Exception(f'Record must be a JSON Object '\n f'but was a {type(json_object)}')\n finally:\n logging.info(f'Processed {self.line_number} lines')\n\n return schema_map, self.error_logs","def ProcessTableOverwrite(ref, args, request):\n dataset_id = ref.datasetId\n table_id = ref.Name()\n project_id = ref.projectId\n\n if args.overwrite:\n if _TableExists(dataset_id, table_id, project_id):\n _TryDeleteTable(dataset_id, table_id, project_id)\n\n return request","def _CreateSchemas(self) -> None:\n self.schema_objs = dict() # Holds OpenAPI representations of types.\n\n # Add the OpenAPI schemas of protobuf primitive types.\n primitive_type_schemas = {\n primitive_type[\"name\"]: primitive_type[\"schema\"]\n for primitive_type in primitive_types.values()\n }\n self.schema_objs.update(\n cast(Dict[str, Dict[str, str]], primitive_type_schemas))\n # Add the OpenAPI schemas of the statically described RDF types.\n self.schema_objs.update(rdf_type_schemas)\n\n # Holds state of type extraction (white/gray nodes).\n visiting: Set[str] = set()\n self._CreateRouterMethodSchemas(visiting)\n self._CreateFlowSchemas(visiting)","def test_compare_schemas_minor(self):\n status = schema_utils.compare_schemas(\n self.base_schema,\n self.minor_change\n )\n\n assert status == schema_utils.Update.minor","def update():\n as3s = AS3Schema()\n as3s.updateschemas()\n as3s_new = AS3Schema()\n\n if as3s.version != as3s_new.version:\n click.echo(\n f\"Updated AS3 JSON Schemas from version:{as3s.version} to:{as3s_new.version}\",\n )\n else:\n click.echo(\n f\"AS3 JSON Schemas are up-to-date, current version:{as3s.version}\",\n )","def get_schema(self, schema_versions_info):\n schema = None\n version = api_version_request.APIVersionRequest(VOLUME_MICROVERSION)\n for items in schema_versions_info:\n min_version = api_version_request.APIVersionRequest(items['min'])\n max_version = api_version_request.APIVersionRequest(items['max'])\n # This is case where COMPUTE_MICROVERSION is None, which means\n # request without microversion So select base v2.1 schema.\n if version.is_null() and items['min'] is None:\n schema = items['schema']\n break\n # else select appropriate schema as per COMPUTE_MICROVERSION\n elif version.matches(min_version, max_version):\n schema = items['schema']\n break\n if schema is None:\n raise exceptions.JSONSchemaNotFound(\n version=version.get_string(),\n schema_versions_info=schema_versions_info)\n return schema","def make_schema_changes(self, session, namespace='ns1'):\n debug(\"make_schema_changes() \" + str(namespace))\n session.execute('USE ks_%s' % namespace)\n # drop keyspace\n session.execute('DROP KEYSPACE ks2_%s' % namespace)\n wait(2)\n\n # create keyspace\n self.create_ks(session, \"ks3_%s\" % namespace, 2)\n session.execute('USE ks_%s' % namespace)\n\n wait(2)\n # drop column family\n session.execute(\"DROP COLUMNFAMILY cf2_%s\" % namespace)\n\n # create column family\n query = \"\"\"\n CREATE TABLE cf3_%s (\n col1 uuid PRIMARY KEY,\n col2 text,\n col3 text,\n col4 text\n );\n \"\"\" % (namespace)\n session.execute(query)\n\n # alter column family\n query = \"\"\"\n ALTER COLUMNFAMILY cf_%s\n ADD col4 text;\n \"\"\" % namespace\n session.execute(query)\n\n # add index\n session.execute(\"CREATE INDEX index2_%s ON cf_%s(col3)\"%(namespace, namespace))\n\n # remove an index\n session.execute(\"DROP INDEX index_%s\" % namespace)","def finalizeSchema(schema, folderish=False, moveDiscussion=True):\n schema.moveField('businessOldLocation', after='workLocations')\n schema.moveField('foldermanagers', after='businessOldLocation')\n# schema.moveField('bound_licences', after='isTransferOfLicence')\n schema.moveField('rubrics', after='folderCategory')\n schema.moveField('description', after='additionalLegalConditions')\n schema.moveField('referenceFT', after='referenceDGATLP')\n schema.moveField('isTransferOfLicence', after='referenceFT')\n\n return schema","def merge_schema(self, schema):\n self.validate_schema(schema)\n\n if self.exclusive is False:\n self.exclusive = schema.exclusive\n\n if self.default is None:\n self.default = schema.default","def _validate(self):\n schema_version = util.schemas[self.schema_name]\n stored_schemas = util.stored_schemas\n\n try:\n schema_obj = stored_schemas[\n \"http://redfish.dmtf.org/schemas/v1/\" + schema_version]\n except KeyError:\n raise OneViewRedfishError(\"{} not found\".format(schema_version))\n\n resolver = jsonschema.RefResolver('', schema_obj, store=stored_schemas)\n jsonschema.validate(self.redfish, schema_obj, resolver=resolver)","def flatten_schema_map(\n schema_map,\n keep_nulls=False,\n sorted_schema=True,\n infer_mode=False,\n input_format='json',\n):\n if not isinstance(schema_map, dict):\n raise Exception(\n f\"Unexpected type '{type(schema_map)}' for schema_map\"\n )\n\n # Build the BigQuery schema from the internal 'schema_map'.\n schema = []\n map_items = sorted(schema_map.items()) if sorted_schema \\\n else schema_map.items()\n for name, meta in map_items:\n # Skip over fields which have been explicitly removed\n if not meta:\n continue\n\n status = meta['status']\n filled = meta['filled']\n info = meta['info']\n\n # Schema entries with a status of 'soft' are caused by 'null' or\n # empty fields. Don't print those out if the 'keep_nulls' flag is\n # False.\n if status == 'soft' and not keep_nulls:\n continue\n\n # Copy the 'info' dictionary into the schema dict, preserving the\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\n # keeps these sorted, so we created them in sorted order using an\n # OrderedDict, so they should preserve order here too.\n new_info = OrderedDict()\n for key, value in info.items():\n if key == 'fields':\n if not value:\n # Create a dummy attribute for an empty RECORD to make\n # the BigQuery importer happy.\n new_value = [\n OrderedDict([\n ('mode', 'NULLABLE'),\n ('name', '__unknown__'),\n ('type', 'STRING'),\n ])\n ]\n else:\n # Recursively flatten the sub-fields of a RECORD entry.\n new_value = flatten_schema_map(\n schema_map=value,\n keep_nulls=keep_nulls,\n sorted_schema=sorted_schema,\n infer_mode=infer_mode,\n input_format=input_format\n )\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\n new_value = value[1:]\n elif key == 'mode':\n # 'infer_mode' to set a field as REQUIRED is supported for only\n # input_format = 'csv' because the header line gives us the\n # complete list of fields to be expected in the CSV file. In\n # JSON data files, certain fields will often be completely\n # missing instead of being set to 'null' or \"\". If the field is\n # not even present, then it becomes incredibly difficult (not\n # impossible, but more effort than I want to expend right now)\n # to figure out which fields are missing so that we can mark the\n # appropriate schema entries with 'filled=False'.\n #\n # The --infer_mode option is activated only for\n # input_format == 'csv' in this function, which allows us to\n # overload the --infer_mode flag to mean that a REQUIRED mode of\n # an existing schema can transition to a NULLABLE mode.\n if (infer_mode and value == 'NULLABLE' and filled\n and input_format == 'csv'):\n new_value = 'REQUIRED'\n else:\n new_value = value\n else:\n new_value = value\n new_info[key] = new_value\n schema.append(new_info)\n return schema","def job_update(request):\n try:\n\n if request.method == 'GET':\n query_dict = request.GET\n else:\n query_dict = json.loads(request.body)\n\n update = {}\n p_update = {}\n\n for key in ['t_id', 'file_link']:\n if key in query_dict:\n update['job.' + key] = query_dict[key]\n if 'status' in query_dict:\n p_update['job.status'] = {\n 'status': query_dict['status'],\n 'time': datetime.now()\n }\n\n for key in ['customer_count', 'sms_sent', 'sms_failed', 'errors']:\n if key in query_dict:\n update['job.report.' + key] = query_dict[key]\n\n if 'id' not in query_dict or not (update or p_update):\n return jsonResponse({\"success\": False, \"query\": query_dict, \"update\": update, \"p_update\": p_update})\n else:\n oid = query_dict['id']\n if oid.endswith('_segment'):\n oid = oid.replace('_segment', '')\n collection = db.segment_jobs\n else:\n collection = db.jobs\n\n final_update = {}\n if update:\n final_update[\"$set\"] = update\n if p_update:\n final_update[\"$push\"] = p_update\n\n collection.update_one({\"_id\": ObjectId(oid)}, final_update)\n return jsonResponse({\"success\": True})\n except Exception, e:\n return basic_error(e)","def process_schema(self, hed_schema, save_merged=False):\n self._save_lib = False\n self._save_base = False\n if hed_schema.with_standard:\n self._save_lib = True\n if save_merged:\n self._save_base = True\n else:\n # Saving a standard schema or a library schema without a standard schema\n save_merged = True\n self._save_lib = True\n self._save_base = True\n self._save_merged = save_merged\n\n\n self._output_header(hed_schema.get_save_header_attributes(self._save_merged), hed_schema.prologue)\n self._output_tags(hed_schema.all_tags)\n self._output_units(hed_schema.unit_classes)\n self._output_section(hed_schema, HedSectionKey.UnitModifiers)\n self._output_section(hed_schema, HedSectionKey.ValueClasses)\n self._output_section(hed_schema, HedSectionKey.Attributes)\n self._output_section(hed_schema, HedSectionKey.Properties)\n self._output_footer(hed_schema.epilogue)\n\n return self.output","def merge_schema(first, second):\n if not (type(first) == type(second) == dict):\n raise ValueError(\"Argument is not a schema\")\n\n if not (first.get('type') == second.get('type') == 'object'):\n raise NotImplementedError(\"Unsupported root type\")\n\n return merge_objects(first, second)","def update(self):\n\n if not self.db: self.validate()\n\n self.logging.debug( \"update(%s)\" % (self.db) )\n\n for name in self.tables:\n self.dbs_tables[name]['md5'] = get_md5( self.dbs_tables[name]['path'] )\n\n self._get_magnitudes()\n self._get_events()","def _prepare_schema(self):\n schema = DaskSchema(self.schema_name)\n\n if not self.tables:\n logger.warning(\"No tables are registered.\")\n\n for name, dc in self.tables.items():\n table = DaskTable(name)\n df = dc.df\n logger.debug(\n f\"Adding table '{name}' to schema with columns: {list(df.columns)}\"\n )\n for column in df.columns:\n data_type = df[column].dtype\n sql_data_type = python_to_sql_type(data_type)\n\n table.addColumn(column, sql_data_type)\n\n schema.addTable(table)\n\n if not self.functions:\n logger.debug(\"No custom functions defined.\")\n\n for function_description in self.function_list:\n name = function_description.name\n sql_return_type = python_to_sql_type(function_description.return_type)\n if function_description.aggregation:\n logger.debug(f\"Adding function '{name}' to schema as aggregation.\")\n dask_function = DaskAggregateFunction(name, sql_return_type)\n else:\n logger.debug(f\"Adding function '{name}' to schema as scalar function.\")\n dask_function = DaskScalarFunction(name, sql_return_type)\n\n dask_function = self._add_parameters_from_description(\n function_description, dask_function\n )\n\n schema.addFunction(dask_function)\n\n return schema","def merge_updates(self, merge_updates_query):\n\n logging.info('{0:s} Merging updates from {1:s} into {2:s}.'.format(\n str(datetime.datetime.now()), self.temp_updates_table_id,\n self.final_table_id))\n\n merge_updates_job_config = bigquery.QueryJobConfig()\n merge_updates_job_config.use_legacy_sql = False\n\n merge_updates_query_job = self.bq_client.query(\n query=merge_updates_query,\n location='US',\n job_config=merge_updates_job_config)\n merge_updates_query_job.result()\n logging.info('{0:s} Successfully merged updates into {1:s}.'.format(\n str(datetime.datetime.now()), self.final_table_id))","def _sync_delta(cursor, user, namespace):\n\n schemas = _fetch_hive_schemas(cursor, namespace.lower())\n if namespace.lower() not in schemas:\n _print_info('No corresponding schema for namespace: \\'{}\\'. Skipping.'.format(namespace))\n\n # sync all for wildcard user\n if user == PUBLIC_READ_USER:\n _print_debug('Syncing all for public read user')\n _sync_all(cursor)\n\n has_permission = _has_read_permission_user_namespace(user, namespace)\n\n # create user schema if does not already exist\n _create_user_schema(cursor, user)\n\n if has_permission:\n _grant_select_privilege(cursor, user, namespace)\n else:\n _revoke_select_privilege(cursor, user, namespace)","def merge_schemas(self, old_schm, new_schm):\n\n old_schm_cols = [x['name'] for x in old_schm]\n\n for col in new_schm:\n if type(col) == dict:\n if col['name'] not in old_schm_cols:\n old_schm.append(col)\n \n for count, old_col in enumerate(old_schm):\n for meta in old_col:\n if type(old_col[meta]) == list:\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\n if meta in new_col:\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\n \n return old_schm","def resolve_schema_references(self, definition):\n # type: (Generator, Dict) -> None\n if \"$ref\" in definition:\n schema_reference = definition.pop(\"$ref\")\n section, name = schema_reference.split(\"/\")[-2:]\n referenced_definition = self.parser.specification[section][name]\n definition.update(referenced_definition)\n\n for value in definition.values():\n if isinstance(value, dict):\n self.resolve_schema_references(value)","def update_table(table_name):\n for filename in table_name_to_funcs[table_name][\"filename\"]:\n choose_file_to_get(table_name_to_funcs[table_name][\"file_type\"], filename)\n\n for process_func in table_name_to_funcs[table_name][\"process\"]:\n process_func()\n for to_sql_func in table_name_to_funcs[table_name][\"to_sql\"]:\n to_sql_func(update=True)","def _read_schema(self):\n schema = self.SCHEMA[self.action]\n assert_keys_match(self.op.keys(), schema, allow_missing=False)\n if 'community' in schema: self._read_community()\n if 'account' in schema: self._read_account()\n if 'permlink' in schema: self._read_permlink()\n if 'role' in schema: self._read_role()\n if 'notes' in schema: self._read_notes()\n if 'title' in schema: self._read_title()\n if 'props' in schema: self._read_props()","def _generate_schema(self):\n\n response = self._request('GET', CosmoSim.SCHEMA_URL,\n auth=(self.username, self.password),\n headers={'Accept': 'application/json'},\n cache=False)\n data = response.json()\n self.db_dict = {}\n for i in range(len(data['databases'])):\n self.db_dict[str(data['databases'][i]['name'])] = {}\n\n sstr = str(data['databases'][i]['name'])\n sid = str(data['databases'][i]['id'])\n self.db_dict[sstr]['id'] = sid\n sdesc = str(data['databases'][i]['description'])\n self.db_dict[sstr]['description'] = sdesc\n self.db_dict[sstr]['tables'] = {}\n for j in range(len(data['databases'][i]['tables'])):\n sstr2 = str(data['databases'][i]['tables'][j]['name'])\n self.db_dict[sstr]['tables'][sstr2] = {}\n sdata = data['databases'][i]['tables'][j]['id']\n self.db_dict[sstr]['tables'][sstr2]['id'] = sdata\n sdesc2 = data['databases'][i]['tables'][j]['description']\n self.db_dict[sstr]['tables'][sstr2]['description'] = sdesc2\n self.db_dict[sstr]['tables'][sstr2]['columns'] = {}\n tmpval = len(data['databases'][i]['tables'][j]['columns'])\n for k in range(tmpval):\n sdata2 = data['databases'][i]['tables'][j]['columns'][k]\n sdata2_id = sdata2['id']\n sstr3 = str(sdata2['name'])\n\n sdesc3 = sdata2['description']\n self.db_dict[sstr]['tables'][sstr2]['columns'][sstr3] = {\n 'id': sdata2_id,\n 'description': sdesc3}\n return response","def process(self):\n try:\n # self.alter_columns()\n self.collect_drop_fk()\n self.update_table()\n self.create_tables()\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\n return True\n except Exception as err:\n logger.error(\"create_tables [error] -> %s\" % err)","def get_schema() -> Dict[str, type]:\n schema: Dict[str, type] = {}\n\n # Add all columns from pipeline configs\n for pipeline in get_pipelines():\n schema.update(pipeline.schema)\n\n # Add new columns from adapter\n for col_old, col_new in OUTPUT_COLUMN_ADAPTER.items():\n if col_old in schema and col_new is not None:\n schema[col_new] = schema[col_old]\n\n return schema","def upgrade():\n pass\n # op.execute(\"\"\"\n # INSERT INTO context_implications (\n # source_context_id, source_context_scope, context_id, context_scope\n # )\n # SELECT DISTINCT rs.context_id as source_context_id,\n # 'Audit' AS source_context_scope,\n # p.context_id,\n # 'Program' AS context_scope\n # FROM relationships r\n # INNER JOIN responses rs\n # ON rs.id = r.source_id\n # AND r.source_type IN ('Response', 'DocumentationResponse',\n # 'InterviewResponse')\n # INNER JOIN programs p\n # ON p.id = r.destination_id\n # AND r.destination_type = 'Program'\n # WHERE p.private = 1\n # AND (SELECT count(*) from context_implications\n # WHERE source_context_id = rs.context_id\n # AND context_id = p.context_id) < 1\n # \"\"\")\n\n # op.execute(\"\"\"\n # INSERT INTO context_implications (\n # source_context_id, source_context_scope, context_id, context_scope\n # )\n # SELECT DISTINCT sp.context_id as source_context_id,\n # 'Program' AS source_context_scope,\n # p.context_id,\n # 'Program' AS context_scope\n # FROM relationships r\n # INNER JOIN responses rs\n # ON rs.id = r.source_id\n # AND r.source_type IN ('Response', 'DocumentationResponse',\n # 'InterviewResponse')\n # INNER JOIN requests rqs\n # ON rqs.id = rs.request_id\n # INNER JOIN audits a\n # ON a.id = rqs.audit_id\n # INNER JOIN programs sp\n # ON sp.id = a.program_id\n # INNER JOIN programs p\n # ON p.id = r.destination_id\n # AND r.destination_type = 'Program'\n # WHERE p.private = 1\n # AND (SELECT count(*) from context_implications\n # WHERE source_context_id = sp.context_id\n # AND context_id = p.context_id) < 1\n # \"\"\")","def BqTableSchemaFileProcessor(file_arg):\n table_schema_type = GetApiMessage('TableSchema')\n schema_field_type = GetApiMessage('TableFieldSchema')\n\n try:\n schema_json = yaml.load(file_arg)\n schema_json = schema_json.get('schema', None)\n\n if not schema_json or not isinstance(schema_json, list):\n raise SchemaFileError(\n 'Error parsing schema file: no schema field list defined in file')\n\n all_fields = []\n for field in schema_json:\n new_field = schema_field_type(name=field['name'],\n type=field['type'],\n mode=field.get('mode', 'NULLABLE'))\n all_fields.append(new_field)\n\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\n except yaml.YAMLParseError as ype:\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\n except (AttributeError, KeyError) as e:\n raise SchemaFileError(\n 'Error parsing schema file, invalid field definition [{}]'.format(e))","def process(self, conn):\n batch = msgpack.unpackb(self._request(conn), raw=False)\n ids = list(batch.keys())\n self.logger.debug(f'Received job ids: {ids}')\n\n # validate request\n validated = []\n errors = []\n for i, byte in enumerate(batch.values()):\n try:\n data = self._unpack(byte)\n obj = self.req_schema.parse_obj(data)\n validated.append(obj)\n self.logger.debug(f'{obj} passes the validation')\n except ValidationError as err:\n errors.append((i, self._pack(err.errors())))\n self.logger.info(\n f'Job {ids[i]} validation error',\n extra={'Validation': err.errors()}\n )\n except (json.JSONDecodeError,\n msgpack.ExtraData, msgpack.FormatError, msgpack.StackError) as err:\n errors.append((i, self._pack(str(err))))\n self.logger.info(f'Job {ids[i]} error: {err}')\n\n # inference\n self.logger.debug(f'Validated: {validated}, Errors: {errors}')\n result = []\n if validated:\n result = self.infer(validated)\n assert len(result) == len(validated), (\n 'Wrong number of inference results. '\n f'Expcet {len(validated)}, get{len(result)}.'\n )\n\n # validate response\n for data in result:\n self.resp_schema.parse_obj(data)\n\n # add errors information\n err_ids = ''\n result = [self._pack(data) for data in result]\n for index, err_msg in errors:\n err_ids += ids[index]\n result.insert(index, err_msg)\n\n # build batch job table\n resp = dict(zip(ids, result))\n if err_ids:\n resp['error_ids'] = err_ids\n self._response(conn, resp)","def _update_per_namespace():\n\n for acc in account.Account.query().iter():\n try:\n acc.refresh_devices()\n acc.put()\n except:\n logging.error('Error refreshing account %s',\n acc.key.string_id(), exc_info=sys.exc_info())\n\n for _room in room.Room.query().iter():\n try:\n _room.update_lights()\n except:\n logging.error('Error updating room %s',\n _room.name, exc_info=sys.exc_info())","def run(\n self,\n input_file=sys.stdin,\n output_file=sys.stdout,\n schema_map=None,\n ):\n schema_map, error_logs = self.deduce_schema(\n input_file, schema_map=schema_map\n )\n\n for error in error_logs:\n logging.info(\n f\"Problem on line {error['line_number']}: {error['msg']}\"\n )\n\n if self.debugging_map:\n json.dump(schema_map, output_file, indent=2)\n print(file=output_file)\n else:\n schema = self.flatten_schema(schema_map)\n json.dump(schema, output_file, indent=2)\n print(file=output_file)","def has_desired_schema(self):\n if self._new_table == self._old_table:\n if not self.rebuild:\n log.info(\"Table already has the desired schema. \")\n return True\n else:\n log.info(\n \"Table already has the desired schema. However \"\n \"--rebuild is specified, doing a rebuild instead\"\n )\n return False\n return False","async def write_schema_definition(controller, schema_definition_request):\n write_schema_resp = await controller.schema.write_schema(\n schema_definition_request.schema_name,\n schema_definition_request.schema_attrs,\n schema_definition_request.schema_version,\n )\n\n if not write_schema_resp or write_schema_resp == {}:\n raise HTTPException(\n status_code=404,\n detail=f\"Something went wrong.\\n Could not write schema to ledger.\\n{schema}\",\n )\n return write_schema_resp","def update_updated_data_sqlite_db(self, table_name: str):\n # go through indicators and get updated data in dataframe\n print('start downloading queries')\n df = self.__get_updated_data(table_name)\n print('api download completed')\n\n # get list of sql queries to insert to sqlite db\n print('start creating queries')\n q_list = self.__get_sql_insert_query_list(df, table_name)\n\n # insert data to sqlite\n print('start inserting data')\n AccessDB().run_insert_query(q_list)\n return 'Process Completed'","def main():\n cur, conn = connect('dwh.cfg')\n \n set_schema = schema_queries[1]\n cur.execute(set_schema)\n \n print('Loading Staging Tables.')\n load_staging_tables(cur, conn)\n \n print('Inserting Rows.')\n insert_tables(cur, conn)\n\n \n conn.close()","def update_tables(tables):\n # First we ensure we can find the file format version number\n # in top-level metadata. Then we proceed to fix up the tables as necessary.\n if not (isinstance(tables.metadata, dict) and 'SLiM' in tables.metadata):\n # Old versions kept information in provenance, not top-level metadata.\n # Note this uses defaults on keys not present in provenance,\n # which prior to 0.5 was everything but generation and model_type.\n values = default_slim_metadata('tree_sequence')['SLiM']\n prov = None\n file_version = 'unknown'\n # use only the last SLiM provenance\n for p in tables.provenances:\n is_slim, this_file_version = slim_provenance_version(p) \n if is_slim:\n prov = p\n file_version = this_file_version\n values['file_version'] = file_version\n try:\n record = json.loads(prov.record)\n if file_version == \"0.1\":\n values['model_type'] = record['model_type']\n values['tick'] = record['generation']\n values['cycle'] = record['generation']\n else:\n if 'generation' in record['slim']:\n values['tick'] = record['slim']['generation']\n values['cycle'] = record['slim']['generation']\n for k in values:\n if k in record['parameters']:\n values[k] = record['parameters'][k]\n if k in record['slim']:\n values[k] = record['slim'][k]\n except:\n raise ValueError(\"Failed to obtain metadata from provenance.\")\n set_tree_sequence_metadata(tables, **values)\n\n file_version = tables.metadata['SLiM']['file_version']\n if file_version != slim_file_version:\n warnings.warn(\"This is a version {} SLiM tree sequence.\".format(file_version) +\n \" When you write this out, \" +\n \"it will be converted to version {}.\".format(slim_file_version))\n\n # the only tables to have metadata schema changed thus far\n # are populations, individuals, mutations, and top-level:\n old_schema = _old_metadata_schema(\"tree_sequence\", file_version)\n if old_schema is not None:\n md = tables.metadata\n new_schema = slim_metadata_schemas[\"tree_sequence\"]\n new_properties = new_schema.asdict()['properties']['SLiM']['required']\n tables.metadata_schema = new_schema\n defaults = default_slim_metadata(\"tree_sequence\")\n for k in new_properties:\n if k not in md['SLiM']:\n if k == \"tick\":\n md['SLiM']['tick'] = md['SLiM']['generation']\n md['SLiM']['cycle'] = md['SLiM']['generation']\n else:\n md['SLiM'][k] = defaults['SLiM'][k]\n tables.metadata = md\n\n old_schema = _old_metadata_schema(\"population\", file_version)\n if old_schema is not None:\n pops = tables.populations.copy()\n tables.populations.clear()\n if pops.metadata_schema == tskit.MetadataSchema(None):\n pops.metadata_schema = old_schema\n new_schema = slim_metadata_schemas[\"population\"]\n tables.populations.metadata_schema = new_schema\n defaults = default_slim_metadata(\"population\")\n # just needs recoding\n for pop in pops:\n tables.populations.append(pop)\n\n old_schema = _old_metadata_schema(\"individual\", file_version)\n if old_schema is not None:\n inds = tables.individuals.copy()\n tables.individuals.clear()\n if inds.metadata_schema == tskit.MetadataSchema(None):\n inds.metadata_schema = old_schema\n new_schema = slim_metadata_schemas[\"individual\"]\n tables.individuals.metadata_schema = new_schema\n defaults = default_slim_metadata(\"individual\")\n d = {}\n for k in [\"pedigree_p1\", \"pedigree_p2\"]:\n d[k] = defaults[k]\n for ind in inds:\n md = ind.metadata\n md.update(d)\n tables.individuals.append(ind.replace(metadata=md))\n\n old_schema = _old_metadata_schema(\"mutation\", file_version)\n if old_schema is not None:\n muts = tables.mutations.copy()\n tables.mutations.clear()\n if muts.metadata_schema == tskit.MetadataSchema(None):\n muts.metadata_schema = old_schema\n tables.mutations.metadata_schema = slim_metadata_schemas[\"mutation\"]\n for mut in muts:\n md = mut.metadata\n for ml in md['mutation_list']:\n ml['nucleotide'] = -1\n tables.mutations.append(mut.replace(metadata=md))\n\n if file_version == \"0.1\":\n # shift times\n slim_generation = tables.metadata['SLiM']['tick']\n node_times = tables.nodes.time + slim_generation\n tables.nodes.set_columns(\n flags=tables.nodes.flags,\n time=node_times,\n population=tables.nodes.population,\n individual=tables.nodes.individual,\n metadata=tables.nodes.metadata,\n metadata_offset=tables.nodes.metadata_offset)\n migration_times = tables.migrations.time + slim_generation\n tables.migrations.set_columns(\n left=tables.migrations.left,\n right=tables.migrations.right,\n node=tables.migrations.node,\n source=tables.migrations.source,\n dest=tables.migrations.dest,\n time=migration_times)\n\n new_record = {\n \"schema_version\": \"1.0.0\",\n \"software\": {\n \"name\": \"pyslim\",\n \"version\": pyslim_version,\n },\n \"parameters\": {\n \"command\": [\"updrade_tables\"],\n \"old_file_version\": file_version,\n \"new_file_version\": slim_file_version,\n },\n \"environment\": get_environment(),\n }\n tskit.validate_provenance(new_record)\n tables.provenances.add_row(json.dumps(new_record))\n\n set_metadata_schemas(tables)\n md = tables.metadata\n md['SLiM']['file_version'] = slim_file_version\n tables.metadata = md","def serializeSchemaContext(schema_context, event=None):\n # find the FTI and model\n fti = schema_context.fti\n schemaName = schema_context.schemaName\n schema = schema_context.schema\n model = fti.lookupModel()\n\n # synchronize changes to the model\n syncSchema(schema, model.schemata[schemaName], overwrite=True)\n fti.model_source = serializeModel(model)","async def send_schema(self, schema_data_json: str) -> str: # issuer\n\n req_json = await ledger.build_schema_request(self.did, schema_data_json)\n resp_json = await ledger.sign_and_submit_request(self.pool.handle, self.wallet_handle, self.did, req_json)\n resp = (json.loads(resp_json))['result']\n return await self.get_schema(resp['identifier'], resp['data']['name'], resp['data']['version'])","def fix_all(self):\n\n altered_tables = {}\n\n for ingestible_db_conf in self.ingestible_db_conf_repo.get_ingestible_dbs():\n target_db= ingestible_db_conf.target_db_name\n db_type = ingestible_db_conf.db_type\n self.logger.info(\"Fixing consistency for DB Type: %s, Target DB: %s\" % (db_type, target_db))\n self.prepare_database(target_db)\n consistency_checker = HiveConsistencyChecker(target_db, db_type)\n\n unused_tables = consistency_checker.get_unused_tables()\n self.remove_unused_tables(unused_tables)\n\n new_tables = consistency_checker.get_new_tables()\n self.create_new_tables(new_tables)\n\n inconsistent_tables = consistency_checker.get_inconsistent_tables()\n self.fix_inconsistent_tables(inconsistent_tables, db_type)\n\n # Combine lists of inconsistent and unused tables\n altered_tables[db_type] = map(lambda qualified_table: qualified_table.split(\".\")[1],\n inconsistent_tables.keys() + unused_tables)\n\n self.logger.debug(\"Altered Tables: %s\" % altered_tables)\n return altered_tables","def test_compare_schemas_empty(self):\n status = schema_utils.compare_schemas(\n {},\n self.base_schema,\n )\n\n assert status == schema_utils.Update.first_run","def schema_handler(self, schema):\n dict_for_render = schema.get('properties', {}).items()\n if schema.get('$ref', None):\n def_name = schema.get('$ref').split('/')[-1]\n dict_for_render = self.definitions[def_name].get('properties', {}).items()\n elif schema.get('properties', None) is None:\n return ''\n\n answer_dict = {}\n json_dict = {}\n for opt_name, opt_value in dict_for_render:\n var_type = opt_value.get('format', None) or opt_value.get('type', None) or 'object'\n json_name = self.indent + f':jsonparameter {var_type} {opt_name}:'\n json_dict[json_name] = self.get_json_props_for_response(var_type, opt_value)\n\n answer_dict[opt_name] = self.get_response_example(opt_name, var_type, opt_value)\n if var_type == 'string':\n answer_dict[opt_name] = answer_dict[opt_name].format(opt_name)\n\n self.write('')\n for line in json.dumps(answer_dict, indent=4).split('\\n'):\n self.write(line, self.indent_depth)\n\n self.write('')\n for json_param_name, json_param_value in json_dict.items():\n desc = f'{json_param_value[\"title\"]}{json_param_value[\"props_str\"]}' or 'None'\n self.write(json_param_name + ' ' + desc)","def create_tables(): \n \n pk_contraint = \"CONSTRAINT {}_pk PRIMARY KEY ({})\"\n uq_contraint = \"CONSTRAINT {}_uq UNIQUE ({})\"\n fk_query = \"\"\"CONSTRAINT {}_fk_{} \n FOREIGN KEY ({}) \n REFERENCES {}({}) \n ON UPDATE CASCADE \n ON DELETE RESTRICT\n \"\"\"\n \n create_dict = {}\n index = 1\n\n\n ############################## public SCHEMA ##############################\n \n schema = 'public'\n create_schema(schema)\n\n #################### site ####################\n table_name = 'site'\n pk_id = 'site_id'\n uq_list = ['site_code']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_code CHAR(3),\n purok VARCHAR,\n sitio VARCHAR,\n barangay VARCHAR,\n municipality VARCHAR,\n province VARCHAR,\n region VARCHAR,\n psgc INTEGER,\n active BOOLEAN NOT NULL DEFAULT TRUE,\n season SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################## spatial SCHEMA ##############################\n \n schema = 'spatial'\n create_schema(schema)\n \n #################### exposure ####################\n table_name = 'exposure'\n pk_id = 'exp_id'\n uq_list = ['exp_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n exp_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### site_exposure ####################\n table_name = 'site_exposure'\n pk_id = 'se_id'\n uq_list = ['site_id', 'exp_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n exp_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### feature ####################\n table_name = 'feature'\n pk_id = 'feat_id'\n uq_list = ['feat_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n feat_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_feature ####################\n table_name = 'site_feature'\n pk_id = 'sf_id'\n uq_list = ['site_id', 'feat_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n feat_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### hazard_zone ####################\n table_name = 'hazard_zone'\n pk_id = 'hz_id'\n uq_list = ['site_id, geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### monitoring ####################\n table_name = 'monitoring'\n pk_id = 'mon_id'\n uq_list = ['mon_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n mon_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### site_monitoring ####################\n table_name = 'site_monitoring'\n pk_id = 'sm_id'\n uq_list = ['site_id', 'mon_id', 'geom']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n mon_id INTEGER,\n label_name VARCHAR,\n geom GEOMETRY,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n deactivated DATE,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################### comm SCHEMA ###############################\n \n schema = 'comm'\n create_schema(schema)\n\n #################### gsm_server ####################\n table_name = 'gsm_server'\n pk_id = 'server_id'\n uq_list = ['server_name']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_name VARCHAR,\n platform_type VARCHAR,\n version SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### server_port ####################\n table_name = 'server_port'\n pk_id = 'port_id'\n uq_list = ['server_id', 'port']\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n server_id INTEGER,\n port BOOLEAN,\n ser_port VARCHAR,\n pwr_on_pin SMALLINT,\n ring_pin SMALLINT,\n module_type SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- left\n 1- right'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### network_type ####################\n table_name = 'network_type'\n pk_id = 'prefix'\n uq_list = ['prefix']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} VARCHAR(3), \n carrier SMALLINT,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '1- globe\n 2- smart\n 3- landline'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### gsm_module ####################\n table_name = 'gsm_module'\n pk_id = 'gsm_id'\n uq_list = ['prefix', 'num', 'activated']\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n prefix VARCHAR(3),\n num CHAR(7),\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n port_id INTEGER,\n {}, {} {}\n );\n \"\"\"\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n ############################# temporal SCHEMA #############################\n \n schema = 'temporal'\n create_schema(schema)\n\n #################### marker_observation ####################\n table_name = 'marker_observation'\n pk_id = 'mo_id'\n uq_list = ['site_id', 'ts']\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n site_id INTEGER,\n ts TIMESTAMP,\n meas_type VARCHAR(7),\n weather VARCHAR,\n observer_name VARCHAR,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_history ####################\n table_name = 'marker_history'\n pk_id = 'hist_id'\n uq_list = ['sm_id', 'ts', 'event']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n sm_id BIGINT,\n ts TIMESTAMP,\n event BOOLEAN,\n label_name VARCHAR,\n {}, {} {}\n );\n \"\"\"\n query += \"\"\" COMMENT ON TABLE {}.{} IS \n '0- rename\n 1- reposition'\n ;\"\"\".format(schema, table_name)\n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_data ####################\n table_name = 'marker_data'\n pk_id = 'data_id'\n uq_list = ['sm_id', 'mo_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n mo_id BIGINT,\n sm_id BIGINT,\n measurement NUMERIC(5,1),\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### marker_alert ####################\n table_name = 'marker_alert'\n pk_id = 'alert_id'\n uq_list = ['data_id']\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n data_id BIGINT,\n displacement NUMERIC(4,1),\n time_delta FLOAT,\n alert_level SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger_model ####################\n table_name = 'logger_model'\n pk_id = 'model_id'\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\n fk_dict = {}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n has_tilt BOOLEAN,\n has_rain BOOLEAN,\n has_piezo BOOLEAN,\n has_soms BOOLEAN,\n logger_type SMALLINT,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n #################### logger ####################\n table_name = 'logger'\n pk_id = 'logger_id'\n uq_list = ['sm_id']\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL, \n sm_id BIGINT,\n model_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n \n #################### logger_mobile ####################\n table_name = 'logger_mobile'\n pk_id = 'mobile_id'\n uq_list = ['logger_id', 'activated']\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\n query = \"\"\"CREATE TABLE IF NOT EXISTS {}.{} (\n {} SERIAL,\n logger_id INTEGER,\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\n sim_num VARCHAR(12),\n gsm_id INTEGER,\n {}, {} {}\n );\n \"\"\" \n create_dict[index] = {'schema': schema,\n 'table_name': table_name,\n 'query': query,\n 'pk_id': pk_id,\n 'uq_list': uq_list,\n 'fk_dict': fk_dict}\n index += 1\n\n\n #################### EXECUTE QUERY TO CREATE TABLES ####################\n for index in create_dict.keys():\n dct = create_dict[index]\n schema = dct['schema']\n table_name = dct['table_name']\n query = dct['query']\n pk_id = dct['pk_id']\n uq_list = dct['uq_list']\n fk_dict = dct['fk_dict']\n if len(fk_dict.keys()) == 0:\n fk_constraint = ''\n else:\n fk_constraint_list = ['']\n for fk_id in fk_dict.keys():\n ref_schema = fk_dict.get(fk_id)['ref_schema']\n ref_table = fk_dict.get(fk_id)['ref_table']\n fk_part = fk_query.format(table_name, ref_table, fk_id,\n \"{}.{}\".format(ref_schema, ref_table),\n fk_id)\n fk_constraint_list.append(fk_part)\n fk_constraint = ', '.join(fk_constraint_list)\n \n query = query.format(schema, table_name, pk_id, \n pk_contraint.format(table_name, pk_id),\n uq_contraint.format(table_name, ', '.join(uq_list)),\n \"{}\".format(fk_constraint))\n qdb.execute(query)","async def get_schema(\n self, refresh: bool = False, headers: Optional[Dict[str, str]] = None\n ) -> graphql.GraphQLSchema:\n # TODO: consider adding ttl logic for expiring schemas for long running services\n if self._schema is None or refresh:\n self._schema = await self.introspect(headers=headers)\n return self._schema","def match_schemas(w_schema, r_schema):\n if isinstance(w_schema, dict) and isinstance(r_schema, dict):\n # Array, Map, Enum, Fixed, Record, Error\n w_type = w_schema['type']\n r_type = r_schema['type']\n if w_type != r_type:\n return False\n if w_type == 'array':\n # 'Both schemas are arrays whose item types match'\n return match_schemas(w_schema['items'], r_schema['items'])\n elif w_type == 'map':\n # 'Both schemas are maps whose value types match'\n return match_schemas(w_schema['values'], r_schema['values'])\n elif w_type in ('enum', 'record', 'error'):\n # 'Both schemas are enums whose names match'\n # 'Both schemas are records with the same name'\n # Note: Futher checks must be applied after data is read in\n # `read_enum()` and `read_record()`\n return w_schema['name'] == r_schema['name']\n elif w_type == 'fixed':\n # 'Both schemas are fixed whose sizes and names match'\n return (\n w_schema['name'] == r_schema['name'] and\n w_schema['size'] == r_schema['size']\n )\n elif w_type == r_type:\n # Unknown type - just return True\n return True\n\n elif isinstance(w_schema, list) or isinstance(r_schema, list):\n # 'Either schema is a union'\n if isinstance(w_schema, list):\n # If the writer is a union, the check is applied in `read_union()`\n # when the correct schema is known.\n return True\n else:\n # If the reader is a union, ensure at least one of the schemas in\n # the reader's union matches the writer's schema.\n return any(match_schemas(w_schema, s) for s in r_schema)\n\n elif w_schema == r_schema:\n return True\n\n # Promotion cases:\n elif w_schema == 'int' and r_schema in ('long', 'float', 'double'):\n return True\n elif w_schema == 'long' and r_schema in ('float', 'double'):\n return True\n elif w_schema == 'float' and r_schema == 'double':\n return True\n elif w_schema == 'string' and r_schema == 'bytes':\n return True\n elif w_schema == 'bytes' and r_schema == 'string':\n return True\n\n return False","def update(self):\n current = LazyRegister(self.db)\n current.render()\n cur = self.db.cursor()\n for table in self.tables:\n if table in current.tables:\n additions, removals = current.tables[table].migrate(self.tables[table])\n for addition in additions:\n cur.execute(\"\"\"ALTER TABLE %s ADD COLUMN %s\"\"\" % (\n table, addition[1].get_sql()\n ))\n print('Added column: ', addition[0])\n for removal in removals:\n #cur.execute(\"\"\"ALTER TABLE %s DROP COLUMN %s\"\"\" % (\n # table, removal[0]\n #))\n #print('Removed column: ', removal[0])\n print('Did not removed column: ', removal[0])\n else:\n schema = self.tables[table].get_create_table_sql()\n cur.execute(schema)\n print('Added table %s' % table)","def _get_schema(self):\n\n schema = ProtocolSchema()\n\n schema.id = self.id\n schema.type = type(self).__name__\n\n for input_path in self.required_inputs:\n\n if not (input_path.start_protocol is None or (input_path.start_protocol == self.id and\n input_path.start_protocol == input_path.last_protocol)):\n\n continue\n\n # Always make sure to only pass a copy of the input. Changing the schema\n # should NOT change the protocol.\n schema.inputs[input_path.full_path] = copy.deepcopy(self.get_value(input_path))\n\n return schema","def process(rec, conn):\n try:\n # Changes members from distinguished name to next_id for roles\n if \"members\" in rec[\"data\"]:\n rec = translate_field_to_next(rec, \"members\")\n if \"owners\" in rec[\"data\"]:\n rec = translate_field_to_next(rec, \"owners\")\n\n add_transaction(rec)\n if \"batch\" not in rec or not rec[\"batch\"]:\n r.table(\"inbound_queue\").get(rec[\"id\"]).delete().run(conn)\n rec[\"sync_direction\"] = \"inbound\"\n r.table(\"sync_errors\").insert(rec).run(conn)\n return\n\n batch = batch_pb2.Batch()\n batch.ParseFromString(rec[\"batch\"])\n batch_list = batch_to_list(batch=batch)\n client = ClientSync()\n status = client.send_batches_get_status(batch_list=batch_list)\n while status[0][\"status\"] == \"PENDING\":\n LOGGER.info(\"Batch status is %s\", status)\n status = client.status_recheck(batch_list)\n if status[0][\"status\"] == \"COMMITTED\":\n if rec[\"data_type\"] == \"user\":\n insert_to_user_mapping(rec)\n if \"metadata\" in rec and rec[\"metadata\"]:\n data = {\n \"address\": rec[\"address\"],\n \"object_type\": rec[\"object_type\"],\n \"object_id\": rec[\"object_id\"],\n \"provider_id\": rec[\"provider_id\"],\n \"created_at\": r.now(),\n \"updated_at\": r.now(),\n **rec[\"metadata\"],\n }\n\n query = (\n r.table(\"metadata\")\n .get(rec[\"address\"])\n .replace(\n lambda doc: r.branch(\n # pylint: disable=singleton-comparison\n (doc == None), # noqa\n r.expr(data),\n doc.merge(\n {\"metadata\": rec[\"metadata\"], \"updated_at\": r.now()}\n ),\n )\n )\n )\n result = query.run(conn)\n if (not result[\"inserted\"] and not result[\"replaced\"]) or result[\n \"errors\"\n ] > 0:\n LOGGER.warning(\n \"error updating metadata record:\\n%s\\n%s\", result, query\n )\n rec[\"sync_direction\"] = \"inbound\"\n r.table(\"changelog\").insert(rec).run(conn)\n r.table(\"inbound_queue\").get(rec[\"id\"]).delete().run(conn)\n else:\n rec[\"error\"] = get_status_error(status)\n rec[\"sync_direction\"] = \"inbound\"\n r.table(\"sync_errors\").insert(rec).run(conn)\n r.table(\"inbound_queue\").get(rec[\"id\"]).delete().run(conn)\n\n except Exception as err: # pylint: disable=broad-except\n LOGGER.exception(\n \"%s exception processing inbound record:\\n%s\", type(err).__name__, rec\n )\n LOGGER.exception(err)","def create_tables_and_apply_patches(self):\n\n if self.authorized and not self.db_tables_initiated:\n with self.connection.cursor() as cursor:\n for statement in self.parse_mysql_sql_file():\n cursor.execute(statement)\n\n PyFunceble.LOGGER.info(\n \"Created the missing tables. Applied all patched\"\n )\n\n self.db_tables_initiated = True","def resolve_nested_schema(self, schema):\n try:\n schema_instance = resolve_schema_instance(schema)\n # If schema is a string and is not found in registry,\n # assume it is a schema reference\n except marshmallow.exceptions.RegistryError:\n return schema\n schema_key = make_schema_key(schema_instance)\n if schema_key not in self.refs:\n name = self.schema_name_resolver(schema)\n if not name:\n try:\n json_schema = self.schema2jsonschema(schema_instance)\n except RuntimeError:\n raise APISpecError(\n \"Name resolver returned None for schema {schema} which is \"\n \"part of a chain of circular referencing schemas. Please\"\n \" ensure that the schema_name_resolver passed to\"\n \" MarshmallowPlugin returns a string for all circular\"\n \" referencing schemas.\".format(schema=schema)\n )\n if getattr(schema, \"many\", False):\n return {\"type\": \"array\", \"items\": json_schema}\n return json_schema\n name = get_unique_schema_name(self.spec.components, name)\n self.spec.components.schema(name, schema=schema)\n return self.get_ref_dict(schema_instance)","def decide_schema(self, json_data):\n pass","def decide_schema(self, json_data):\n pass","def check_schema_existence_api_call(context, schema, version):\n check_schema_existence(context, schema, version, \"api\")","def _AddNewColsToSchema(new_fields, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for new_field in new_fields:\n if new_field.name in orig_schema_map:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n updated_schema_map[new_field.name] = new_field\n return updated_schema_map","def do_export_schema(self):\n export_schema = self.get_arg_value(\"export_schema\")\n\n if export_schema:\n row = {\"schemas\": self.final_schemas}\n self.write_rows(rows=row)\n del row","def patch(self):\n if not self.validate_complaint_document(\"update\"):\n return\n if apply_patch(self.request, src=self.request.context.serialize()):\n update_file_content_type(self.request)\n self.LOGGER.info(\n \"Updated tender award complaint document {}\".format(self.request.context.id),\n extra=context_unpack(self.request, {\"MESSAGE_ID\": \"tender_award_complaint_document_patch\"}),\n )\n return {\"data\": self.request.context.serialize(\"view\")}","def load(self, base_schema):\n if base_schema == []:\n _base = []\n else:\n _base = base_schema or BASE_SCHEMA or []\n\n _base_schema = []\n for _sc in _base:\n if _sc == \"schema\" or _sc == \"schema.org\":\n self.schema_org_version = get_schemaorg_version()\n _base_schema.append(\n load_schemaorg(version=self.schema_org_version, verbose=self.verbose)\n )\n continue\n elif self.is_a_dde_schema(_sc):\n _base_schema.append(self.load_dde_schemas(_sc))\n\n _base_schema = merge_schema(*_base_schema)\n return _base_schema","def __matchSchema(self, featureClass):\n fClassFields = []\n for field in arcpy.ListFields(featureClass):\n fieldName = field.name.lower()\n if fieldName == 'objectid' or fieldName == 'oid' or 'shape' in fieldName or field.name in self.userFields:\n pass\n else:\n fClassFields.append(field.name)\n fClassFields.insert(0, 'Shape@')\n objFields = [f['name'] for f in self.updateFields]\n return sorted(fClassFields) == sorted(objFields)"],"string":"[\n \"def compute_schema_updates(self):\\n data = self.client._perform_json(\\n \\\"GET\\\", \\\"/projects/%s/recipes/%s/schema-update\\\" % (self.project_key, self.recipe_name))\\n return RequiredSchemaUpdates(self, data)\",\n \"async def upgradeSchema(self) -> None:\",\n \"def merge_schema_entry(\\n self,\\n old_schema_entry,\\n new_schema_entry,\\n base_path=None,\\n ):\\n if not old_schema_entry:\\n return new_schema_entry\\n\\n # If the new schema is None, return immediately.\\n if not new_schema_entry:\\n return new_schema_entry\\n\\n # If a field value is missing, permanently set 'filled' to False.\\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\\n old_schema_entry['filled'] = False\\n new_schema_entry['filled'] = False\\n\\n old_status = old_schema_entry['status']\\n new_status = new_schema_entry['status']\\n\\n # new 'soft' does not clobber old 'hard'\\n if old_status == 'hard' and new_status == 'soft':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n old_schema_entry['info']['mode'] = mode\\n return old_schema_entry\\n\\n # new 'hard' clobbers old 'soft'\\n if old_status == 'soft' and new_status == 'hard':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n new_schema_entry['info']['mode'] = mode\\n return new_schema_entry\\n\\n # Verify that it's soft->soft or hard->hard\\n if old_status != new_status:\\n raise Exception(\\n f'Unexpected schema_entry type, this should never happen: '\\n f'old ({old_status}); new ({new_status})'\\n )\\n\\n old_info = old_schema_entry['info']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_mode = old_info['mode']\\n new_info = new_schema_entry['info']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_mode = new_info['mode']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # Defensive check, names should always be the same.\\n if old_name != new_name:\\n if old_name.lower() != new_name.lower():\\n raise Exception(\\n 'Unexpected difference in name, should never happen:'\\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\\n )\\n else:\\n # preserve old name if case is different\\n new_info['name'] = old_info['name']\\n\\n # Recursively merge in the subfields of a RECORD, allowing\\n # NULLABLE to become REPEATED (because 'bq load' allows it).\\n if old_type == 'RECORD' and new_type == 'RECORD':\\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\\n # 'bq load' allows it.\\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\\n old_info['mode'] = 'REPEATED'\\n self.log_error(\\n f'Converting schema for \\\"{full_old_name}\\\" from '\\n 'NULLABLE RECORD into REPEATED RECORD'\\n )\\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\\n # TODO: Maybe remove this warning output. It was helpful during\\n # development, but maybe it's just natural.\\n self.log_error(\\n f'Leaving schema for \\\"{full_old_name}\\\" as REPEATED RECORD'\\n )\\n\\n # RECORD type needs a recursive merging of sub-fields. We merge into\\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\\n # can be modified in situ.\\n old_fields = old_info['fields']\\n new_fields = new_info['fields']\\n for key, new_entry in new_fields.items():\\n old_entry = old_fields.get(key)\\n new_base_path = json_full_path(base_path, old_name)\\n old_fields[key] = self.merge_schema_entry(\\n old_schema_entry=old_entry,\\n new_schema_entry=new_entry,\\n base_path=new_base_path,\\n )\\n return old_schema_entry\\n\\n new_mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if new_mode is None:\\n return None\\n new_schema_entry['info']['mode'] = new_mode\\n\\n # For all other types...\\n if old_type != new_type:\\n # Check that the converted types are compatible.\\n candidate_type = convert_type(old_type, new_type)\\n if not candidate_type:\\n self.log_error(\\n f'Ignoring field with mismatched type: '\\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\\n )\\n return None\\n\\n new_info['type'] = candidate_type\\n return new_schema_entry\",\n \"def resolve_schema_in_request_body(self, request_body):\\n content = request_body[\\\"content\\\"]\\n for content_type in content:\\n schema = content[content_type][\\\"schema\\\"]\\n content[content_type][\\\"schema\\\"] = self.openapi.resolve_schema_dict(schema)\",\n \"def process(*, schemas: types.Schemas) -> None:\\n # Retrieve back references\\n backrefs = process_helper.get_artifacts(\\n schemas=schemas, get_schema_artifacts=_get_schema_backrefs\\n )\\n # Map to a schema for each grouped back references\\n backref_schemas = process_helper.calculate_outputs(\\n artifacts=backrefs, calculate_output=_backrefs_to_schema\\n )\\n # Convert to list to resolve iterator\\n backref_schema_list = list(backref_schemas)\\n # Add backreferences to schemas\\n for name, backref_schema in backref_schema_list:\\n schemas[name] = {\\\"allOf\\\": [schemas[name], backref_schema]}\",\n \"def _GetUpdatedSchema(\\n original_schema,\\n new_columns=None,\\n relaxed_columns=None):\\n orig_field_map = (\\n {f.name: f for f in original_schema.fields} if original_schema else {})\\n\\n if relaxed_columns:\\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\\n\\n if new_columns:\\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\\n\\n return sorted(orig_field_map.values(), key=lambda x: x.name)\",\n \"def resolve_schema(self, data):\\n if not isinstance(data, dict):\\n return\\n\\n # OAS 2 component or OAS 3 header\\n if \\\"schema\\\" in data:\\n data[\\\"schema\\\"] = self.openapi.resolve_schema_dict(data[\\\"schema\\\"])\\n # OAS 3 component except header\\n if self.openapi_version.major >= 3:\\n if \\\"content\\\" in data:\\n for content_type in data[\\\"content\\\"]:\\n schema = data[\\\"content\\\"][content_type][\\\"schema\\\"]\\n data[\\\"content\\\"][content_type][\\n \\\"schema\\\"\\n ] = self.openapi.resolve_schema_dict(schema)\",\n \"def update_schema(self, new_schema):\\n return self.conn.update_schema(new_schema)\",\n \"def upgrade_schema():\\n\\n db_version = get_db_version()\\n try:\\n while db_version < CURRENT_DATABASE_VERSION:\\n db_version += 1\\n upgrade_script = 'upgrade_to_'+str(db_version)\\n globals()[upgrade_script]()\\n except KeyError as e:\\n logging.exception('Attempted to upgrade using script that does not exist: {}'.format(e))\\n sys.exit(1)\\n except Exception as e:\\n logging.exception('Incremental upgrade of db failed')\\n sys.exit(1)\\n else:\\n config.db.singletons.update_one({'_id': 'version'}, {'$set': {'database': CURRENT_DATABASE_VERSION}})\\n sys.exit(0)\",\n \"def update_schema(self, engine_name, schema):\\n endpoint = \\\"engines/{}/schema\\\".format(engine_name)\\n data = json.dumps(schema)\\n return self.swiftype_session.request('post', endpoint, data=data)\",\n \"def merge_schema(self, schema):\\n for _, attr_schema in schema.iter_attributes():\\n self.merge_attribute_schema(attr_schema)\",\n \"def test_compare_schemas_happypath(self):\\n status = schema_utils.compare_schemas(\\n self.base_schema,\\n self.base_schema\\n )\\n\\n assert status == schema_utils.Update.no_update\",\n \"def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\\n old_info = old_schema_entry['info']\\n new_info = new_schema_entry['info']\\n old_mode = old_info['mode']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_status = old_schema_entry['status']\\n new_mode = new_info['mode']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_status = new_schema_entry['status']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # If the old field is a REQUIRED primitive (which could only have come\\n # from an existing schema), the new field can be either a\\n # NULLABLE(filled) or a NULLABLE(unfilled).\\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\\n # If the new field is filled, then retain the REQUIRED.\\n if new_schema_entry['filled']:\\n return old_mode\\n else:\\n # The new field is not filled (i.e. an empty or null field).\\n # If --infer_mode is active, then we allow the REQUIRED to\\n # revert back to NULLABLE.\\n if self.infer_mode:\\n return new_mode\\n else:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode.'\\n ' cannot convert to NULLABLE because infer_schema not'\\n ' set:'\\n f' old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n elif old_mode != new_mode:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode: '\\n f'old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n return old_mode\",\n \"def _patch_schema(self):\\n fields = get_json()['data']['attributes'].keys()\\n return make_entity_schema(\\n self.SCHEMA, self.RESOURCE_NAME,\\n make_data_schema(\\n self.SCHEMA, id_required=True,\\n only=fields, partial=True\\n )\\n )\",\n \"def _update(self, schema: 'Schema'):\\n for method in schema._get_methods():\\n if method.id in self:\\n raise ValueError(\\n f\\\"Duplicate method id for {method.method} id: {method.id}\\\"\\n )\\n\\n for combinator in schema._get_combinators():\\n if combinator.id in self:\\n raise ValueError(\\n f\\\"Duplicate combinator id for {combinator.predicate} \\\" +\\n f\\\"id: {combinator.id}\\\"\\n )\\n\\n self.constructors += schema.constructors\\n self.functions += schema.functions\\n\\n self._build_schema_data()\",\n \"def preprocess_schema(schema, imported_schemas, elements, xsd_uri, dialect, http, cache, force_download, wsdl_basedir, global_namespaces=None, qualified=False):\\n\\n from .simplexml import SimpleXMLElement # here to avoid recursive imports\\n\\n # analyze the namespaces used in this schema\\n local_namespaces = {}\\n for k, v in schema[:]:\\n if k.startswith(\\\"xmlns\\\"):\\n local_namespaces[get_local_name(k)] = v\\n if k == 'targetNamespace':\\n # URI namespace reference for this schema\\n if v == \\\"urn:DefaultNamespace\\\":\\n v = global_namespaces[None]\\n local_namespaces[None] = v\\n if k == 'elementFormDefault':\\n qualified = (v == \\\"qualified\\\")\\n # add schema namespaces to the global namespace dict = {URI: ns prefix}\\n for ns in local_namespaces.values():\\n if ns not in global_namespaces:\\n global_namespaces[ns] = 'ns%s' % len(global_namespaces)\\n \\n for element in schema.children() or []:\\n if element.get_local_name() in ('import', 'include',):\\n schema_namespace = element['namespace']\\n schema_location = element['schemaLocation']\\n if schema_location is None:\\n log.debug('Schema location not provided for %s!' % schema_namespace)\\n continue\\n if schema_location in imported_schemas:\\n log.debug('Schema %s already imported!' % schema_location)\\n continue\\n imported_schemas[schema_location] = schema_namespace\\n log.debug('Importing schema %s from %s' % (schema_namespace, schema_location))\\n # Open uri and read xml:\\n xml = fetch(schema_location, http, cache, force_download, wsdl_basedir)\\n\\n # Parse imported XML schema (recursively):\\n imported_schema = SimpleXMLElement(xml, namespace=xsd_uri)\\n preprocess_schema(imported_schema, imported_schemas, elements, xsd_uri, dialect, http, cache, force_download, wsdl_basedir, global_namespaces, qualified)\\n\\n element_type = element.get_local_name()\\n if element_type in ('element', 'complexType', \\\"simpleType\\\"):\\n namespace = local_namespaces[None] # get targetNamespace\\n element_ns = global_namespaces[ns] # get the prefix\\n element_name = element['name']\\n log.debug(\\\"Parsing Element %s: %s\\\" % (element_type, element_name))\\n if element.get_local_name() == 'complexType':\\n children = element.children()\\n elif element.get_local_name() == 'simpleType':\\n children = element('restriction', ns=xsd_uri)\\n elif element.get_local_name() == 'element' and element['type']:\\n children = element\\n else:\\n children = element.children()\\n if children:\\n children = children.children()\\n elif element.get_local_name() == 'element':\\n children = element\\n if children:\\n process_element(elements, element_name, children, element_type, xsd_uri, dialect, namespace, qualified)\",\n \"def modify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\\n\\n return provision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)\",\n \"def modify_bigquery_schema(self, schema, info_keys):\\n # type: (bigquery.TableSchema, Set[str]) -> None\",\n \"async def update_db(appname, schema, table, action):\\n loop = asyncio.get_event_loop()\\n if args.action == 'info':\\n await schema_info(args.appname, args.schema)\\n sys.exit()\\n\\n dbstate = await schema_state(args.appname, args.schema, args.table)\\n modstate = model_state(args.appname, args.schema, args.table)\\n updiff, downdiff = compare_state(args.appname, args.schema, args.table,\\n dbstate, modstate)\\n if args.action == 'upgrade':\\n await set_state(args.appname, updiff)\\n elif args.action == 'downgrade':\\n await set_state(args.appname, downdiff)\\n else:\\n print(\\\"upgrade diff looks like\\\")\\n print(updiff)\\n print(\\\"downgrade diff looks like\\\")\\n print(downdiff)\",\n \"def _Dynamic_GetSchema(self, req, schema, request_id=None):\\n # This is not used, but it is required for the method signature.\\n del request_id\\n\\n app_str = req.app()\\n self.__ValidateAppId(app_str)\\n schema.set_more_results(False)\",\n \"def status_changes_schema():\\n schema = endpoint_schema(\\\"status_changes\\\")\\n items = schema[\\\"properties\\\"][\\\"data\\\"][\\\"properties\\\"][\\\"status_changes\\\"][\\\"items\\\"]\\n\\n # merge the state machine definitions and transition combinations rule\\n state_machine_defs, transitions = common.vehicle_state_machine(\\\"vehicle_state\\\", \\\"event_types\\\")\\n schema[\\\"definitions\\\"].update(state_machine_defs)\\n items[\\\"allOf\\\"].append(transitions)\\n\\n trip_id_ref = common.load_definitions(\\\"trip_id_reference\\\")\\n items[\\\"allOf\\\"].append(trip_id_ref)\\n\\n # verify and return\\n return common.check_schema(schema)\",\n \"def update(self, schema: 'Schema'):\\n self._update(schema)\",\n \"def test_schema_updates(self):\\n with patch(\\\"openedx.core.djangoapps.content_libraries.libraries_index.ContentLibraryIndexer.SCHEMA_VERSION\\\",\\n new=0):\\n result = self._create_library(slug=\\\"test-lib-schemaupdates-1\\\", title=\\\"Title 1\\\", description=\\\"Description\\\")\\n library_key = LibraryLocatorV2.from_string(result['id'])\\n assert len(ContentLibraryIndexer.get_items([library_key])) == 1\\n\\n with patch(\\\"openedx.core.djangoapps.content_libraries.libraries_index.ContentLibraryIndexer.SCHEMA_VERSION\\\",\\n new=1):\\n assert len(ContentLibraryIndexer.get_items([library_key])) == 0\\n\\n call_command(\\\"reindex_content_library\\\", all=True, force=True)\\n\\n assert len(ContentLibraryIndexer.get_items([library_key])) == 1\",\n \"def process_updates():\\n print \\\"[{x}] Processing Requests\\\".format(x=dates.now())\\n WorkflowApi.process_requests()\\n WorkflowApi.process_enhancements()\",\n \"def fetch_schema(self) -> None:\\n if self.schema_file:\\n logger.info(\\\"Loaded schema from file '%s'\\\", self.schema_file)\\n self._schema = load_schema_file(self.schema_file)\\n else:\\n url = self.schema_url or urljoin(self.base_url, \\\"schema/openapi.yaml\\\")\\n logger.info(\\\"Fetching schema at '%s'\\\", url)\\n self._schema = schema_fetcher.fetch(url, {\\\"v\\\": \\\"3\\\"})\",\n \"def ensure_internal_schema_updated(self):\\n if self._internal_schema_updated:\\n return\\n if internalmigrations.needs_upgrading(self):\\n assert not self._in_transaction\\n with self.lock():\\n internalmigrations.upgrade(self)\\n self.connection.commit()\\n self._internal_schema_updated = True\",\n \"def rebuild(self, dframe, overwrite=False):\\n current_schema = self\\n new_schema = schema_from_dframe(dframe, self)\\n\\n if current_schema and not overwrite:\\n # merge new schema with existing schema\\n current_schema.update(new_schema)\\n new_schema = current_schema\\n\\n return new_schema\",\n \"def test_schema_updates(self):\\n lib = self._create_library(slug=\\\"test-lib--block-schemaupdates-1\\\", title=\\\"Title 1\\\", description=\\\"Description\\\")\\n with patch(\\\"openedx.core.djangoapps.content_libraries.libraries_index.LibraryBlockIndexer.SCHEMA_VERSION\\\",\\n new=0):\\n block = self._add_block_to_library(lib['id'], \\\"problem\\\", \\\"problem1\\\")\\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 1\\n\\n with patch(\\\"openedx.core.djangoapps.content_libraries.libraries_index.LibraryBlockIndexer.SCHEMA_VERSION\\\",\\n new=1):\\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 0\\n\\n call_command(\\\"reindex_content_library\\\", all=True, force=True)\\n\\n assert len(LibraryBlockIndexer.get_items([block['id']])) == 1\",\n \"def test_compare_schemas_major(self):\\n status = schema_utils.compare_schemas(\\n self.base_schema,\\n self.major_removed_value\\n )\\n\\n assert status == schema_utils.Update.major\",\n \"def _load_schema(self, mode=\\\"staging\\\"):\\n\\n self._check_mode(mode)\\n\\n json_path = self.table_folder / f\\\"schema-{mode}.json\\\"\\n columns = self.table_config[\\\"columns\\\"]\\n\\n if mode == \\\"staging\\\":\\n new_columns = []\\n for c in columns:\\n # case is_in_staging are None then must be True\\n is_in_staging = (\\n True if c.get(\\\"is_in_staging\\\") is None else c[\\\"is_in_staging\\\"]\\n )\\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\\n if is_in_staging and not c.get(\\\"is_partition\\\"):\\n c[\\\"type\\\"] = \\\"STRING\\\"\\n new_columns.append(c)\\n\\n del columns\\n columns = new_columns\\n\\n elif mode == \\\"prod\\\":\\n schema = self._get_table_obj(mode).schema\\n\\n # get field names for fields at schema and at table_config.yaml\\n column_names = [c[\\\"name\\\"] for c in columns]\\n schema_names = [s.name for s in schema]\\n\\n # check if there are mismatched fields\\n not_in_columns = [name for name in schema_names if name not in column_names]\\n not_in_schema = [name for name in column_names if name not in schema_names]\\n\\n # raise if field is not in table_config\\n if not_in_columns:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in table_config.yaml. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_columns,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # raise if field is not in schema\\n if not_in_schema:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in publish.sql. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_schema,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # if field is in schema, get field_type and field_mode\\n for c in columns:\\n for s in schema:\\n if c[\\\"name\\\"] == s.name:\\n c[\\\"type\\\"] = s.field_type\\n c[\\\"mode\\\"] = s.mode\\n break\\n ## force utf-8, write schema_{mode}.json\\n json.dump(columns, (json_path).open(\\\"w\\\", encoding=\\\"utf-8\\\"))\\n\\n # load new created schema\\n return self.client[f\\\"bigquery_{mode}\\\"].schema_from_json(str(json_path))\",\n \"async def schemas(\\n self,\\n *,\\n query_params: Optional[Dict[str, any]] = None,\\n headers: Optional[Dict[str, str]] = None,\\n ) -> AuditLogsResponse:\\n return await self.api_call(\\n path=\\\"schemas\\\",\\n query_params=query_params,\\n headers=headers,\\n )\",\n \"def parse_schema(schemaurl, schema_dir=None):\\n if schema_dir:\\n try:\\n # attempts to open .schema file in directory schema_dir\\n local_schema_path = schema_dir + \\\"/\\\" + \\\\\\n schemaurl[schemaurl.rfind('/') + 1:-1] + \\\".schema\\\"\\n print \\\"Looking for schema in file %s\\\" % (local_schema_path)\\n schema = json.load(open(local_schema_path))\\n except Exception as e:\\n print \\\"Couldn't load schema %s from file %s\\\\n%s\\\" % (\\n schemaurl, schema_dir, str(e))\\n return None\\n else:\\n # load the schema directly from schemaurl, i.e., from the web\\n try:\\n schema = json.load(urllib2.urlopen(schemaurl))\\n except Exception as e:\\n print \\\"Couldn't load schema %s\\\\n%s\\\" % (schemaurl, str(e))\\n return None\\n\\n if 'extends' in schema and '$ref' in schema['extends']:\\n\\n parent_schema = json.load(urllib2.urlopen(schema['extends']['$ref']))\\n while (True): # exits loop when no additional extensions (break below)\\n for key in sorted(parent_schema.keys()):\\n if key not in schema:\\n schema[key] = parent_schema[key]\\n # need to merge these keys individually\\n if key == 'properties':\\n for key in sorted(parent_schema['properties'].keys()):\\n if key not in schema['properties']:\\n schema['properties'][key] = parent_schema[\\n 'properties'][key]\\n if 'extends' in parent_schema:\\n parent_schema = json.load(\\n urllib2.urlopen(parent_schema['extends']['$ref']))\\n else:\\n break\\n # essentially a do while loop (exit condition)\\n\\n return schema\",\n \"def deduce_schema_for_record(self, json_object, schema_map, base_path=None):\\n for key, value in json_object.items():\\n # The canonical key is the lower-cased version of the sanitized key\\n # so that the case of the field name is preserved when generating\\n # the schema but we don't create invalid, duplicate, fields since\\n # BigQuery is case insensitive\\n canonical_key = self.sanitize_name(key).lower()\\n schema_entry = schema_map.get(canonical_key)\\n new_schema_entry = self.get_schema_entry(\\n key=key,\\n value=value,\\n base_path=base_path\\n )\\n schema_map[canonical_key] = self.merge_schema_entry(\\n old_schema_entry=schema_entry,\\n new_schema_entry=new_schema_entry,\\n base_path=base_path\\n )\",\n \"def update_all():\\n req_data = request.get_json()\\n jobs = JobModel.get_one_job(job_id)\\n if not jobs:\\n return custom_response({'Error': 'Job Not Found'}, 404)\\n\\n data, error = job_schema.load(req_data, partial=True)\\n if error:\\n return custom_response(error, 400)\\n\\n for job in jobs:\\n job.update(data)\\n job_message = job_schema.dump(job)\\n\\n return custom_response(job_message, 200)\",\n \"def test_json_merge_patch():\\n schemas = {}\\n\\n basenames = (\\n 'record-package-schema.json',\\n 'release-package-schema.json',\\n 'release-schema.json',\\n 'versioned-release-validation-schema.json',\\n )\\n\\n if ocds_version or not use_development_version:\\n url_pattern = ocds_schema_base_url + ocds_tag + '/{}'\\n else:\\n url_pattern = development_base_url + '/{}'\\n\\n for basename in basenames:\\n schemas[basename] = http_get(url_pattern.format(basename)).json()\\n\\n if basename == 'release-schema.json':\\n path = os.path.join(extensiondir, 'extension.json')\\n with open(path) as f:\\n metadata = json.load(f, object_pairs_hook=rejecting_dict)\\n schemas[basename] = extend_schema(basename, schemas[basename], metadata, codelists=external_codelists)\\n\\n # This loop is somewhat unnecessary, as repositories contain at most one of each schema file.\\n for path, name, text, data in walk_json_data(patch):\\n if is_json_merge_patch(data):\\n if name in basenames:\\n unpatched = deepcopy(schemas[name])\\n try:\\n patched = merge(unpatched, data)\\n except Exception as e:\\n assert False, f'Exception: {e} {path}'\\n\\n # All metadata should be present.\\n validate_json_schema(path, name, patched, metaschemas()['metaschema'], full_schema=True)\\n\\n # Empty patches aren't allowed. json_merge_patch mutates `unpatched`, so `schemas[name]` is tested.\\n assert patched != schemas[name]\",\n \"def forwards_func(apps, schema_editor):\\n judge_file = apps.get_model(\\\"judges\\\", \\\"JudgeFile\\\")\\n db_alias = schema_editor.connection.alias\\n judge_file.objects.using(db_alias).filter(\\n file_type='ruling').update(file_type='rulings')\\n judge_file.objects.using(db_alias).filter(\\n file_type='verdict').update(file_type='verdicts')\\n judge_file.objects.using(db_alias).filter(\\n file_type='transcript').update(file_type='transcripts')\\n judge_file.objects.using(db_alias).filter(\\n file_type='image').update(file_type='campaigns')\",\n \"def update_all(self, request):\\n\\n schema = self.session.info['schema']\\n\\n for item in self.query().filter_by(schema=schema):\\n self.session.delete(item)\\n\\n for item in ElectionCollection(self.session).query():\\n self.update(item, request)\\n\\n for item in ElectionCompoundCollection(self.session).query():\\n self.update(item, request)\\n\\n for item in VoteCollection(self.session).query():\\n self.update(item, request)\",\n \"def _get_and_validate_schema_mapping(schema1, schema2, strict=False):\\n\\n len_schema1 = len(schema1)\\n len_schema2 = len(schema2)\\n\\n # If both non-empty, must be same length\\n if 0 < len_schema1 != len_schema2 > 0:\\n raise ValueError(\\\"Attempted to merge profiles with different \\\"\\n \\\"numbers of columns\\\")\\n\\n # In the case of __add__ with one of the schemas not initialized\\n if strict and (len_schema1 == 0 or len_schema2 == 0):\\n raise ValueError(\\\"Cannot merge empty profiles.\\\")\\n\\n # In the case of _update_from_chunk with uninitialized schema\\n if not strict and len_schema2 == 0:\\n return {col_ind: col_ind for col_ind_list in schema1.values()\\n for col_ind in col_ind_list}\\n\\n # Map indices in schema1 to indices in schema2\\n schema_mapping = dict()\\n\\n for key in schema1:\\n # Pandas columns are int by default, but need to fuzzy match strs\\n if isinstance(key, str):\\n key = key.lower()\\n if key not in schema2:\\n raise ValueError(\\\"Columns do not match, cannot update \\\"\\n \\\"or merge profiles.\\\")\\n\\n elif len(schema1[key]) != len(schema2[key]):\\n raise ValueError(f\\\"Different number of columns detected for \\\"\\n f\\\"'{key}', cannot update or merge profiles.\\\")\\n\\n is_duplicate_col = len(schema1[key]) > 1\\n for schema1_col_ind, schema2_col_ind in zip(schema1[key],\\n schema2[key]):\\n if is_duplicate_col and (schema1_col_ind != schema2_col_ind):\\n raise ValueError(f\\\"Different column indices under \\\"\\n f\\\"duplicate name '{key}', cannot update \\\"\\n f\\\"or merge unless schema is identical.\\\")\\n schema_mapping[schema1_col_ind] = schema2_col_ind\\n\\n return schema_mapping\",\n \"def _process_json(self, json_content):\\n if self._ns_sqlcon.connection is None:\\n LOG.error(f'failed to open connection to DB')\\n return\\n entries = [entry for entry in json_content]\\n LOG.info('started updating DB')\\n num_of_entries = len(entries)\\n for x in range(num_of_entries):\\n entry = entries[x]\\n try:\\n self._ns_sqlcon.update_plugins_table(entry['_source'])\\n except AttributeError:\\n LOG.exception(f'malformed entry: {entry}')\\n if x % 2000 != 0:\\n continue\\n LOG.info(f'Updated {x} records')\\n\\n LOG.info(f'Updated {num_of_entries} records')\\n try:\\n LOG.info('Commit started')\\n self._ns_sqlcon.session.commit()\\n LOG.info('Commit finished')\\n except sqlalchemy.exc.IntegrityError:\\n LOG.exception('failed committing updates to DB')\\n self._ns_sqlcon.session.rollback()\\n\\n LOG.info('Finished updating DB')\",\n \"def formatSchema(self):\\n schema = json.loads(self.schemaSource)\\n stack = [schema]\\n # Strip out all the docs\\n while len(stack) > 0:\\n elm = stack.pop()\\n if \\\"doc\\\" in elm:\\n elm[\\\"doc\\\"] = \\\"\\\"\\n for value in elm.values():\\n if isinstance(value, dict):\\n stack.append(value)\\n elif isinstance(value, list):\\n for dic in value:\\n if isinstance(dic, dict):\\n stack.append(dic)\\n jsonData = json.dumps(schema)\\n output = \\\"\\\\n\\\".join(textwrap.wrap(jsonData)) + \\\"\\\\n\\\"\\n return output\",\n \"def schema_helper(self, name, _, schema=None, **kwargs):\\n if schema is None:\\n return None\\n\\n schema_instance = resolve_schema_instance(schema)\\n\\n schema_key = make_schema_key(schema_instance)\\n self.warn_if_schema_already_in_spec(schema_key)\\n self.openapi.refs[schema_key] = name\\n\\n json_schema = self.openapi.schema2jsonschema(schema_instance)\\n\\n return json_schema\",\n \"def _TryGetCurrentSchema(dataset_id, table_id, project_id):\\n client = GetApiClient()\\n service = client.tables\\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\\n get_request = get_request_type(datasetId=dataset_id,\\n tableId=table_id,\\n projectId=project_id)\\n try:\\n table = service.Get(get_request)\\n if not table or table.type != 'TABLE':\\n raise SchemaUpdateError('Schema modifications only supported '\\n 'on TABLE objects received [{}]'.format(\\n table))\\n except apitools_exceptions.HttpNotFoundError:\\n raise SchemaUpdateError('Table with id [{}:{}:{}] not found.'.format(\\n project_id, dataset_id, table_id))\\n\\n return table.schema\",\n \"def generate_update(stmt, schema, path, rpc=None):\\n if path:\\n path_params = get_input_path_parameters(path)\\n put = {}\\n generate_api_header(stmt, put, 'Update', path)\\n # Input parameters\\n if path:\\n put['parameters'] = create_parameter_list(path_params)\\n else:\\n put['parameters'] = []\\n put['parameters'].append(create_body_dict(stmt.arg, schema))\\n # Responses\\n if rpc:\\n response = create_responses(stmt.arg, rpc)\\n else:\\n response = create_responses(stmt.arg)\\n put['responses'] = response\\n return put\",\n \"def update(self, mode=\\\"all\\\"):\\n\\n self._check_mode(mode)\\n\\n mode = [\\\"prod\\\", \\\"staging\\\"] if mode == \\\"all\\\" else [mode]\\n for m in mode:\\n\\n try:\\n table = self._get_table_obj(m)\\n except google.api_core.exceptions.NotFound:\\n continue\\n\\n # if m == \\\"staging\\\":\\n\\n table.description = self._render_template(\\n Path(\\\"table/table_description.txt\\\"), self.table_config\\n )\\n\\n # save table description\\n with open(\\n self.metadata_path\\n / self.dataset_id\\n / self.table_id\\n / \\\"table_description.txt\\\",\\n \\\"w\\\",\\n encoding=\\\"utf-8\\\",\\n ) as f:\\n f.write(table.description)\\n\\n # when mode is staging the table schema already exists\\n table.schema = self._load_schema(m)\\n fields = [\\\"description\\\", \\\"schema\\\"] if m == \\\"prod\\\" else [\\\"description\\\"]\\n self.client[f\\\"bigquery_{m}\\\"].update_table(table, fields=fields)\\n\\n logger.success(\\n \\\" {object} {object_id} was {action}!\\\",\\n object_id=self.table_id,\\n object=\\\"Table\\\",\\n action=\\\"updated\\\",\\n )\",\n \"def deduce_schema(self, input_data, *, schema_map=None):\\n\\n if self.input_format == 'csv':\\n if self.csv_dialect:\\n reader = csv.DictReader(input_data, dialect=self.csv_dialect)\\n else:\\n reader = csv.DictReader(input_data)\\n elif self.input_format == 'json' or self.input_format is None:\\n reader = json_reader(input_data)\\n elif self.input_format == 'dict':\\n reader = input_data\\n else:\\n raise Exception(f\\\"Unknown input_format '{self.input_format}'\\\")\\n\\n if schema_map is None:\\n schema_map = OrderedDict()\\n\\n try:\\n for json_object in reader:\\n\\n # Print a progress message periodically.\\n self.line_number += 1\\n if self.line_number % self.debugging_interval == 0:\\n logging.info(f'Processing line {self.line_number}')\\n\\n # Deduce the schema from this given data record.\\n if isinstance(json_object, dict):\\n self.deduce_schema_for_record(\\n json_object=json_object,\\n schema_map=schema_map,\\n )\\n elif isinstance(json_object, Exception):\\n self.log_error(\\n f'Record could not be parsed: Exception: {json_object}'\\n )\\n if not self.ignore_invalid_lines:\\n raise json_object\\n else:\\n self.log_error(\\n 'Record should be a JSON Object '\\n f'but was a {type(json_object)}'\\n )\\n if not self.ignore_invalid_lines:\\n raise Exception(f'Record must be a JSON Object '\\n f'but was a {type(json_object)}')\\n finally:\\n logging.info(f'Processed {self.line_number} lines')\\n\\n return schema_map, self.error_logs\",\n \"def ProcessTableOverwrite(ref, args, request):\\n dataset_id = ref.datasetId\\n table_id = ref.Name()\\n project_id = ref.projectId\\n\\n if args.overwrite:\\n if _TableExists(dataset_id, table_id, project_id):\\n _TryDeleteTable(dataset_id, table_id, project_id)\\n\\n return request\",\n \"def _CreateSchemas(self) -> None:\\n self.schema_objs = dict() # Holds OpenAPI representations of types.\\n\\n # Add the OpenAPI schemas of protobuf primitive types.\\n primitive_type_schemas = {\\n primitive_type[\\\"name\\\"]: primitive_type[\\\"schema\\\"]\\n for primitive_type in primitive_types.values()\\n }\\n self.schema_objs.update(\\n cast(Dict[str, Dict[str, str]], primitive_type_schemas))\\n # Add the OpenAPI schemas of the statically described RDF types.\\n self.schema_objs.update(rdf_type_schemas)\\n\\n # Holds state of type extraction (white/gray nodes).\\n visiting: Set[str] = set()\\n self._CreateRouterMethodSchemas(visiting)\\n self._CreateFlowSchemas(visiting)\",\n \"def test_compare_schemas_minor(self):\\n status = schema_utils.compare_schemas(\\n self.base_schema,\\n self.minor_change\\n )\\n\\n assert status == schema_utils.Update.minor\",\n \"def update():\\n as3s = AS3Schema()\\n as3s.updateschemas()\\n as3s_new = AS3Schema()\\n\\n if as3s.version != as3s_new.version:\\n click.echo(\\n f\\\"Updated AS3 JSON Schemas from version:{as3s.version} to:{as3s_new.version}\\\",\\n )\\n else:\\n click.echo(\\n f\\\"AS3 JSON Schemas are up-to-date, current version:{as3s.version}\\\",\\n )\",\n \"def get_schema(self, schema_versions_info):\\n schema = None\\n version = api_version_request.APIVersionRequest(VOLUME_MICROVERSION)\\n for items in schema_versions_info:\\n min_version = api_version_request.APIVersionRequest(items['min'])\\n max_version = api_version_request.APIVersionRequest(items['max'])\\n # This is case where COMPUTE_MICROVERSION is None, which means\\n # request without microversion So select base v2.1 schema.\\n if version.is_null() and items['min'] is None:\\n schema = items['schema']\\n break\\n # else select appropriate schema as per COMPUTE_MICROVERSION\\n elif version.matches(min_version, max_version):\\n schema = items['schema']\\n break\\n if schema is None:\\n raise exceptions.JSONSchemaNotFound(\\n version=version.get_string(),\\n schema_versions_info=schema_versions_info)\\n return schema\",\n \"def make_schema_changes(self, session, namespace='ns1'):\\n debug(\\\"make_schema_changes() \\\" + str(namespace))\\n session.execute('USE ks_%s' % namespace)\\n # drop keyspace\\n session.execute('DROP KEYSPACE ks2_%s' % namespace)\\n wait(2)\\n\\n # create keyspace\\n self.create_ks(session, \\\"ks3_%s\\\" % namespace, 2)\\n session.execute('USE ks_%s' % namespace)\\n\\n wait(2)\\n # drop column family\\n session.execute(\\\"DROP COLUMNFAMILY cf2_%s\\\" % namespace)\\n\\n # create column family\\n query = \\\"\\\"\\\"\\n CREATE TABLE cf3_%s (\\n col1 uuid PRIMARY KEY,\\n col2 text,\\n col3 text,\\n col4 text\\n );\\n \\\"\\\"\\\" % (namespace)\\n session.execute(query)\\n\\n # alter column family\\n query = \\\"\\\"\\\"\\n ALTER COLUMNFAMILY cf_%s\\n ADD col4 text;\\n \\\"\\\"\\\" % namespace\\n session.execute(query)\\n\\n # add index\\n session.execute(\\\"CREATE INDEX index2_%s ON cf_%s(col3)\\\"%(namespace, namespace))\\n\\n # remove an index\\n session.execute(\\\"DROP INDEX index_%s\\\" % namespace)\",\n \"def finalizeSchema(schema, folderish=False, moveDiscussion=True):\\n schema.moveField('businessOldLocation', after='workLocations')\\n schema.moveField('foldermanagers', after='businessOldLocation')\\n# schema.moveField('bound_licences', after='isTransferOfLicence')\\n schema.moveField('rubrics', after='folderCategory')\\n schema.moveField('description', after='additionalLegalConditions')\\n schema.moveField('referenceFT', after='referenceDGATLP')\\n schema.moveField('isTransferOfLicence', after='referenceFT')\\n\\n return schema\",\n \"def merge_schema(self, schema):\\n self.validate_schema(schema)\\n\\n if self.exclusive is False:\\n self.exclusive = schema.exclusive\\n\\n if self.default is None:\\n self.default = schema.default\",\n \"def _validate(self):\\n schema_version = util.schemas[self.schema_name]\\n stored_schemas = util.stored_schemas\\n\\n try:\\n schema_obj = stored_schemas[\\n \\\"http://redfish.dmtf.org/schemas/v1/\\\" + schema_version]\\n except KeyError:\\n raise OneViewRedfishError(\\\"{} not found\\\".format(schema_version))\\n\\n resolver = jsonschema.RefResolver('', schema_obj, store=stored_schemas)\\n jsonschema.validate(self.redfish, schema_obj, resolver=resolver)\",\n \"def flatten_schema_map(\\n schema_map,\\n keep_nulls=False,\\n sorted_schema=True,\\n infer_mode=False,\\n input_format='json',\\n):\\n if not isinstance(schema_map, dict):\\n raise Exception(\\n f\\\"Unexpected type '{type(schema_map)}' for schema_map\\\"\\n )\\n\\n # Build the BigQuery schema from the internal 'schema_map'.\\n schema = []\\n map_items = sorted(schema_map.items()) if sorted_schema \\\\\\n else schema_map.items()\\n for name, meta in map_items:\\n # Skip over fields which have been explicitly removed\\n if not meta:\\n continue\\n\\n status = meta['status']\\n filled = meta['filled']\\n info = meta['info']\\n\\n # Schema entries with a status of 'soft' are caused by 'null' or\\n # empty fields. Don't print those out if the 'keep_nulls' flag is\\n # False.\\n if status == 'soft' and not keep_nulls:\\n continue\\n\\n # Copy the 'info' dictionary into the schema dict, preserving the\\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\\n # keeps these sorted, so we created them in sorted order using an\\n # OrderedDict, so they should preserve order here too.\\n new_info = OrderedDict()\\n for key, value in info.items():\\n if key == 'fields':\\n if not value:\\n # Create a dummy attribute for an empty RECORD to make\\n # the BigQuery importer happy.\\n new_value = [\\n OrderedDict([\\n ('mode', 'NULLABLE'),\\n ('name', '__unknown__'),\\n ('type', 'STRING'),\\n ])\\n ]\\n else:\\n # Recursively flatten the sub-fields of a RECORD entry.\\n new_value = flatten_schema_map(\\n schema_map=value,\\n keep_nulls=keep_nulls,\\n sorted_schema=sorted_schema,\\n infer_mode=infer_mode,\\n input_format=input_format\\n )\\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\\n new_value = value[1:]\\n elif key == 'mode':\\n # 'infer_mode' to set a field as REQUIRED is supported for only\\n # input_format = 'csv' because the header line gives us the\\n # complete list of fields to be expected in the CSV file. In\\n # JSON data files, certain fields will often be completely\\n # missing instead of being set to 'null' or \\\"\\\". If the field is\\n # not even present, then it becomes incredibly difficult (not\\n # impossible, but more effort than I want to expend right now)\\n # to figure out which fields are missing so that we can mark the\\n # appropriate schema entries with 'filled=False'.\\n #\\n # The --infer_mode option is activated only for\\n # input_format == 'csv' in this function, which allows us to\\n # overload the --infer_mode flag to mean that a REQUIRED mode of\\n # an existing schema can transition to a NULLABLE mode.\\n if (infer_mode and value == 'NULLABLE' and filled\\n and input_format == 'csv'):\\n new_value = 'REQUIRED'\\n else:\\n new_value = value\\n else:\\n new_value = value\\n new_info[key] = new_value\\n schema.append(new_info)\\n return schema\",\n \"def job_update(request):\\n try:\\n\\n if request.method == 'GET':\\n query_dict = request.GET\\n else:\\n query_dict = json.loads(request.body)\\n\\n update = {}\\n p_update = {}\\n\\n for key in ['t_id', 'file_link']:\\n if key in query_dict:\\n update['job.' + key] = query_dict[key]\\n if 'status' in query_dict:\\n p_update['job.status'] = {\\n 'status': query_dict['status'],\\n 'time': datetime.now()\\n }\\n\\n for key in ['customer_count', 'sms_sent', 'sms_failed', 'errors']:\\n if key in query_dict:\\n update['job.report.' + key] = query_dict[key]\\n\\n if 'id' not in query_dict or not (update or p_update):\\n return jsonResponse({\\\"success\\\": False, \\\"query\\\": query_dict, \\\"update\\\": update, \\\"p_update\\\": p_update})\\n else:\\n oid = query_dict['id']\\n if oid.endswith('_segment'):\\n oid = oid.replace('_segment', '')\\n collection = db.segment_jobs\\n else:\\n collection = db.jobs\\n\\n final_update = {}\\n if update:\\n final_update[\\\"$set\\\"] = update\\n if p_update:\\n final_update[\\\"$push\\\"] = p_update\\n\\n collection.update_one({\\\"_id\\\": ObjectId(oid)}, final_update)\\n return jsonResponse({\\\"success\\\": True})\\n except Exception, e:\\n return basic_error(e)\",\n \"def process_schema(self, hed_schema, save_merged=False):\\n self._save_lib = False\\n self._save_base = False\\n if hed_schema.with_standard:\\n self._save_lib = True\\n if save_merged:\\n self._save_base = True\\n else:\\n # Saving a standard schema or a library schema without a standard schema\\n save_merged = True\\n self._save_lib = True\\n self._save_base = True\\n self._save_merged = save_merged\\n\\n\\n self._output_header(hed_schema.get_save_header_attributes(self._save_merged), hed_schema.prologue)\\n self._output_tags(hed_schema.all_tags)\\n self._output_units(hed_schema.unit_classes)\\n self._output_section(hed_schema, HedSectionKey.UnitModifiers)\\n self._output_section(hed_schema, HedSectionKey.ValueClasses)\\n self._output_section(hed_schema, HedSectionKey.Attributes)\\n self._output_section(hed_schema, HedSectionKey.Properties)\\n self._output_footer(hed_schema.epilogue)\\n\\n return self.output\",\n \"def merge_schema(first, second):\\n if not (type(first) == type(second) == dict):\\n raise ValueError(\\\"Argument is not a schema\\\")\\n\\n if not (first.get('type') == second.get('type') == 'object'):\\n raise NotImplementedError(\\\"Unsupported root type\\\")\\n\\n return merge_objects(first, second)\",\n \"def update(self):\\n\\n if not self.db: self.validate()\\n\\n self.logging.debug( \\\"update(%s)\\\" % (self.db) )\\n\\n for name in self.tables:\\n self.dbs_tables[name]['md5'] = get_md5( self.dbs_tables[name]['path'] )\\n\\n self._get_magnitudes()\\n self._get_events()\",\n \"def _prepare_schema(self):\\n schema = DaskSchema(self.schema_name)\\n\\n if not self.tables:\\n logger.warning(\\\"No tables are registered.\\\")\\n\\n for name, dc in self.tables.items():\\n table = DaskTable(name)\\n df = dc.df\\n logger.debug(\\n f\\\"Adding table '{name}' to schema with columns: {list(df.columns)}\\\"\\n )\\n for column in df.columns:\\n data_type = df[column].dtype\\n sql_data_type = python_to_sql_type(data_type)\\n\\n table.addColumn(column, sql_data_type)\\n\\n schema.addTable(table)\\n\\n if not self.functions:\\n logger.debug(\\\"No custom functions defined.\\\")\\n\\n for function_description in self.function_list:\\n name = function_description.name\\n sql_return_type = python_to_sql_type(function_description.return_type)\\n if function_description.aggregation:\\n logger.debug(f\\\"Adding function '{name}' to schema as aggregation.\\\")\\n dask_function = DaskAggregateFunction(name, sql_return_type)\\n else:\\n logger.debug(f\\\"Adding function '{name}' to schema as scalar function.\\\")\\n dask_function = DaskScalarFunction(name, sql_return_type)\\n\\n dask_function = self._add_parameters_from_description(\\n function_description, dask_function\\n )\\n\\n schema.addFunction(dask_function)\\n\\n return schema\",\n \"def merge_updates(self, merge_updates_query):\\n\\n logging.info('{0:s} Merging updates from {1:s} into {2:s}.'.format(\\n str(datetime.datetime.now()), self.temp_updates_table_id,\\n self.final_table_id))\\n\\n merge_updates_job_config = bigquery.QueryJobConfig()\\n merge_updates_job_config.use_legacy_sql = False\\n\\n merge_updates_query_job = self.bq_client.query(\\n query=merge_updates_query,\\n location='US',\\n job_config=merge_updates_job_config)\\n merge_updates_query_job.result()\\n logging.info('{0:s} Successfully merged updates into {1:s}.'.format(\\n str(datetime.datetime.now()), self.final_table_id))\",\n \"def _sync_delta(cursor, user, namespace):\\n\\n schemas = _fetch_hive_schemas(cursor, namespace.lower())\\n if namespace.lower() not in schemas:\\n _print_info('No corresponding schema for namespace: \\\\'{}\\\\'. Skipping.'.format(namespace))\\n\\n # sync all for wildcard user\\n if user == PUBLIC_READ_USER:\\n _print_debug('Syncing all for public read user')\\n _sync_all(cursor)\\n\\n has_permission = _has_read_permission_user_namespace(user, namespace)\\n\\n # create user schema if does not already exist\\n _create_user_schema(cursor, user)\\n\\n if has_permission:\\n _grant_select_privilege(cursor, user, namespace)\\n else:\\n _revoke_select_privilege(cursor, user, namespace)\",\n \"def merge_schemas(self, old_schm, new_schm):\\n\\n old_schm_cols = [x['name'] for x in old_schm]\\n\\n for col in new_schm:\\n if type(col) == dict:\\n if col['name'] not in old_schm_cols:\\n old_schm.append(col)\\n \\n for count, old_col in enumerate(old_schm):\\n for meta in old_col:\\n if type(old_col[meta]) == list:\\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\\n if meta in new_col:\\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\\n \\n return old_schm\",\n \"def resolve_schema_references(self, definition):\\n # type: (Generator, Dict) -> None\\n if \\\"$ref\\\" in definition:\\n schema_reference = definition.pop(\\\"$ref\\\")\\n section, name = schema_reference.split(\\\"/\\\")[-2:]\\n referenced_definition = self.parser.specification[section][name]\\n definition.update(referenced_definition)\\n\\n for value in definition.values():\\n if isinstance(value, dict):\\n self.resolve_schema_references(value)\",\n \"def update_table(table_name):\\n for filename in table_name_to_funcs[table_name][\\\"filename\\\"]:\\n choose_file_to_get(table_name_to_funcs[table_name][\\\"file_type\\\"], filename)\\n\\n for process_func in table_name_to_funcs[table_name][\\\"process\\\"]:\\n process_func()\\n for to_sql_func in table_name_to_funcs[table_name][\\\"to_sql\\\"]:\\n to_sql_func(update=True)\",\n \"def _read_schema(self):\\n schema = self.SCHEMA[self.action]\\n assert_keys_match(self.op.keys(), schema, allow_missing=False)\\n if 'community' in schema: self._read_community()\\n if 'account' in schema: self._read_account()\\n if 'permlink' in schema: self._read_permlink()\\n if 'role' in schema: self._read_role()\\n if 'notes' in schema: self._read_notes()\\n if 'title' in schema: self._read_title()\\n if 'props' in schema: self._read_props()\",\n \"def _generate_schema(self):\\n\\n response = self._request('GET', CosmoSim.SCHEMA_URL,\\n auth=(self.username, self.password),\\n headers={'Accept': 'application/json'},\\n cache=False)\\n data = response.json()\\n self.db_dict = {}\\n for i in range(len(data['databases'])):\\n self.db_dict[str(data['databases'][i]['name'])] = {}\\n\\n sstr = str(data['databases'][i]['name'])\\n sid = str(data['databases'][i]['id'])\\n self.db_dict[sstr]['id'] = sid\\n sdesc = str(data['databases'][i]['description'])\\n self.db_dict[sstr]['description'] = sdesc\\n self.db_dict[sstr]['tables'] = {}\\n for j in range(len(data['databases'][i]['tables'])):\\n sstr2 = str(data['databases'][i]['tables'][j]['name'])\\n self.db_dict[sstr]['tables'][sstr2] = {}\\n sdata = data['databases'][i]['tables'][j]['id']\\n self.db_dict[sstr]['tables'][sstr2]['id'] = sdata\\n sdesc2 = data['databases'][i]['tables'][j]['description']\\n self.db_dict[sstr]['tables'][sstr2]['description'] = sdesc2\\n self.db_dict[sstr]['tables'][sstr2]['columns'] = {}\\n tmpval = len(data['databases'][i]['tables'][j]['columns'])\\n for k in range(tmpval):\\n sdata2 = data['databases'][i]['tables'][j]['columns'][k]\\n sdata2_id = sdata2['id']\\n sstr3 = str(sdata2['name'])\\n\\n sdesc3 = sdata2['description']\\n self.db_dict[sstr]['tables'][sstr2]['columns'][sstr3] = {\\n 'id': sdata2_id,\\n 'description': sdesc3}\\n return response\",\n \"def process(self):\\n try:\\n # self.alter_columns()\\n self.collect_drop_fk()\\n self.update_table()\\n self.create_tables()\\n self.db_operations.create_fk_constraint(self.fk_constraints, self.contraints_columns)\\n return True\\n except Exception as err:\\n logger.error(\\\"create_tables [error] -> %s\\\" % err)\",\n \"def get_schema() -> Dict[str, type]:\\n schema: Dict[str, type] = {}\\n\\n # Add all columns from pipeline configs\\n for pipeline in get_pipelines():\\n schema.update(pipeline.schema)\\n\\n # Add new columns from adapter\\n for col_old, col_new in OUTPUT_COLUMN_ADAPTER.items():\\n if col_old in schema and col_new is not None:\\n schema[col_new] = schema[col_old]\\n\\n return schema\",\n \"def upgrade():\\n pass\\n # op.execute(\\\"\\\"\\\"\\n # INSERT INTO context_implications (\\n # source_context_id, source_context_scope, context_id, context_scope\\n # )\\n # SELECT DISTINCT rs.context_id as source_context_id,\\n # 'Audit' AS source_context_scope,\\n # p.context_id,\\n # 'Program' AS context_scope\\n # FROM relationships r\\n # INNER JOIN responses rs\\n # ON rs.id = r.source_id\\n # AND r.source_type IN ('Response', 'DocumentationResponse',\\n # 'InterviewResponse')\\n # INNER JOIN programs p\\n # ON p.id = r.destination_id\\n # AND r.destination_type = 'Program'\\n # WHERE p.private = 1\\n # AND (SELECT count(*) from context_implications\\n # WHERE source_context_id = rs.context_id\\n # AND context_id = p.context_id) < 1\\n # \\\"\\\"\\\")\\n\\n # op.execute(\\\"\\\"\\\"\\n # INSERT INTO context_implications (\\n # source_context_id, source_context_scope, context_id, context_scope\\n # )\\n # SELECT DISTINCT sp.context_id as source_context_id,\\n # 'Program' AS source_context_scope,\\n # p.context_id,\\n # 'Program' AS context_scope\\n # FROM relationships r\\n # INNER JOIN responses rs\\n # ON rs.id = r.source_id\\n # AND r.source_type IN ('Response', 'DocumentationResponse',\\n # 'InterviewResponse')\\n # INNER JOIN requests rqs\\n # ON rqs.id = rs.request_id\\n # INNER JOIN audits a\\n # ON a.id = rqs.audit_id\\n # INNER JOIN programs sp\\n # ON sp.id = a.program_id\\n # INNER JOIN programs p\\n # ON p.id = r.destination_id\\n # AND r.destination_type = 'Program'\\n # WHERE p.private = 1\\n # AND (SELECT count(*) from context_implications\\n # WHERE source_context_id = sp.context_id\\n # AND context_id = p.context_id) < 1\\n # \\\"\\\"\\\")\",\n \"def BqTableSchemaFileProcessor(file_arg):\\n table_schema_type = GetApiMessage('TableSchema')\\n schema_field_type = GetApiMessage('TableFieldSchema')\\n\\n try:\\n schema_json = yaml.load(file_arg)\\n schema_json = schema_json.get('schema', None)\\n\\n if not schema_json or not isinstance(schema_json, list):\\n raise SchemaFileError(\\n 'Error parsing schema file: no schema field list defined in file')\\n\\n all_fields = []\\n for field in schema_json:\\n new_field = schema_field_type(name=field['name'],\\n type=field['type'],\\n mode=field.get('mode', 'NULLABLE'))\\n all_fields.append(new_field)\\n\\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\\n except yaml.YAMLParseError as ype:\\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\\n except (AttributeError, KeyError) as e:\\n raise SchemaFileError(\\n 'Error parsing schema file, invalid field definition [{}]'.format(e))\",\n \"def process(self, conn):\\n batch = msgpack.unpackb(self._request(conn), raw=False)\\n ids = list(batch.keys())\\n self.logger.debug(f'Received job ids: {ids}')\\n\\n # validate request\\n validated = []\\n errors = []\\n for i, byte in enumerate(batch.values()):\\n try:\\n data = self._unpack(byte)\\n obj = self.req_schema.parse_obj(data)\\n validated.append(obj)\\n self.logger.debug(f'{obj} passes the validation')\\n except ValidationError as err:\\n errors.append((i, self._pack(err.errors())))\\n self.logger.info(\\n f'Job {ids[i]} validation error',\\n extra={'Validation': err.errors()}\\n )\\n except (json.JSONDecodeError,\\n msgpack.ExtraData, msgpack.FormatError, msgpack.StackError) as err:\\n errors.append((i, self._pack(str(err))))\\n self.logger.info(f'Job {ids[i]} error: {err}')\\n\\n # inference\\n self.logger.debug(f'Validated: {validated}, Errors: {errors}')\\n result = []\\n if validated:\\n result = self.infer(validated)\\n assert len(result) == len(validated), (\\n 'Wrong number of inference results. '\\n f'Expcet {len(validated)}, get{len(result)}.'\\n )\\n\\n # validate response\\n for data in result:\\n self.resp_schema.parse_obj(data)\\n\\n # add errors information\\n err_ids = ''\\n result = [self._pack(data) for data in result]\\n for index, err_msg in errors:\\n err_ids += ids[index]\\n result.insert(index, err_msg)\\n\\n # build batch job table\\n resp = dict(zip(ids, result))\\n if err_ids:\\n resp['error_ids'] = err_ids\\n self._response(conn, resp)\",\n \"def _update_per_namespace():\\n\\n for acc in account.Account.query().iter():\\n try:\\n acc.refresh_devices()\\n acc.put()\\n except:\\n logging.error('Error refreshing account %s',\\n acc.key.string_id(), exc_info=sys.exc_info())\\n\\n for _room in room.Room.query().iter():\\n try:\\n _room.update_lights()\\n except:\\n logging.error('Error updating room %s',\\n _room.name, exc_info=sys.exc_info())\",\n \"def run(\\n self,\\n input_file=sys.stdin,\\n output_file=sys.stdout,\\n schema_map=None,\\n ):\\n schema_map, error_logs = self.deduce_schema(\\n input_file, schema_map=schema_map\\n )\\n\\n for error in error_logs:\\n logging.info(\\n f\\\"Problem on line {error['line_number']}: {error['msg']}\\\"\\n )\\n\\n if self.debugging_map:\\n json.dump(schema_map, output_file, indent=2)\\n print(file=output_file)\\n else:\\n schema = self.flatten_schema(schema_map)\\n json.dump(schema, output_file, indent=2)\\n print(file=output_file)\",\n \"def has_desired_schema(self):\\n if self._new_table == self._old_table:\\n if not self.rebuild:\\n log.info(\\\"Table already has the desired schema. \\\")\\n return True\\n else:\\n log.info(\\n \\\"Table already has the desired schema. However \\\"\\n \\\"--rebuild is specified, doing a rebuild instead\\\"\\n )\\n return False\\n return False\",\n \"async def write_schema_definition(controller, schema_definition_request):\\n write_schema_resp = await controller.schema.write_schema(\\n schema_definition_request.schema_name,\\n schema_definition_request.schema_attrs,\\n schema_definition_request.schema_version,\\n )\\n\\n if not write_schema_resp or write_schema_resp == {}:\\n raise HTTPException(\\n status_code=404,\\n detail=f\\\"Something went wrong.\\\\n Could not write schema to ledger.\\\\n{schema}\\\",\\n )\\n return write_schema_resp\",\n \"def update_updated_data_sqlite_db(self, table_name: str):\\n # go through indicators and get updated data in dataframe\\n print('start downloading queries')\\n df = self.__get_updated_data(table_name)\\n print('api download completed')\\n\\n # get list of sql queries to insert to sqlite db\\n print('start creating queries')\\n q_list = self.__get_sql_insert_query_list(df, table_name)\\n\\n # insert data to sqlite\\n print('start inserting data')\\n AccessDB().run_insert_query(q_list)\\n return 'Process Completed'\",\n \"def main():\\n cur, conn = connect('dwh.cfg')\\n \\n set_schema = schema_queries[1]\\n cur.execute(set_schema)\\n \\n print('Loading Staging Tables.')\\n load_staging_tables(cur, conn)\\n \\n print('Inserting Rows.')\\n insert_tables(cur, conn)\\n\\n \\n conn.close()\",\n \"def update_tables(tables):\\n # First we ensure we can find the file format version number\\n # in top-level metadata. Then we proceed to fix up the tables as necessary.\\n if not (isinstance(tables.metadata, dict) and 'SLiM' in tables.metadata):\\n # Old versions kept information in provenance, not top-level metadata.\\n # Note this uses defaults on keys not present in provenance,\\n # which prior to 0.5 was everything but generation and model_type.\\n values = default_slim_metadata('tree_sequence')['SLiM']\\n prov = None\\n file_version = 'unknown'\\n # use only the last SLiM provenance\\n for p in tables.provenances:\\n is_slim, this_file_version = slim_provenance_version(p) \\n if is_slim:\\n prov = p\\n file_version = this_file_version\\n values['file_version'] = file_version\\n try:\\n record = json.loads(prov.record)\\n if file_version == \\\"0.1\\\":\\n values['model_type'] = record['model_type']\\n values['tick'] = record['generation']\\n values['cycle'] = record['generation']\\n else:\\n if 'generation' in record['slim']:\\n values['tick'] = record['slim']['generation']\\n values['cycle'] = record['slim']['generation']\\n for k in values:\\n if k in record['parameters']:\\n values[k] = record['parameters'][k]\\n if k in record['slim']:\\n values[k] = record['slim'][k]\\n except:\\n raise ValueError(\\\"Failed to obtain metadata from provenance.\\\")\\n set_tree_sequence_metadata(tables, **values)\\n\\n file_version = tables.metadata['SLiM']['file_version']\\n if file_version != slim_file_version:\\n warnings.warn(\\\"This is a version {} SLiM tree sequence.\\\".format(file_version) +\\n \\\" When you write this out, \\\" +\\n \\\"it will be converted to version {}.\\\".format(slim_file_version))\\n\\n # the only tables to have metadata schema changed thus far\\n # are populations, individuals, mutations, and top-level:\\n old_schema = _old_metadata_schema(\\\"tree_sequence\\\", file_version)\\n if old_schema is not None:\\n md = tables.metadata\\n new_schema = slim_metadata_schemas[\\\"tree_sequence\\\"]\\n new_properties = new_schema.asdict()['properties']['SLiM']['required']\\n tables.metadata_schema = new_schema\\n defaults = default_slim_metadata(\\\"tree_sequence\\\")\\n for k in new_properties:\\n if k not in md['SLiM']:\\n if k == \\\"tick\\\":\\n md['SLiM']['tick'] = md['SLiM']['generation']\\n md['SLiM']['cycle'] = md['SLiM']['generation']\\n else:\\n md['SLiM'][k] = defaults['SLiM'][k]\\n tables.metadata = md\\n\\n old_schema = _old_metadata_schema(\\\"population\\\", file_version)\\n if old_schema is not None:\\n pops = tables.populations.copy()\\n tables.populations.clear()\\n if pops.metadata_schema == tskit.MetadataSchema(None):\\n pops.metadata_schema = old_schema\\n new_schema = slim_metadata_schemas[\\\"population\\\"]\\n tables.populations.metadata_schema = new_schema\\n defaults = default_slim_metadata(\\\"population\\\")\\n # just needs recoding\\n for pop in pops:\\n tables.populations.append(pop)\\n\\n old_schema = _old_metadata_schema(\\\"individual\\\", file_version)\\n if old_schema is not None:\\n inds = tables.individuals.copy()\\n tables.individuals.clear()\\n if inds.metadata_schema == tskit.MetadataSchema(None):\\n inds.metadata_schema = old_schema\\n new_schema = slim_metadata_schemas[\\\"individual\\\"]\\n tables.individuals.metadata_schema = new_schema\\n defaults = default_slim_metadata(\\\"individual\\\")\\n d = {}\\n for k in [\\\"pedigree_p1\\\", \\\"pedigree_p2\\\"]:\\n d[k] = defaults[k]\\n for ind in inds:\\n md = ind.metadata\\n md.update(d)\\n tables.individuals.append(ind.replace(metadata=md))\\n\\n old_schema = _old_metadata_schema(\\\"mutation\\\", file_version)\\n if old_schema is not None:\\n muts = tables.mutations.copy()\\n tables.mutations.clear()\\n if muts.metadata_schema == tskit.MetadataSchema(None):\\n muts.metadata_schema = old_schema\\n tables.mutations.metadata_schema = slim_metadata_schemas[\\\"mutation\\\"]\\n for mut in muts:\\n md = mut.metadata\\n for ml in md['mutation_list']:\\n ml['nucleotide'] = -1\\n tables.mutations.append(mut.replace(metadata=md))\\n\\n if file_version == \\\"0.1\\\":\\n # shift times\\n slim_generation = tables.metadata['SLiM']['tick']\\n node_times = tables.nodes.time + slim_generation\\n tables.nodes.set_columns(\\n flags=tables.nodes.flags,\\n time=node_times,\\n population=tables.nodes.population,\\n individual=tables.nodes.individual,\\n metadata=tables.nodes.metadata,\\n metadata_offset=tables.nodes.metadata_offset)\\n migration_times = tables.migrations.time + slim_generation\\n tables.migrations.set_columns(\\n left=tables.migrations.left,\\n right=tables.migrations.right,\\n node=tables.migrations.node,\\n source=tables.migrations.source,\\n dest=tables.migrations.dest,\\n time=migration_times)\\n\\n new_record = {\\n \\\"schema_version\\\": \\\"1.0.0\\\",\\n \\\"software\\\": {\\n \\\"name\\\": \\\"pyslim\\\",\\n \\\"version\\\": pyslim_version,\\n },\\n \\\"parameters\\\": {\\n \\\"command\\\": [\\\"updrade_tables\\\"],\\n \\\"old_file_version\\\": file_version,\\n \\\"new_file_version\\\": slim_file_version,\\n },\\n \\\"environment\\\": get_environment(),\\n }\\n tskit.validate_provenance(new_record)\\n tables.provenances.add_row(json.dumps(new_record))\\n\\n set_metadata_schemas(tables)\\n md = tables.metadata\\n md['SLiM']['file_version'] = slim_file_version\\n tables.metadata = md\",\n \"def serializeSchemaContext(schema_context, event=None):\\n # find the FTI and model\\n fti = schema_context.fti\\n schemaName = schema_context.schemaName\\n schema = schema_context.schema\\n model = fti.lookupModel()\\n\\n # synchronize changes to the model\\n syncSchema(schema, model.schemata[schemaName], overwrite=True)\\n fti.model_source = serializeModel(model)\",\n \"async def send_schema(self, schema_data_json: str) -> str: # issuer\\n\\n req_json = await ledger.build_schema_request(self.did, schema_data_json)\\n resp_json = await ledger.sign_and_submit_request(self.pool.handle, self.wallet_handle, self.did, req_json)\\n resp = (json.loads(resp_json))['result']\\n return await self.get_schema(resp['identifier'], resp['data']['name'], resp['data']['version'])\",\n \"def fix_all(self):\\n\\n altered_tables = {}\\n\\n for ingestible_db_conf in self.ingestible_db_conf_repo.get_ingestible_dbs():\\n target_db= ingestible_db_conf.target_db_name\\n db_type = ingestible_db_conf.db_type\\n self.logger.info(\\\"Fixing consistency for DB Type: %s, Target DB: %s\\\" % (db_type, target_db))\\n self.prepare_database(target_db)\\n consistency_checker = HiveConsistencyChecker(target_db, db_type)\\n\\n unused_tables = consistency_checker.get_unused_tables()\\n self.remove_unused_tables(unused_tables)\\n\\n new_tables = consistency_checker.get_new_tables()\\n self.create_new_tables(new_tables)\\n\\n inconsistent_tables = consistency_checker.get_inconsistent_tables()\\n self.fix_inconsistent_tables(inconsistent_tables, db_type)\\n\\n # Combine lists of inconsistent and unused tables\\n altered_tables[db_type] = map(lambda qualified_table: qualified_table.split(\\\".\\\")[1],\\n inconsistent_tables.keys() + unused_tables)\\n\\n self.logger.debug(\\\"Altered Tables: %s\\\" % altered_tables)\\n return altered_tables\",\n \"def test_compare_schemas_empty(self):\\n status = schema_utils.compare_schemas(\\n {},\\n self.base_schema,\\n )\\n\\n assert status == schema_utils.Update.first_run\",\n \"def schema_handler(self, schema):\\n dict_for_render = schema.get('properties', {}).items()\\n if schema.get('$ref', None):\\n def_name = schema.get('$ref').split('/')[-1]\\n dict_for_render = self.definitions[def_name].get('properties', {}).items()\\n elif schema.get('properties', None) is None:\\n return ''\\n\\n answer_dict = {}\\n json_dict = {}\\n for opt_name, opt_value in dict_for_render:\\n var_type = opt_value.get('format', None) or opt_value.get('type', None) or 'object'\\n json_name = self.indent + f':jsonparameter {var_type} {opt_name}:'\\n json_dict[json_name] = self.get_json_props_for_response(var_type, opt_value)\\n\\n answer_dict[opt_name] = self.get_response_example(opt_name, var_type, opt_value)\\n if var_type == 'string':\\n answer_dict[opt_name] = answer_dict[opt_name].format(opt_name)\\n\\n self.write('')\\n for line in json.dumps(answer_dict, indent=4).split('\\\\n'):\\n self.write(line, self.indent_depth)\\n\\n self.write('')\\n for json_param_name, json_param_value in json_dict.items():\\n desc = f'{json_param_value[\\\"title\\\"]}{json_param_value[\\\"props_str\\\"]}' or 'None'\\n self.write(json_param_name + ' ' + desc)\",\n \"def create_tables(): \\n \\n pk_contraint = \\\"CONSTRAINT {}_pk PRIMARY KEY ({})\\\"\\n uq_contraint = \\\"CONSTRAINT {}_uq UNIQUE ({})\\\"\\n fk_query = \\\"\\\"\\\"CONSTRAINT {}_fk_{} \\n FOREIGN KEY ({}) \\n REFERENCES {}({}) \\n ON UPDATE CASCADE \\n ON DELETE RESTRICT\\n \\\"\\\"\\\"\\n \\n create_dict = {}\\n index = 1\\n\\n\\n ############################## public SCHEMA ##############################\\n \\n schema = 'public'\\n create_schema(schema)\\n\\n #################### site ####################\\n table_name = 'site'\\n pk_id = 'site_id'\\n uq_list = ['site_code']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_code CHAR(3),\\n purok VARCHAR,\\n sitio VARCHAR,\\n barangay VARCHAR,\\n municipality VARCHAR,\\n province VARCHAR,\\n region VARCHAR,\\n psgc INTEGER,\\n active BOOLEAN NOT NULL DEFAULT TRUE,\\n season SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################## spatial SCHEMA ##############################\\n \\n schema = 'spatial'\\n create_schema(schema)\\n \\n #################### exposure ####################\\n table_name = 'exposure'\\n pk_id = 'exp_id'\\n uq_list = ['exp_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n exp_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### site_exposure ####################\\n table_name = 'site_exposure'\\n pk_id = 'se_id'\\n uq_list = ['site_id', 'exp_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'exp_id': {'ref_schema': 'spatial', 'ref_table': 'exposure'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n exp_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### feature ####################\\n table_name = 'feature'\\n pk_id = 'feat_id'\\n uq_list = ['feat_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n feat_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_feature ####################\\n table_name = 'site_feature'\\n pk_id = 'sf_id'\\n uq_list = ['site_id', 'feat_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'feat_id': {'ref_schema': 'spatial', 'ref_table': 'feature'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n feat_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### hazard_zone ####################\\n table_name = 'hazard_zone'\\n pk_id = 'hz_id'\\n uq_list = ['site_id, geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### monitoring ####################\\n table_name = 'monitoring'\\n pk_id = 'mon_id'\\n uq_list = ['mon_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n mon_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### site_monitoring ####################\\n table_name = 'site_monitoring'\\n pk_id = 'sm_id'\\n uq_list = ['site_id', 'mon_id', 'geom']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'},\\n 'mon_id': {'ref_schema': 'spatial', 'ref_table': 'monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n mon_id INTEGER,\\n label_name VARCHAR,\\n geom GEOMETRY,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n deactivated DATE,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################### comm SCHEMA ###############################\\n \\n schema = 'comm'\\n create_schema(schema)\\n\\n #################### gsm_server ####################\\n table_name = 'gsm_server'\\n pk_id = 'server_id'\\n uq_list = ['server_name']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_name VARCHAR,\\n platform_type VARCHAR,\\n version SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### server_port ####################\\n table_name = 'server_port'\\n pk_id = 'port_id'\\n uq_list = ['server_id', 'port']\\n fk_dict = {'server_id': {'ref_schema': 'comm', 'ref_table': 'gsm_server'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n server_id INTEGER,\\n port BOOLEAN,\\n ser_port VARCHAR,\\n pwr_on_pin SMALLINT,\\n ring_pin SMALLINT,\\n module_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- left\\n 1- right'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### network_type ####################\\n table_name = 'network_type'\\n pk_id = 'prefix'\\n uq_list = ['prefix']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} VARCHAR(3), \\n carrier SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '1- globe\\n 2- smart\\n 3- landline'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### gsm_module ####################\\n table_name = 'gsm_module'\\n pk_id = 'gsm_id'\\n uq_list = ['prefix', 'num', 'activated']\\n fk_dict = {'prefix': {'ref_schema': 'comm', 'ref_table': 'network_type'},\\n 'port_id': {'ref_schema': 'comm', 'ref_table': 'server_port'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n prefix VARCHAR(3),\\n num CHAR(7),\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n port_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n ############################# temporal SCHEMA #############################\\n \\n schema = 'temporal'\\n create_schema(schema)\\n\\n #################### marker_observation ####################\\n table_name = 'marker_observation'\\n pk_id = 'mo_id'\\n uq_list = ['site_id', 'ts']\\n fk_dict = {'site_id': {'ref_schema': 'public', 'ref_table': 'site'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n site_id INTEGER,\\n ts TIMESTAMP,\\n meas_type VARCHAR(7),\\n weather VARCHAR,\\n observer_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_history ####################\\n table_name = 'marker_history'\\n pk_id = 'hist_id'\\n uq_list = ['sm_id', 'ts', 'event']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n sm_id BIGINT,\\n ts TIMESTAMP,\\n event BOOLEAN,\\n label_name VARCHAR,\\n {}, {} {}\\n );\\n \\\"\\\"\\\"\\n query += \\\"\\\"\\\" COMMENT ON TABLE {}.{} IS \\n '0- rename\\n 1- reposition'\\n ;\\\"\\\"\\\".format(schema, table_name)\\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_data ####################\\n table_name = 'marker_data'\\n pk_id = 'data_id'\\n uq_list = ['sm_id', 'mo_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'mo_id': {'ref_schema': 'temporal', 'ref_table': 'marker_observation'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n mo_id BIGINT,\\n sm_id BIGINT,\\n measurement NUMERIC(5,1),\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### marker_alert ####################\\n table_name = 'marker_alert'\\n pk_id = 'alert_id'\\n uq_list = ['data_id']\\n fk_dict = {'data_id': {'ref_schema': 'temporal', 'ref_table': 'marker_data'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n data_id BIGINT,\\n displacement NUMERIC(4,1),\\n time_delta FLOAT,\\n alert_level SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger_model ####################\\n table_name = 'logger_model'\\n pk_id = 'model_id'\\n uq_list = ['has_tilt', 'has_rain', 'has_piezo', 'has_soms', 'logger_type']\\n fk_dict = {}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n has_tilt BOOLEAN,\\n has_rain BOOLEAN,\\n has_piezo BOOLEAN,\\n has_soms BOOLEAN,\\n logger_type SMALLINT,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n #################### logger ####################\\n table_name = 'logger'\\n pk_id = 'logger_id'\\n uq_list = ['sm_id']\\n fk_dict = {'sm_id': {'ref_schema': 'spatial', 'ref_table': 'site_monitoring'},\\n 'model_id': {'ref_schema': 'temporal', 'ref_table': 'logger_model'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL, \\n sm_id BIGINT,\\n model_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n \\n #################### logger_mobile ####################\\n table_name = 'logger_mobile'\\n pk_id = 'mobile_id'\\n uq_list = ['logger_id', 'activated']\\n fk_dict = {'logger_id': {'ref_schema': 'temporal', 'ref_table': 'logger'},\\n 'gsm_id': {'ref_schema': 'comm', 'ref_table': 'gsm_module'}}\\n query = \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS {}.{} (\\n {} SERIAL,\\n logger_id INTEGER,\\n activated DATE NOT NULL DEFAULT CURRENT_DATE,\\n sim_num VARCHAR(12),\\n gsm_id INTEGER,\\n {}, {} {}\\n );\\n \\\"\\\"\\\" \\n create_dict[index] = {'schema': schema,\\n 'table_name': table_name,\\n 'query': query,\\n 'pk_id': pk_id,\\n 'uq_list': uq_list,\\n 'fk_dict': fk_dict}\\n index += 1\\n\\n\\n #################### EXECUTE QUERY TO CREATE TABLES ####################\\n for index in create_dict.keys():\\n dct = create_dict[index]\\n schema = dct['schema']\\n table_name = dct['table_name']\\n query = dct['query']\\n pk_id = dct['pk_id']\\n uq_list = dct['uq_list']\\n fk_dict = dct['fk_dict']\\n if len(fk_dict.keys()) == 0:\\n fk_constraint = ''\\n else:\\n fk_constraint_list = ['']\\n for fk_id in fk_dict.keys():\\n ref_schema = fk_dict.get(fk_id)['ref_schema']\\n ref_table = fk_dict.get(fk_id)['ref_table']\\n fk_part = fk_query.format(table_name, ref_table, fk_id,\\n \\\"{}.{}\\\".format(ref_schema, ref_table),\\n fk_id)\\n fk_constraint_list.append(fk_part)\\n fk_constraint = ', '.join(fk_constraint_list)\\n \\n query = query.format(schema, table_name, pk_id, \\n pk_contraint.format(table_name, pk_id),\\n uq_contraint.format(table_name, ', '.join(uq_list)),\\n \\\"{}\\\".format(fk_constraint))\\n qdb.execute(query)\",\n \"async def get_schema(\\n self, refresh: bool = False, headers: Optional[Dict[str, str]] = None\\n ) -> graphql.GraphQLSchema:\\n # TODO: consider adding ttl logic for expiring schemas for long running services\\n if self._schema is None or refresh:\\n self._schema = await self.introspect(headers=headers)\\n return self._schema\",\n \"def match_schemas(w_schema, r_schema):\\n if isinstance(w_schema, dict) and isinstance(r_schema, dict):\\n # Array, Map, Enum, Fixed, Record, Error\\n w_type = w_schema['type']\\n r_type = r_schema['type']\\n if w_type != r_type:\\n return False\\n if w_type == 'array':\\n # 'Both schemas are arrays whose item types match'\\n return match_schemas(w_schema['items'], r_schema['items'])\\n elif w_type == 'map':\\n # 'Both schemas are maps whose value types match'\\n return match_schemas(w_schema['values'], r_schema['values'])\\n elif w_type in ('enum', 'record', 'error'):\\n # 'Both schemas are enums whose names match'\\n # 'Both schemas are records with the same name'\\n # Note: Futher checks must be applied after data is read in\\n # `read_enum()` and `read_record()`\\n return w_schema['name'] == r_schema['name']\\n elif w_type == 'fixed':\\n # 'Both schemas are fixed whose sizes and names match'\\n return (\\n w_schema['name'] == r_schema['name'] and\\n w_schema['size'] == r_schema['size']\\n )\\n elif w_type == r_type:\\n # Unknown type - just return True\\n return True\\n\\n elif isinstance(w_schema, list) or isinstance(r_schema, list):\\n # 'Either schema is a union'\\n if isinstance(w_schema, list):\\n # If the writer is a union, the check is applied in `read_union()`\\n # when the correct schema is known.\\n return True\\n else:\\n # If the reader is a union, ensure at least one of the schemas in\\n # the reader's union matches the writer's schema.\\n return any(match_schemas(w_schema, s) for s in r_schema)\\n\\n elif w_schema == r_schema:\\n return True\\n\\n # Promotion cases:\\n elif w_schema == 'int' and r_schema in ('long', 'float', 'double'):\\n return True\\n elif w_schema == 'long' and r_schema in ('float', 'double'):\\n return True\\n elif w_schema == 'float' and r_schema == 'double':\\n return True\\n elif w_schema == 'string' and r_schema == 'bytes':\\n return True\\n elif w_schema == 'bytes' and r_schema == 'string':\\n return True\\n\\n return False\",\n \"def update(self):\\n current = LazyRegister(self.db)\\n current.render()\\n cur = self.db.cursor()\\n for table in self.tables:\\n if table in current.tables:\\n additions, removals = current.tables[table].migrate(self.tables[table])\\n for addition in additions:\\n cur.execute(\\\"\\\"\\\"ALTER TABLE %s ADD COLUMN %s\\\"\\\"\\\" % (\\n table, addition[1].get_sql()\\n ))\\n print('Added column: ', addition[0])\\n for removal in removals:\\n #cur.execute(\\\"\\\"\\\"ALTER TABLE %s DROP COLUMN %s\\\"\\\"\\\" % (\\n # table, removal[0]\\n #))\\n #print('Removed column: ', removal[0])\\n print('Did not removed column: ', removal[0])\\n else:\\n schema = self.tables[table].get_create_table_sql()\\n cur.execute(schema)\\n print('Added table %s' % table)\",\n \"def _get_schema(self):\\n\\n schema = ProtocolSchema()\\n\\n schema.id = self.id\\n schema.type = type(self).__name__\\n\\n for input_path in self.required_inputs:\\n\\n if not (input_path.start_protocol is None or (input_path.start_protocol == self.id and\\n input_path.start_protocol == input_path.last_protocol)):\\n\\n continue\\n\\n # Always make sure to only pass a copy of the input. Changing the schema\\n # should NOT change the protocol.\\n schema.inputs[input_path.full_path] = copy.deepcopy(self.get_value(input_path))\\n\\n return schema\",\n \"def process(rec, conn):\\n try:\\n # Changes members from distinguished name to next_id for roles\\n if \\\"members\\\" in rec[\\\"data\\\"]:\\n rec = translate_field_to_next(rec, \\\"members\\\")\\n if \\\"owners\\\" in rec[\\\"data\\\"]:\\n rec = translate_field_to_next(rec, \\\"owners\\\")\\n\\n add_transaction(rec)\\n if \\\"batch\\\" not in rec or not rec[\\\"batch\\\"]:\\n r.table(\\\"inbound_queue\\\").get(rec[\\\"id\\\"]).delete().run(conn)\\n rec[\\\"sync_direction\\\"] = \\\"inbound\\\"\\n r.table(\\\"sync_errors\\\").insert(rec).run(conn)\\n return\\n\\n batch = batch_pb2.Batch()\\n batch.ParseFromString(rec[\\\"batch\\\"])\\n batch_list = batch_to_list(batch=batch)\\n client = ClientSync()\\n status = client.send_batches_get_status(batch_list=batch_list)\\n while status[0][\\\"status\\\"] == \\\"PENDING\\\":\\n LOGGER.info(\\\"Batch status is %s\\\", status)\\n status = client.status_recheck(batch_list)\\n if status[0][\\\"status\\\"] == \\\"COMMITTED\\\":\\n if rec[\\\"data_type\\\"] == \\\"user\\\":\\n insert_to_user_mapping(rec)\\n if \\\"metadata\\\" in rec and rec[\\\"metadata\\\"]:\\n data = {\\n \\\"address\\\": rec[\\\"address\\\"],\\n \\\"object_type\\\": rec[\\\"object_type\\\"],\\n \\\"object_id\\\": rec[\\\"object_id\\\"],\\n \\\"provider_id\\\": rec[\\\"provider_id\\\"],\\n \\\"created_at\\\": r.now(),\\n \\\"updated_at\\\": r.now(),\\n **rec[\\\"metadata\\\"],\\n }\\n\\n query = (\\n r.table(\\\"metadata\\\")\\n .get(rec[\\\"address\\\"])\\n .replace(\\n lambda doc: r.branch(\\n # pylint: disable=singleton-comparison\\n (doc == None), # noqa\\n r.expr(data),\\n doc.merge(\\n {\\\"metadata\\\": rec[\\\"metadata\\\"], \\\"updated_at\\\": r.now()}\\n ),\\n )\\n )\\n )\\n result = query.run(conn)\\n if (not result[\\\"inserted\\\"] and not result[\\\"replaced\\\"]) or result[\\n \\\"errors\\\"\\n ] > 0:\\n LOGGER.warning(\\n \\\"error updating metadata record:\\\\n%s\\\\n%s\\\", result, query\\n )\\n rec[\\\"sync_direction\\\"] = \\\"inbound\\\"\\n r.table(\\\"changelog\\\").insert(rec).run(conn)\\n r.table(\\\"inbound_queue\\\").get(rec[\\\"id\\\"]).delete().run(conn)\\n else:\\n rec[\\\"error\\\"] = get_status_error(status)\\n rec[\\\"sync_direction\\\"] = \\\"inbound\\\"\\n r.table(\\\"sync_errors\\\").insert(rec).run(conn)\\n r.table(\\\"inbound_queue\\\").get(rec[\\\"id\\\"]).delete().run(conn)\\n\\n except Exception as err: # pylint: disable=broad-except\\n LOGGER.exception(\\n \\\"%s exception processing inbound record:\\\\n%s\\\", type(err).__name__, rec\\n )\\n LOGGER.exception(err)\",\n \"def create_tables_and_apply_patches(self):\\n\\n if self.authorized and not self.db_tables_initiated:\\n with self.connection.cursor() as cursor:\\n for statement in self.parse_mysql_sql_file():\\n cursor.execute(statement)\\n\\n PyFunceble.LOGGER.info(\\n \\\"Created the missing tables. Applied all patched\\\"\\n )\\n\\n self.db_tables_initiated = True\",\n \"def resolve_nested_schema(self, schema):\\n try:\\n schema_instance = resolve_schema_instance(schema)\\n # If schema is a string and is not found in registry,\\n # assume it is a schema reference\\n except marshmallow.exceptions.RegistryError:\\n return schema\\n schema_key = make_schema_key(schema_instance)\\n if schema_key not in self.refs:\\n name = self.schema_name_resolver(schema)\\n if not name:\\n try:\\n json_schema = self.schema2jsonschema(schema_instance)\\n except RuntimeError:\\n raise APISpecError(\\n \\\"Name resolver returned None for schema {schema} which is \\\"\\n \\\"part of a chain of circular referencing schemas. Please\\\"\\n \\\" ensure that the schema_name_resolver passed to\\\"\\n \\\" MarshmallowPlugin returns a string for all circular\\\"\\n \\\" referencing schemas.\\\".format(schema=schema)\\n )\\n if getattr(schema, \\\"many\\\", False):\\n return {\\\"type\\\": \\\"array\\\", \\\"items\\\": json_schema}\\n return json_schema\\n name = get_unique_schema_name(self.spec.components, name)\\n self.spec.components.schema(name, schema=schema)\\n return self.get_ref_dict(schema_instance)\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def decide_schema(self, json_data):\\n pass\",\n \"def check_schema_existence_api_call(context, schema, version):\\n check_schema_existence(context, schema, version, \\\"api\\\")\",\n \"def _AddNewColsToSchema(new_fields, orig_schema_map):\\n updated_schema_map = orig_schema_map.copy()\\n for new_field in new_fields:\\n if new_field.name in orig_schema_map:\\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\\n updated_schema_map[new_field.name] = new_field\\n return updated_schema_map\",\n \"def do_export_schema(self):\\n export_schema = self.get_arg_value(\\\"export_schema\\\")\\n\\n if export_schema:\\n row = {\\\"schemas\\\": self.final_schemas}\\n self.write_rows(rows=row)\\n del row\",\n \"def patch(self):\\n if not self.validate_complaint_document(\\\"update\\\"):\\n return\\n if apply_patch(self.request, src=self.request.context.serialize()):\\n update_file_content_type(self.request)\\n self.LOGGER.info(\\n \\\"Updated tender award complaint document {}\\\".format(self.request.context.id),\\n extra=context_unpack(self.request, {\\\"MESSAGE_ID\\\": \\\"tender_award_complaint_document_patch\\\"}),\\n )\\n return {\\\"data\\\": self.request.context.serialize(\\\"view\\\")}\",\n \"def load(self, base_schema):\\n if base_schema == []:\\n _base = []\\n else:\\n _base = base_schema or BASE_SCHEMA or []\\n\\n _base_schema = []\\n for _sc in _base:\\n if _sc == \\\"schema\\\" or _sc == \\\"schema.org\\\":\\n self.schema_org_version = get_schemaorg_version()\\n _base_schema.append(\\n load_schemaorg(version=self.schema_org_version, verbose=self.verbose)\\n )\\n continue\\n elif self.is_a_dde_schema(_sc):\\n _base_schema.append(self.load_dde_schemas(_sc))\\n\\n _base_schema = merge_schema(*_base_schema)\\n return _base_schema\",\n \"def __matchSchema(self, featureClass):\\n fClassFields = []\\n for field in arcpy.ListFields(featureClass):\\n fieldName = field.name.lower()\\n if fieldName == 'objectid' or fieldName == 'oid' or 'shape' in fieldName or field.name in self.userFields:\\n pass\\n else:\\n fClassFields.append(field.name)\\n fClassFields.insert(0, 'Shape@')\\n objFields = [f['name'] for f in self.updateFields]\\n return sorted(fClassFields) == sorted(objFields)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65370333","0.61016726","0.59257406","0.59054583","0.57786834","0.5593872","0.5549331","0.5481114","0.5472658","0.54690826","0.5401272","0.5361555","0.53470576","0.5315268","0.5254957","0.52487254","0.5139043","0.50770354","0.5074396","0.5061819","0.5033071","0.502315","0.5017254","0.50041014","0.5001959","0.50011426","0.49769256","0.49501354","0.49407235","0.4929252","0.49250436","0.49121267","0.4900479","0.4880573","0.48635983","0.48530206","0.48388177","0.48343465","0.4824842","0.48192585","0.4817013","0.47990775","0.47986832","0.47926039","0.4791585","0.4790972","0.47862694","0.47694156","0.47690782","0.47657046","0.47607344","0.4751095","0.47428063","0.4735867","0.47179085","0.47115967","0.4699601","0.46832496","0.46828026","0.46818277","0.46787435","0.46737728","0.46716136","0.46694294","0.46316704","0.46195805","0.46052155","0.4562152","0.45620155","0.4556141","0.4555454","0.4551104","0.454958","0.4547384","0.45462012","0.45443198","0.45382723","0.4530371","0.45241508","0.45235947","0.45217818","0.4521111","0.45162898","0.450814","0.45065898","0.45054102","0.44995424","0.44988978","0.44957325","0.44954717","0.4494832","0.4493811","0.44930992","0.44930992","0.44914076","0.44845492","0.44745573","0.4471194","0.44623452","0.44609377"],"string":"[\n \"0.65370333\",\n \"0.61016726\",\n \"0.59257406\",\n \"0.59054583\",\n \"0.57786834\",\n \"0.5593872\",\n \"0.5549331\",\n \"0.5481114\",\n \"0.5472658\",\n \"0.54690826\",\n \"0.5401272\",\n \"0.5361555\",\n \"0.53470576\",\n \"0.5315268\",\n \"0.5254957\",\n \"0.52487254\",\n \"0.5139043\",\n \"0.50770354\",\n \"0.5074396\",\n \"0.5061819\",\n \"0.5033071\",\n \"0.502315\",\n \"0.5017254\",\n \"0.50041014\",\n \"0.5001959\",\n \"0.50011426\",\n \"0.49769256\",\n \"0.49501354\",\n \"0.49407235\",\n \"0.4929252\",\n \"0.49250436\",\n \"0.49121267\",\n \"0.4900479\",\n \"0.4880573\",\n \"0.48635983\",\n \"0.48530206\",\n \"0.48388177\",\n \"0.48343465\",\n \"0.4824842\",\n \"0.48192585\",\n \"0.4817013\",\n \"0.47990775\",\n \"0.47986832\",\n \"0.47926039\",\n \"0.4791585\",\n \"0.4790972\",\n \"0.47862694\",\n \"0.47694156\",\n \"0.47690782\",\n \"0.47657046\",\n \"0.47607344\",\n \"0.4751095\",\n \"0.47428063\",\n \"0.4735867\",\n \"0.47179085\",\n \"0.47115967\",\n \"0.4699601\",\n \"0.46832496\",\n \"0.46828026\",\n \"0.46818277\",\n \"0.46787435\",\n \"0.46737728\",\n \"0.46716136\",\n \"0.46694294\",\n \"0.46316704\",\n \"0.46195805\",\n \"0.46052155\",\n \"0.4562152\",\n \"0.45620155\",\n \"0.4556141\",\n \"0.4555454\",\n \"0.4551104\",\n \"0.454958\",\n \"0.4547384\",\n \"0.45462012\",\n \"0.45443198\",\n \"0.45382723\",\n \"0.4530371\",\n \"0.45241508\",\n \"0.45235947\",\n \"0.45217818\",\n \"0.4521111\",\n \"0.45162898\",\n \"0.450814\",\n \"0.45065898\",\n \"0.45054102\",\n \"0.44995424\",\n \"0.44988978\",\n \"0.44957325\",\n \"0.44954717\",\n \"0.4494832\",\n \"0.4493811\",\n \"0.44930992\",\n \"0.44930992\",\n \"0.44914076\",\n \"0.44845492\",\n \"0.44745573\",\n \"0.4471194\",\n \"0.44623452\",\n \"0.44609377\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8179473"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2288,"cells":{"query":{"kind":"string","value":"Try to retrieve the current BigQuery TableSchema for a table_ref. Tries to fetch the schema of an existing table. Raises SchemaUpdateError if table is not found or if table is not of type 'TABLE'."},"document":{"kind":"string","value":"def _TryGetCurrentSchema(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\n get_request = get_request_type(datasetId=dataset_id,\n tableId=table_id,\n projectId=project_id)\n try:\n table = service.Get(get_request)\n if not table or table.type != 'TABLE':\n raise SchemaUpdateError('Schema modifications only supported '\n 'on TABLE objects received [{}]'.format(\n table))\n except apitools_exceptions.HttpNotFoundError:\n raise SchemaUpdateError('Table with id [{}:{}:{}] not found.'.format(\n project_id, dataset_id, table_id))\n\n return table.schema"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_table_schema(dataset_id, table_id):\n logging.info('getting table schema')\n bigquery_client = bigquery.Client()\n dataset_ref = bigquery_client.dataset(dataset_id)\n bg_tableref = bigquery.table.TableReference(dataset_ref, table_id)\n bg_table = bigquery_client.get_table(bg_tableref)\n return bg_table.schema","def fetch_table_schema(self, table_name):\n ddl = self.query(sql.show_create_table(table_name))\n if ddl:\n try:\n return parse_create(ddl[0][\"Create Table\"])\n except ParseError as e:\n raise OSCError(\n \"TABLE_PARSING_ERROR\",\n {\"db\": self._current_db, \"table\": self.table_name, \"msg\": str(e)},\n )","def _get_stored_schema(self, table: str) -> Optional[TableSchema]:\n try:\n with open(self.schemas / (table + '.json'), 'r') as f:\n return json.load(f)\n except FileNotFoundError:\n return None","def _get_table_reflection(self, schema: str, table: str) -> Table:\n return self.sql_metadata.tables.get(f\"{schema}.{table}\",\n Table(table, self.sql_metadata, schema=schema, autoload=True))","def ProcessSchemaUpdate(ref, args, request):\n table = request.table\n relaxed_columns = args.relax_columns\n if not table.schema and not relaxed_columns: # if not updating schema,\n return request # then just return.\n\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\n ref.Name(),\n ref.projectId)\n\n new_schema_columns = table.schema\n updated_fields = _GetUpdatedSchema(original_schema,\n new_schema_columns,\n relaxed_columns)\n\n table_schema_type = GetApiMessage('TableSchema')\n request.table.schema = table_schema_type(fields=updated_fields)\n\n return request","def CreateTableFromJson(self, table_name, schema_json):\n try:\n schema = json.JSONDecoder().decode(schema_json)\n except ValueError, e:\n raise SchemaError('Could not parse fields:\\n%s\\n%s' %\n (schema_json, str(e)))\n\n conn = self._Connect()\n result = conn.Call(\n dict(method='bigquery.tables.insert',\n collection='tables',\n operation=bq.REST.INSERT,\n params=dict(name=table_name, fields=schema)))\n return result","def create_tables(client: bigquery.Client, tableSchemas: dict) -> dict:\n ds = create_dataset(client, f'FusionTable_Autoimport_{datetime.now()}')\n\n def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\n \"\"\"Create a SchemaField from the dict\"\"\"\n name = to_safe_name(col_schema['name'])\n return bigquery.SchemaField(\n name,\n col_schema.get('type'),\n col_schema.get('mode', 'NULLABLE'),\n col_schema.get('description', '')\n )\n\n def _table_from_ft(ft_schema: dict) -> bigquery.Table:\n \"\"\"Create a local representation of a BigQuery table\"\"\"\n # A \"TableSchema\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\n schema = list(map(_create_field_schema, ft_schema['columns']))\n table = bigquery.Table(\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\n schema\n )\n table.description = ft_schema.get('description', '')\n return table\n\n return {\n ftId: client.create_table(_table_from_ft(ftSchema))\n for (ftId, ftSchema) in tableSchemas.items()\n }","def get_schema(self, repo, table):\n return self.user_con.get_schema(repo=repo, table=table)","def create_bq_table(client, dataset, table, schema):\n \n print('Creating table %s.%s' % (dataset, table))\n exists = client.check_table(dataset, table)\n if exists:\n raise AssertionError(\"Table already exists: %s.%s\" % (dataset,table))\n created = client.create_table(dataset, table, schema)\n # Check that the empty table was created\n exists = client.check_table(dataset, table)\n if not exists:\n raise RuntimeError('Table creation failed: %s.%s' % (dataset, table))","def __check_table(input_table):\n\n try:\n table = TABLE_TYPES[input_table]\n return table\n except KeyError:\n raise InvalidTableType(input_table)","def CreateTableFromFile(self, table_name, schema_path):\n try:\n schema_file = open(schema_path)\n schema_json = schema_file.read()\n schema_file.close()\n except IOError, e:\n raise SchemaError('Could not read file (%s):\\n%s' %\n (schema_path, str(e)))\n return self.CreateTableFromJson(table_name, schema_json)","def DescribeTable(self, table_name):\n conn = self._Connect()\n cursor = conn.cursor()\n return cursor.bq_get_table_metadata(table_name)","def getTableSchema(self,tableName):\n\tif not self.schemaDict.has_key(tableName):\n\t if self.dbType==\"sqlite\":\n\t query = \"SELECT * FROM sqlite_master WHERE name='%s'\"%tableName\n\t tup = self.fetchOne(query)\n\t schema= tup[4]\n\t else: # MySQL \n\t query = \"DESCRIBE %s\"%tableName\n\t tup = self.fetchAll(query)\n\t schema= \"CREATE TABLE %s (\"%tableName\n\t for item in tup:\n\t name = item[0]\n\t\t type = item[1]\n\t\t priKey = item[3]\n\t\t autoInc = item[5] \n\t schema+=name+' '+type+' '+priKey+' '+autoInc\n\t\t if item!=tup[-1]:\n\t\t schema+=','\n\t schema+=\" )\"\n\t return schema\n\telse:\n\t return self.schemaDict[tableName]","def _table_from_ft(ft_schema: dict) -> bigquery.Table:\n # A \"TableSchema\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\n schema = list(map(_create_field_schema, ft_schema['columns']))\n table = bigquery.Table(\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\n schema\n )\n table.description = ft_schema.get('description', '')\n return table","def get_schema(db, sourcename):\n try:\n schema = db[\"tables\"][sourcename]\n schema[\"type\"] = constants.TABLE\n except KeyError:\n try:\n schema = db[\"views\"][sourcename]\n schema[\"type\"] = constants.VIEW\n except KeyError:\n raise ValueError(\"no such table/view\")\n return schema","def get_tables_in_schema(self, conn, schema_name):\n return conn.get_tables(schema_name)['table_name']","def _get_table_schema(self):\n\n return {\n 'AttributeDefinitions': [\n {\n 'AttributeName': self._key_field.name,\n 'AttributeType': self._key_field.data_type\n }\n ],\n 'TableName': self.table_name,\n 'KeySchema': [\n {\n 'AttributeName': self._key_field.name,\n 'KeyType': 'HASH'\n }\n ],\n 'ProvisionedThroughput': {\n 'ReadCapacityUnits': self.read_capacity_units,\n 'WriteCapacityUnits': self.write_capacity_units\n }\n }","def get_table_definition(jwt_payload: dict, schema_name: str, table_name: str):\n DJConnector.set_datajoint_config(jwt_payload)\n\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\n return getattr(schema_virtual_module, table_name).describe()","def _create_table_if_not_exists(self) -> bigquery.Table:\n table = self.client.create_table(\n table=bigquery.Table(table_ref=self._table_ref, schema=Schema),\n exists_ok=True,\n )\n logging.info(\"table %s already exists.\", table.full_table_id)\n return table","def getTableSchema(self, lsstLevel, dbName, tableName):\n return self._doRequest(self.httpClient.getTableSchema, lsstLevel, dbName, tableName)","def schema(self) -> 'outputs.TableSchemaResponse':\n return pulumi.get(self, \"schema\")","def get_schema(self, get_stats=False):\n query = \"schema {}\"\n\n results = self.run_dgraph_query_raw(query)\n\n schema = {}\n\n for row in results[\"schema\"]:\n table_name = row[\"predicate\"]\n\n if table_name not in schema:\n schema[table_name] = {\"name\": table_name, \"columns\": []}\n\n return list(schema.values())","def schema_ref(schema, table):\n return schema + '.' + table","def get_table_exists(schema_name, table_name):\n sql = (\"SELECT * FROM sys.objects so JOIN sys.schemas ss on (so.schema_id = ss.schema_id) \"\n \"WHERE so.type = 'U' AND so.name = ? and ss.name = ?\")\n\n row = fetch_row(sql, [table_name, schema_name])\n\n return True if row else False","def ensure_schema(client, table_name):\n query = ''.join([\n 'CREATE TABLE {cf} ',\n '(\"lockId\" ascii, \"claimId\" timeuuid, PRIMARY KEY(\"lockId\", \"claimId\"));'])\n\n def errback(failure):\n failure.trap(InvalidRequestException)\n\n return client.execute(query.format(cf=table_name),\n {}, ConsistencyLevel.QUORUM).addErrback(errback)","def BqTableSchemaFileProcessor(file_arg):\n table_schema_type = GetApiMessage('TableSchema')\n schema_field_type = GetApiMessage('TableFieldSchema')\n\n try:\n schema_json = yaml.load(file_arg)\n schema_json = schema_json.get('schema', None)\n\n if not schema_json or not isinstance(schema_json, list):\n raise SchemaFileError(\n 'Error parsing schema file: no schema field list defined in file')\n\n all_fields = []\n for field in schema_json:\n new_field = schema_field_type(name=field['name'],\n type=field['type'],\n mode=field.get('mode', 'NULLABLE'))\n all_fields.append(new_field)\n\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\n except yaml.YAMLParseError as ype:\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\n except (AttributeError, KeyError) as e:\n raise SchemaFileError(\n 'Error parsing schema file, invalid field definition [{}]'.format(e))","def validate_table(self, table, table_struct, verbose=True):\n \n assert(self.connected)\n try: \n assert(self.check_table(table, verbose=False)) \n except AssertionError: \n raise TableNotFoundError\n \n GET_SCHEMA_INFORMATION_COMMAND = \"SELECT ORDINAL_POSITION, COLUMN_NAME, COLUMN_TYPE, IS_NULLABLE, COLUMN_KEY, EXTRA \" \\\n \t \"FROM INFORMATION_SCHEMA.COLUMNS \" \\\n \t \"WHERE TABLE_NAME='{0}' ORDER BY ORDINAL_POSITION\".format(table)\n \n GET_SCHEMA_FK_INFORMATION_COMMAND = \"SELECT COLUMN_NAME, CONSTRAINT_NAME, REFERENCED_TABLE_NAME, REFERENCED_COLUMN_NAME \" \\\n \"FROM INFORMATION_SCHEMA.KEY_COLUMN_USAGE \" \\\n \"WHERE REFERENCED_TABLE_SCHEMA = '{0}' AND TABLE_NAME = '{1}' AND COLUMN_NAME = '{2}'\"\n \n CHANGE_TYPE_COMMAND = \"ALTER TABLE {0} MODIFY {1} {2} {3}\"\n \n ADD_FK_COMMAND = \"ALTER TABLE {0} ADD FOREIGN KEY ({1}) REFERENCES {2}({3})\" \n \n DROP_FK_CONSTRAINT_COMMAND = \"ALTER TABLE {0} DROP FOREIGN KEY {1}\" \n \n \n self.cursor.execute(GET_SCHEMA_INFORMATION_COMMAND)\n \n # load all column info from the database \n columns = {}\n for c in self.cursor:\n columns[c[1]] = c\n \n for column,db_col in zip(table_struct,columns):\n \n # load parameter values from the DB \n (ord_pos, name, col_type, isnull, key_type, extra) = columns[db_col]\n \n isnull = isnull == 'YES'\n auto_increment = extra == 'auto_increment'\n foreign_key = key_type == 'MUL'\n \n # parse new parameter values\n struct_type = table_struct[column][0]\n parameters = table_struct[column][1] if ( len(table_struct[column]) > 1) else None\n \n # get parameters values in boolean format\n if (parameters == None):\n new_isnull = True\n new_auto_increment = False\n new_foreign_key = False\n else:\n if 'not_null' in parameters: new_isnull = not parameters['not_null']\n else: new_isnull = True\n \n if 'auto_increment' in parameters: new_auto_increment = parameters['auto_increment']\n else: new_auto_increment = False\n \n if 'foreign_key' in parameters: new_foreign_key = parameters['foreign_key']\n else: new_foreign_key = False\n \n \n \n \n if verbose: \n print(\"\\n---\\n\\nChecking column '{0}'...\".format(column))\n \n # check name, type and each parameter \n if name == column:\n \n # if something doesn't match, change within the database\n if ( col_type != struct_type ): \n if verbose:\n print(\"Column '{0}' found in the correct position with the incorrect type.\".format(column))\n print(\"Changing the type of '{0}' from '{1}' to '{2}'\".format(column, col_type, struct_type),)\n \n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), '')\n \n if verbose: print(\"\\t\" + cmd)\n \n self.cursor.execute(cmd) \n \n if ( isnull != new_isnull ):\n \n if verbose:\n print(\"Column '{0}' found in the correct position an incorrect parameter.\".format(column))\n print(\"Changing the type of '{0}' from '{1}' to '{2}'\".format(column, \"NOT NULLABLE\" if new_isnull else \"NULLABLE\", \"NULLABLE\" if new_isnull else \"NOT NULLABLE\"))\n \n \n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), \"NOT NULL\" if not new_isnull else \"\" )\n \n if verbose: print(\"\\t\" + cmd)\n \n \n self.cursor.execute(cmd)\n \n if ( auto_increment != new_auto_increment ):\n \n if verbose:\n print(\"Column '{0}' found in the correct position an incorrect parameter.\".format(column))\n print(\"Changing the type of '{0}' from '{1}' to '{2}'\".format(column, \"AUTO INCREMENT\" if new_auto_increment else \"none\", \"none\" if new_auto_increment else \"AUTO INCREMENT\"))\n \n \n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), \"AUTO INCREMENT\" if new_auto_increment else \"\" )\n \n if verbose: print(\"\\t\" + cmd)\n \n \n self.cursor.execute(cmd)\n \n \n if ( foreign_key != new_foreign_key ):\n \n \n if verbose:\n print(\"Column '{0}' found in the correct position an incorrect parameter.\".format(column))\n print(\"Changing the type of '{0}' from '{1}' to '{2}'\".format(column, \"FOREIGN KEY\" if new_auto_increment else \"none\", \"none\" if new_auto_increment else \"FOREIGN KEY\"))\n \n \n \n if ('foreign_key' in parameters and parameters['foreign_key']):\n \n referenced_table = parameters['references'].split('(')[0]\n referenced_column = parameters['references'].split('(')[1][:-1] \n \n \n if (not self.check_table(referenced_table, verbose=False)):\n raise(TableNotFoundError)\n \n \n if (not self.check_column(referenced_column, referenced_table, verbose=False)):\n raise(ColumnNotFoundError)\n \n \n cmd = ADD_FK_COMMAND.format(table,column,referenced_table, referenced_column)\n\n \n \n if verbose: print(\"\\t\" + cmd)\n \n try:\n self.cursor.execute(cmd) \n except:\n print(\" > Error: Cannot add foreign key constraint to column '{0}' in the table '{1}'. You must remove all data from\\n > this column using the clear_column() command first.\".format(column, table))\n \n else:\n \n # check if column has a foreign key constraint\n \n cmd = GET_SCHEMA_FK_INFORMATION_COMMAND.format(self.config['database'], table, column)\n \n self.cursor.execute(cmd)\n \n fk_name = None\n for row in self.cursor:\n fk_name = row[1]\n break\n \n if fk_name != None:\n cmd = DROP_FK_CONSTRAINT_COMMAND.format(table, fk_name)\n \n if verbose: \n print(\"Column '{0}' involved in foreign key constraint '{1}'\".format(column, fk_name))\n print(\"Dropping foreign key constraint '{0}'\".format(fk_name))\n print(\"\\t\" + cmd)\n \n self.cursor.execute(cmd)\n\n \n \n if verbose: print(\"Done.\")\n \n \n if (len(columns) > len(table_struct)):\n \n if verbose: print(\"\\n---\\n\\nExtra columns found in database\")\n \n for col in columns:\n if (col not in table_struct): \n \n if verbose:\n print(\"Column '{0}' found in the database but not found in the configuration.\".format(col))\n \n self.delete_column(col, table)\n \n \n elif(len(table_struct) > len(columns)):\n \n if verbose: print(\"\\n---\\n\\nExtra columns found in configuration. \")\n\n for col in table_struct:\n if col not in columns:\n if verbose: print(\"Column '{0}' found in configuration but not in database\".format(col))\n self.insert_column(col, table_struct[col][0], table, params = table_struct[col][1] if ( len(table_struct[col]) > 1) else None)","def _load_bigquery_schemas(self):\n logger.info(\"Reading BigQuery schema files...\")\n for table_name in self.tables + self.type_tables:\n logger.info(f\"Reading schema file for table '{table_name}'...\")\n schema_json = resource_stream('sotorrent_pipeline',\n f'bigquery_schemas/{table_name}.json').read().decode()\n self.bigquery_schemas[table_name] = json.loads(schema_json)\n self.bigquery_schemas_with_fields[table_name] = json.loads('{\"fields\":' + schema_json + '}')\n logger.info(f\"Read {len(self.bigquery_schemas)} schema file(s).\")","def is_table_exist(table_name: str, schema: str) -> str:\n\n return f\"\"\"\n SELECT\n table_name\n FROM\n information_schema.tables\n WHERE\n table_name = '{table_name}' AND\n table_schema='{schema}'\n LIMIT 1\n \"\"\"","def read_schema_from_db(cur, table):\n num_rows = cur.execute(\"\"\"DESCRIBE {}\"\"\".format(table))\n tbl_schema = []\n for i in range(num_rows):\n row = cur.fetchone()\n tbl_schema.append([row[0], row[1]])\n return tbl_schema","def delete_bq_table(client, dataset, table):\n \n exists = client.check_table(dataset, table)\n if exists:\n print('WARNING: Deleting existing table %s.%s' % (dataset, table))\n deleted = client.delete_table(dataset, table)\n if not deleted:\n raise RuntimeError('Table deletion failed: %s.%s' % (dataset, table))","def get_schemas(self, conn):\n return conn.get_schemas()['table_schema']","async def schema_state(appname, schema, table):\n base = sprout.cfg.db_str(appname)\n con = await asyncpg.connect(base)\n req = ', '.join([\n 'table_catalog',\n 'table_schema',\n 'table_name',\n 'column_name',\n 'data_type'\n ])\n q = f\"\"\"select {req} from information_schema.columns\nwhere table_schema='{schema}' and table_name='{table}';\"\"\"\n try:\n ret = await con.fetch(q)\n df = pd.DataFrame.from_records(ret, columns=ret[0].keys())\n return df\n except Exception as e:\n sprout.cfg.log.error(f\"fetching current table state failed: {e}\")\n finally:\n await con.close()","def ReadSchemaFile(schema_file, bigquery_messages):\n\n if os.path.exists(schema_file):\n with open(schema_file, mode='r') as f:\n try:\n def UpperOrNone(string):\n return string and string.upper()\n field_schemas = [\n bigquery_messages.TableFieldSchema(\n name=json_object.get('name'),\n type=json_object.get('type').upper(),\n mode=UpperOrNone(json_object.get('mode')))\n for json_object in json.load(f)]\n return bigquery_messages.TableSchema(fields=field_schemas)\n except ValueError as e:\n raise bigquery.SchemaError(\n 'Error decoding JSON schema from file {0}: {1}.'.format(\n schema_file, e))\n else:\n raise bigquery.SchemaError(\n 'Error reading schema: File \"{0}\" was not found.'.format(schema_file))","def table_reference(self) -> 'outputs.PreventionJobTriggerInspectJobStorageConfigBigQueryOptionsTableReference':\n return pulumi.get(self, \"table_reference\")","async def add_table(self, table: TableSchema) -> None:\n name = table['name']\n if not self._schema_valid_prod(table):\n if self.update_schema: # Interactively create or upgrade table schema\n stored_schema = self._get_stored_schema(name)\n if stored_schema: # Generate migrations from previous schema\n table, requests = update_table_schema(stored_schema, table)\n self._create_migration(table, requests)\n self._schema_write(table) # Write new schema to disk\n elif self.prod_mode: # Crash if production mode is on\n raise MigrationException(f\"in prod, and table {name} has outdated schema\")\n\n current_level = await self._get_migration_level(name)\n if current_level is None: # New table\n self._new_table_queue.append(table)\n elif self._needs_migrations(name, current_level): # Needs migration\n self._migration_queue.append(table)\n # else: no need to do anything for this table","def _TryDeleteTable(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')\n delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,\n projectId=project_id)\n service.Delete(delete_request)\n log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id))","def schema(self):\n return self.table_info.schema","def _TableExists(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\n get_request = get_request_type(datasetId=dataset_id, tableId=table_id,\n projectId=project_id)\n try:\n service.Get(get_request)\n return True\n except apitools_exceptions.HttpNotFoundError:\n log.info('Table with id [{}:{}:{}] not found.'.format(\n project_id, dataset_id, table_id))\n\n return False","def verify_table(self):\n metadata = MetaData()\n metadata.reflect(bind = StatusSource.engine)\n mine = str(self.table.columns)\n verified = str(metadata.tables[self.tablename].columns)\n if mine != verified:\n raise DbException(\"Table '%s' in the database has schema %s whereas the query's schema is %s\" % (self.tablename, verified, mine))","def tableExists(self, schema, table):\r\n r = self.fetchSqlRecords(\r\n \"SELECT to_regclass('{}.{}')\".format(schema, table))\r\n return r[0][0]","def get_schema_entry(self, key, value, base_path=None):\n value_mode, value_type = self.infer_bigquery_type(value)\n if not value_mode or not value_type:\n return None\n sanitized_key = self.sanitize_name(key)\n\n # yapf: disable\n if value_type == 'RECORD':\n new_base_path = json_full_path(base_path, key)\n # recursively figure out the RECORD\n fields = OrderedDict()\n if value_mode == 'NULLABLE':\n self.deduce_schema_for_record(\n json_object=value,\n schema_map=fields,\n base_path=new_base_path,\n )\n else:\n for val in value:\n self.deduce_schema_for_record(\n json_object=val,\n schema_map=fields,\n base_path=new_base_path,\n )\n\n schema_entry = OrderedDict([\n ('status', 'hard'),\n ('filled', True),\n ('info', OrderedDict([\n ('fields', fields),\n ('mode', value_mode),\n ('name', sanitized_key),\n ('type', value_type),\n ])),\n ])\n elif value_type == '__null__':\n schema_entry = OrderedDict([\n ('status', 'soft'),\n ('filled', False),\n ('info', OrderedDict([\n ('mode', 'NULLABLE'),\n ('name', sanitized_key),\n ('type', 'STRING'),\n ])),\n ])\n elif value_type == '__empty_array__':\n schema_entry = OrderedDict([\n ('status', 'soft'),\n ('filled', False),\n ('info', OrderedDict([\n ('mode', 'REPEATED'),\n ('name', sanitized_key),\n ('type', 'STRING'),\n ])),\n ])\n elif value_type == '__empty_record__':\n schema_entry = OrderedDict([\n ('status', 'soft'),\n ('filled', False),\n ('info', OrderedDict([\n ('fields', OrderedDict()),\n ('mode', value_mode),\n ('name', sanitized_key),\n ('type', 'RECORD'),\n ])),\n ])\n else:\n # Empty fields are returned as empty strings, and must be treated as\n # a (soft String) to allow clobbering by subsquent non-empty fields.\n if value == \"\" and self.input_format == 'csv':\n status = 'soft'\n filled = False\n else:\n status = 'hard'\n filled = True\n schema_entry = OrderedDict([\n ('status', status),\n ('filled', filled),\n ('info', OrderedDict([\n ('mode', value_mode),\n ('name', sanitized_key),\n ('type', value_type),\n ])),\n ])\n # yapf: enable\n return schema_entry","def use_table(self):\n connection = self._get_connection()\n cursor = connection.cursor()\n cursor.execute(\n 'select exists(select * from information_schema.tables where table_name=%s)',\n (self.table,),\n )\n if cursor.fetchone()[0]:\n self.logger.info('Using existing table')\n else:\n try:\n cursor.execute(\n f'CREATE TABLE {self.table} ( \\\n ID VARCHAR PRIMARY KEY, \\\n DOC BYTEA);'\n )\n self.logger.info('Successfully created table')\n except (Exception, psycopg2.Error) as error:\n self.logger.error('Error while creating table!')\n connection.commit()\n self._close_connection(connection)","def clean_table(self, a_schema, a_table):\n \n self._conn.execute(\"delete from %s.%s;\" %(a_schema, a_table))","def create_staging_schema(cursor,table_schema):\n create_schema = \"CREATE SCHEMA IF NOT EXISTS \" + table_schema + \";\"\n cursor.execute(create_schema)","def GetTable(self, table_id):\n for table in self.tables:\n if table.table_id == table_id:\n return table\n\n return None","def raise_exception_for_table(table_reference):\n if table_reference.table_id == non_existing_table_id:\n raise cloud.exceptions.NotFound('')","def verify_table(self):\r\n metadata = MetaData()\r\n metadata.reflect(bind = DbInsertStatusHandler.engine)\r\n mine = str(self.table.columns)\r\n verified = str(metadata.tables[self.tablename].columns)\r\n if mine != verified:\r\n raise DbException(\"Table '%s' in the database has schema %s whereas the query's schema is %s\" % (self.tablename, verified, mine))","def flatten_schema_map(\n schema_map,\n keep_nulls=False,\n sorted_schema=True,\n infer_mode=False,\n input_format='json',\n):\n if not isinstance(schema_map, dict):\n raise Exception(\n f\"Unexpected type '{type(schema_map)}' for schema_map\"\n )\n\n # Build the BigQuery schema from the internal 'schema_map'.\n schema = []\n map_items = sorted(schema_map.items()) if sorted_schema \\\n else schema_map.items()\n for name, meta in map_items:\n # Skip over fields which have been explicitly removed\n if not meta:\n continue\n\n status = meta['status']\n filled = meta['filled']\n info = meta['info']\n\n # Schema entries with a status of 'soft' are caused by 'null' or\n # empty fields. Don't print those out if the 'keep_nulls' flag is\n # False.\n if status == 'soft' and not keep_nulls:\n continue\n\n # Copy the 'info' dictionary into the schema dict, preserving the\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\n # keeps these sorted, so we created them in sorted order using an\n # OrderedDict, so they should preserve order here too.\n new_info = OrderedDict()\n for key, value in info.items():\n if key == 'fields':\n if not value:\n # Create a dummy attribute for an empty RECORD to make\n # the BigQuery importer happy.\n new_value = [\n OrderedDict([\n ('mode', 'NULLABLE'),\n ('name', '__unknown__'),\n ('type', 'STRING'),\n ])\n ]\n else:\n # Recursively flatten the sub-fields of a RECORD entry.\n new_value = flatten_schema_map(\n schema_map=value,\n keep_nulls=keep_nulls,\n sorted_schema=sorted_schema,\n infer_mode=infer_mode,\n input_format=input_format\n )\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\n new_value = value[1:]\n elif key == 'mode':\n # 'infer_mode' to set a field as REQUIRED is supported for only\n # input_format = 'csv' because the header line gives us the\n # complete list of fields to be expected in the CSV file. In\n # JSON data files, certain fields will often be completely\n # missing instead of being set to 'null' or \"\". If the field is\n # not even present, then it becomes incredibly difficult (not\n # impossible, but more effort than I want to expend right now)\n # to figure out which fields are missing so that we can mark the\n # appropriate schema entries with 'filled=False'.\n #\n # The --infer_mode option is activated only for\n # input_format == 'csv' in this function, which allows us to\n # overload the --infer_mode flag to mean that a REQUIRED mode of\n # an existing schema can transition to a NULLABLE mode.\n if (infer_mode and value == 'NULLABLE' and filled\n and input_format == 'csv'):\n new_value = 'REQUIRED'\n else:\n new_value = value\n else:\n new_value = value\n new_info[key] = new_value\n schema.append(new_info)\n return schema","def get_table_meta(self, table_name):\n table = self._metadata['tables'].get(table_name)\n if table is None:\n raise ValueError('Table \"{}\" does not exist'.format(table_name))\n\n return copy.deepcopy(table)","def decode_fusionTable_schema(tables: list) -> dict:\n def _map_col(col: dict) -> dict:\n col_schema = {k: col.get(k, '') for k in ('name', 'columnId', 'description')}\n if col['name'] != 'Comment':\n col_schema['mode'] = 'REQUIRED'\n # We can actually use int/float now!\n col_type: str = col['type']\n if col_type == 'NUMBER':\n col_type = 'INT64' if col['formatPattern'] == 'NUMBER_INTEGER' else 'FLOAT64'\n col_schema['type'] = col_type\n return col_schema\n\n def _map_table(table: dict) -> dict:\n table_schema = {k: table.get(k, '') for k in ('name', 'tableId', 'description')}\n table_schema['columns'] = list(map(_map_col, table['columns']))\n return table_schema\n\n return dict((s.get('tableId'), s) for s in map(_map_table, tables))","def read_sql_table(table_name, engine, schema=None, meta=None, index_col=None,\n coerce_float=True, parse_dates=None, columns=None,\n chunksize=None):\n if meta is None:\n meta = MetaData(engine, schema=schema)\n \n try:\n meta.reflect(only=[table_name])\n \n except exc.InvalidRequestError:\n raise ValueError(\"Table %s not found\" % table_name)\n\n pandas_sql = SQLDatabase(engine, meta=meta)\n \n table = pandas_sql.read_table(table_name, index_col=index_col, coerce_float=coerce_float,\n parse_dates=parse_dates, columns=columns, chunksize=chunksize)\n\n if table is not None:\n return table\n else:\n raise ValueError(\"Table %s not found\" % table_name, con)","def does_table_exist(table_name):\n result = call_bq(\n ['show', table_name], project='khan-academy', raise_exception=False)\n\n if \"Not found: Table\" in result:\n return False\n else:\n return True","def create_schema(cursor, connection, table):\n error_message = []\n error_rc = 0\n utils.logit(\"info\", \"In create_schema function\", 0)\n if (table == \"all\"):\n tables = tls_tables.keys()\n utils.logit(\"info\", \"Request to create entire schema\", 0)\n else:\n utils.logit(\"info\", \"Request to create table --> {}\".format(table), 0)\n tables = table if type(table) is list else [table]\n\n for table_name in tables:\n utils.logit(\"info\", \"Creating table --> {}\".format(table_name), 1)\n (create_sql, *args) = tls_tables.get(table_name, fail)(table_name)\n try:\n cursor.execute(create_sql)\n error_detail = [\"Successfully created table --> {}\".format(table_name)]\n utils.logit(\"info\", error_detail, 0)\n connection.commit()\n except Exception as e:\n error_rc += 1\n error_detail = [\"ERROR creating table --> {}\".format(table_name)]\n utils.logit(\"warning\", error_detail, 0)\n utils.logit(\"warning\", \"SQL Error --> {}\".format(e), 0)\n error_detail.append(e)\n\n # sql_stmt = cursor.mogrify(create_sql)\n utils.logit(\"info\", \"SQL Statement --> {}\".format(create_sql), 0)\n error_message.append(error_detail)\n error_message.append(create_sql)\n\n return(error_message, error_rc)","def fetch_schema(self) -> None:\n if self.schema_file:\n logger.info(\"Loaded schema from file '%s'\", self.schema_file)\n self._schema = load_schema_file(self.schema_file)\n else:\n url = self.schema_url or urljoin(self.base_url, \"schema/openapi.yaml\")\n logger.info(\"Fetching schema at '%s'\", url)\n self._schema = schema_fetcher.fetch(url, {\"v\": \"3\"})","def parse_schema(schemaurl, schema_dir=None):\n if schema_dir:\n try:\n # attempts to open .schema file in directory schema_dir\n local_schema_path = schema_dir + \"/\" + \\\n schemaurl[schemaurl.rfind('/') + 1:-1] + \".schema\"\n print \"Looking for schema in file %s\" % (local_schema_path)\n schema = json.load(open(local_schema_path))\n except Exception as e:\n print \"Couldn't load schema %s from file %s\\n%s\" % (\n schemaurl, schema_dir, str(e))\n return None\n else:\n # load the schema directly from schemaurl, i.e., from the web\n try:\n schema = json.load(urllib2.urlopen(schemaurl))\n except Exception as e:\n print \"Couldn't load schema %s\\n%s\" % (schemaurl, str(e))\n return None\n\n if 'extends' in schema and '$ref' in schema['extends']:\n\n parent_schema = json.load(urllib2.urlopen(schema['extends']['$ref']))\n while (True): # exits loop when no additional extensions (break below)\n for key in sorted(parent_schema.keys()):\n if key not in schema:\n schema[key] = parent_schema[key]\n # need to merge these keys individually\n if key == 'properties':\n for key in sorted(parent_schema['properties'].keys()):\n if key not in schema['properties']:\n schema['properties'][key] = parent_schema[\n 'properties'][key]\n if 'extends' in parent_schema:\n parent_schema = json.load(\n urllib2.urlopen(parent_schema['extends']['$ref']))\n else:\n break\n # essentially a do while loop (exit condition)\n\n return schema","def check_table(table_name = None):\n\n if table_name is None:\n table_name = config[\"default-table\"]\n\n conn, tunnel = create_db_conn()\n \n result = None\n\n try:\n cur = conn.cursor()\n cur.execute(\"\"\"\n USE %s\n \"\"\"%(config['db'], ))\n\n cur.execute(\"\"\"\n SHOW TABLES;\n \"\"\")\n \n all_tables = cur.fetchall()\n if (table_name,) in all_tables:\n result = True\n else:\n result = False\n except Exception as e:\n print(\"check_table FAILED\")\n print(e)\n\n conn.close()\n tunnel.close()\n return result","def column_to_bq_schema(self):\n kwargs = {}\n if len(self.fields) > 0:\n fields = [field.column_to_bq_schema() for field in self.fields]\n kwargs = {\"fields\": fields}\n\n return google.cloud.bigquery.SchemaField(self.name, self.dtype,\n self.mode, **kwargs)","def has_table(table_name, engine, schema=None):\n pandas_sql = SQLDatabase(engine, schema=schema, meta=None)\n return pandas_sql.has_table(table_name)","def _add_table_schema(table_desc, table_name, schema):\n table_desc['TableName'] = table_name\n table_desc['AttributeDefinitions'] = [{\n 'AttributeName': item['name'],\n 'AttributeType': DynamoStubber._encode_type(item['type'])\n } for item in schema]\n table_desc['KeySchema'] = [{\n 'AttributeName': item['name'],\n 'KeyType': item['key_type']\n } for item in schema]","def _get_or_create_table(self):\n\n table_schema = self._get_table_schema()\n try:\n table_description = self.client.create_table(**table_schema)\n logging.info('DynamoDB Table %s did not exist, creating.',self.table_name)\n\n # In case we created the table, wait until it becomes available.\n self._wait_for_table_status('ACTIVE')\n logging.info('DynamoDB Table %s is now available.',self.table_name)\n\n self.client.update_time_to_live(\n TableName=self.table_name,\n TimeToLiveSpecification={\n 'Enabled': True,\n 'AttributeName': self._expiry_field.name\n }\n )\n logging.info('DynamoDB Table %s now expires items',self.table_name)\n\n return table_description\n\n except ClientError as e:\n error_code = e.response['Error'].get('Code', 'Unknown')\n # If table exists, do not fail, just return the description.\n if error_code == 'ResourceInUseException':\n return self.client.describe_table(TableName=self.table_name)\n else:\n raise e","def getTableDefForTable(self, tableName):\n\t\tif not \".\" in tableName:\n\t\t\ttableName = \"public.\"+tableName\n\t\t\n\t\tfor row in self.readerConnection.queryToDicts(\n\t\t\t\t\"select sourcerd, tablename from dc.tablemeta where\"\n\t\t\t\t\" lower(tableName)=%(tableName)s\",\n\t\t\t\t{\"tableName\": tableName.lower()}):\n\t\t\tbreak\n\t\telse:\n\t\t\traise base.ui.logOldExc(\n\t\t\t\tbase.NotFoundError(tableName, \"table\", \"dc_tables\"))\n\n\t\treturn base.caches.getRD(row[\"sourcerd\"]\n\t\t\t).getById(row[\"tablename\"].split(\".\")[-1])","def ReadSchema(schema, bigquery_messages):\n\n return bigquery_messages.TableSchema(\n fields=[\n _TableFieldSchemaForEntry(entry, bigquery_messages)\n for entry in schema.split(',')])","def check_schema(\n self, client: Any, dataframe: DataFrame, table_name: str, database: str = None\n ) -> DataFrame:","def setup_table(table_name = None, reconstruct = False):\n \n if table_name is None:\n table_name = config[\"default-table\"]\n\n conn, tunnel = create_db_conn()\n try:\n cur = conn.cursor()\n cur.execute(\"\"\"\n USE %s\n \"\"\"%(config['db'], ))\n\n if reconstruct:\n cur.execute(\"\"\"\n DROP TABLE IF EXISTS `%s`;\n \"\"\"%(table_name,))\n cur.execute(\"\"\"CREATE TABLE `%s` (\n `id` INT UNSIGNED AUTO_INCREMENT,\n `actual value` INT UNSIGNED,\n `predict value` INT UNSIGNED,\n PRIMARY KEY(`id`)\n )\n ;\"\"\"%(table_name,))\n conn.commit()\n\n cur.execute(\"\"\"\n SHOW TABLES;\n \"\"\")\n conn.commit()\n \n all_tables = cur.fetchall()\n assert((table_name,) in all_tables)\n print(\"setup_table PASSED\")\n except Exception as e:\n print(\"setup_table FAILED\")\n print(e)\n\n conn.close()\n tunnel.close()","def init_tables(self) -> None:\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\n # it to be?\n # \"How to know that schema changes?\"\n # logger.warning(\"some message\")\n with self.table_access_condition:\n conn = self._get_connection()\n conn.execute(\"PRAGMA foreign_keys = 1\")\n with conn:\n c = conn.cursor()\n c.execute(CREATE_PROJECTS_TABLE)\n c.execute(CREATE_TASKS_TABLE)\n c.execute(CREATE_REQUESTERS_TABLE)\n c.execute(CREATE_TASK_RUNS_TABLE)\n c.execute(CREATE_ASSIGNMENTS_TABLE)\n c.execute(CREATE_UNITS_TABLE)\n c.execute(CREATE_WORKERS_TABLE)\n c.execute(CREATE_AGENTS_TABLE)\n c.execute(CREATE_QUALIFICATIONS_TABLE)\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)","def generate_bq_schema(self, file_name, schema_file_name=None):\n if not schema_file_name:\n schema_file_name = f'{self.directory}/schema_temp.json'\n os.system(f\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\")\n\n schema = open(schema_file_name, 'r').read()\n\n os.remove(schema_file_name)\n\n return json.loads(schema)","def check_if_table_exists(self, table_name):\n cursor = self.conn.cursor()\n cursor.execute(\"SELECT EXISTS(SELECT * FROM information_schema.tables WHERE table_name=%s)\", (table_name,)), \n self.conn.commit()\n return cursor.fetchone()[0]","def check_db_schema(self):\n if not self.db.get_tables():\n self.create_db_schema()","def _find_table(name):\n tables = Base.metadata.tables\n table = tables.get(name, None)\n if table is not None:\n return table\n else:\n raise NameError('Unable to locate table: %s' % name)","def get_schema(self, engine_name):\n endpoint = \"engines/{}/schema\".format(engine_name)\n return self.swiftype_session.request('get', endpoint)","def create_temporary_table(self, table_name, custom_sql, schema_name=None):\n\n ###\n # NOTE: 20200310 - The update to support snowflake transient table creation revealed several\n # import cases that are not fully handled.\n # The snowflake-related change updated behavior to allow both custom_sql and schema to be specified. But\n # the underlying incomplete handling of schema remains.\n #\n # Several cases we need to consider:\n #\n # 1. Distributed backends (e.g. Snowflake and BigQuery) often use a `<database>.<schema>.<table>`\n # syntax, but currently we are biased towards only allowing schema.table\n #\n # 2. In the wild, we see people using several ways to declare the schema they want to use:\n # a. In the connection string, the original RFC only specifies database, but schema is supported by some\n # backends (Snowflake) as a query parameter.\n # b. As a default for a user (the equivalent of USE SCHEMA being provided at the beginning of a session)\n # c. As part of individual queries.\n #\n # 3. We currently don't make it possible to select from a table in one query, but create a temporary table in\n # another schema, except for with BigQuery and (now) snowflake, where you can specify the table name (and\n # potentially triple of database, schema, table) in the batch_kwargs.\n #\n # The SqlAlchemyDataset interface essentially predates the batch_kwargs concept and so part of what's going\n # on, I think, is a mismatch between those. I think we should rename custom_sql -> \"temp_table_query\" or\n # similar, for example.\n ###\n\n engine_dialect = self.sql_engine_dialect.name.lower()\n # handle cases where dialect.name.lower() returns a byte string (e.g. databricks)\n if isinstance(engine_dialect, bytes):\n engine_dialect = str(engine_dialect, \"utf-8\")\n\n if engine_dialect == \"bigquery\":\n stmt = \"CREATE OR REPLACE VIEW `{table_name}` AS {custom_sql}\".format(\n table_name=table_name, custom_sql=custom_sql\n )\n elif engine_dialect == \"databricks\":\n stmt = \"CREATE OR REPLACE VIEW `{table_name}` AS {custom_sql}\".format(\n table_name=table_name, custom_sql=custom_sql\n )\n elif engine_dialect == \"snowflake\":\n table_type = \"TEMPORARY\" if self.generated_table_name else \"TRANSIENT\"\n\n logger.info(\"Creating temporary table %s\" % table_name)\n if schema_name is not None:\n table_name = schema_name + \".\" + table_name\n stmt = \"CREATE OR REPLACE {table_type} TABLE {table_name} AS {custom_sql}\".format(\n table_type=table_type, table_name=table_name, custom_sql=custom_sql\n )\n elif self.sql_engine_dialect.name == \"mysql\":\n # Note: We can keep the \"MySQL\" clause separate for clarity, even though it is the same as the generic case.\n stmt = \"CREATE TEMPORARY TABLE {table_name} AS {custom_sql}\".format(\n table_name=table_name, custom_sql=custom_sql\n )\n elif self.sql_engine_dialect.name == \"mssql\":\n # Insert \"into #{table_name}\" in the custom sql query right before the \"from\" clause\n # Split is case sensitive so detect case.\n # Note: transforming custom_sql to uppercase/lowercase has uninteded consequences (i.e., changing column names), so this is not an option!\n if \"from\" in custom_sql:\n strsep = \"from\"\n else:\n strsep = \"FROM\"\n custom_sqlmod = custom_sql.split(strsep, maxsplit=1)\n stmt = (\n custom_sqlmod[0] + \"into {table_name} from\" + custom_sqlmod[1]\n ).format(table_name=table_name)\n elif engine_dialect == \"awsathena\":\n stmt = \"CREATE TABLE {table_name} AS {custom_sql}\".format(\n table_name=table_name, custom_sql=custom_sql\n )\n elif engine_dialect == \"oracle\":\n stmt = \"CREATE GLOBAL TEMPORARY TABLE {table_name} ON COMMIT PRESERVE ROWS AS {custom_sql}\".format(\n table_name=table_name, custom_sql=custom_sql\n )\n else:\n stmt = 'CREATE TEMPORARY TABLE \"{table_name}\" AS {custom_sql}'.format(\n table_name=table_name, custom_sql=custom_sql\n )\n\n self.engine.execute(stmt)","def upload_table_data(client: bigquery.Client, tableRef: bigquery.Table, fusionFile: str) -> bigquery.LoadJob:\n with open(fusionFile, mode='rb') as file:\n job = client.load_table_from_file(file, tableRef)\n return job","def get_table(self, command, schema_name):\n self.log.debug(\"command:%s, schema_name:%s\" % (command, schema_name))\n if command is None:\n self.log.debug(\"No command provided: %s\" % command)\n return common.status_codes.FAILURE\n\n response = self.run_cli(command)\n if response is common.status_codes.FAILURE:\n return response\n schema_class = self.get_cli_schema_class(schema_name)\n self.set_schema_class(schema_class)\n schema_object = self.get_schema_object()\n response = self.preprocess_response(response, schema_name)\n #skip the command in response\n n = response.index('\\n')\n response = response[n:]\n schema_object.set_data_raw(response)\n\n return schema_object.table","def write_to_bq(self, \n table_name, \n file_name, \n append=True, \n ignore_unknown_values=False, \n bq_schema_autodetect=False):\n table_name = table_name.lower().replace(\"-\",\"_\")\n self.log.info(f\"Writing {table_name} to BQ from file {file_name}\")\n dataset_ref = self.bq_client.dataset(self.dataset_id)\n table_ref = dataset_ref.table(table_name)\n\n job_config = bigquery.LoadJobConfig()\n job_config.source_format = 'NEWLINE_DELIMITED_JSON'\n\n if bq_schema_autodetect == False:\n # prepare for schema manipulation\n current_tables = [x.table_id for x in self.bq_client.list_tables(dataset_ref)]\n new_schm = self.generate_bq_schema(file_name)\n\n # if table exists, edit schema. otherwise, use new_schm\n if table_name in current_tables:\t\n table = self.bq_client.get_table(table_ref)\t\n new_schm = self.merge_schemas(table.to_api_repr()['schema']['fields'], new_schm)\n\n # move new_schm into job_config through the api_repr options\n api_repr = job_config.to_api_repr()\n api_repr['load']['schema'] = {'fields': new_schm}\n job_config = job_config.from_api_repr(api_repr)\n else:\n job_config.autodetect = True\n \n # handle write options\n if append == False:\n job_config.write_disposition = \"WRITE_TRUNCATE\"\n else:\n job_config.write_disposition = \"WRITE_APPEND\"\n job_config.schema_update_options = ['ALLOW_FIELD_ADDITION']\n\n if ignore_unknown_values:\n job_config.ignore_unknown_values = True\n\n # send to BQ\n with open(file_name, 'rb') as source_file:\n job = self.bq_client.load_table_from_file(\n source_file,\n table_ref,\n job_config=job_config) # API request\n \n try:\n job.result() # Waits for table load to complete.\n except: \n self.log.info(job.errors)\n job.result()","def check_table(self, table_name: str) -> bool:\n try:\n if self.engine.dialect.has_table(self.engine.connect(), table_name):\n return self.get_input(table_name)\n return False\n except Exception as err:\n logger.error(\"check_table [error] -> %s\" % err)\n return False","def json_schema(schema_file=None, output=\"-\"):\n schemas = read_yaml(schema_file)\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))","def import_table(self,\n db_type: t.Union[DBType, str],\n table: str,\n input_file: t.Union[Path, str],\n schema: str = 'public'):\n db_type = DBType(db_type)\n db_engine = self.get_db_engine(db_type=db_type)\n input_file = Path(input_file).resolve()\n\n if not check_if_table_or_view_exists(db_engine=db_engine, table_or_view=table, schema=schema):\n raise LookupError(f\"Can't load into '{schema}.{table}' - does not exist in '{db_type.value}' db.\")\n\n import_from_csv(\n db_engine=db_engine,\n input_file=input_file,\n table=table,\n schema=schema\n )","def get_schema(self, engine, frame, name, keys=None):\n pandas_sql = SQLDatabase(engine, schema=None, meta=None)\n return pandas_sql._create_sql_schema(frame, name, keys=keys)","def get_schema(self):\n response = self.client.get(self._get_collection_url('schema'))\n\n return response.get('schema', {})","def truncateTable(self, schema, table):\r\n return self.runSql('TRUNCATE TABLE {}'.format(self.encodeTableName(schema, table)))","def _create_table_if_not_exists(self) -> None:\n COLUMN_DEFINITIONS = 'definitions'\n COLUMN_TYPE = 'type'\n\n KEY_REF = '$ref'\n\n TYPE_LOOKUP = {\n 'string': 'VARCHAR(255)',\n 'integer': 'INTEGER',\n 'boolean': 'BOOLEAN',\n 'number': 'INTEGER',\n }\n\n def ref_lookup(\n property: Dict[str, Any], fields: Dict[str, Any]\n ) -> Dict[str, Any]:\n ref = property[KEY_REF]\n property_lookup_name = ref[ref.rfind('/') + 1 :]\n return fields[COLUMN_DEFINITIONS][property_lookup_name]\n\n field_queries = []\n fields = json.loads(self.schema.schema_json())\n\n del fields[Keywords.Properties.value][\n Keywords.ID.value\n ] # Remove primary key field. It is handled with auto increment below.\n\n for property_name, property in fields[Keywords.Properties.value].items():\n if KEY_REF in property:\n property = ref_lookup(property, fields)\n field_queries.append(\n f'{property_name} {TYPE_LOOKUP[property[COLUMN_TYPE]]}'\n )\n table_columns = ', '.join(field_queries)\n\n with connect(**BaseModel.db_settings) as connection:\n cursor = connection.cursor()\n cursor.execute(\n f'CREATE TABLE IF NOT EXISTS {self.table_name} (ID INTEGER PRIMARY KEY AUTO_INCREMENT, {table_columns})'\n )\n self._table_created[self.table_name] = True","def get_table(self, table, format=\"FITS\", verbose=False):\n # make sure the table exists\n try:\n results = self.quick(\"select top 0 * from {}\".format(table),context=\"MYDB\")\n except Exception as e:\n # raise ValueError(\"table MyDB.{} not found\".format(table)) from None\n raise_from(ValueError(\"table MyDB.{} not found\".format(table)), None)\n # first try to get it as a quick request, which is much faster if it works\n try:\n return self.quick(\"select * from {}\".format(table),context=\"MYDB\",astropy=True)\n except Exception as e:\n pass\n \n # sigh, have to go through output queue\n t0 = time.time()\n format = format.upper()\n if format not in [\"FITS\",\"CSV\"]:\n # just force a good value\n format = \"FITS\"\n if verbose:\n print(\"Making output request for {}-format data\".format(format))\n job_id = self.request_output(table,format)\n status = self.monitor(job_id)\n if status[0] != 5:\n raise Exception(\"Output request failed.\")\n job_info = self.job_info(jobid=job_id)[0]\n url = job_info[\"OutputLoc\"]\n if format == \"FITS\":\n fh = fits.open(url)\n # TDIM keywords in the Casjobs FITS header are simply wrong\n # Have to delete them to avoid bad problems in astropy.io.fits\n del fh[1].header['TDIM*']\n tab = Table(fh[1].data)\n fh.close()\n else:\n r = requests.get(url)\n r.raise_for_status()\n tab = ascii.read(MastCasJobs.replacenull(r.text),format='csv')\n if verbose:\n print(\"{:.1f} s: Retrieved {} row {} table\".format(time.time()-t0,len(tab),format))\n return tab","def get_schema():\n if not os.path.isfile(_schema_file):\n create_schema()\n with open(_schema_file, 'r') as fd:\n out = decode_json(fd)\n return out","def _load_schema(self, mode=\"staging\"):\n\n self._check_mode(mode)\n\n json_path = self.table_folder / f\"schema-{mode}.json\"\n columns = self.table_config[\"columns\"]\n\n if mode == \"staging\":\n new_columns = []\n for c in columns:\n # case is_in_staging are None then must be True\n is_in_staging = (\n True if c.get(\"is_in_staging\") is None else c[\"is_in_staging\"]\n )\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\n if is_in_staging and not c.get(\"is_partition\"):\n c[\"type\"] = \"STRING\"\n new_columns.append(c)\n\n del columns\n columns = new_columns\n\n elif mode == \"prod\":\n schema = self._get_table_obj(mode).schema\n\n # get field names for fields at schema and at table_config.yaml\n column_names = [c[\"name\"] for c in columns]\n schema_names = [s.name for s in schema]\n\n # check if there are mismatched fields\n not_in_columns = [name for name in schema_names if name not in column_names]\n not_in_schema = [name for name in column_names if name not in schema_names]\n\n # raise if field is not in table_config\n if not_in_columns:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in table_config.yaml. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_columns,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # raise if field is not in schema\n if not_in_schema:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in publish.sql. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_schema,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # if field is in schema, get field_type and field_mode\n for c in columns:\n for s in schema:\n if c[\"name\"] == s.name:\n c[\"type\"] = s.field_type\n c[\"mode\"] = s.mode\n break\n ## force utf-8, write schema_{mode}.json\n json.dump(columns, (json_path).open(\"w\", encoding=\"utf-8\"))\n\n # load new created schema\n return self.client[f\"bigquery_{mode}\"].schema_from_json(str(json_path))","async def get_schema(\n self, refresh: bool = False, headers: Optional[Dict[str, str]] = None\n ) -> graphql.GraphQLSchema:\n # TODO: consider adding ttl logic for expiring schemas for long running services\n if self._schema is None or refresh:\n self._schema = await self.introspect(headers=headers)\n return self._schema","def _get_schema_using_query(self, query: str) -> sch.Schema:\n return sch.Schema.from_tuples(self._metadata(query))","def generate_url_schema():\n json_str = json.dumps({'fields': [\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\n return parse_table_schema_from_json(json_str)","def get_sql_create_table(schema, if_not_exists=False):\n if not schema.get(\"name\"):\n raise ValueError(\"no table name defined\")\n if not schema.get(\"columns\"):\n raise ValueError(\"no columns defined\")\n names = set()\n for column in schema[\"columns\"]:\n if utils.name_in_nocase(column[\"name\"], names):\n raise ValueError(\"column name %s repeated\" % column[\"name\"])\n if column[\"name\"] == \"rowid\":\n raise ValueError(\"column name 'rowid' is reserved by the system\")\n names.add(column[\"name\"])\n # Collect columns forming primary key.\n primarykey = []\n for column in schema[\"columns\"]:\n if column.get(\"primarykey\"):\n primarykey.append(column[\"name\"])\n # Column definitions, including column constraints.\n clauses = []\n for column in schema[\"columns\"]:\n coldef = [f\"\"\"\"{column['name']}\" {column['type']}\"\"\"]\n if column[\"name\"] in primarykey:\n column[\"notnull\"] = True\n if len(primarykey) == 1:\n coldef.append(\"PRIMARY KEY\")\n if column.get(\"notnull\"):\n coldef.append(\"NOT NULL\")\n clauses.append(\" \".join(coldef))\n # Primary key when more than one column.\n if len(primarykey) >= 2:\n clauses.append(\"PRIMARY KEY (%s)\" % \",\".join(['\"%s\"' for k in primarykey]))\n # Foreign keys.\n for foreignkey in schema.get(\"foreignkeys\", []):\n clauses.append(\n 'FOREIGN KEY (%s) REFERENCES \"%s\" (%s)'\n % (\n \",\".join([f'\"{c}\"' for c in foreignkey[\"columns\"]]),\n foreignkey[\"ref\"],\n \",\".join([f'\"{c}\"' for c in foreignkey[\"refcolumns\"]]),\n )\n )\n sql = [\"CREATE TABLE\"]\n if if_not_exists:\n sql.append(\"IF NOT EXISTS\")\n sql.append('\"%s\"' % schema[\"name\"])\n sql.append(\"(%s)\" % \", \".join(clauses))\n return \" \".join(sql)","def check_schema_uri(self):\n import asdf\n\n if self.schema_uri is not None:\n with log.augment_exception(\"Invalid ASDF schema URI:\", self.schema_uri):\n asdf.schema.load_schema(self.schema_uri)","def get_schema(self, schema_versions_info):\n schema = None\n version = api_version_request.APIVersionRequest(VOLUME_MICROVERSION)\n for items in schema_versions_info:\n min_version = api_version_request.APIVersionRequest(items['min'])\n max_version = api_version_request.APIVersionRequest(items['max'])\n # This is case where COMPUTE_MICROVERSION is None, which means\n # request without microversion So select base v2.1 schema.\n if version.is_null() and items['min'] is None:\n schema = items['schema']\n break\n # else select appropriate schema as per COMPUTE_MICROVERSION\n elif version.matches(min_version, max_version):\n schema = items['schema']\n break\n if schema is None:\n raise exceptions.JSONSchemaNotFound(\n version=version.get_string(),\n schema_versions_info=schema_versions_info)\n return schema","def create_table(self, schema: str, table: str, col_types: dict, non_null_columns: List[str]):\n return","def has_desired_schema(self):\n if self._new_table == self._old_table:\n if not self.rebuild:\n log.info(\"Table already has the desired schema. \")\n return True\n else:\n log.info(\n \"Table already has the desired schema. However \"\n \"--rebuild is specified, doing a rebuild instead\"\n )\n return False\n return False","def check_table_exists(self, table_name):\n query_success, query_resp = self.run_athena_query(\n query='SHOW TABLES LIKE \\'{}\\';'.format(table_name),\n database=self.DATABASE_STREAMALERT\n )\n\n if query_success and query_resp['ResultSet']['Rows']:\n return True\n\n LOGGER.info('The streamalert table \\'%s\\' does not exist. '\n 'For alert buckets, create it with the following command: \\n'\n '$ python stream_alert_cli.py athena create-table '\n '--type alerts --bucket s3.bucket.id',\n table_name)\n return False","def standardize_table_name(self, schema_name: str, table: str) -> str:\n return table","def get_schema_by_name(parent_schema, full_name):\n\n # If no proper schema was provided, return None.\n if parent_schema is None:\n return None\n\n # Find a schema in the full schema that has a full name that\n # matches the provided one.\n # If the provided schema is a union schema, search the subschemas.\n if parent_schema.type == Utils._AVRO_UNION_TYPE:\n for schema in parent_schema.schemas:\n target_schema = Utils.get_schema_by_name(schema, full_name)\n if target_schema is not None:\n return target_schema\n\n # If the provided schema has a nested record definition, search that.\n elif parent_schema.type == Utils._AVRO_RECORD_TYPE:\n\n # If our parent schema has the name we are looking for, return it.\n if parent_schema.fullname == full_name:\n return parent_schema\n\n for field in parent_schema.fields:\n # For whatever reason, the schema of a record is stored in\n # a field named type.\n schema = field.type\n target_schema = Utils.get_schema_by_name(schema, full_name)\n if target_schema is not None:\n return target_schema\n\n # If no matching schema was found, return None.\n return None","def check_schema(self, response):\n self.assertEqual(response.status_code, http.client.OK)\n result = response.json()\n url = response.links['schema']['url']\n try:\n schema = self.schemas[url]\n except KeyError:\n r = self.GET(url)\n self.assertEqual(r.status_code, http.client.OK)\n schema = r.json()\n self.schemas[url] = schema\n self.validate_schema(result, schema)\n return result","def get_default_schema(self):\n schema = self._connection.settings.get(\"schema\")\n if schema:\n res = (\n self.sql(_SELECT_SCHEMA_NAME_QUERY.format(escape(schema)))\n .execute()\n .fetch_all()\n )\n try:\n if res[0][0] == schema:\n return Schema(self, schema)\n except IndexError:\n raise ProgrammingError(\n f\"Default schema '{schema}' does not exists\"\n ) from None\n return None","def to_json_schema(dataframe_schema):\n empty = pd.DataFrame(columns=dataframe_schema.columns.keys()).astype(\n {k: v.type for k, v in dataframe_schema.dtypes.items()}\n )\n table_schema = pd.io.json.build_table_schema(empty)\n\n def _field_json_schema(field):\n return {\n \"type\": \"array\",\n \"items\": {\"type\": field[\"type\"]},\n }\n\n return {\n \"title\": dataframe_schema.name or \"pandera.DataFrameSchema\",\n \"type\": \"object\",\n \"properties\": {\n field[\"name\"]: _field_json_schema(field)\n for field in table_schema[\"fields\"]\n },\n }","def getTable(self, tablename):\n tablename = self.prefix + tablename\n if not tablename in self.tables:\n self.tables[tablename] = Table( tablename, self.metadata, \\\n autoload=True, autoload_with=self.conn )\n\n return self.tables[tablename]"],"string":"[\n \"def get_table_schema(dataset_id, table_id):\\n logging.info('getting table schema')\\n bigquery_client = bigquery.Client()\\n dataset_ref = bigquery_client.dataset(dataset_id)\\n bg_tableref = bigquery.table.TableReference(dataset_ref, table_id)\\n bg_table = bigquery_client.get_table(bg_tableref)\\n return bg_table.schema\",\n \"def fetch_table_schema(self, table_name):\\n ddl = self.query(sql.show_create_table(table_name))\\n if ddl:\\n try:\\n return parse_create(ddl[0][\\\"Create Table\\\"])\\n except ParseError as e:\\n raise OSCError(\\n \\\"TABLE_PARSING_ERROR\\\",\\n {\\\"db\\\": self._current_db, \\\"table\\\": self.table_name, \\\"msg\\\": str(e)},\\n )\",\n \"def _get_stored_schema(self, table: str) -> Optional[TableSchema]:\\n try:\\n with open(self.schemas / (table + '.json'), 'r') as f:\\n return json.load(f)\\n except FileNotFoundError:\\n return None\",\n \"def _get_table_reflection(self, schema: str, table: str) -> Table:\\n return self.sql_metadata.tables.get(f\\\"{schema}.{table}\\\",\\n Table(table, self.sql_metadata, schema=schema, autoload=True))\",\n \"def ProcessSchemaUpdate(ref, args, request):\\n table = request.table\\n relaxed_columns = args.relax_columns\\n if not table.schema and not relaxed_columns: # if not updating schema,\\n return request # then just return.\\n\\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\\n ref.Name(),\\n ref.projectId)\\n\\n new_schema_columns = table.schema\\n updated_fields = _GetUpdatedSchema(original_schema,\\n new_schema_columns,\\n relaxed_columns)\\n\\n table_schema_type = GetApiMessage('TableSchema')\\n request.table.schema = table_schema_type(fields=updated_fields)\\n\\n return request\",\n \"def CreateTableFromJson(self, table_name, schema_json):\\n try:\\n schema = json.JSONDecoder().decode(schema_json)\\n except ValueError, e:\\n raise SchemaError('Could not parse fields:\\\\n%s\\\\n%s' %\\n (schema_json, str(e)))\\n\\n conn = self._Connect()\\n result = conn.Call(\\n dict(method='bigquery.tables.insert',\\n collection='tables',\\n operation=bq.REST.INSERT,\\n params=dict(name=table_name, fields=schema)))\\n return result\",\n \"def create_tables(client: bigquery.Client, tableSchemas: dict) -> dict:\\n ds = create_dataset(client, f'FusionTable_Autoimport_{datetime.now()}')\\n\\n def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\\n \\\"\\\"\\\"Create a SchemaField from the dict\\\"\\\"\\\"\\n name = to_safe_name(col_schema['name'])\\n return bigquery.SchemaField(\\n name,\\n col_schema.get('type'),\\n col_schema.get('mode', 'NULLABLE'),\\n col_schema.get('description', '')\\n )\\n\\n def _table_from_ft(ft_schema: dict) -> bigquery.Table:\\n \\\"\\\"\\\"Create a local representation of a BigQuery table\\\"\\\"\\\"\\n # A \\\"TableSchema\\\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\\n schema = list(map(_create_field_schema, ft_schema['columns']))\\n table = bigquery.Table(\\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\\n schema\\n )\\n table.description = ft_schema.get('description', '')\\n return table\\n\\n return {\\n ftId: client.create_table(_table_from_ft(ftSchema))\\n for (ftId, ftSchema) in tableSchemas.items()\\n }\",\n \"def get_schema(self, repo, table):\\n return self.user_con.get_schema(repo=repo, table=table)\",\n \"def create_bq_table(client, dataset, table, schema):\\n \\n print('Creating table %s.%s' % (dataset, table))\\n exists = client.check_table(dataset, table)\\n if exists:\\n raise AssertionError(\\\"Table already exists: %s.%s\\\" % (dataset,table))\\n created = client.create_table(dataset, table, schema)\\n # Check that the empty table was created\\n exists = client.check_table(dataset, table)\\n if not exists:\\n raise RuntimeError('Table creation failed: %s.%s' % (dataset, table))\",\n \"def __check_table(input_table):\\n\\n try:\\n table = TABLE_TYPES[input_table]\\n return table\\n except KeyError:\\n raise InvalidTableType(input_table)\",\n \"def CreateTableFromFile(self, table_name, schema_path):\\n try:\\n schema_file = open(schema_path)\\n schema_json = schema_file.read()\\n schema_file.close()\\n except IOError, e:\\n raise SchemaError('Could not read file (%s):\\\\n%s' %\\n (schema_path, str(e)))\\n return self.CreateTableFromJson(table_name, schema_json)\",\n \"def DescribeTable(self, table_name):\\n conn = self._Connect()\\n cursor = conn.cursor()\\n return cursor.bq_get_table_metadata(table_name)\",\n \"def getTableSchema(self,tableName):\\n\\tif not self.schemaDict.has_key(tableName):\\n\\t if self.dbType==\\\"sqlite\\\":\\n\\t query = \\\"SELECT * FROM sqlite_master WHERE name='%s'\\\"%tableName\\n\\t tup = self.fetchOne(query)\\n\\t schema= tup[4]\\n\\t else: # MySQL \\n\\t query = \\\"DESCRIBE %s\\\"%tableName\\n\\t tup = self.fetchAll(query)\\n\\t schema= \\\"CREATE TABLE %s (\\\"%tableName\\n\\t for item in tup:\\n\\t name = item[0]\\n\\t\\t type = item[1]\\n\\t\\t priKey = item[3]\\n\\t\\t autoInc = item[5] \\n\\t schema+=name+' '+type+' '+priKey+' '+autoInc\\n\\t\\t if item!=tup[-1]:\\n\\t\\t schema+=','\\n\\t schema+=\\\" )\\\"\\n\\t return schema\\n\\telse:\\n\\t return self.schemaDict[tableName]\",\n \"def _table_from_ft(ft_schema: dict) -> bigquery.Table:\\n # A \\\"TableSchema\\\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\\n schema = list(map(_create_field_schema, ft_schema['columns']))\\n table = bigquery.Table(\\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\\n schema\\n )\\n table.description = ft_schema.get('description', '')\\n return table\",\n \"def get_schema(db, sourcename):\\n try:\\n schema = db[\\\"tables\\\"][sourcename]\\n schema[\\\"type\\\"] = constants.TABLE\\n except KeyError:\\n try:\\n schema = db[\\\"views\\\"][sourcename]\\n schema[\\\"type\\\"] = constants.VIEW\\n except KeyError:\\n raise ValueError(\\\"no such table/view\\\")\\n return schema\",\n \"def get_tables_in_schema(self, conn, schema_name):\\n return conn.get_tables(schema_name)['table_name']\",\n \"def _get_table_schema(self):\\n\\n return {\\n 'AttributeDefinitions': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'AttributeType': self._key_field.data_type\\n }\\n ],\\n 'TableName': self.table_name,\\n 'KeySchema': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'KeyType': 'HASH'\\n }\\n ],\\n 'ProvisionedThroughput': {\\n 'ReadCapacityUnits': self.read_capacity_units,\\n 'WriteCapacityUnits': self.write_capacity_units\\n }\\n }\",\n \"def get_table_definition(jwt_payload: dict, schema_name: str, table_name: str):\\n DJConnector.set_datajoint_config(jwt_payload)\\n\\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\\n return getattr(schema_virtual_module, table_name).describe()\",\n \"def _create_table_if_not_exists(self) -> bigquery.Table:\\n table = self.client.create_table(\\n table=bigquery.Table(table_ref=self._table_ref, schema=Schema),\\n exists_ok=True,\\n )\\n logging.info(\\\"table %s already exists.\\\", table.full_table_id)\\n return table\",\n \"def getTableSchema(self, lsstLevel, dbName, tableName):\\n return self._doRequest(self.httpClient.getTableSchema, lsstLevel, dbName, tableName)\",\n \"def schema(self) -> 'outputs.TableSchemaResponse':\\n return pulumi.get(self, \\\"schema\\\")\",\n \"def get_schema(self, get_stats=False):\\n query = \\\"schema {}\\\"\\n\\n results = self.run_dgraph_query_raw(query)\\n\\n schema = {}\\n\\n for row in results[\\\"schema\\\"]:\\n table_name = row[\\\"predicate\\\"]\\n\\n if table_name not in schema:\\n schema[table_name] = {\\\"name\\\": table_name, \\\"columns\\\": []}\\n\\n return list(schema.values())\",\n \"def schema_ref(schema, table):\\n return schema + '.' + table\",\n \"def get_table_exists(schema_name, table_name):\\n sql = (\\\"SELECT * FROM sys.objects so JOIN sys.schemas ss on (so.schema_id = ss.schema_id) \\\"\\n \\\"WHERE so.type = 'U' AND so.name = ? and ss.name = ?\\\")\\n\\n row = fetch_row(sql, [table_name, schema_name])\\n\\n return True if row else False\",\n \"def ensure_schema(client, table_name):\\n query = ''.join([\\n 'CREATE TABLE {cf} ',\\n '(\\\"lockId\\\" ascii, \\\"claimId\\\" timeuuid, PRIMARY KEY(\\\"lockId\\\", \\\"claimId\\\"));'])\\n\\n def errback(failure):\\n failure.trap(InvalidRequestException)\\n\\n return client.execute(query.format(cf=table_name),\\n {}, ConsistencyLevel.QUORUM).addErrback(errback)\",\n \"def BqTableSchemaFileProcessor(file_arg):\\n table_schema_type = GetApiMessage('TableSchema')\\n schema_field_type = GetApiMessage('TableFieldSchema')\\n\\n try:\\n schema_json = yaml.load(file_arg)\\n schema_json = schema_json.get('schema', None)\\n\\n if not schema_json or not isinstance(schema_json, list):\\n raise SchemaFileError(\\n 'Error parsing schema file: no schema field list defined in file')\\n\\n all_fields = []\\n for field in schema_json:\\n new_field = schema_field_type(name=field['name'],\\n type=field['type'],\\n mode=field.get('mode', 'NULLABLE'))\\n all_fields.append(new_field)\\n\\n return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))\\n except yaml.YAMLParseError as ype:\\n raise SchemaFileError('Error parsing schema file [{}]'.format(ype))\\n except (AttributeError, KeyError) as e:\\n raise SchemaFileError(\\n 'Error parsing schema file, invalid field definition [{}]'.format(e))\",\n \"def validate_table(self, table, table_struct, verbose=True):\\n \\n assert(self.connected)\\n try: \\n assert(self.check_table(table, verbose=False)) \\n except AssertionError: \\n raise TableNotFoundError\\n \\n GET_SCHEMA_INFORMATION_COMMAND = \\\"SELECT ORDINAL_POSITION, COLUMN_NAME, COLUMN_TYPE, IS_NULLABLE, COLUMN_KEY, EXTRA \\\" \\\\\\n \\t \\\"FROM INFORMATION_SCHEMA.COLUMNS \\\" \\\\\\n \\t \\\"WHERE TABLE_NAME='{0}' ORDER BY ORDINAL_POSITION\\\".format(table)\\n \\n GET_SCHEMA_FK_INFORMATION_COMMAND = \\\"SELECT COLUMN_NAME, CONSTRAINT_NAME, REFERENCED_TABLE_NAME, REFERENCED_COLUMN_NAME \\\" \\\\\\n \\\"FROM INFORMATION_SCHEMA.KEY_COLUMN_USAGE \\\" \\\\\\n \\\"WHERE REFERENCED_TABLE_SCHEMA = '{0}' AND TABLE_NAME = '{1}' AND COLUMN_NAME = '{2}'\\\"\\n \\n CHANGE_TYPE_COMMAND = \\\"ALTER TABLE {0} MODIFY {1} {2} {3}\\\"\\n \\n ADD_FK_COMMAND = \\\"ALTER TABLE {0} ADD FOREIGN KEY ({1}) REFERENCES {2}({3})\\\" \\n \\n DROP_FK_CONSTRAINT_COMMAND = \\\"ALTER TABLE {0} DROP FOREIGN KEY {1}\\\" \\n \\n \\n self.cursor.execute(GET_SCHEMA_INFORMATION_COMMAND)\\n \\n # load all column info from the database \\n columns = {}\\n for c in self.cursor:\\n columns[c[1]] = c\\n \\n for column,db_col in zip(table_struct,columns):\\n \\n # load parameter values from the DB \\n (ord_pos, name, col_type, isnull, key_type, extra) = columns[db_col]\\n \\n isnull = isnull == 'YES'\\n auto_increment = extra == 'auto_increment'\\n foreign_key = key_type == 'MUL'\\n \\n # parse new parameter values\\n struct_type = table_struct[column][0]\\n parameters = table_struct[column][1] if ( len(table_struct[column]) > 1) else None\\n \\n # get parameters values in boolean format\\n if (parameters == None):\\n new_isnull = True\\n new_auto_increment = False\\n new_foreign_key = False\\n else:\\n if 'not_null' in parameters: new_isnull = not parameters['not_null']\\n else: new_isnull = True\\n \\n if 'auto_increment' in parameters: new_auto_increment = parameters['auto_increment']\\n else: new_auto_increment = False\\n \\n if 'foreign_key' in parameters: new_foreign_key = parameters['foreign_key']\\n else: new_foreign_key = False\\n \\n \\n \\n \\n if verbose: \\n print(\\\"\\\\n---\\\\n\\\\nChecking column '{0}'...\\\".format(column))\\n \\n # check name, type and each parameter \\n if name == column:\\n \\n # if something doesn't match, change within the database\\n if ( col_type != struct_type ): \\n if verbose:\\n print(\\\"Column '{0}' found in the correct position with the incorrect type.\\\".format(column))\\n print(\\\"Changing the type of '{0}' from '{1}' to '{2}'\\\".format(column, col_type, struct_type),)\\n \\n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), '')\\n \\n if verbose: print(\\\"\\\\t\\\" + cmd)\\n \\n self.cursor.execute(cmd) \\n \\n if ( isnull != new_isnull ):\\n \\n if verbose:\\n print(\\\"Column '{0}' found in the correct position an incorrect parameter.\\\".format(column))\\n print(\\\"Changing the type of '{0}' from '{1}' to '{2}'\\\".format(column, \\\"NOT NULLABLE\\\" if new_isnull else \\\"NULLABLE\\\", \\\"NULLABLE\\\" if new_isnull else \\\"NOT NULLABLE\\\"))\\n \\n \\n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), \\\"NOT NULL\\\" if not new_isnull else \\\"\\\" )\\n \\n if verbose: print(\\\"\\\\t\\\" + cmd)\\n \\n \\n self.cursor.execute(cmd)\\n \\n if ( auto_increment != new_auto_increment ):\\n \\n if verbose:\\n print(\\\"Column '{0}' found in the correct position an incorrect parameter.\\\".format(column))\\n print(\\\"Changing the type of '{0}' from '{1}' to '{2}'\\\".format(column, \\\"AUTO INCREMENT\\\" if new_auto_increment else \\\"none\\\", \\\"none\\\" if new_auto_increment else \\\"AUTO INCREMENT\\\"))\\n \\n \\n cmd = CHANGE_TYPE_COMMAND.format(table, column, struct_type.upper(), \\\"AUTO INCREMENT\\\" if new_auto_increment else \\\"\\\" )\\n \\n if verbose: print(\\\"\\\\t\\\" + cmd)\\n \\n \\n self.cursor.execute(cmd)\\n \\n \\n if ( foreign_key != new_foreign_key ):\\n \\n \\n if verbose:\\n print(\\\"Column '{0}' found in the correct position an incorrect parameter.\\\".format(column))\\n print(\\\"Changing the type of '{0}' from '{1}' to '{2}'\\\".format(column, \\\"FOREIGN KEY\\\" if new_auto_increment else \\\"none\\\", \\\"none\\\" if new_auto_increment else \\\"FOREIGN KEY\\\"))\\n \\n \\n \\n if ('foreign_key' in parameters and parameters['foreign_key']):\\n \\n referenced_table = parameters['references'].split('(')[0]\\n referenced_column = parameters['references'].split('(')[1][:-1] \\n \\n \\n if (not self.check_table(referenced_table, verbose=False)):\\n raise(TableNotFoundError)\\n \\n \\n if (not self.check_column(referenced_column, referenced_table, verbose=False)):\\n raise(ColumnNotFoundError)\\n \\n \\n cmd = ADD_FK_COMMAND.format(table,column,referenced_table, referenced_column)\\n\\n \\n \\n if verbose: print(\\\"\\\\t\\\" + cmd)\\n \\n try:\\n self.cursor.execute(cmd) \\n except:\\n print(\\\" > Error: Cannot add foreign key constraint to column '{0}' in the table '{1}'. You must remove all data from\\\\n > this column using the clear_column() command first.\\\".format(column, table))\\n \\n else:\\n \\n # check if column has a foreign key constraint\\n \\n cmd = GET_SCHEMA_FK_INFORMATION_COMMAND.format(self.config['database'], table, column)\\n \\n self.cursor.execute(cmd)\\n \\n fk_name = None\\n for row in self.cursor:\\n fk_name = row[1]\\n break\\n \\n if fk_name != None:\\n cmd = DROP_FK_CONSTRAINT_COMMAND.format(table, fk_name)\\n \\n if verbose: \\n print(\\\"Column '{0}' involved in foreign key constraint '{1}'\\\".format(column, fk_name))\\n print(\\\"Dropping foreign key constraint '{0}'\\\".format(fk_name))\\n print(\\\"\\\\t\\\" + cmd)\\n \\n self.cursor.execute(cmd)\\n\\n \\n \\n if verbose: print(\\\"Done.\\\")\\n \\n \\n if (len(columns) > len(table_struct)):\\n \\n if verbose: print(\\\"\\\\n---\\\\n\\\\nExtra columns found in database\\\")\\n \\n for col in columns:\\n if (col not in table_struct): \\n \\n if verbose:\\n print(\\\"Column '{0}' found in the database but not found in the configuration.\\\".format(col))\\n \\n self.delete_column(col, table)\\n \\n \\n elif(len(table_struct) > len(columns)):\\n \\n if verbose: print(\\\"\\\\n---\\\\n\\\\nExtra columns found in configuration. \\\")\\n\\n for col in table_struct:\\n if col not in columns:\\n if verbose: print(\\\"Column '{0}' found in configuration but not in database\\\".format(col))\\n self.insert_column(col, table_struct[col][0], table, params = table_struct[col][1] if ( len(table_struct[col]) > 1) else None)\",\n \"def _load_bigquery_schemas(self):\\n logger.info(\\\"Reading BigQuery schema files...\\\")\\n for table_name in self.tables + self.type_tables:\\n logger.info(f\\\"Reading schema file for table '{table_name}'...\\\")\\n schema_json = resource_stream('sotorrent_pipeline',\\n f'bigquery_schemas/{table_name}.json').read().decode()\\n self.bigquery_schemas[table_name] = json.loads(schema_json)\\n self.bigquery_schemas_with_fields[table_name] = json.loads('{\\\"fields\\\":' + schema_json + '}')\\n logger.info(f\\\"Read {len(self.bigquery_schemas)} schema file(s).\\\")\",\n \"def is_table_exist(table_name: str, schema: str) -> str:\\n\\n return f\\\"\\\"\\\"\\n SELECT\\n table_name\\n FROM\\n information_schema.tables\\n WHERE\\n table_name = '{table_name}' AND\\n table_schema='{schema}'\\n LIMIT 1\\n \\\"\\\"\\\"\",\n \"def read_schema_from_db(cur, table):\\n num_rows = cur.execute(\\\"\\\"\\\"DESCRIBE {}\\\"\\\"\\\".format(table))\\n tbl_schema = []\\n for i in range(num_rows):\\n row = cur.fetchone()\\n tbl_schema.append([row[0], row[1]])\\n return tbl_schema\",\n \"def delete_bq_table(client, dataset, table):\\n \\n exists = client.check_table(dataset, table)\\n if exists:\\n print('WARNING: Deleting existing table %s.%s' % (dataset, table))\\n deleted = client.delete_table(dataset, table)\\n if not deleted:\\n raise RuntimeError('Table deletion failed: %s.%s' % (dataset, table))\",\n \"def get_schemas(self, conn):\\n return conn.get_schemas()['table_schema']\",\n \"async def schema_state(appname, schema, table):\\n base = sprout.cfg.db_str(appname)\\n con = await asyncpg.connect(base)\\n req = ', '.join([\\n 'table_catalog',\\n 'table_schema',\\n 'table_name',\\n 'column_name',\\n 'data_type'\\n ])\\n q = f\\\"\\\"\\\"select {req} from information_schema.columns\\nwhere table_schema='{schema}' and table_name='{table}';\\\"\\\"\\\"\\n try:\\n ret = await con.fetch(q)\\n df = pd.DataFrame.from_records(ret, columns=ret[0].keys())\\n return df\\n except Exception as e:\\n sprout.cfg.log.error(f\\\"fetching current table state failed: {e}\\\")\\n finally:\\n await con.close()\",\n \"def ReadSchemaFile(schema_file, bigquery_messages):\\n\\n if os.path.exists(schema_file):\\n with open(schema_file, mode='r') as f:\\n try:\\n def UpperOrNone(string):\\n return string and string.upper()\\n field_schemas = [\\n bigquery_messages.TableFieldSchema(\\n name=json_object.get('name'),\\n type=json_object.get('type').upper(),\\n mode=UpperOrNone(json_object.get('mode')))\\n for json_object in json.load(f)]\\n return bigquery_messages.TableSchema(fields=field_schemas)\\n except ValueError as e:\\n raise bigquery.SchemaError(\\n 'Error decoding JSON schema from file {0}: {1}.'.format(\\n schema_file, e))\\n else:\\n raise bigquery.SchemaError(\\n 'Error reading schema: File \\\"{0}\\\" was not found.'.format(schema_file))\",\n \"def table_reference(self) -> 'outputs.PreventionJobTriggerInspectJobStorageConfigBigQueryOptionsTableReference':\\n return pulumi.get(self, \\\"table_reference\\\")\",\n \"async def add_table(self, table: TableSchema) -> None:\\n name = table['name']\\n if not self._schema_valid_prod(table):\\n if self.update_schema: # Interactively create or upgrade table schema\\n stored_schema = self._get_stored_schema(name)\\n if stored_schema: # Generate migrations from previous schema\\n table, requests = update_table_schema(stored_schema, table)\\n self._create_migration(table, requests)\\n self._schema_write(table) # Write new schema to disk\\n elif self.prod_mode: # Crash if production mode is on\\n raise MigrationException(f\\\"in prod, and table {name} has outdated schema\\\")\\n\\n current_level = await self._get_migration_level(name)\\n if current_level is None: # New table\\n self._new_table_queue.append(table)\\n elif self._needs_migrations(name, current_level): # Needs migration\\n self._migration_queue.append(table)\\n # else: no need to do anything for this table\",\n \"def _TryDeleteTable(dataset_id, table_id, project_id):\\n client = GetApiClient()\\n service = client.tables\\n delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')\\n delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,\\n projectId=project_id)\\n service.Delete(delete_request)\\n log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id))\",\n \"def schema(self):\\n return self.table_info.schema\",\n \"def _TableExists(dataset_id, table_id, project_id):\\n client = GetApiClient()\\n service = client.tables\\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\\n get_request = get_request_type(datasetId=dataset_id, tableId=table_id,\\n projectId=project_id)\\n try:\\n service.Get(get_request)\\n return True\\n except apitools_exceptions.HttpNotFoundError:\\n log.info('Table with id [{}:{}:{}] not found.'.format(\\n project_id, dataset_id, table_id))\\n\\n return False\",\n \"def verify_table(self):\\n metadata = MetaData()\\n metadata.reflect(bind = StatusSource.engine)\\n mine = str(self.table.columns)\\n verified = str(metadata.tables[self.tablename].columns)\\n if mine != verified:\\n raise DbException(\\\"Table '%s' in the database has schema %s whereas the query's schema is %s\\\" % (self.tablename, verified, mine))\",\n \"def tableExists(self, schema, table):\\r\\n r = self.fetchSqlRecords(\\r\\n \\\"SELECT to_regclass('{}.{}')\\\".format(schema, table))\\r\\n return r[0][0]\",\n \"def get_schema_entry(self, key, value, base_path=None):\\n value_mode, value_type = self.infer_bigquery_type(value)\\n if not value_mode or not value_type:\\n return None\\n sanitized_key = self.sanitize_name(key)\\n\\n # yapf: disable\\n if value_type == 'RECORD':\\n new_base_path = json_full_path(base_path, key)\\n # recursively figure out the RECORD\\n fields = OrderedDict()\\n if value_mode == 'NULLABLE':\\n self.deduce_schema_for_record(\\n json_object=value,\\n schema_map=fields,\\n base_path=new_base_path,\\n )\\n else:\\n for val in value:\\n self.deduce_schema_for_record(\\n json_object=val,\\n schema_map=fields,\\n base_path=new_base_path,\\n )\\n\\n schema_entry = OrderedDict([\\n ('status', 'hard'),\\n ('filled', True),\\n ('info', OrderedDict([\\n ('fields', fields),\\n ('mode', value_mode),\\n ('name', sanitized_key),\\n ('type', value_type),\\n ])),\\n ])\\n elif value_type == '__null__':\\n schema_entry = OrderedDict([\\n ('status', 'soft'),\\n ('filled', False),\\n ('info', OrderedDict([\\n ('mode', 'NULLABLE'),\\n ('name', sanitized_key),\\n ('type', 'STRING'),\\n ])),\\n ])\\n elif value_type == '__empty_array__':\\n schema_entry = OrderedDict([\\n ('status', 'soft'),\\n ('filled', False),\\n ('info', OrderedDict([\\n ('mode', 'REPEATED'),\\n ('name', sanitized_key),\\n ('type', 'STRING'),\\n ])),\\n ])\\n elif value_type == '__empty_record__':\\n schema_entry = OrderedDict([\\n ('status', 'soft'),\\n ('filled', False),\\n ('info', OrderedDict([\\n ('fields', OrderedDict()),\\n ('mode', value_mode),\\n ('name', sanitized_key),\\n ('type', 'RECORD'),\\n ])),\\n ])\\n else:\\n # Empty fields are returned as empty strings, and must be treated as\\n # a (soft String) to allow clobbering by subsquent non-empty fields.\\n if value == \\\"\\\" and self.input_format == 'csv':\\n status = 'soft'\\n filled = False\\n else:\\n status = 'hard'\\n filled = True\\n schema_entry = OrderedDict([\\n ('status', status),\\n ('filled', filled),\\n ('info', OrderedDict([\\n ('mode', value_mode),\\n ('name', sanitized_key),\\n ('type', value_type),\\n ])),\\n ])\\n # yapf: enable\\n return schema_entry\",\n \"def use_table(self):\\n connection = self._get_connection()\\n cursor = connection.cursor()\\n cursor.execute(\\n 'select exists(select * from information_schema.tables where table_name=%s)',\\n (self.table,),\\n )\\n if cursor.fetchone()[0]:\\n self.logger.info('Using existing table')\\n else:\\n try:\\n cursor.execute(\\n f'CREATE TABLE {self.table} ( \\\\\\n ID VARCHAR PRIMARY KEY, \\\\\\n DOC BYTEA);'\\n )\\n self.logger.info('Successfully created table')\\n except (Exception, psycopg2.Error) as error:\\n self.logger.error('Error while creating table!')\\n connection.commit()\\n self._close_connection(connection)\",\n \"def clean_table(self, a_schema, a_table):\\n \\n self._conn.execute(\\\"delete from %s.%s;\\\" %(a_schema, a_table))\",\n \"def create_staging_schema(cursor,table_schema):\\n create_schema = \\\"CREATE SCHEMA IF NOT EXISTS \\\" + table_schema + \\\";\\\"\\n cursor.execute(create_schema)\",\n \"def GetTable(self, table_id):\\n for table in self.tables:\\n if table.table_id == table_id:\\n return table\\n\\n return None\",\n \"def raise_exception_for_table(table_reference):\\n if table_reference.table_id == non_existing_table_id:\\n raise cloud.exceptions.NotFound('')\",\n \"def verify_table(self):\\r\\n metadata = MetaData()\\r\\n metadata.reflect(bind = DbInsertStatusHandler.engine)\\r\\n mine = str(self.table.columns)\\r\\n verified = str(metadata.tables[self.tablename].columns)\\r\\n if mine != verified:\\r\\n raise DbException(\\\"Table '%s' in the database has schema %s whereas the query's schema is %s\\\" % (self.tablename, verified, mine))\",\n \"def flatten_schema_map(\\n schema_map,\\n keep_nulls=False,\\n sorted_schema=True,\\n infer_mode=False,\\n input_format='json',\\n):\\n if not isinstance(schema_map, dict):\\n raise Exception(\\n f\\\"Unexpected type '{type(schema_map)}' for schema_map\\\"\\n )\\n\\n # Build the BigQuery schema from the internal 'schema_map'.\\n schema = []\\n map_items = sorted(schema_map.items()) if sorted_schema \\\\\\n else schema_map.items()\\n for name, meta in map_items:\\n # Skip over fields which have been explicitly removed\\n if not meta:\\n continue\\n\\n status = meta['status']\\n filled = meta['filled']\\n info = meta['info']\\n\\n # Schema entries with a status of 'soft' are caused by 'null' or\\n # empty fields. Don't print those out if the 'keep_nulls' flag is\\n # False.\\n if status == 'soft' and not keep_nulls:\\n continue\\n\\n # Copy the 'info' dictionary into the schema dict, preserving the\\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\\n # keeps these sorted, so we created them in sorted order using an\\n # OrderedDict, so they should preserve order here too.\\n new_info = OrderedDict()\\n for key, value in info.items():\\n if key == 'fields':\\n if not value:\\n # Create a dummy attribute for an empty RECORD to make\\n # the BigQuery importer happy.\\n new_value = [\\n OrderedDict([\\n ('mode', 'NULLABLE'),\\n ('name', '__unknown__'),\\n ('type', 'STRING'),\\n ])\\n ]\\n else:\\n # Recursively flatten the sub-fields of a RECORD entry.\\n new_value = flatten_schema_map(\\n schema_map=value,\\n keep_nulls=keep_nulls,\\n sorted_schema=sorted_schema,\\n infer_mode=infer_mode,\\n input_format=input_format\\n )\\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\\n new_value = value[1:]\\n elif key == 'mode':\\n # 'infer_mode' to set a field as REQUIRED is supported for only\\n # input_format = 'csv' because the header line gives us the\\n # complete list of fields to be expected in the CSV file. In\\n # JSON data files, certain fields will often be completely\\n # missing instead of being set to 'null' or \\\"\\\". If the field is\\n # not even present, then it becomes incredibly difficult (not\\n # impossible, but more effort than I want to expend right now)\\n # to figure out which fields are missing so that we can mark the\\n # appropriate schema entries with 'filled=False'.\\n #\\n # The --infer_mode option is activated only for\\n # input_format == 'csv' in this function, which allows us to\\n # overload the --infer_mode flag to mean that a REQUIRED mode of\\n # an existing schema can transition to a NULLABLE mode.\\n if (infer_mode and value == 'NULLABLE' and filled\\n and input_format == 'csv'):\\n new_value = 'REQUIRED'\\n else:\\n new_value = value\\n else:\\n new_value = value\\n new_info[key] = new_value\\n schema.append(new_info)\\n return schema\",\n \"def get_table_meta(self, table_name):\\n table = self._metadata['tables'].get(table_name)\\n if table is None:\\n raise ValueError('Table \\\"{}\\\" does not exist'.format(table_name))\\n\\n return copy.deepcopy(table)\",\n \"def decode_fusionTable_schema(tables: list) -> dict:\\n def _map_col(col: dict) -> dict:\\n col_schema = {k: col.get(k, '') for k in ('name', 'columnId', 'description')}\\n if col['name'] != 'Comment':\\n col_schema['mode'] = 'REQUIRED'\\n # We can actually use int/float now!\\n col_type: str = col['type']\\n if col_type == 'NUMBER':\\n col_type = 'INT64' if col['formatPattern'] == 'NUMBER_INTEGER' else 'FLOAT64'\\n col_schema['type'] = col_type\\n return col_schema\\n\\n def _map_table(table: dict) -> dict:\\n table_schema = {k: table.get(k, '') for k in ('name', 'tableId', 'description')}\\n table_schema['columns'] = list(map(_map_col, table['columns']))\\n return table_schema\\n\\n return dict((s.get('tableId'), s) for s in map(_map_table, tables))\",\n \"def read_sql_table(table_name, engine, schema=None, meta=None, index_col=None,\\n coerce_float=True, parse_dates=None, columns=None,\\n chunksize=None):\\n if meta is None:\\n meta = MetaData(engine, schema=schema)\\n \\n try:\\n meta.reflect(only=[table_name])\\n \\n except exc.InvalidRequestError:\\n raise ValueError(\\\"Table %s not found\\\" % table_name)\\n\\n pandas_sql = SQLDatabase(engine, meta=meta)\\n \\n table = pandas_sql.read_table(table_name, index_col=index_col, coerce_float=coerce_float,\\n parse_dates=parse_dates, columns=columns, chunksize=chunksize)\\n\\n if table is not None:\\n return table\\n else:\\n raise ValueError(\\\"Table %s not found\\\" % table_name, con)\",\n \"def does_table_exist(table_name):\\n result = call_bq(\\n ['show', table_name], project='khan-academy', raise_exception=False)\\n\\n if \\\"Not found: Table\\\" in result:\\n return False\\n else:\\n return True\",\n \"def create_schema(cursor, connection, table):\\n error_message = []\\n error_rc = 0\\n utils.logit(\\\"info\\\", \\\"In create_schema function\\\", 0)\\n if (table == \\\"all\\\"):\\n tables = tls_tables.keys()\\n utils.logit(\\\"info\\\", \\\"Request to create entire schema\\\", 0)\\n else:\\n utils.logit(\\\"info\\\", \\\"Request to create table --> {}\\\".format(table), 0)\\n tables = table if type(table) is list else [table]\\n\\n for table_name in tables:\\n utils.logit(\\\"info\\\", \\\"Creating table --> {}\\\".format(table_name), 1)\\n (create_sql, *args) = tls_tables.get(table_name, fail)(table_name)\\n try:\\n cursor.execute(create_sql)\\n error_detail = [\\\"Successfully created table --> {}\\\".format(table_name)]\\n utils.logit(\\\"info\\\", error_detail, 0)\\n connection.commit()\\n except Exception as e:\\n error_rc += 1\\n error_detail = [\\\"ERROR creating table --> {}\\\".format(table_name)]\\n utils.logit(\\\"warning\\\", error_detail, 0)\\n utils.logit(\\\"warning\\\", \\\"SQL Error --> {}\\\".format(e), 0)\\n error_detail.append(e)\\n\\n # sql_stmt = cursor.mogrify(create_sql)\\n utils.logit(\\\"info\\\", \\\"SQL Statement --> {}\\\".format(create_sql), 0)\\n error_message.append(error_detail)\\n error_message.append(create_sql)\\n\\n return(error_message, error_rc)\",\n \"def fetch_schema(self) -> None:\\n if self.schema_file:\\n logger.info(\\\"Loaded schema from file '%s'\\\", self.schema_file)\\n self._schema = load_schema_file(self.schema_file)\\n else:\\n url = self.schema_url or urljoin(self.base_url, \\\"schema/openapi.yaml\\\")\\n logger.info(\\\"Fetching schema at '%s'\\\", url)\\n self._schema = schema_fetcher.fetch(url, {\\\"v\\\": \\\"3\\\"})\",\n \"def parse_schema(schemaurl, schema_dir=None):\\n if schema_dir:\\n try:\\n # attempts to open .schema file in directory schema_dir\\n local_schema_path = schema_dir + \\\"/\\\" + \\\\\\n schemaurl[schemaurl.rfind('/') + 1:-1] + \\\".schema\\\"\\n print \\\"Looking for schema in file %s\\\" % (local_schema_path)\\n schema = json.load(open(local_schema_path))\\n except Exception as e:\\n print \\\"Couldn't load schema %s from file %s\\\\n%s\\\" % (\\n schemaurl, schema_dir, str(e))\\n return None\\n else:\\n # load the schema directly from schemaurl, i.e., from the web\\n try:\\n schema = json.load(urllib2.urlopen(schemaurl))\\n except Exception as e:\\n print \\\"Couldn't load schema %s\\\\n%s\\\" % (schemaurl, str(e))\\n return None\\n\\n if 'extends' in schema and '$ref' in schema['extends']:\\n\\n parent_schema = json.load(urllib2.urlopen(schema['extends']['$ref']))\\n while (True): # exits loop when no additional extensions (break below)\\n for key in sorted(parent_schema.keys()):\\n if key not in schema:\\n schema[key] = parent_schema[key]\\n # need to merge these keys individually\\n if key == 'properties':\\n for key in sorted(parent_schema['properties'].keys()):\\n if key not in schema['properties']:\\n schema['properties'][key] = parent_schema[\\n 'properties'][key]\\n if 'extends' in parent_schema:\\n parent_schema = json.load(\\n urllib2.urlopen(parent_schema['extends']['$ref']))\\n else:\\n break\\n # essentially a do while loop (exit condition)\\n\\n return schema\",\n \"def check_table(table_name = None):\\n\\n if table_name is None:\\n table_name = config[\\\"default-table\\\"]\\n\\n conn, tunnel = create_db_conn()\\n \\n result = None\\n\\n try:\\n cur = conn.cursor()\\n cur.execute(\\\"\\\"\\\"\\n USE %s\\n \\\"\\\"\\\"%(config['db'], ))\\n\\n cur.execute(\\\"\\\"\\\"\\n SHOW TABLES;\\n \\\"\\\"\\\")\\n \\n all_tables = cur.fetchall()\\n if (table_name,) in all_tables:\\n result = True\\n else:\\n result = False\\n except Exception as e:\\n print(\\\"check_table FAILED\\\")\\n print(e)\\n\\n conn.close()\\n tunnel.close()\\n return result\",\n \"def column_to_bq_schema(self):\\n kwargs = {}\\n if len(self.fields) > 0:\\n fields = [field.column_to_bq_schema() for field in self.fields]\\n kwargs = {\\\"fields\\\": fields}\\n\\n return google.cloud.bigquery.SchemaField(self.name, self.dtype,\\n self.mode, **kwargs)\",\n \"def has_table(table_name, engine, schema=None):\\n pandas_sql = SQLDatabase(engine, schema=schema, meta=None)\\n return pandas_sql.has_table(table_name)\",\n \"def _add_table_schema(table_desc, table_name, schema):\\n table_desc['TableName'] = table_name\\n table_desc['AttributeDefinitions'] = [{\\n 'AttributeName': item['name'],\\n 'AttributeType': DynamoStubber._encode_type(item['type'])\\n } for item in schema]\\n table_desc['KeySchema'] = [{\\n 'AttributeName': item['name'],\\n 'KeyType': item['key_type']\\n } for item in schema]\",\n \"def _get_or_create_table(self):\\n\\n table_schema = self._get_table_schema()\\n try:\\n table_description = self.client.create_table(**table_schema)\\n logging.info('DynamoDB Table %s did not exist, creating.',self.table_name)\\n\\n # In case we created the table, wait until it becomes available.\\n self._wait_for_table_status('ACTIVE')\\n logging.info('DynamoDB Table %s is now available.',self.table_name)\\n\\n self.client.update_time_to_live(\\n TableName=self.table_name,\\n TimeToLiveSpecification={\\n 'Enabled': True,\\n 'AttributeName': self._expiry_field.name\\n }\\n )\\n logging.info('DynamoDB Table %s now expires items',self.table_name)\\n\\n return table_description\\n\\n except ClientError as e:\\n error_code = e.response['Error'].get('Code', 'Unknown')\\n # If table exists, do not fail, just return the description.\\n if error_code == 'ResourceInUseException':\\n return self.client.describe_table(TableName=self.table_name)\\n else:\\n raise e\",\n \"def getTableDefForTable(self, tableName):\\n\\t\\tif not \\\".\\\" in tableName:\\n\\t\\t\\ttableName = \\\"public.\\\"+tableName\\n\\t\\t\\n\\t\\tfor row in self.readerConnection.queryToDicts(\\n\\t\\t\\t\\t\\\"select sourcerd, tablename from dc.tablemeta where\\\"\\n\\t\\t\\t\\t\\\" lower(tableName)=%(tableName)s\\\",\\n\\t\\t\\t\\t{\\\"tableName\\\": tableName.lower()}):\\n\\t\\t\\tbreak\\n\\t\\telse:\\n\\t\\t\\traise base.ui.logOldExc(\\n\\t\\t\\t\\tbase.NotFoundError(tableName, \\\"table\\\", \\\"dc_tables\\\"))\\n\\n\\t\\treturn base.caches.getRD(row[\\\"sourcerd\\\"]\\n\\t\\t\\t).getById(row[\\\"tablename\\\"].split(\\\".\\\")[-1])\",\n \"def ReadSchema(schema, bigquery_messages):\\n\\n return bigquery_messages.TableSchema(\\n fields=[\\n _TableFieldSchemaForEntry(entry, bigquery_messages)\\n for entry in schema.split(',')])\",\n \"def check_schema(\\n self, client: Any, dataframe: DataFrame, table_name: str, database: str = None\\n ) -> DataFrame:\",\n \"def setup_table(table_name = None, reconstruct = False):\\n \\n if table_name is None:\\n table_name = config[\\\"default-table\\\"]\\n\\n conn, tunnel = create_db_conn()\\n try:\\n cur = conn.cursor()\\n cur.execute(\\\"\\\"\\\"\\n USE %s\\n \\\"\\\"\\\"%(config['db'], ))\\n\\n if reconstruct:\\n cur.execute(\\\"\\\"\\\"\\n DROP TABLE IF EXISTS `%s`;\\n \\\"\\\"\\\"%(table_name,))\\n cur.execute(\\\"\\\"\\\"CREATE TABLE `%s` (\\n `id` INT UNSIGNED AUTO_INCREMENT,\\n `actual value` INT UNSIGNED,\\n `predict value` INT UNSIGNED,\\n PRIMARY KEY(`id`)\\n )\\n ;\\\"\\\"\\\"%(table_name,))\\n conn.commit()\\n\\n cur.execute(\\\"\\\"\\\"\\n SHOW TABLES;\\n \\\"\\\"\\\")\\n conn.commit()\\n \\n all_tables = cur.fetchall()\\n assert((table_name,) in all_tables)\\n print(\\\"setup_table PASSED\\\")\\n except Exception as e:\\n print(\\\"setup_table FAILED\\\")\\n print(e)\\n\\n conn.close()\\n tunnel.close()\",\n \"def init_tables(self) -> None:\\n # TODO(#93) maybe raise flag when the schema of existing tables isn't what we expect\\n # it to be?\\n # \\\"How to know that schema changes?\\\"\\n # logger.warning(\\\"some message\\\")\\n with self.table_access_condition:\\n conn = self._get_connection()\\n conn.execute(\\\"PRAGMA foreign_keys = 1\\\")\\n with conn:\\n c = conn.cursor()\\n c.execute(CREATE_PROJECTS_TABLE)\\n c.execute(CREATE_TASKS_TABLE)\\n c.execute(CREATE_REQUESTERS_TABLE)\\n c.execute(CREATE_TASK_RUNS_TABLE)\\n c.execute(CREATE_ASSIGNMENTS_TABLE)\\n c.execute(CREATE_UNITS_TABLE)\\n c.execute(CREATE_WORKERS_TABLE)\\n c.execute(CREATE_AGENTS_TABLE)\\n c.execute(CREATE_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_GRANTED_QUALIFICATIONS_TABLE)\\n c.execute(CREATE_ONBOARDING_AGENTS_TABLE)\",\n \"def generate_bq_schema(self, file_name, schema_file_name=None):\\n if not schema_file_name:\\n schema_file_name = f'{self.directory}/schema_temp.json'\\n os.system(f\\\"generate-schema --keep_nulls < {file_name} > {schema_file_name}\\\")\\n\\n schema = open(schema_file_name, 'r').read()\\n\\n os.remove(schema_file_name)\\n\\n return json.loads(schema)\",\n \"def check_if_table_exists(self, table_name):\\n cursor = self.conn.cursor()\\n cursor.execute(\\\"SELECT EXISTS(SELECT * FROM information_schema.tables WHERE table_name=%s)\\\", (table_name,)), \\n self.conn.commit()\\n return cursor.fetchone()[0]\",\n \"def check_db_schema(self):\\n if not self.db.get_tables():\\n self.create_db_schema()\",\n \"def _find_table(name):\\n tables = Base.metadata.tables\\n table = tables.get(name, None)\\n if table is not None:\\n return table\\n else:\\n raise NameError('Unable to locate table: %s' % name)\",\n \"def get_schema(self, engine_name):\\n endpoint = \\\"engines/{}/schema\\\".format(engine_name)\\n return self.swiftype_session.request('get', endpoint)\",\n \"def create_temporary_table(self, table_name, custom_sql, schema_name=None):\\n\\n ###\\n # NOTE: 20200310 - The update to support snowflake transient table creation revealed several\\n # import cases that are not fully handled.\\n # The snowflake-related change updated behavior to allow both custom_sql and schema to be specified. But\\n # the underlying incomplete handling of schema remains.\\n #\\n # Several cases we need to consider:\\n #\\n # 1. Distributed backends (e.g. Snowflake and BigQuery) often use a `<database>.<schema>.<table>`\\n # syntax, but currently we are biased towards only allowing schema.table\\n #\\n # 2. In the wild, we see people using several ways to declare the schema they want to use:\\n # a. In the connection string, the original RFC only specifies database, but schema is supported by some\\n # backends (Snowflake) as a query parameter.\\n # b. As a default for a user (the equivalent of USE SCHEMA being provided at the beginning of a session)\\n # c. As part of individual queries.\\n #\\n # 3. We currently don't make it possible to select from a table in one query, but create a temporary table in\\n # another schema, except for with BigQuery and (now) snowflake, where you can specify the table name (and\\n # potentially triple of database, schema, table) in the batch_kwargs.\\n #\\n # The SqlAlchemyDataset interface essentially predates the batch_kwargs concept and so part of what's going\\n # on, I think, is a mismatch between those. I think we should rename custom_sql -> \\\"temp_table_query\\\" or\\n # similar, for example.\\n ###\\n\\n engine_dialect = self.sql_engine_dialect.name.lower()\\n # handle cases where dialect.name.lower() returns a byte string (e.g. databricks)\\n if isinstance(engine_dialect, bytes):\\n engine_dialect = str(engine_dialect, \\\"utf-8\\\")\\n\\n if engine_dialect == \\\"bigquery\\\":\\n stmt = \\\"CREATE OR REPLACE VIEW `{table_name}` AS {custom_sql}\\\".format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n elif engine_dialect == \\\"databricks\\\":\\n stmt = \\\"CREATE OR REPLACE VIEW `{table_name}` AS {custom_sql}\\\".format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n elif engine_dialect == \\\"snowflake\\\":\\n table_type = \\\"TEMPORARY\\\" if self.generated_table_name else \\\"TRANSIENT\\\"\\n\\n logger.info(\\\"Creating temporary table %s\\\" % table_name)\\n if schema_name is not None:\\n table_name = schema_name + \\\".\\\" + table_name\\n stmt = \\\"CREATE OR REPLACE {table_type} TABLE {table_name} AS {custom_sql}\\\".format(\\n table_type=table_type, table_name=table_name, custom_sql=custom_sql\\n )\\n elif self.sql_engine_dialect.name == \\\"mysql\\\":\\n # Note: We can keep the \\\"MySQL\\\" clause separate for clarity, even though it is the same as the generic case.\\n stmt = \\\"CREATE TEMPORARY TABLE {table_name} AS {custom_sql}\\\".format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n elif self.sql_engine_dialect.name == \\\"mssql\\\":\\n # Insert \\\"into #{table_name}\\\" in the custom sql query right before the \\\"from\\\" clause\\n # Split is case sensitive so detect case.\\n # Note: transforming custom_sql to uppercase/lowercase has uninteded consequences (i.e., changing column names), so this is not an option!\\n if \\\"from\\\" in custom_sql:\\n strsep = \\\"from\\\"\\n else:\\n strsep = \\\"FROM\\\"\\n custom_sqlmod = custom_sql.split(strsep, maxsplit=1)\\n stmt = (\\n custom_sqlmod[0] + \\\"into {table_name} from\\\" + custom_sqlmod[1]\\n ).format(table_name=table_name)\\n elif engine_dialect == \\\"awsathena\\\":\\n stmt = \\\"CREATE TABLE {table_name} AS {custom_sql}\\\".format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n elif engine_dialect == \\\"oracle\\\":\\n stmt = \\\"CREATE GLOBAL TEMPORARY TABLE {table_name} ON COMMIT PRESERVE ROWS AS {custom_sql}\\\".format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n else:\\n stmt = 'CREATE TEMPORARY TABLE \\\"{table_name}\\\" AS {custom_sql}'.format(\\n table_name=table_name, custom_sql=custom_sql\\n )\\n\\n self.engine.execute(stmt)\",\n \"def upload_table_data(client: bigquery.Client, tableRef: bigquery.Table, fusionFile: str) -> bigquery.LoadJob:\\n with open(fusionFile, mode='rb') as file:\\n job = client.load_table_from_file(file, tableRef)\\n return job\",\n \"def get_table(self, command, schema_name):\\n self.log.debug(\\\"command:%s, schema_name:%s\\\" % (command, schema_name))\\n if command is None:\\n self.log.debug(\\\"No command provided: %s\\\" % command)\\n return common.status_codes.FAILURE\\n\\n response = self.run_cli(command)\\n if response is common.status_codes.FAILURE:\\n return response\\n schema_class = self.get_cli_schema_class(schema_name)\\n self.set_schema_class(schema_class)\\n schema_object = self.get_schema_object()\\n response = self.preprocess_response(response, schema_name)\\n #skip the command in response\\n n = response.index('\\\\n')\\n response = response[n:]\\n schema_object.set_data_raw(response)\\n\\n return schema_object.table\",\n \"def write_to_bq(self, \\n table_name, \\n file_name, \\n append=True, \\n ignore_unknown_values=False, \\n bq_schema_autodetect=False):\\n table_name = table_name.lower().replace(\\\"-\\\",\\\"_\\\")\\n self.log.info(f\\\"Writing {table_name} to BQ from file {file_name}\\\")\\n dataset_ref = self.bq_client.dataset(self.dataset_id)\\n table_ref = dataset_ref.table(table_name)\\n\\n job_config = bigquery.LoadJobConfig()\\n job_config.source_format = 'NEWLINE_DELIMITED_JSON'\\n\\n if bq_schema_autodetect == False:\\n # prepare for schema manipulation\\n current_tables = [x.table_id for x in self.bq_client.list_tables(dataset_ref)]\\n new_schm = self.generate_bq_schema(file_name)\\n\\n # if table exists, edit schema. otherwise, use new_schm\\n if table_name in current_tables:\\t\\n table = self.bq_client.get_table(table_ref)\\t\\n new_schm = self.merge_schemas(table.to_api_repr()['schema']['fields'], new_schm)\\n\\n # move new_schm into job_config through the api_repr options\\n api_repr = job_config.to_api_repr()\\n api_repr['load']['schema'] = {'fields': new_schm}\\n job_config = job_config.from_api_repr(api_repr)\\n else:\\n job_config.autodetect = True\\n \\n # handle write options\\n if append == False:\\n job_config.write_disposition = \\\"WRITE_TRUNCATE\\\"\\n else:\\n job_config.write_disposition = \\\"WRITE_APPEND\\\"\\n job_config.schema_update_options = ['ALLOW_FIELD_ADDITION']\\n\\n if ignore_unknown_values:\\n job_config.ignore_unknown_values = True\\n\\n # send to BQ\\n with open(file_name, 'rb') as source_file:\\n job = self.bq_client.load_table_from_file(\\n source_file,\\n table_ref,\\n job_config=job_config) # API request\\n \\n try:\\n job.result() # Waits for table load to complete.\\n except: \\n self.log.info(job.errors)\\n job.result()\",\n \"def check_table(self, table_name: str) -> bool:\\n try:\\n if self.engine.dialect.has_table(self.engine.connect(), table_name):\\n return self.get_input(table_name)\\n return False\\n except Exception as err:\\n logger.error(\\\"check_table [error] -> %s\\\" % err)\\n return False\",\n \"def json_schema(schema_file=None, output=\\\"-\\\"):\\n schemas = read_yaml(schema_file)\\n dump_yaml(output, JsonSchemaConverterFromAccessSchema.convert_schemas(schemas))\",\n \"def import_table(self,\\n db_type: t.Union[DBType, str],\\n table: str,\\n input_file: t.Union[Path, str],\\n schema: str = 'public'):\\n db_type = DBType(db_type)\\n db_engine = self.get_db_engine(db_type=db_type)\\n input_file = Path(input_file).resolve()\\n\\n if not check_if_table_or_view_exists(db_engine=db_engine, table_or_view=table, schema=schema):\\n raise LookupError(f\\\"Can't load into '{schema}.{table}' - does not exist in '{db_type.value}' db.\\\")\\n\\n import_from_csv(\\n db_engine=db_engine,\\n input_file=input_file,\\n table=table,\\n schema=schema\\n )\",\n \"def get_schema(self, engine, frame, name, keys=None):\\n pandas_sql = SQLDatabase(engine, schema=None, meta=None)\\n return pandas_sql._create_sql_schema(frame, name, keys=keys)\",\n \"def get_schema(self):\\n response = self.client.get(self._get_collection_url('schema'))\\n\\n return response.get('schema', {})\",\n \"def truncateTable(self, schema, table):\\r\\n return self.runSql('TRUNCATE TABLE {}'.format(self.encodeTableName(schema, table)))\",\n \"def _create_table_if_not_exists(self) -> None:\\n COLUMN_DEFINITIONS = 'definitions'\\n COLUMN_TYPE = 'type'\\n\\n KEY_REF = '$ref'\\n\\n TYPE_LOOKUP = {\\n 'string': 'VARCHAR(255)',\\n 'integer': 'INTEGER',\\n 'boolean': 'BOOLEAN',\\n 'number': 'INTEGER',\\n }\\n\\n def ref_lookup(\\n property: Dict[str, Any], fields: Dict[str, Any]\\n ) -> Dict[str, Any]:\\n ref = property[KEY_REF]\\n property_lookup_name = ref[ref.rfind('/') + 1 :]\\n return fields[COLUMN_DEFINITIONS][property_lookup_name]\\n\\n field_queries = []\\n fields = json.loads(self.schema.schema_json())\\n\\n del fields[Keywords.Properties.value][\\n Keywords.ID.value\\n ] # Remove primary key field. It is handled with auto increment below.\\n\\n for property_name, property in fields[Keywords.Properties.value].items():\\n if KEY_REF in property:\\n property = ref_lookup(property, fields)\\n field_queries.append(\\n f'{property_name} {TYPE_LOOKUP[property[COLUMN_TYPE]]}'\\n )\\n table_columns = ', '.join(field_queries)\\n\\n with connect(**BaseModel.db_settings) as connection:\\n cursor = connection.cursor()\\n cursor.execute(\\n f'CREATE TABLE IF NOT EXISTS {self.table_name} (ID INTEGER PRIMARY KEY AUTO_INCREMENT, {table_columns})'\\n )\\n self._table_created[self.table_name] = True\",\n \"def get_table(self, table, format=\\\"FITS\\\", verbose=False):\\n # make sure the table exists\\n try:\\n results = self.quick(\\\"select top 0 * from {}\\\".format(table),context=\\\"MYDB\\\")\\n except Exception as e:\\n # raise ValueError(\\\"table MyDB.{} not found\\\".format(table)) from None\\n raise_from(ValueError(\\\"table MyDB.{} not found\\\".format(table)), None)\\n # first try to get it as a quick request, which is much faster if it works\\n try:\\n return self.quick(\\\"select * from {}\\\".format(table),context=\\\"MYDB\\\",astropy=True)\\n except Exception as e:\\n pass\\n \\n # sigh, have to go through output queue\\n t0 = time.time()\\n format = format.upper()\\n if format not in [\\\"FITS\\\",\\\"CSV\\\"]:\\n # just force a good value\\n format = \\\"FITS\\\"\\n if verbose:\\n print(\\\"Making output request for {}-format data\\\".format(format))\\n job_id = self.request_output(table,format)\\n status = self.monitor(job_id)\\n if status[0] != 5:\\n raise Exception(\\\"Output request failed.\\\")\\n job_info = self.job_info(jobid=job_id)[0]\\n url = job_info[\\\"OutputLoc\\\"]\\n if format == \\\"FITS\\\":\\n fh = fits.open(url)\\n # TDIM keywords in the Casjobs FITS header are simply wrong\\n # Have to delete them to avoid bad problems in astropy.io.fits\\n del fh[1].header['TDIM*']\\n tab = Table(fh[1].data)\\n fh.close()\\n else:\\n r = requests.get(url)\\n r.raise_for_status()\\n tab = ascii.read(MastCasJobs.replacenull(r.text),format='csv')\\n if verbose:\\n print(\\\"{:.1f} s: Retrieved {} row {} table\\\".format(time.time()-t0,len(tab),format))\\n return tab\",\n \"def get_schema():\\n if not os.path.isfile(_schema_file):\\n create_schema()\\n with open(_schema_file, 'r') as fd:\\n out = decode_json(fd)\\n return out\",\n \"def _load_schema(self, mode=\\\"staging\\\"):\\n\\n self._check_mode(mode)\\n\\n json_path = self.table_folder / f\\\"schema-{mode}.json\\\"\\n columns = self.table_config[\\\"columns\\\"]\\n\\n if mode == \\\"staging\\\":\\n new_columns = []\\n for c in columns:\\n # case is_in_staging are None then must be True\\n is_in_staging = (\\n True if c.get(\\\"is_in_staging\\\") is None else c[\\\"is_in_staging\\\"]\\n )\\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\\n if is_in_staging and not c.get(\\\"is_partition\\\"):\\n c[\\\"type\\\"] = \\\"STRING\\\"\\n new_columns.append(c)\\n\\n del columns\\n columns = new_columns\\n\\n elif mode == \\\"prod\\\":\\n schema = self._get_table_obj(mode).schema\\n\\n # get field names for fields at schema and at table_config.yaml\\n column_names = [c[\\\"name\\\"] for c in columns]\\n schema_names = [s.name for s in schema]\\n\\n # check if there are mismatched fields\\n not_in_columns = [name for name in schema_names if name not in column_names]\\n not_in_schema = [name for name in column_names if name not in schema_names]\\n\\n # raise if field is not in table_config\\n if not_in_columns:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in table_config.yaml. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_columns,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # raise if field is not in schema\\n if not_in_schema:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in publish.sql. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_schema,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # if field is in schema, get field_type and field_mode\\n for c in columns:\\n for s in schema:\\n if c[\\\"name\\\"] == s.name:\\n c[\\\"type\\\"] = s.field_type\\n c[\\\"mode\\\"] = s.mode\\n break\\n ## force utf-8, write schema_{mode}.json\\n json.dump(columns, (json_path).open(\\\"w\\\", encoding=\\\"utf-8\\\"))\\n\\n # load new created schema\\n return self.client[f\\\"bigquery_{mode}\\\"].schema_from_json(str(json_path))\",\n \"async def get_schema(\\n self, refresh: bool = False, headers: Optional[Dict[str, str]] = None\\n ) -> graphql.GraphQLSchema:\\n # TODO: consider adding ttl logic for expiring schemas for long running services\\n if self._schema is None or refresh:\\n self._schema = await self.introspect(headers=headers)\\n return self._schema\",\n \"def _get_schema_using_query(self, query: str) -> sch.Schema:\\n return sch.Schema.from_tuples(self._metadata(query))\",\n \"def generate_url_schema():\\n json_str = json.dumps({'fields': [\\n {'name': 'url', 'type': 'STRING', 'mode': 'NULLABLE'},\\n {'name': 'count', 'type': 'INTEGER', 'mode': 'NULLABLE'},\\n {'name': 'ts', 'type': 'TIMESTAMP', 'mode': 'NULLABLE'}]})\\n return parse_table_schema_from_json(json_str)\",\n \"def get_sql_create_table(schema, if_not_exists=False):\\n if not schema.get(\\\"name\\\"):\\n raise ValueError(\\\"no table name defined\\\")\\n if not schema.get(\\\"columns\\\"):\\n raise ValueError(\\\"no columns defined\\\")\\n names = set()\\n for column in schema[\\\"columns\\\"]:\\n if utils.name_in_nocase(column[\\\"name\\\"], names):\\n raise ValueError(\\\"column name %s repeated\\\" % column[\\\"name\\\"])\\n if column[\\\"name\\\"] == \\\"rowid\\\":\\n raise ValueError(\\\"column name 'rowid' is reserved by the system\\\")\\n names.add(column[\\\"name\\\"])\\n # Collect columns forming primary key.\\n primarykey = []\\n for column in schema[\\\"columns\\\"]:\\n if column.get(\\\"primarykey\\\"):\\n primarykey.append(column[\\\"name\\\"])\\n # Column definitions, including column constraints.\\n clauses = []\\n for column in schema[\\\"columns\\\"]:\\n coldef = [f\\\"\\\"\\\"\\\"{column['name']}\\\" {column['type']}\\\"\\\"\\\"]\\n if column[\\\"name\\\"] in primarykey:\\n column[\\\"notnull\\\"] = True\\n if len(primarykey) == 1:\\n coldef.append(\\\"PRIMARY KEY\\\")\\n if column.get(\\\"notnull\\\"):\\n coldef.append(\\\"NOT NULL\\\")\\n clauses.append(\\\" \\\".join(coldef))\\n # Primary key when more than one column.\\n if len(primarykey) >= 2:\\n clauses.append(\\\"PRIMARY KEY (%s)\\\" % \\\",\\\".join(['\\\"%s\\\"' for k in primarykey]))\\n # Foreign keys.\\n for foreignkey in schema.get(\\\"foreignkeys\\\", []):\\n clauses.append(\\n 'FOREIGN KEY (%s) REFERENCES \\\"%s\\\" (%s)'\\n % (\\n \\\",\\\".join([f'\\\"{c}\\\"' for c in foreignkey[\\\"columns\\\"]]),\\n foreignkey[\\\"ref\\\"],\\n \\\",\\\".join([f'\\\"{c}\\\"' for c in foreignkey[\\\"refcolumns\\\"]]),\\n )\\n )\\n sql = [\\\"CREATE TABLE\\\"]\\n if if_not_exists:\\n sql.append(\\\"IF NOT EXISTS\\\")\\n sql.append('\\\"%s\\\"' % schema[\\\"name\\\"])\\n sql.append(\\\"(%s)\\\" % \\\", \\\".join(clauses))\\n return \\\" \\\".join(sql)\",\n \"def check_schema_uri(self):\\n import asdf\\n\\n if self.schema_uri is not None:\\n with log.augment_exception(\\\"Invalid ASDF schema URI:\\\", self.schema_uri):\\n asdf.schema.load_schema(self.schema_uri)\",\n \"def get_schema(self, schema_versions_info):\\n schema = None\\n version = api_version_request.APIVersionRequest(VOLUME_MICROVERSION)\\n for items in schema_versions_info:\\n min_version = api_version_request.APIVersionRequest(items['min'])\\n max_version = api_version_request.APIVersionRequest(items['max'])\\n # This is case where COMPUTE_MICROVERSION is None, which means\\n # request without microversion So select base v2.1 schema.\\n if version.is_null() and items['min'] is None:\\n schema = items['schema']\\n break\\n # else select appropriate schema as per COMPUTE_MICROVERSION\\n elif version.matches(min_version, max_version):\\n schema = items['schema']\\n break\\n if schema is None:\\n raise exceptions.JSONSchemaNotFound(\\n version=version.get_string(),\\n schema_versions_info=schema_versions_info)\\n return schema\",\n \"def create_table(self, schema: str, table: str, col_types: dict, non_null_columns: List[str]):\\n return\",\n \"def has_desired_schema(self):\\n if self._new_table == self._old_table:\\n if not self.rebuild:\\n log.info(\\\"Table already has the desired schema. \\\")\\n return True\\n else:\\n log.info(\\n \\\"Table already has the desired schema. However \\\"\\n \\\"--rebuild is specified, doing a rebuild instead\\\"\\n )\\n return False\\n return False\",\n \"def check_table_exists(self, table_name):\\n query_success, query_resp = self.run_athena_query(\\n query='SHOW TABLES LIKE \\\\'{}\\\\';'.format(table_name),\\n database=self.DATABASE_STREAMALERT\\n )\\n\\n if query_success and query_resp['ResultSet']['Rows']:\\n return True\\n\\n LOGGER.info('The streamalert table \\\\'%s\\\\' does not exist. '\\n 'For alert buckets, create it with the following command: \\\\n'\\n '$ python stream_alert_cli.py athena create-table '\\n '--type alerts --bucket s3.bucket.id',\\n table_name)\\n return False\",\n \"def standardize_table_name(self, schema_name: str, table: str) -> str:\\n return table\",\n \"def get_schema_by_name(parent_schema, full_name):\\n\\n # If no proper schema was provided, return None.\\n if parent_schema is None:\\n return None\\n\\n # Find a schema in the full schema that has a full name that\\n # matches the provided one.\\n # If the provided schema is a union schema, search the subschemas.\\n if parent_schema.type == Utils._AVRO_UNION_TYPE:\\n for schema in parent_schema.schemas:\\n target_schema = Utils.get_schema_by_name(schema, full_name)\\n if target_schema is not None:\\n return target_schema\\n\\n # If the provided schema has a nested record definition, search that.\\n elif parent_schema.type == Utils._AVRO_RECORD_TYPE:\\n\\n # If our parent schema has the name we are looking for, return it.\\n if parent_schema.fullname == full_name:\\n return parent_schema\\n\\n for field in parent_schema.fields:\\n # For whatever reason, the schema of a record is stored in\\n # a field named type.\\n schema = field.type\\n target_schema = Utils.get_schema_by_name(schema, full_name)\\n if target_schema is not None:\\n return target_schema\\n\\n # If no matching schema was found, return None.\\n return None\",\n \"def check_schema(self, response):\\n self.assertEqual(response.status_code, http.client.OK)\\n result = response.json()\\n url = response.links['schema']['url']\\n try:\\n schema = self.schemas[url]\\n except KeyError:\\n r = self.GET(url)\\n self.assertEqual(r.status_code, http.client.OK)\\n schema = r.json()\\n self.schemas[url] = schema\\n self.validate_schema(result, schema)\\n return result\",\n \"def get_default_schema(self):\\n schema = self._connection.settings.get(\\\"schema\\\")\\n if schema:\\n res = (\\n self.sql(_SELECT_SCHEMA_NAME_QUERY.format(escape(schema)))\\n .execute()\\n .fetch_all()\\n )\\n try:\\n if res[0][0] == schema:\\n return Schema(self, schema)\\n except IndexError:\\n raise ProgrammingError(\\n f\\\"Default schema '{schema}' does not exists\\\"\\n ) from None\\n return None\",\n \"def to_json_schema(dataframe_schema):\\n empty = pd.DataFrame(columns=dataframe_schema.columns.keys()).astype(\\n {k: v.type for k, v in dataframe_schema.dtypes.items()}\\n )\\n table_schema = pd.io.json.build_table_schema(empty)\\n\\n def _field_json_schema(field):\\n return {\\n \\\"type\\\": \\\"array\\\",\\n \\\"items\\\": {\\\"type\\\": field[\\\"type\\\"]},\\n }\\n\\n return {\\n \\\"title\\\": dataframe_schema.name or \\\"pandera.DataFrameSchema\\\",\\n \\\"type\\\": \\\"object\\\",\\n \\\"properties\\\": {\\n field[\\\"name\\\"]: _field_json_schema(field)\\n for field in table_schema[\\\"fields\\\"]\\n },\\n }\",\n \"def getTable(self, tablename):\\n tablename = self.prefix + tablename\\n if not tablename in self.tables:\\n self.tables[tablename] = Table( tablename, self.metadata, \\\\\\n autoload=True, autoload_with=self.conn )\\n\\n return self.tables[tablename]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.73889893","0.6379297","0.6305416","0.6051959","0.58043814","0.57696646","0.56733495","0.5627315","0.5534374","0.5378048","0.5363961","0.53382576","0.5309689","0.5298764","0.5259146","0.52387893","0.52369916","0.52243495","0.52111673","0.5200395","0.5174603","0.5162272","0.5160721","0.51297754","0.5118883","0.5115819","0.5082074","0.5081547","0.50572026","0.5016008","0.498506","0.49842352","0.49795562","0.49772573","0.49673092","0.491708","0.4915413","0.4913952","0.4895537","0.4884174","0.4873055","0.48575428","0.48561898","0.4832509","0.48121166","0.4802197","0.47910953","0.47888026","0.47582287","0.47488788","0.47448787","0.47356552","0.4732936","0.47316298","0.47284755","0.47191116","0.4717631","0.47126135","0.46999872","0.46964434","0.46911573","0.46806735","0.4666518","0.46501893","0.4640006","0.4635662","0.46354452","0.46347308","0.46346077","0.46314654","0.46275786","0.46191004","0.4615498","0.4600725","0.4593944","0.4592192","0.4581459","0.45786935","0.45763713","0.45721313","0.45705548","0.45664695","0.45610282","0.45532814","0.45438793","0.45363635","0.4511637","0.44847524","0.44781804","0.44760057","0.44756955","0.44748446","0.44651833","0.4457048","0.44540232","0.44483903","0.44442904","0.44186062","0.4416051","0.44065487"],"string":"[\n \"0.73889893\",\n \"0.6379297\",\n \"0.6305416\",\n \"0.6051959\",\n \"0.58043814\",\n \"0.57696646\",\n \"0.56733495\",\n \"0.5627315\",\n \"0.5534374\",\n \"0.5378048\",\n \"0.5363961\",\n \"0.53382576\",\n \"0.5309689\",\n \"0.5298764\",\n \"0.5259146\",\n \"0.52387893\",\n \"0.52369916\",\n \"0.52243495\",\n \"0.52111673\",\n \"0.5200395\",\n \"0.5174603\",\n \"0.5162272\",\n \"0.5160721\",\n \"0.51297754\",\n \"0.5118883\",\n \"0.5115819\",\n \"0.5082074\",\n \"0.5081547\",\n \"0.50572026\",\n \"0.5016008\",\n \"0.498506\",\n \"0.49842352\",\n \"0.49795562\",\n \"0.49772573\",\n \"0.49673092\",\n \"0.491708\",\n \"0.4915413\",\n \"0.4913952\",\n \"0.4895537\",\n \"0.4884174\",\n \"0.4873055\",\n \"0.48575428\",\n \"0.48561898\",\n \"0.4832509\",\n \"0.48121166\",\n \"0.4802197\",\n \"0.47910953\",\n \"0.47888026\",\n \"0.47582287\",\n \"0.47488788\",\n \"0.47448787\",\n \"0.47356552\",\n \"0.4732936\",\n \"0.47316298\",\n \"0.47284755\",\n \"0.47191116\",\n \"0.4717631\",\n \"0.47126135\",\n \"0.46999872\",\n \"0.46964434\",\n \"0.46911573\",\n \"0.46806735\",\n \"0.4666518\",\n \"0.46501893\",\n \"0.4640006\",\n \"0.4635662\",\n \"0.46354452\",\n \"0.46347308\",\n \"0.46346077\",\n \"0.46314654\",\n \"0.46275786\",\n \"0.46191004\",\n \"0.4615498\",\n \"0.4600725\",\n \"0.4593944\",\n \"0.4592192\",\n \"0.4581459\",\n \"0.45786935\",\n \"0.45763713\",\n \"0.45721313\",\n \"0.45705548\",\n \"0.45664695\",\n \"0.45610282\",\n \"0.45532814\",\n \"0.45438793\",\n \"0.45363635\",\n \"0.4511637\",\n \"0.44847524\",\n \"0.44781804\",\n \"0.44760057\",\n \"0.44756955\",\n \"0.44748446\",\n \"0.44651833\",\n \"0.4457048\",\n \"0.44540232\",\n \"0.44483903\",\n \"0.44442904\",\n \"0.44186062\",\n \"0.4416051\",\n \"0.44065487\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.74110204"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2289,"cells":{"query":{"kind":"string","value":"Update original_schema by adding and/or relaxing mode on columns."},"document":{"kind":"string","value":"def _GetUpdatedSchema(\n original_schema,\n new_columns=None,\n relaxed_columns=None):\n orig_field_map = (\n {f.name: f for f in original_schema.fields} if original_schema else {})\n\n if relaxed_columns:\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\n\n if new_columns:\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\n\n return sorted(orig_field_map.values(), key=lambda x: x.name)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _GetRelaxedCols(relaxed_columns, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for col in relaxed_columns:\n if col in orig_schema_map:\n updated_schema_map[col].mode = 'NULLABLE'\n else:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n return updated_schema_map","async def upgradeSchema(self) -> None:","def ProcessSchemaUpdate(ref, args, request):\n table = request.table\n relaxed_columns = args.relax_columns\n if not table.schema and not relaxed_columns: # if not updating schema,\n return request # then just return.\n\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\n ref.Name(),\n ref.projectId)\n\n new_schema_columns = table.schema\n updated_fields = _GetUpdatedSchema(original_schema,\n new_schema_columns,\n relaxed_columns)\n\n table_schema_type = GetApiMessage('TableSchema')\n request.table.schema = table_schema_type(fields=updated_fields)\n\n return request","def _add_to_schema(self, new: dict):\n self._defaults.update(new)\n self._migrate()","def update_schema(self, new_schema):\n return self.conn.update_schema(new_schema)","def _AddNewColsToSchema(new_fields, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for new_field in new_fields:\n if new_field.name in orig_schema_map:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n updated_schema_map[new_field.name] = new_field\n return updated_schema_map","def rebuild(self, dframe, overwrite=False):\n current_schema = self\n new_schema = schema_from_dframe(dframe, self)\n\n if current_schema and not overwrite:\n # merge new schema with existing schema\n current_schema.update(new_schema)\n new_schema = current_schema\n\n return new_schema","def ensure_internal_schema_updated(self):\n if self._internal_schema_updated:\n return\n if internalmigrations.needs_upgrading(self):\n assert not self._in_transaction\n with self.lock():\n internalmigrations.upgrade(self)\n self.connection.commit()\n self._internal_schema_updated = True","def merge_schema(self, schema):\n self.validate_schema(schema)\n\n if self.exclusive is False:\n self.exclusive = schema.exclusive\n\n if self.default is None:\n self.default = schema.default","def _patch_schema(self):\n fields = get_json()['data']['attributes'].keys()\n return make_entity_schema(\n self.SCHEMA, self.RESOURCE_NAME,\n make_data_schema(\n self.SCHEMA, id_required=True,\n only=fields, partial=True\n )\n )","def _ensure_schema_has_covariates(self, x_underscore_columns):\n previous_rename = self.covariate_rename\n if set(x_underscore_columns) == set(previous_rename.values()):\n return\n # Only rewrite schema if the x_<integer> list has changed.\n # because the schema depends on the number of covariates, not\n # their names.\n covariate_columns = list(x_underscore_columns)\n # ASCII sorting isn't correct b/c x_11 is before x_2.\n covariate_columns.sort(key=lambda x: int(x[2:]))\n for create_name in [\"data\", \"avgint\"]:\n empty = self.dismod_file.empty_table(create_name)\n without = [c for c in empty.columns if not c.startswith(\"x_\")]\n # The wrapper needs these columns to have a dtype of Real.\n empty = empty[without].assign(**{cname: np.empty((0,), dtype=np.float) for cname in covariate_columns})\n self.dismod_file.update_table_columns(create_name, empty)\n if getattr(self.dismod_file, create_name).empty:\n CODELOG.debug(f\"Writing empty {create_name} table with columns {covariate_columns}\")\n setattr(self.dismod_file, create_name, empty)\n else:\n CODELOG.debug(f\"Adding to {create_name} table schema the columns {covariate_columns}\")","def upgrade_schema():\n\n db_version = get_db_version()\n try:\n while db_version < CURRENT_DATABASE_VERSION:\n db_version += 1\n upgrade_script = 'upgrade_to_'+str(db_version)\n globals()[upgrade_script]()\n except KeyError as e:\n logging.exception('Attempted to upgrade using script that does not exist: {}'.format(e))\n sys.exit(1)\n except Exception as e:\n logging.exception('Incremental upgrade of db failed')\n sys.exit(1)\n else:\n config.db.singletons.update_one({'_id': 'version'}, {'$set': {'database': CURRENT_DATABASE_VERSION}})\n sys.exit(0)","def make_schema_changes(self, session, namespace='ns1'):\n debug(\"make_schema_changes() \" + str(namespace))\n session.execute('USE ks_%s' % namespace)\n # drop keyspace\n session.execute('DROP KEYSPACE ks2_%s' % namespace)\n wait(2)\n\n # create keyspace\n self.create_ks(session, \"ks3_%s\" % namespace, 2)\n session.execute('USE ks_%s' % namespace)\n\n wait(2)\n # drop column family\n session.execute(\"DROP COLUMNFAMILY cf2_%s\" % namespace)\n\n # create column family\n query = \"\"\"\n CREATE TABLE cf3_%s (\n col1 uuid PRIMARY KEY,\n col2 text,\n col3 text,\n col4 text\n );\n \"\"\" % (namespace)\n session.execute(query)\n\n # alter column family\n query = \"\"\"\n ALTER COLUMNFAMILY cf_%s\n ADD col4 text;\n \"\"\" % namespace\n session.execute(query)\n\n # add index\n session.execute(\"CREATE INDEX index2_%s ON cf_%s(col3)\"%(namespace, namespace))\n\n # remove an index\n session.execute(\"DROP INDEX index_%s\" % namespace)","def recreate_db(self, run=False):\n if run:\n db_schema = open(self.db_schema_file).read().splitlines()\n for s in db_schema:\n t = s.strip()\n if len(t):\n self.cur.execute(t)","def build_schema(self, dframe, overwrite=False, set_num_columns=True):\n new_schema = self.schema.rebuild(dframe, overwrite)\n self.set_schema(new_schema,\n set_num_columns=(set_num_columns or overwrite))","def update(self, schema: 'Schema'):\n self._update(schema)","def modify_tbl(self):\n debug = False\n dd = mg.DATADETS_OBJ\n orig_tblname = dd.tbl\n ## other (i.e. not the sofa_id) field details\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\n if debug:\n print('oth_name_types to feed into '\n f'make_strict_typing_tbl {oth_name_types}')\n try: ## 1 way or other must do strict_cleanup()\n make_strict_typing_tbl(\n orig_tblname, oth_name_types, self.settings_data)\n except sqlite.IntegrityError as e: #@UndefinedVariable\n if debug: print(b.ue(e))\n strict_cleanup(restore_tblname=orig_tblname)\n raise FldMismatchException\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n raise Exception('Problem making strictly-typed table.'\n f'\\nCaused by error: {b.ue(e)}')\n copy_orig_tbl(orig_tblname)\n wipe_tbl(orig_tblname)\n final_name = self.tblname_lst[0] ## may have been renamed\n try:\n make_redesigned_tbl(final_name, oth_name_types)\n strict_cleanup(restore_tblname=final_name)\n dd.set_tbl(tbl=final_name)\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\n dd.set_tbl(tbl=orig_tblname)\n raise Exception('Problem making redesigned table.'\n f'\\nCaused by error: {b.ue(e)}')\n wipe_tbl(mg.TMP_TBLNAME2)","def merge_schema(self, schema):\n for _, attr_schema in schema.iter_attributes():\n self.merge_attribute_schema(attr_schema)","def update(self, force=False):\n if (self.__fields is None) or force:\n self.__fields = [f for f in self.dbms.fields(self.table, self.db)]","def reset_schema_defs():\n SCHEMA_DEFS.clear()\n SCHEMA_DEFS.update((typ, typ) for typ in PRIMITIVE_TYPES)","def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\n old_info = old_schema_entry['info']\n new_info = new_schema_entry['info']\n old_mode = old_info['mode']\n old_name = old_info['name']\n old_type = old_info['type']\n old_status = old_schema_entry['status']\n new_mode = new_info['mode']\n new_name = new_info['name']\n new_type = new_info['type']\n new_status = new_schema_entry['status']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # If the old field is a REQUIRED primitive (which could only have come\n # from an existing schema), the new field can be either a\n # NULLABLE(filled) or a NULLABLE(unfilled).\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\n # If the new field is filled, then retain the REQUIRED.\n if new_schema_entry['filled']:\n return old_mode\n else:\n # The new field is not filled (i.e. an empty or null field).\n # If --infer_mode is active, then we allow the REQUIRED to\n # revert back to NULLABLE.\n if self.infer_mode:\n return new_mode\n else:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode.'\n ' cannot convert to NULLABLE because infer_schema not'\n ' set:'\n f' old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n elif old_mode != new_mode:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode: '\n f'old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n return old_mode","def initialize_schema(self, dry_run=False):\n if not dry_run:\n self.flush()","def modify_bigquery_schema(self, schema, info_keys):\n # type: (bigquery.TableSchema, Set[str]) -> None","def merge_schema_entry(\n self,\n old_schema_entry,\n new_schema_entry,\n base_path=None,\n ):\n if not old_schema_entry:\n return new_schema_entry\n\n # If the new schema is None, return immediately.\n if not new_schema_entry:\n return new_schema_entry\n\n # If a field value is missing, permanently set 'filled' to False.\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\n old_schema_entry['filled'] = False\n new_schema_entry['filled'] = False\n\n old_status = old_schema_entry['status']\n new_status = new_schema_entry['status']\n\n # new 'soft' does not clobber old 'hard'\n if old_status == 'hard' and new_status == 'soft':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n old_schema_entry['info']['mode'] = mode\n return old_schema_entry\n\n # new 'hard' clobbers old 'soft'\n if old_status == 'soft' and new_status == 'hard':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n new_schema_entry['info']['mode'] = mode\n return new_schema_entry\n\n # Verify that it's soft->soft or hard->hard\n if old_status != new_status:\n raise Exception(\n f'Unexpected schema_entry type, this should never happen: '\n f'old ({old_status}); new ({new_status})'\n )\n\n old_info = old_schema_entry['info']\n old_name = old_info['name']\n old_type = old_info['type']\n old_mode = old_info['mode']\n new_info = new_schema_entry['info']\n new_name = new_info['name']\n new_type = new_info['type']\n new_mode = new_info['mode']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # Defensive check, names should always be the same.\n if old_name != new_name:\n if old_name.lower() != new_name.lower():\n raise Exception(\n 'Unexpected difference in name, should never happen:'\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\n )\n else:\n # preserve old name if case is different\n new_info['name'] = old_info['name']\n\n # Recursively merge in the subfields of a RECORD, allowing\n # NULLABLE to become REPEATED (because 'bq load' allows it).\n if old_type == 'RECORD' and new_type == 'RECORD':\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\n # 'bq load' allows it.\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\n old_info['mode'] = 'REPEATED'\n self.log_error(\n f'Converting schema for \"{full_old_name}\" from '\n 'NULLABLE RECORD into REPEATED RECORD'\n )\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\n # TODO: Maybe remove this warning output. It was helpful during\n # development, but maybe it's just natural.\n self.log_error(\n f'Leaving schema for \"{full_old_name}\" as REPEATED RECORD'\n )\n\n # RECORD type needs a recursive merging of sub-fields. We merge into\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\n # can be modified in situ.\n old_fields = old_info['fields']\n new_fields = new_info['fields']\n for key, new_entry in new_fields.items():\n old_entry = old_fields.get(key)\n new_base_path = json_full_path(base_path, old_name)\n old_fields[key] = self.merge_schema_entry(\n old_schema_entry=old_entry,\n new_schema_entry=new_entry,\n base_path=new_base_path,\n )\n return old_schema_entry\n\n new_mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if new_mode is None:\n return None\n new_schema_entry['info']['mode'] = new_mode\n\n # For all other types...\n if old_type != new_type:\n # Check that the converted types are compatible.\n candidate_type = convert_type(old_type, new_type)\n if not candidate_type:\n self.log_error(\n f'Ignoring field with mismatched type: '\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\n )\n return None\n\n new_info['type'] = candidate_type\n return new_schema_entry","def add_column(self, schema):\n self[schema.name] = schema.copy()","def fix_incremental(meta, bind):\n meta.create_all(bind=bind, checkfirst=True)\n ref = inspect(bind)\n for table in meta.sorted_tables:\n orm_cols = set(col.name for col in table.c)\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\n col_to_create = orm_cols - ref_cols\n col_to_delete = ref_cols - orm_cols\n if col_to_create:\n print table.name, 'has diff to create', col_to_create\n with bind.begin() as conn:\n for col_name in col_to_create:\n col = table.c.get(col_name)\n column_sql = CreateColumn(col).compile(bind).string\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\n if col.default:\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\n if not col.nullable:\n sql += ' NOT NULL'\n print 'executing sql: ' + sql\n conn.execute(sql)\n\n # Workaround to ensure updated DBs start with \"False\" in ignore column\n if list(col_to_create)[0] == 'ignore':\n sessionmaker = get_sessionmaker(bind.url.database)\n session = sessionmaker()\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\n items = session.query(query_object).all()\n for item in items:\n item.ignore = False\n session.flush()\n\n if col_to_delete:\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\n \"\"\"\n BEGIN TRANSACTION;\n CREATE TEMPORARY TABLE t1_backup(a,b);\n INSERT INTO t1_backup SELECT a,b FROM t1;\n DROP TABLE t1;\n CREATE TABLE t1(a,b);\n INSERT INTO t1 SELECT a,b FROM t1_backup;\n DROP TABLE t1_backup;\n COMMIT;\n \"\"\"","def compute_schema_updates(self):\n data = self.client._perform_json(\n \"GET\", \"/projects/%s/recipes/%s/schema-update\" % (self.project_key, self.recipe_name))\n return RequiredSchemaUpdates(self, data)","def has_desired_schema(self):\n if self._new_table == self._old_table:\n if not self.rebuild:\n log.info(\"Table already has the desired schema. \")\n return True\n else:\n log.info(\n \"Table already has the desired schema. However \"\n \"--rebuild is specified, doing a rebuild instead\"\n )\n return False\n return False","def modify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\n\n return provision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)","def merge_schema(self, schema):\n super(BooleanAttributeSchema, self).merge_schema(schema)\n self.values.update(schema.values)","def update(self):\n current = LazyRegister(self.db)\n current.render()\n cur = self.db.cursor()\n for table in self.tables:\n if table in current.tables:\n additions, removals = current.tables[table].migrate(self.tables[table])\n for addition in additions:\n cur.execute(\"\"\"ALTER TABLE %s ADD COLUMN %s\"\"\" % (\n table, addition[1].get_sql()\n ))\n print('Added column: ', addition[0])\n for removal in removals:\n #cur.execute(\"\"\"ALTER TABLE %s DROP COLUMN %s\"\"\" % (\n # table, removal[0]\n #))\n #print('Removed column: ', removal[0])\n print('Did not removed column: ', removal[0])\n else:\n schema = self.tables[table].get_create_table_sql()\n cur.execute(schema)\n print('Added table %s' % table)","def schema(self, schema):\n self._schema = schema","def schema(self, schema):\n\n self._schema = schema","def schema(self, schema):\n\n self._schema = schema","def schema(self, schema):\n\n self._schema = schema","def upgrade():\n op.execute(\n f\"\"\"\n ALTER TABLE\n {config.CLEAN_SCHEMA}.forecasts\n RENAME COLUMN\n training_horizon\n TO\n train_horizon;\n \"\"\",\n ) # noqa:WPS355","def update_schema(self, engine_name, schema):\n endpoint = \"engines/{}/schema\".format(engine_name)\n data = json.dumps(schema)\n return self.swiftype_session.request('post', endpoint, data=data)","def filter_schema(schema):\n for column, column_schema in schema.iteritems():\n if column_schema.get(CARDINALITY):\n del column_schema[CARDINALITY]\n schema[column] = column_schema\n\n return schema","def set_schema(self, schema, set_num_columns=True):\n update_dict = {self.SCHEMA: schema}\n\n if set_num_columns:\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\n\n self.update(update_dict)","def finalizeSchema(schema, folderish=False, moveDiscussion=True):\n schema.moveField('businessOldLocation', after='workLocations')\n schema.moveField('foldermanagers', after='businessOldLocation')\n# schema.moveField('bound_licences', after='isTransferOfLicence')\n schema.moveField('rubrics', after='folderCategory')\n schema.moveField('description', after='additionalLegalConditions')\n schema.moveField('referenceFT', after='referenceDGATLP')\n schema.moveField('isTransferOfLicence', after='referenceFT')\n\n return schema","def _alter_field(\n self,\n model,\n old_field,\n new_field,\n old_type,\n new_type,\n old_db_params,\n new_db_params,\n strict=False,\n ):\n\n super()._alter_field(\n model,\n old_field,\n new_field,\n old_type,\n new_type,\n old_db_params,\n new_db_params,\n strict,\n )\n\n # If the pkey was dropped in the previous distribute migration,\n # foreign key constraints didn't previously exists so django does not\n # recreated them.\n # Here we test if we are in this case\n if isinstance(new_field, TenantForeignKey) and new_field.db_constraint:\n from_model = get_model_by_db_table(model._meta.db_table)\n fk_names = self._constraint_names(\n model, [new_field.column], foreign_key=True\n ) + self._constraint_names(\n model,\n [new_field.column, get_tenant_column(from_model)],\n foreign_key=True,\n )\n if not fk_names:\n self.execute(\n self._create_fk_sql(\n model, new_field, \"_fk_%(to_table)s_%(to_column)s\"\n )\n )","def merge_attribute_schema(self, attr_schema):\n name = attr_schema.name\n if name not in self.schema:\n self.schema[name] = attr_schema\n else:\n self.schema[name].merge_schema(attr_schema)","def setAllColumns(self, newAllColumns):\n \n pass","def _clean_up_columns(\n self):\n self.log.debug('starting the ``_clean_up_columns`` method')\n\n tableName = self.dbTableName\n\n print \"cleaning up %(tableName)s columns\" % locals()\n\n sqlQuery = u\"\"\"\n set sql_mode=\"STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION\";\n \"\"\" % locals()\n writequery(\n log=self.log,\n sqlQuery=sqlQuery,\n dbConn=self.cataloguesDbConn,\n )\n\n sqlQuery = u\"\"\"\n update %(tableName)s set dist_mod_err = null where dist_mod_err = 0;\n update %(tableName)s set dist_in_ned_flag = null where dist_in_ned_flag = \"\";\n update %(tableName)s set notes = null where notes = \"\";\n update %(tableName)s set redshift = null where redshift = 0;\n update %(tableName)s set dist_derived_from_sn = null where dist_derived_from_sn = \"\";\n update %(tableName)s set hubble_const = null where hubble_const = 0;\n update %(tableName)s set lmc_mod = null where lmc_mod = 0;\n update %(tableName)s set master_row = 0;\n update %(tableName)s set master_row = 1 where primaryId in (select * from (select distinct primaryId from %(tableName)s group by galaxy_index_id) as alias);\n \"\"\" % locals()\n writequery(\n log=self.log,\n sqlQuery=sqlQuery,\n dbConn=self.cataloguesDbConn,\n )\n\n self.log.debug('completed the ``_clean_up_columns`` method')\n return None","def apply_to(self, df: pd.DataFrame) -> pd.DataFrame:\n schema_names = self.names\n data_columns = df.columns\n\n assert len(schema_names) == len(\n data_columns\n ), \"schema column count does not match input data column count\"\n\n for column, dtype in zip(data_columns, self.types):\n pandas_dtype = dtype.to_pandas()\n\n col = df[column]\n col_dtype = col.dtype\n\n try:\n not_equal = pandas_dtype != col_dtype\n except TypeError:\n # ugh, we can't compare dtypes coming from pandas,\n # assume not equal\n not_equal = True\n\n if not_equal or not dtype.is_primitive():\n new_col = convert(col_dtype, dtype, col)\n else:\n new_col = col\n df[column] = new_col\n\n # return data with the schema's columns which may be different than the\n # input columns\n df.columns = schema_names\n return df","def generate_altered_fields(self):\n result = super(MigrationAutodetector, self).generate_altered_fields()\n self.generate_sql_changes()\n return result","def apply_patch():\n assert BaseDatabaseSchemaEditor is not None\n\n def _create_unique_sql(self, *args, **kwargs):\n from django.db.backends.ddl_references import IndexName\n\n statement = orig_create_unique_sql(self, *args, **kwargs)\n\n if statement is not None:\n index_name = statement.parts['name']\n\n if (isinstance(index_name, IndexName) and\n index_name.create_index_name == self._create_index_name):\n # The result will be unquoted. Let's quote it.\n index_name.create_index_name = lambda *args, **kwargs: \\\n self.quote_name(self._create_index_name(*args, **kwargs))\n\n return statement\n\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql","def upgrade():\n with op.batch_alter_table(\"slot_pool\") as batch_op:\n batch_op.add_column(sa.Column(\"include_deferred\", sa.Boolean))\n # Different databases support different literal for FALSE. This is fine.\n op.execute(sa.text(f\"UPDATE slot_pool SET include_deferred = {sa.false().compile(op.get_bind())}\"))\n with op.batch_alter_table(\"slot_pool\") as batch_op:\n batch_op.alter_column(\"include_deferred\", existing_type=sa.Boolean, nullable=False)","def db_schema_32():\n with old_db_schema(\"32\"):\n yield","def update_table_columns(self, table_name, table):\n table_definition = self._table_definitions[table_name]\n new_columns = table.columns.difference(table_definition.c.keys())\n new_column_types = {c: table.dtypes[c] for c in new_columns}\n\n allows_covariates = table_definition.name in [\"avgint\", \"data\"]\n\n good_prefixes = [\"c_\"]\n if allows_covariates:\n good_prefixes.append(\"x_\")\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\n if bad_column_names:\n msg = f\"\"\"\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\n It allows additional comment columns, which must start 'c_'.\"\"\"\n if allows_covariates:\n msg += \" In addition it allows covariate columns, which must start with 'x_'.\"\n msg += f\" You supplied columns that don't meet those requirements: {bad_column_names}\"\n\n raise ValueError(dedent(msg))\n\n add_columns_to_table(table_definition, new_column_types)","def set_schema(self, schema):\r\n self.__schema = schema","def extend_schema(\n schema: GraphQLSchema,\n document_ast: DocumentNode,\n assume_valid=False,\n assume_valid_sdl=False,\n) -> GraphQLSchema:\n assert_schema(schema)\n\n if not isinstance(document_ast, DocumentNode):\n \"Must provide valid Document AST\"\n\n if not (assume_valid or assume_valid_sdl):\n from ..validation.validate import assert_valid_sdl_extension\n\n assert_valid_sdl_extension(document_ast, schema)\n\n # Collect the type definitions and extensions found in the document.\n type_defs: List[TypeDefinitionNode] = []\n type_exts_map: Dict[str, Any] = defaultdict(list)\n\n # New directives and types are separate because a directives and types can have the\n # same name. For example, a type named \"skip\".\n directive_defs: List[DirectiveDefinitionNode] = []\n\n schema_def: Optional[SchemaDefinitionNode] = None\n # Schema extensions are collected which may add additional operation types.\n schema_exts: List[SchemaExtensionNode] = []\n\n for def_ in document_ast.definitions:\n if isinstance(def_, SchemaDefinitionNode):\n schema_def = def_\n elif isinstance(def_, SchemaExtensionNode):\n schema_exts.append(def_)\n elif isinstance(def_, TypeDefinitionNode):\n type_defs.append(def_)\n elif isinstance(def_, TypeExtensionNode):\n extended_type_name = def_.name.value\n type_exts_map[extended_type_name].append(def_)\n elif isinstance(def_, DirectiveDefinitionNode):\n directive_defs.append(def_)\n\n # If this document contains no new types, extensions, or directives then return the\n # same unmodified GraphQLSchema instance.\n if (\n not type_exts_map\n and not type_defs\n and not directive_defs\n and not schema_exts\n and not schema_def\n ):\n return schema\n\n # Below are functions used for producing this schema that have closed over this\n # scope and have access to the schema, cache, and newly defined types.\n\n # noinspection PyTypeChecker,PyUnresolvedReferences\n def replace_type(type_: GraphQLType) -> GraphQLType:\n if is_list_type(type_):\n return GraphQLList(replace_type(type_.of_type)) # type: ignore\n if is_non_null_type(type_):\n return GraphQLNonNull(replace_type(type_.of_type)) # type: ignore\n return replace_named_type(type_) # type: ignore\n\n def replace_named_type(type_: GraphQLNamedType) -> GraphQLNamedType:\n return type_map[type_.name]\n\n def get_maybe_type_by_name(type_name: Optional[str]) -> Optional[GraphQLNamedType]:\n return type_map[type_name] if type_name else None\n\n def get_merged_directives() -> List[GraphQLDirective]:\n if not schema.directives:\n raise TypeError(\"schema must have default directives\")\n\n return list(\n chain(\n map(extend_directive, schema.directives),\n map(ast_builder.build_directive, directive_defs),\n )\n )\n\n def extend_named_type(type_: GraphQLNamedType) -> GraphQLNamedType:\n if is_introspection_type(type_) or is_specified_scalar_type(type_):\n # Builtin types are not extended.\n return type_\n if is_scalar_type(type_):\n type_ = cast(GraphQLScalarType, type_)\n return extend_scalar_type(type_)\n if is_object_type(type_):\n type_ = cast(GraphQLObjectType, type_)\n return extend_object_type(type_)\n if is_interface_type(type_):\n type_ = cast(GraphQLInterfaceType, type_)\n return extend_interface_type(type_)\n if is_union_type(type_):\n type_ = cast(GraphQLUnionType, type_)\n return extend_union_type(type_)\n if is_enum_type(type_):\n type_ = cast(GraphQLEnumType, type_)\n return extend_enum_type(type_)\n if is_input_object_type(type_):\n type_ = cast(GraphQLInputObjectType, type_)\n return extend_input_object_type(type_)\n\n # Not reachable. All possible types have been considered.\n raise TypeError(f\"Unexpected type: '{inspect(type_)}'.\") # pragma: no cover\n\n def extend_directive(directive: GraphQLDirective) -> GraphQLDirective:\n kwargs = directive.to_kwargs()\n return GraphQLDirective( # type: ignore\n **{\n **kwargs,\n \"args\": {name: extend_arg(arg) for name, arg in kwargs[\"args\"].items()},\n }\n )\n\n def extend_input_object_type(\n type_: GraphQLInputObjectType\n ) -> GraphQLInputObjectType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\n\n return GraphQLInputObjectType(\n **{\n **kwargs,\n \"fields\": lambda: {\n **{\n name: GraphQLInputField( # type: ignore\n **{**field.to_kwargs(), \"type_\": replace_type(field.type)}\n )\n for name, field in kwargs[\"fields\"].items()\n },\n **{\n field.name.value: ast_builder.build_input_field(field)\n for field in field_nodes\n },\n },\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_enum_type(type_: GraphQLEnumType) -> GraphQLEnumType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n value_nodes = chain.from_iterable(node.values or [] for node in extensions)\n\n return GraphQLEnumType(\n **{\n **kwargs,\n \"values\": {\n **kwargs[\"values\"],\n **{\n value.name.value: ast_builder.build_enum_value(value)\n for value in value_nodes\n },\n },\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_scalar_type(type_: GraphQLScalarType) -> GraphQLScalarType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n\n return GraphQLScalarType(\n **{\n **kwargs,\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_object_type(type_: GraphQLObjectType) -> GraphQLObjectType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n interface_nodes = chain.from_iterable(\n node.interfaces or [] for node in extensions\n )\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\n\n return GraphQLObjectType(\n **{\n **kwargs,\n \"interfaces\": lambda: [\n replace_named_type(interface) for interface in kwargs[\"interfaces\"]\n ]\n # Note: While this could make early assertions to get the correctly\n # typed values, that would throw immediately while type system\n # validation with validate_schema will produce more actionable results.\n + [ast_builder.get_named_type(node) for node in interface_nodes],\n \"fields\": lambda: {\n **{\n name: extend_field(field)\n for name, field in kwargs[\"fields\"].items()\n },\n **{\n node.name.value: ast_builder.build_field(node)\n for node in field_nodes\n },\n },\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_interface_type(type_: GraphQLInterfaceType) -> GraphQLInterfaceType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\n\n return GraphQLInterfaceType(\n **{\n **kwargs,\n \"fields\": lambda: {\n **{\n name: extend_field(field)\n for name, field in kwargs[\"fields\"].items()\n },\n **{\n node.name.value: ast_builder.build_field(node)\n for node in field_nodes\n },\n },\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_union_type(type_: GraphQLUnionType) -> GraphQLUnionType:\n kwargs = type_.to_kwargs()\n extensions = type_exts_map.get(kwargs[\"name\"], [])\n type_nodes = chain.from_iterable(node.types or [] for node in extensions)\n\n return GraphQLUnionType(\n **{\n **kwargs,\n \"types\": lambda: [\n replace_named_type(member_type) for member_type in kwargs[\"types\"]\n ]\n # Note: While this could make early assertions to get the correctly\n # typed values, that would throw immediately while type system\n # validation with validate_schema will produce more actionable results.\n + [ast_builder.get_named_type(node) for node in type_nodes],\n \"extension_ast_nodes\": kwargs[\"extension_ast_nodes\"] + extensions,\n }\n )\n\n def extend_field(field: GraphQLField) -> GraphQLField:\n return GraphQLField( # type: ignore\n **{\n **field.to_kwargs(),\n \"type_\": replace_type(field.type),\n \"args\": {name: extend_arg(arg) for name, arg in field.args.items()},\n }\n )\n\n def extend_arg(arg: GraphQLArgument) -> GraphQLArgument:\n return GraphQLArgument( # type: ignore\n **{**arg.to_kwargs(), \"type_\": replace_type(arg.type)}\n )\n\n # noinspection PyShadowingNames\n def resolve_type(type_name: str) -> GraphQLNamedType:\n type_ = type_map.get(type_name)\n if not type_:\n raise TypeError(f\"Unknown type: '{type_name}'.\")\n return type_\n\n ast_builder = ASTDefinitionBuilder(\n assume_valid=assume_valid, resolve_type=resolve_type\n )\n\n type_map = {node.name.value: ast_builder.build_type(node) for node in type_defs}\n for existing_type_name, existing_type in schema.type_map.items():\n type_map[existing_type_name] = extend_named_type(existing_type)\n\n # Get the extended root operation types.\n operation_types: Dict[OperationType, Optional[str]] = {\n OperationType.QUERY: schema.query_type.name if schema.query_type else None,\n OperationType.MUTATION: schema.mutation_type.name\n if schema.mutation_type\n else None,\n OperationType.SUBSCRIPTION: schema.subscription_type.name\n if schema.subscription_type\n else None,\n }\n\n if schema_def:\n for operation_type in schema_def.operation_types:\n operation = operation_type.operation\n operation_types[operation] = operation_type.type.name.value\n\n # Then, incorporate schema definition and all schema extensions.\n for schema_ext in schema_exts:\n if schema_ext.operation_types:\n for operation_type in schema_ext.operation_types:\n operation = operation_type.operation\n operation_types[operation] = operation_type.type.name.value\n\n # Then produce and return a Schema with these types.\n return GraphQLSchema( # type: ignore\n # Note: While this could make early assertions to get the correctly\n # typed values, that would throw immediately while type system\n # validation with validateSchema() will produce more actionable results.\n query=get_maybe_type_by_name(operation_types[OperationType.QUERY]),\n mutation=get_maybe_type_by_name(operation_types[OperationType.MUTATION]),\n subscription=get_maybe_type_by_name(\n operation_types[OperationType.SUBSCRIPTION]\n ),\n types=list(type_map.values()),\n directives=get_merged_directives(),\n ast_node=schema_def or schema.ast_node,\n extension_ast_nodes=(\n (\n schema.extension_ast_nodes\n or cast(FrozenList[SchemaExtensionNode], FrozenList())\n )\n + schema_exts\n )\n or None,\n )","def test_compare_schemas_happypath(self):\n status = schema_utils.compare_schemas(\n self.base_schema,\n self.base_schema\n )\n\n assert status == schema_utils.Update.no_update","def correct_db_schema_precision(\n instance: Recorder,\n table_object: type[DeclarativeBase],\n schema_errors: set[str],\n) -> None:\n table_name = table_object.__tablename__\n\n if f\"{table_name}.double precision\" in schema_errors:\n from ..migration import ( # pylint: disable=import-outside-toplevel\n _modify_columns,\n )\n\n precision_columns = _get_precision_column_types(table_object)\n # Attempt to convert timestamp columns to µs precision\n session_maker = instance.get_session\n engine = instance.engine\n assert engine is not None, \"Engine should be set\"\n _modify_columns(\n session_maker,\n engine,\n table_name,\n [f\"{column} {DOUBLE_PRECISION_TYPE_SQL}\" for column in precision_columns],\n )","def _update(self, schema: 'Schema'):\n for method in schema._get_methods():\n if method.id in self:\n raise ValueError(\n f\"Duplicate method id for {method.method} id: {method.id}\"\n )\n\n for combinator in schema._get_combinators():\n if combinator.id in self:\n raise ValueError(\n f\"Duplicate combinator id for {combinator.predicate} \" +\n f\"id: {combinator.id}\"\n )\n\n self.constructors += schema.constructors\n self.functions += schema.functions\n\n self._build_schema_data()","def upgrade():\n op.add_column(\n 'wish', sa.Column(\n 'admin_votes_num', sa.Integer(), server_default='0',\n nullable=True))\n op.add_column(\n 'wish', sa.Column('real_votes_num', sa.Integer(), nullable=True))\n op.execute('UPDATE wish SET real_votes_num = votes_num')\n op.drop_column('wish', 'votes_num')","def merge_schemas(self, old_schm, new_schm):\n\n old_schm_cols = [x['name'] for x in old_schm]\n\n for col in new_schm:\n if type(col) == dict:\n if col['name'] not in old_schm_cols:\n old_schm.append(col)\n \n for count, old_col in enumerate(old_schm):\n for meta in old_col:\n if type(old_col[meta]) == list:\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\n if meta in new_col:\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\n \n return old_schm","def update_2xto30():\r\n if db_version > 300:\r\n log.debug('Database newer than schema version 300.')\r\n return # No update needed\r\n\r\n log.debug('Updating to schema 300.')\r\n QtSql.QSqlQuery('ALTER TABLE presentations RENAME TO presentations_old') # temporary table\r\n self.__create_presentations_table(PRESENTATIONS_SCHEMA_300)\r\n QtSql.QSqlQuery(\"\"\"INSERT INTO presentations\r\n SELECT Id, Title, Speaker, Description, Level, Event, Room, Time FROM presentations_old\"\"\")\r\n QtSql.QSqlQuery('DROP TABLE presentations_old')","def _migrate_if_necessary(self, entries):\r\n entries = [\r\n self._migrate[entry.get('schema', 0)](self, entry)\r\n for entry in entries\r\n ]\r\n return entries","def upgrade():\n\n conn = op.get_bind()\n invalid_acr = get_invalid_acrs(conn, models_names)\n\n if invalid_acr:\n invalid_acr_ids = [x.id for x in invalid_acr]\n add_to_objects_without_revisions_bulk(conn,\n invalid_acr_ids,\n acr,\n \"deleted\")\n delete_invalid_acr(conn, models_names)","def fix_all(self):\n\n altered_tables = {}\n\n for ingestible_db_conf in self.ingestible_db_conf_repo.get_ingestible_dbs():\n target_db= ingestible_db_conf.target_db_name\n db_type = ingestible_db_conf.db_type\n self.logger.info(\"Fixing consistency for DB Type: %s, Target DB: %s\" % (db_type, target_db))\n self.prepare_database(target_db)\n consistency_checker = HiveConsistencyChecker(target_db, db_type)\n\n unused_tables = consistency_checker.get_unused_tables()\n self.remove_unused_tables(unused_tables)\n\n new_tables = consistency_checker.get_new_tables()\n self.create_new_tables(new_tables)\n\n inconsistent_tables = consistency_checker.get_inconsistent_tables()\n self.fix_inconsistent_tables(inconsistent_tables, db_type)\n\n # Combine lists of inconsistent and unused tables\n altered_tables[db_type] = map(lambda qualified_table: qualified_table.split(\".\")[1],\n inconsistent_tables.keys() + unused_tables)\n\n self.logger.debug(\"Altered Tables: %s\" % altered_tables)\n return altered_tables","def setup_schema(self):\n models.Base.metadata.create_all(self.session.bind)","def schema_upgrades():\n op.create_table('vpp_licenses',\n sa.Column('license_id', sa.Integer(), nullable=False),\n sa.Column('adam_id', sa.String(), nullable=True),\n sa.Column('product_type', sa.Enum('Software', 'Application', 'Publication', name='vppproducttype'), nullable=True),\n sa.Column('product_type_name', sa.String(), nullable=True),\n sa.Column('pricing_param', sa.Enum('StandardQuality', 'HighQuality', name='vpppricingparam'), nullable=True),\n sa.Column('is_irrevocable', sa.Boolean(), nullable=True),\n sa.Column('user_id', sa.Integer(), nullable=True),\n sa.Column('client_user_id', commandment.dbtypes.GUID(), nullable=True),\n sa.Column('its_id_hash', sa.String(), nullable=True),\n sa.ForeignKeyConstraint(['client_user_id'], ['vpp_users.client_user_id'], ),\n sa.ForeignKeyConstraint(['user_id'], ['vpp_users.user_id'], ),\n sa.PrimaryKeyConstraint('license_id')\n )","def same_schema(self):\n return self._same_schema","def enforce_constraints(self):\n self.session.flush()\n try:\n self.session.execute('SET CONSTRAINTS ALL IMMEDIATE')\n except DatabaseError:\n handle_sqlalchemy_database_error()","def resolve_schema(self, data):\n if not isinstance(data, dict):\n return\n\n # OAS 2 component or OAS 3 header\n if \"schema\" in data:\n data[\"schema\"] = self.openapi.resolve_schema_dict(data[\"schema\"])\n # OAS 3 component except header\n if self.openapi_version.major >= 3:\n if \"content\" in data:\n for content_type in data[\"content\"]:\n schema = data[\"content\"][content_type][\"schema\"]\n data[\"content\"][content_type][\n \"schema\"\n ] = self.openapi.resolve_schema_dict(schema)","def finalizeSchema(schema, folderish=False, moveDiscussion=True):\n schema.moveField('description', after='architects')\n return schema","def downgrade():\n op.execute(\n f\"\"\"\n ALTER TABLE\n {config.CLEAN_SCHEMA}.forecasts\n RENAME COLUMN\n train_horizon\n TO\n training_horizon;\n \"\"\",\n ) # noqa:WPS355","def clone_schema(base_schema_name: str, new_schema_name: str, dry_run: bool = False):\n check_schema_name(new_schema_name)\n cursor = connection.cursor()\n\n # check if the clone_schema function already exists in the db\n try:\n cursor.execute(\n \"SELECT 'public.clone_schema(text, text, public.cloneparms[])'::regprocedure\"\n )\n except ProgrammingError: # pragma: no cover\n _create_clone_schema_function()\n transaction.commit()\n\n try:\n with transaction.atomic():\n cursor.callproc(\"clone_schema\", [base_schema_name, new_schema_name, \"DATA\"])\n cursor.close()\n if dry_run:\n raise DryRunException\n except DryRunException:\n cursor.close()","def regenerate_constraints(self):\n\n # Let us not forget to remove fields that migh be empty by now\n if hasattr(self, '_cons_kinds'):\n for k in self._cons_kinds:\n attrname = camel2underscores(k)\n try:\n delattr(self, attrname)\n except AttributeError:\n pass # The attribute may not have been set up yet\n\n _cons_kinds = defaultdict(DictList)\n\n for k, v in self._cons_dict.items():\n _cons_kinds[v.__class__.__name__].append(v)\n\n for k in _cons_kinds:\n attrname = camel2underscores(k)\n setattr(self, attrname, _cons_kinds[k])\n\n self._cons_kinds = _cons_kinds","def add_cols(self, source) :\n\n cols = source.get_cols()\n types = source.get_types()\n\n new_cols = []\n new_types = []\n for i in range(len(cols)) :\n if cols[i] not in self.cols :\n new_cols.append(cols[i])\n new_types.append(types[i])\n self.cols.extend(new_cols)\n self.types.extend(new_types)\n\n self._alter_table(new_cols, new_types)\n\n row_ids = self.get_values('__ROWID')\n \n for col in new_cols :\n new_vals = source.get_values(col)\n if len(row_ids) == 0 :\n for val in new_vals :\n self._insert_internal(['__ROWID', col], [0, val])\n\n row_ids = self.get_values('__ROWID')\n\n else :\n binds = zip(new_vals, row_ids)\n q = self._quoter(col)\n sql_base = 'UPDATE \"%s\" SET \"%s\" = %s WHERE \"__ROWID\" = %%d' % (self.name, col, q)\n cur = self.con.cursor()\n for bind in binds :\n if bind[0] :\n update_sql = sql_base % (str(bind[0]), bind[1])\n cur.execute(update_sql)\n\n self.version += 1","def upgrade_to_14():\n config.db.singletons.find_one_and_update(\n {'_id': 'config', 'persistent.schema_path': {'$exists': True}},\n {'$unset': {'persistent.schema_path': ''}})","def upgrade_to_13():\n config.db.singletons.find_one_and_update(\n {'_id': 'config', 'persistent.schema_path': {'$exists': True}},\n {'$unset': {'persistent.schema_path': ''}})","def merge_schema(self, schema):\n super(CategoricalAttributeSchema, self).merge_schema(schema)\n self.categories.update(schema.categories)","def deferred_to_columns_cb(self, target, model, fields):\n table = model._meta.db_table\n if table not in target:\n target[table] = set()\n for field in fields:\n if not hasattr(field.column, \"columns\"):\n target[table].add(field.column)\n else:\n target[table].update(field.column.columns)","def upgrade_to_6():\n\n colls = config.db.collections.find({'modified': {'$type': 2}}) # type string\n for c in colls:\n fixed_mod = dateutil.parser.parse(c['modified'])\n config.db.collections.update_one({'_id': c['_id']}, {'$set': {'modified': fixed_mod}})","def _refactor_time_columns(write_cursor: 'DBCursor') -> None:\n log.debug('Enter _refactor_time_columns')\n write_cursor.execute('ALTER TABLE timed_balances RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE timed_location_data RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE trades RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE asset_movements RENAME COLUMN time TO timestamp')\n log.debug('Exit _refactor_time_columns')","def repair(self):\n # self.add_cons_vars([x.constraint for x in self._cons_dict.values()])\n # self.add_cons_vars([x.variable for x in self._var_dict.values()])\n self._push_queue()\n Model.repair(self)\n self.regenerate_constraints()\n self.regenerate_variables()","def strict_startup(self):\n self.load_up_initial_db(TIMESTAMP_PARSE_DICT)\n self.clean()\n self.add_numeric_cols()","def upkeep(self) -> None:\n if self.atype in ['REINFORCE', 'A2C']:\n self._db.reset()","def unmodify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\n\n return deprovision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)","def modify(self, fields=None, **fields_kwargs):\n modified_fields = set()\n fields = self.make_dict(fields, fields_kwargs)\n fields = self._modify(fields)\n for field_name, field_val in fields.items():\n in_schema = field_name in self.schema.fields\n if in_schema:\n setattr(self, field_name, field_val)\n modified_fields.add(field_name)\n\n return modified_fields","def reset_modified(self):\n self.modified_fields = set()\n\n # compensate for us not having knowledge of certain fields changing\n for field_name, field in self.schema.normal_fields.items():\n if isinstance(field, ObjectField):\n self.modified_fields.add(field_name)","def migrate(env):\n registry = env['registry']\n settings = registry.settings\n readonly_backends = ('storage', 'permission')\n readonly_mode = asbool(settings.get('readonly', False))\n\n for backend in ('cache', 'storage', 'permission'):\n if hasattr(registry, backend):\n if readonly_mode and backend in readonly_backends:\n message = ('Cannot migrate the %s backend while '\n 'in readonly mode.' % backend)\n warnings.warn(message)\n else:\n getattr(registry, backend).initialize_schema()","def ibis_schema_apply_to(schema, df):\n\n for column, dtype in schema.items():\n pandas_dtype = dtype.to_pandas()\n if isinstance(dtype, dt.Interval):\n df[column] = df[column].values.astype(pandas_dtype)\n else:\n df[column] = df[column].astype(pandas_dtype, errors='ignore')\n\n if PY2 and dtype == dt.string:\n df[column] = df[column].str.decode('utf-8', errors='ignore')\n\n return df","def _rewrite_project(self, node: saldag.Project):\n\n selected_cols = node.selected_cols\n\n for in_col, out_col in zip(selected_cols, node.out_rel.columns):\n out_col.coll_sets |= copy.deepcopy(in_col.coll_sets)","def update(self, schema: ISchema) -> ISchema:\n schema = super().update(schema)\n\n schema = cast(EventSchema, schema)\n if not schema.Active and schema.Sport > 0:\n self.select('ID', 'Sport', 'Active').filter(\n 'Sport', Operators.Equals, schema.Sport,\n ).filter('Active', Operators.Equals, 1)\n result = self.execute()\n if not result:\n sm = SportModel()\n sport = sm.find(schema.Sport)\n sport = cast(SportSchema, sport)\n sport.Active = False\n sm.update(sport)\n return schema","def test_can_update_risk_type_schema(self):\n risk_type = self.create_risk_type()\n for r in risk_type.schema:\n if r['field_type'] == 'text':\n r['field_type'] = 'textarea'\n break\n\n response = self.client.put(\n f'/api/v0/risk-types/{risk_type.id}/',\n data={\n 'type_name': 'New Risk Type',\n 'schema': risk_type.schema,\n }, format='json')\n risk_type.refresh_from_db()\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n self.assertEqual(risk_type.schema[0].get('field_type'), 'textarea')","def upgrade():\n op.add_column(\n 'assessments',\n sa.Column(\n 'assessment_type',\n sa.String(length=250),\n nullable=False,\n server_default=\"Control\",\n )\n )\n # Change CA help text \"Assessment type\" to \"Assessment Category\"\n op.execute(\n 'UPDATE custom_attribute_definitions '\n 'SET helptext = \"Assessment Category\" '\n 'WHERE helptext = \"Assessment type\" '\n 'AND definition_type = \"assessment\" AND title = \"Type\";'\n )","def migrate(env, dry_run=False):\n registry = env['registry']\n settings = registry.settings\n readonly_backends = ('storage', 'permission')\n readonly_mode = asbool(settings.get('readonly', False))\n\n for backend in ('cache', 'storage', 'permission'):\n if hasattr(registry, backend):\n if readonly_mode and backend in readonly_backends:\n message = ('Cannot migrate the %s backend while '\n 'in readonly mode.' % backend)\n logger.error(message)\n else:\n getattr(registry, backend).initialize_schema(dry_run=dry_run)","def _prepare_schema(self):\n schema = DaskSchema(self.schema_name)\n\n if not self.tables:\n logger.warning(\"No tables are registered.\")\n\n for name, dc in self.tables.items():\n table = DaskTable(name)\n df = dc.df\n logger.debug(\n f\"Adding table '{name}' to schema with columns: {list(df.columns)}\"\n )\n for column in df.columns:\n data_type = df[column].dtype\n sql_data_type = python_to_sql_type(data_type)\n\n table.addColumn(column, sql_data_type)\n\n schema.addTable(table)\n\n if not self.functions:\n logger.debug(\"No custom functions defined.\")\n\n for function_description in self.function_list:\n name = function_description.name\n sql_return_type = python_to_sql_type(function_description.return_type)\n if function_description.aggregation:\n logger.debug(f\"Adding function '{name}' to schema as aggregation.\")\n dask_function = DaskAggregateFunction(name, sql_return_type)\n else:\n logger.debug(f\"Adding function '{name}' to schema as scalar function.\")\n dask_function = DaskScalarFunction(name, sql_return_type)\n\n dask_function = self._add_parameters_from_description(\n function_description, dask_function\n )\n\n schema.addFunction(dask_function)\n\n return schema","def _create_schema(self):\n self._conn.executescript(self._db_schema)","def _create_clone_schema_function():\n with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), \"clone_schema.sql\")) as f:\n CLONE_SCHEMA_FUNCTION = (\n f.read()\n .replace(\"RAISE NOTICE ' source schema\", \"RAISE EXCEPTION ' source schema\")\n .replace(\"RAISE NOTICE ' dest schema\", \"RAISE EXCEPTION ' dest schema\")\n )\n\n cursor = connection.cursor()\n cursor.execute(CLONE_SCHEMA_FUNCTION)\n cursor.close()","def test_compare_schemas_major(self):\n status = schema_utils.compare_schemas(\n self.base_schema,\n self.major_removed_value\n )\n\n assert status == schema_utils.Update.major","def extend_schema(schema, documentAST=None):\n\n assert isinstance(schema, GraphQLSchema), \"Must provide valid GraphQLSchema\"\n assert documentAST and isinstance(\n documentAST, ast.Document\n ), \"Must provide valid Document AST\"\n\n # Collect the type definitions and extensions found in the document.\n type_definition_map = {}\n type_extensions_map = defaultdict(list)\n\n for _def in documentAST.definitions:\n if isinstance(\n _def,\n (\n ast.ObjectTypeDefinition,\n ast.InterfaceTypeDefinition,\n ast.EnumTypeDefinition,\n ast.UnionTypeDefinition,\n ast.ScalarTypeDefinition,\n ast.InputObjectTypeDefinition,\n ),\n ):\n # Sanity check that none of the defined types conflict with the\n # schema's existing types.\n type_name = _def.name.value\n if schema.get_type(type_name):\n raise GraphQLError(\n (\n 'Type \"{}\" already exists in the schema. It cannot also '\n + \"be defined in this type definition.\"\n ).format(type_name),\n [_def],\n )\n\n type_definition_map[type_name] = _def\n elif isinstance(_def, ast.TypeExtensionDefinition):\n # Sanity check that this type extension exists within the\n # schema's existing types.\n extended_type_name = _def.definition.name.value\n existing_type = schema.get_type(extended_type_name)\n if not existing_type:\n raise GraphQLError(\n (\n 'Cannot extend type \"{}\" because it does not '\n + \"exist in the existing schema.\"\n ).format(extended_type_name),\n [_def.definition],\n )\n if not isinstance(existing_type, GraphQLObjectType):\n raise GraphQLError(\n 'Cannot extend non-object type \"{}\".'.format(extended_type_name),\n [_def.definition],\n )\n\n type_extensions_map[extended_type_name].append(_def)\n\n # Below are functions used for producing this schema that have closed over\n # this scope and have access to the schema, cache, and newly defined types.\n\n def get_type_from_def(type_def):\n type = _get_named_type(type_def.name)\n assert type, \"Invalid schema\"\n return type\n\n def get_type_from_AST(astNode):\n type = _get_named_type(astNode.name.value)\n if not type:\n raise GraphQLError(\n (\n 'Unknown type: \"{}\". Ensure that this type exists '\n + \"either in the original schema, or is added in a type definition.\"\n ).format(astNode.name.value),\n [astNode],\n )\n return type\n\n # Given a name, returns a type from either the existing schema or an\n # added type.\n def _get_named_type(typeName):\n cached_type_def = type_def_cache.get(typeName)\n if cached_type_def:\n return cached_type_def\n\n existing_type = schema.get_type(typeName)\n if existing_type:\n type_def = extend_type(existing_type)\n type_def_cache[typeName] = type_def\n return type_def\n\n type_ast = type_definition_map.get(typeName)\n if type_ast:\n type_def = build_type(type_ast)\n type_def_cache[typeName] = type_def\n return type_def\n\n # Given a type's introspection result, construct the correct\n # GraphQLType instance.\n def extend_type(type):\n if isinstance(type, GraphQLObjectType):\n return extend_object_type(type)\n if isinstance(type, GraphQLInterfaceType):\n return extend_interface_type(type)\n if isinstance(type, GraphQLUnionType):\n return extend_union_type(type)\n return type\n\n def extend_object_type(type):\n return GraphQLObjectType(\n name=type.name,\n description=type.description,\n interfaces=lambda: extend_implemented_interfaces(type),\n fields=lambda: extend_field_map(type),\n )\n\n def extend_interface_type(type):\n return GraphQLInterfaceType(\n name=type.name,\n description=type.description,\n fields=lambda: extend_field_map(type),\n resolve_type=cannot_execute_client_schema,\n )\n\n def extend_union_type(type):\n return GraphQLUnionType(\n name=type.name,\n description=type.description,\n types=list(map(get_type_from_def, type.types)),\n resolve_type=cannot_execute_client_schema,\n )\n\n def extend_implemented_interfaces(type):\n interfaces = list(map(get_type_from_def, type.interfaces))\n\n # If there are any extensions to the interfaces, apply those here.\n extensions = type_extensions_map[type.name]\n for extension in extensions:\n for namedType in extension.definition.interfaces:\n interface_name = namedType.name.value\n if any([_def.name == interface_name for _def in interfaces]):\n raise GraphQLError(\n (\n 'Type \"{}\" already implements \"{}\". '\n + \"It cannot also be implemented in this type extension.\"\n ).format(type.name, interface_name),\n [namedType],\n )\n interfaces.append(get_type_from_AST(namedType))\n\n return interfaces\n\n def extend_field_map(type):\n new_field_map = OrderedDict()\n old_field_map = type.fields\n for field_name, field in old_field_map.items():\n new_field_map[field_name] = GraphQLField(\n extend_field_type(field.type),\n description=field.description,\n deprecation_reason=field.deprecation_reason,\n args=field.args,\n resolver=cannot_execute_client_schema,\n )\n\n # If there are any extensions to the fields, apply those here.\n extensions = type_extensions_map[type.name]\n for extension in extensions:\n for field in extension.definition.fields:\n field_name = field.name.value\n if field_name in old_field_map:\n raise GraphQLError(\n (\n 'Field \"{}.{}\" already exists in the '\n + \"schema. It cannot also be defined in this type extension.\"\n ).format(type.name, field_name),\n [field],\n )\n new_field_map[field_name] = GraphQLField(\n build_field_type(field.type),\n args=build_input_values(field.arguments),\n resolver=cannot_execute_client_schema,\n )\n\n return new_field_map\n\n def extend_field_type(type):\n if isinstance(type, GraphQLList):\n return GraphQLList(extend_field_type(type.of_type))\n if isinstance(type, GraphQLNonNull):\n return GraphQLNonNull(extend_field_type(type.of_type))\n return get_type_from_def(type)\n\n def build_type(type_ast):\n _type_build = {\n ast.ObjectTypeDefinition: build_object_type,\n ast.InterfaceTypeDefinition: build_interface_type,\n ast.UnionTypeDefinition: build_union_type,\n ast.ScalarTypeDefinition: build_scalar_type,\n ast.EnumTypeDefinition: build_enum_type,\n ast.InputObjectTypeDefinition: build_input_object_type,\n }\n func = _type_build.get(type(type_ast))\n if func:\n return func(type_ast)\n\n def build_object_type(type_ast):\n return GraphQLObjectType(\n type_ast.name.value,\n interfaces=lambda: build_implemented_interfaces(type_ast),\n fields=lambda: build_field_map(type_ast),\n )\n\n def build_interface_type(type_ast):\n return GraphQLInterfaceType(\n type_ast.name.value,\n fields=lambda: build_field_map(type_ast),\n resolve_type=cannot_execute_client_schema,\n )\n\n def build_union_type(type_ast):\n return GraphQLUnionType(\n type_ast.name.value,\n types=list(map(get_type_from_AST, type_ast.types)),\n resolve_type=cannot_execute_client_schema,\n )\n\n def build_scalar_type(type_ast):\n return GraphQLScalarType(\n type_ast.name.value,\n serialize=lambda *args, **kwargs: None,\n # Note: validation calls the parse functions to determine if a\n # literal value is correct. Returning null would cause use of custom\n # scalars to always fail validation. Returning false causes them to\n # always pass validation.\n parse_value=lambda *args, **kwargs: False,\n parse_literal=lambda *args, **kwargs: False,\n )\n\n def build_enum_type(type_ast):\n return GraphQLEnumType(\n type_ast.name.value,\n values={v.name.value: GraphQLEnumValue() for v in type_ast.values},\n )\n\n def build_input_object_type(type_ast):\n return GraphQLInputObjectType(\n type_ast.name.value,\n fields=lambda: build_input_values(type_ast.fields, GraphQLInputObjectField),\n )\n\n def build_implemented_interfaces(type_ast):\n return list(map(get_type_from_AST, type_ast.interfaces))\n\n def build_field_map(type_ast):\n return {\n field.name.value: GraphQLField(\n build_field_type(field.type),\n args=build_input_values(field.arguments),\n resolver=cannot_execute_client_schema,\n )\n for field in type_ast.fields\n }\n\n def build_input_values(values, input_type=GraphQLArgument):\n input_values = OrderedDict()\n for value in values:\n type = build_field_type(value.type)\n input_values[value.name.value] = input_type(\n type, default_value=value_from_ast(value.default_value, type)\n )\n return input_values\n\n def build_field_type(type_ast):\n if isinstance(type_ast, ast.ListType):\n return GraphQLList(build_field_type(type_ast.type))\n if isinstance(type_ast, ast.NonNullType):\n return GraphQLNonNull(build_field_type(type_ast.type))\n return get_type_from_AST(type_ast)\n\n # If this document contains no new types, then return the same unmodified\n # GraphQLSchema instance.\n if not type_extensions_map and not type_definition_map:\n return schema\n\n # A cache to use to store the actual GraphQLType definition objects by name.\n # Initialize to the GraphQL built in scalars and introspection types. All\n # functions below are inline so that this type def cache is within the scope\n # of the closure.\n\n type_def_cache = {\n \"String\": GraphQLString,\n \"Int\": GraphQLInt,\n \"Float\": GraphQLFloat,\n \"Boolean\": GraphQLBoolean,\n \"ID\": GraphQLID,\n \"__Schema\": __Schema,\n \"__Directive\": __Directive,\n \"__DirectiveLocation\": __DirectiveLocation,\n \"__Type\": __Type,\n \"__Field\": __Field,\n \"__InputValue\": __InputValue,\n \"__EnumValue\": __EnumValue,\n \"__TypeKind\": __TypeKind,\n }\n\n # Get the root Query, Mutation, and Subscription types.\n query_type = get_type_from_def(schema.get_query_type())\n\n existing_mutation_type = schema.get_mutation_type()\n mutationType = (\n existing_mutation_type and get_type_from_def(existing_mutation_type) or None\n )\n\n existing_subscription_type = schema.get_subscription_type()\n subscription_type = (\n existing_subscription_type\n and get_type_from_def(existing_subscription_type)\n or None\n )\n\n # Iterate through all types, getting the type definition for each, ensuring\n # that any type not directly referenced by a field will get created.\n types = [get_type_from_def(_def) for _def in schema.get_type_map().values()]\n\n # Do the same with new types, appending to the list of defined types.\n types += [get_type_from_AST(_def) for _def in type_definition_map.values()]\n\n # Then produce and return a Schema with these types.\n return GraphQLSchema(\n query=query_type,\n mutation=mutationType,\n subscription=subscription_type,\n # Copy directives.\n directives=schema.get_directives(),\n types=types,\n )","def _swapcolumns(self):\n return self.reindex_axis([self.columns[1], self.columns[0]], axis=1)","def _load_schema(self, mode=\"staging\"):\n\n self._check_mode(mode)\n\n json_path = self.table_folder / f\"schema-{mode}.json\"\n columns = self.table_config[\"columns\"]\n\n if mode == \"staging\":\n new_columns = []\n for c in columns:\n # case is_in_staging are None then must be True\n is_in_staging = (\n True if c.get(\"is_in_staging\") is None else c[\"is_in_staging\"]\n )\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\n if is_in_staging and not c.get(\"is_partition\"):\n c[\"type\"] = \"STRING\"\n new_columns.append(c)\n\n del columns\n columns = new_columns\n\n elif mode == \"prod\":\n schema = self._get_table_obj(mode).schema\n\n # get field names for fields at schema and at table_config.yaml\n column_names = [c[\"name\"] for c in columns]\n schema_names = [s.name for s in schema]\n\n # check if there are mismatched fields\n not_in_columns = [name for name in schema_names if name not in column_names]\n not_in_schema = [name for name in column_names if name not in schema_names]\n\n # raise if field is not in table_config\n if not_in_columns:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in table_config.yaml. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_columns,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # raise if field is not in schema\n if not_in_schema:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in publish.sql. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_schema,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # if field is in schema, get field_type and field_mode\n for c in columns:\n for s in schema:\n if c[\"name\"] == s.name:\n c[\"type\"] = s.field_type\n c[\"mode\"] = s.mode\n break\n ## force utf-8, write schema_{mode}.json\n json.dump(columns, (json_path).open(\"w\", encoding=\"utf-8\"))\n\n # load new created schema\n return self.client[f\"bigquery_{mode}\"].schema_from_json(str(json_path))","async def reload_database(self, schema='conf/schema.sql'):\n with open(schema) as schema:\n await self.dao.build((schema.read()))","def upgrade():\n op.execute(\n \"\"\"\n insert ignore into relationships (\n modified_by_id,\n created_at,\n updated_at,\n source_id,\n source_type,\n destination_id,\n destination_type\n )\n select\n modified_by_id,\n created_at,\n updated_at,\n parent_id as source_id,\n parent_type as source_type,\n child_id as destination_id,\n child_type as destination_type\n from snapshots\n \"\"\"\n )","def upgrade_to_py3(self):\n # Rewrite database metadata pickles to force to version 3.\n for name, (id, attrs, idx) in self._object_types.items():\n self._db_query(\"UPDATE types SET attrs_pickle=?, idx_pickle=? WHERE id=?\", (self._pickle(attrs), self._pickle(idx), id))\n for name, ivtidx in self._inverted_indexes.items():\n self._db_query(\"UPDATE inverted_indexes SET value=? WHERE name=? AND attr=?\", (self._pickle(ivtidx), name, 'definition'))\n self.commit()\n self._readonly = False"],"string":"[\n \"def _GetRelaxedCols(relaxed_columns, orig_schema_map):\\n updated_schema_map = orig_schema_map.copy()\\n for col in relaxed_columns:\\n if col in orig_schema_map:\\n updated_schema_map[col].mode = 'NULLABLE'\\n else:\\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\\n return updated_schema_map\",\n \"async def upgradeSchema(self) -> None:\",\n \"def ProcessSchemaUpdate(ref, args, request):\\n table = request.table\\n relaxed_columns = args.relax_columns\\n if not table.schema and not relaxed_columns: # if not updating schema,\\n return request # then just return.\\n\\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\\n ref.Name(),\\n ref.projectId)\\n\\n new_schema_columns = table.schema\\n updated_fields = _GetUpdatedSchema(original_schema,\\n new_schema_columns,\\n relaxed_columns)\\n\\n table_schema_type = GetApiMessage('TableSchema')\\n request.table.schema = table_schema_type(fields=updated_fields)\\n\\n return request\",\n \"def _add_to_schema(self, new: dict):\\n self._defaults.update(new)\\n self._migrate()\",\n \"def update_schema(self, new_schema):\\n return self.conn.update_schema(new_schema)\",\n \"def _AddNewColsToSchema(new_fields, orig_schema_map):\\n updated_schema_map = orig_schema_map.copy()\\n for new_field in new_fields:\\n if new_field.name in orig_schema_map:\\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\\n updated_schema_map[new_field.name] = new_field\\n return updated_schema_map\",\n \"def rebuild(self, dframe, overwrite=False):\\n current_schema = self\\n new_schema = schema_from_dframe(dframe, self)\\n\\n if current_schema and not overwrite:\\n # merge new schema with existing schema\\n current_schema.update(new_schema)\\n new_schema = current_schema\\n\\n return new_schema\",\n \"def ensure_internal_schema_updated(self):\\n if self._internal_schema_updated:\\n return\\n if internalmigrations.needs_upgrading(self):\\n assert not self._in_transaction\\n with self.lock():\\n internalmigrations.upgrade(self)\\n self.connection.commit()\\n self._internal_schema_updated = True\",\n \"def merge_schema(self, schema):\\n self.validate_schema(schema)\\n\\n if self.exclusive is False:\\n self.exclusive = schema.exclusive\\n\\n if self.default is None:\\n self.default = schema.default\",\n \"def _patch_schema(self):\\n fields = get_json()['data']['attributes'].keys()\\n return make_entity_schema(\\n self.SCHEMA, self.RESOURCE_NAME,\\n make_data_schema(\\n self.SCHEMA, id_required=True,\\n only=fields, partial=True\\n )\\n )\",\n \"def _ensure_schema_has_covariates(self, x_underscore_columns):\\n previous_rename = self.covariate_rename\\n if set(x_underscore_columns) == set(previous_rename.values()):\\n return\\n # Only rewrite schema if the x_<integer> list has changed.\\n # because the schema depends on the number of covariates, not\\n # their names.\\n covariate_columns = list(x_underscore_columns)\\n # ASCII sorting isn't correct b/c x_11 is before x_2.\\n covariate_columns.sort(key=lambda x: int(x[2:]))\\n for create_name in [\\\"data\\\", \\\"avgint\\\"]:\\n empty = self.dismod_file.empty_table(create_name)\\n without = [c for c in empty.columns if not c.startswith(\\\"x_\\\")]\\n # The wrapper needs these columns to have a dtype of Real.\\n empty = empty[without].assign(**{cname: np.empty((0,), dtype=np.float) for cname in covariate_columns})\\n self.dismod_file.update_table_columns(create_name, empty)\\n if getattr(self.dismod_file, create_name).empty:\\n CODELOG.debug(f\\\"Writing empty {create_name} table with columns {covariate_columns}\\\")\\n setattr(self.dismod_file, create_name, empty)\\n else:\\n CODELOG.debug(f\\\"Adding to {create_name} table schema the columns {covariate_columns}\\\")\",\n \"def upgrade_schema():\\n\\n db_version = get_db_version()\\n try:\\n while db_version < CURRENT_DATABASE_VERSION:\\n db_version += 1\\n upgrade_script = 'upgrade_to_'+str(db_version)\\n globals()[upgrade_script]()\\n except KeyError as e:\\n logging.exception('Attempted to upgrade using script that does not exist: {}'.format(e))\\n sys.exit(1)\\n except Exception as e:\\n logging.exception('Incremental upgrade of db failed')\\n sys.exit(1)\\n else:\\n config.db.singletons.update_one({'_id': 'version'}, {'$set': {'database': CURRENT_DATABASE_VERSION}})\\n sys.exit(0)\",\n \"def make_schema_changes(self, session, namespace='ns1'):\\n debug(\\\"make_schema_changes() \\\" + str(namespace))\\n session.execute('USE ks_%s' % namespace)\\n # drop keyspace\\n session.execute('DROP KEYSPACE ks2_%s' % namespace)\\n wait(2)\\n\\n # create keyspace\\n self.create_ks(session, \\\"ks3_%s\\\" % namespace, 2)\\n session.execute('USE ks_%s' % namespace)\\n\\n wait(2)\\n # drop column family\\n session.execute(\\\"DROP COLUMNFAMILY cf2_%s\\\" % namespace)\\n\\n # create column family\\n query = \\\"\\\"\\\"\\n CREATE TABLE cf3_%s (\\n col1 uuid PRIMARY KEY,\\n col2 text,\\n col3 text,\\n col4 text\\n );\\n \\\"\\\"\\\" % (namespace)\\n session.execute(query)\\n\\n # alter column family\\n query = \\\"\\\"\\\"\\n ALTER COLUMNFAMILY cf_%s\\n ADD col4 text;\\n \\\"\\\"\\\" % namespace\\n session.execute(query)\\n\\n # add index\\n session.execute(\\\"CREATE INDEX index2_%s ON cf_%s(col3)\\\"%(namespace, namespace))\\n\\n # remove an index\\n session.execute(\\\"DROP INDEX index_%s\\\" % namespace)\",\n \"def recreate_db(self, run=False):\\n if run:\\n db_schema = open(self.db_schema_file).read().splitlines()\\n for s in db_schema:\\n t = s.strip()\\n if len(t):\\n self.cur.execute(t)\",\n \"def build_schema(self, dframe, overwrite=False, set_num_columns=True):\\n new_schema = self.schema.rebuild(dframe, overwrite)\\n self.set_schema(new_schema,\\n set_num_columns=(set_num_columns or overwrite))\",\n \"def update(self, schema: 'Schema'):\\n self._update(schema)\",\n \"def modify_tbl(self):\\n debug = False\\n dd = mg.DATADETS_OBJ\\n orig_tblname = dd.tbl\\n ## other (i.e. not the sofa_id) field details\\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\\n if debug:\\n print('oth_name_types to feed into '\\n f'make_strict_typing_tbl {oth_name_types}')\\n try: ## 1 way or other must do strict_cleanup()\\n make_strict_typing_tbl(\\n orig_tblname, oth_name_types, self.settings_data)\\n except sqlite.IntegrityError as e: #@UndefinedVariable\\n if debug: print(b.ue(e))\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise FldMismatchException\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise Exception('Problem making strictly-typed table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n copy_orig_tbl(orig_tblname)\\n wipe_tbl(orig_tblname)\\n final_name = self.tblname_lst[0] ## may have been renamed\\n try:\\n make_redesigned_tbl(final_name, oth_name_types)\\n strict_cleanup(restore_tblname=final_name)\\n dd.set_tbl(tbl=final_name)\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\\n dd.set_tbl(tbl=orig_tblname)\\n raise Exception('Problem making redesigned table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n wipe_tbl(mg.TMP_TBLNAME2)\",\n \"def merge_schema(self, schema):\\n for _, attr_schema in schema.iter_attributes():\\n self.merge_attribute_schema(attr_schema)\",\n \"def update(self, force=False):\\n if (self.__fields is None) or force:\\n self.__fields = [f for f in self.dbms.fields(self.table, self.db)]\",\n \"def reset_schema_defs():\\n SCHEMA_DEFS.clear()\\n SCHEMA_DEFS.update((typ, typ) for typ in PRIMITIVE_TYPES)\",\n \"def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\\n old_info = old_schema_entry['info']\\n new_info = new_schema_entry['info']\\n old_mode = old_info['mode']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_status = old_schema_entry['status']\\n new_mode = new_info['mode']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_status = new_schema_entry['status']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # If the old field is a REQUIRED primitive (which could only have come\\n # from an existing schema), the new field can be either a\\n # NULLABLE(filled) or a NULLABLE(unfilled).\\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\\n # If the new field is filled, then retain the REQUIRED.\\n if new_schema_entry['filled']:\\n return old_mode\\n else:\\n # The new field is not filled (i.e. an empty or null field).\\n # If --infer_mode is active, then we allow the REQUIRED to\\n # revert back to NULLABLE.\\n if self.infer_mode:\\n return new_mode\\n else:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode.'\\n ' cannot convert to NULLABLE because infer_schema not'\\n ' set:'\\n f' old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n elif old_mode != new_mode:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode: '\\n f'old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n return old_mode\",\n \"def initialize_schema(self, dry_run=False):\\n if not dry_run:\\n self.flush()\",\n \"def modify_bigquery_schema(self, schema, info_keys):\\n # type: (bigquery.TableSchema, Set[str]) -> None\",\n \"def merge_schema_entry(\\n self,\\n old_schema_entry,\\n new_schema_entry,\\n base_path=None,\\n ):\\n if not old_schema_entry:\\n return new_schema_entry\\n\\n # If the new schema is None, return immediately.\\n if not new_schema_entry:\\n return new_schema_entry\\n\\n # If a field value is missing, permanently set 'filled' to False.\\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\\n old_schema_entry['filled'] = False\\n new_schema_entry['filled'] = False\\n\\n old_status = old_schema_entry['status']\\n new_status = new_schema_entry['status']\\n\\n # new 'soft' does not clobber old 'hard'\\n if old_status == 'hard' and new_status == 'soft':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n old_schema_entry['info']['mode'] = mode\\n return old_schema_entry\\n\\n # new 'hard' clobbers old 'soft'\\n if old_status == 'soft' and new_status == 'hard':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n new_schema_entry['info']['mode'] = mode\\n return new_schema_entry\\n\\n # Verify that it's soft->soft or hard->hard\\n if old_status != new_status:\\n raise Exception(\\n f'Unexpected schema_entry type, this should never happen: '\\n f'old ({old_status}); new ({new_status})'\\n )\\n\\n old_info = old_schema_entry['info']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_mode = old_info['mode']\\n new_info = new_schema_entry['info']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_mode = new_info['mode']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # Defensive check, names should always be the same.\\n if old_name != new_name:\\n if old_name.lower() != new_name.lower():\\n raise Exception(\\n 'Unexpected difference in name, should never happen:'\\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\\n )\\n else:\\n # preserve old name if case is different\\n new_info['name'] = old_info['name']\\n\\n # Recursively merge in the subfields of a RECORD, allowing\\n # NULLABLE to become REPEATED (because 'bq load' allows it).\\n if old_type == 'RECORD' and new_type == 'RECORD':\\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\\n # 'bq load' allows it.\\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\\n old_info['mode'] = 'REPEATED'\\n self.log_error(\\n f'Converting schema for \\\"{full_old_name}\\\" from '\\n 'NULLABLE RECORD into REPEATED RECORD'\\n )\\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\\n # TODO: Maybe remove this warning output. It was helpful during\\n # development, but maybe it's just natural.\\n self.log_error(\\n f'Leaving schema for \\\"{full_old_name}\\\" as REPEATED RECORD'\\n )\\n\\n # RECORD type needs a recursive merging of sub-fields. We merge into\\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\\n # can be modified in situ.\\n old_fields = old_info['fields']\\n new_fields = new_info['fields']\\n for key, new_entry in new_fields.items():\\n old_entry = old_fields.get(key)\\n new_base_path = json_full_path(base_path, old_name)\\n old_fields[key] = self.merge_schema_entry(\\n old_schema_entry=old_entry,\\n new_schema_entry=new_entry,\\n base_path=new_base_path,\\n )\\n return old_schema_entry\\n\\n new_mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if new_mode is None:\\n return None\\n new_schema_entry['info']['mode'] = new_mode\\n\\n # For all other types...\\n if old_type != new_type:\\n # Check that the converted types are compatible.\\n candidate_type = convert_type(old_type, new_type)\\n if not candidate_type:\\n self.log_error(\\n f'Ignoring field with mismatched type: '\\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\\n )\\n return None\\n\\n new_info['type'] = candidate_type\\n return new_schema_entry\",\n \"def add_column(self, schema):\\n self[schema.name] = schema.copy()\",\n \"def fix_incremental(meta, bind):\\n meta.create_all(bind=bind, checkfirst=True)\\n ref = inspect(bind)\\n for table in meta.sorted_tables:\\n orm_cols = set(col.name for col in table.c)\\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\\n col_to_create = orm_cols - ref_cols\\n col_to_delete = ref_cols - orm_cols\\n if col_to_create:\\n print table.name, 'has diff to create', col_to_create\\n with bind.begin() as conn:\\n for col_name in col_to_create:\\n col = table.c.get(col_name)\\n column_sql = CreateColumn(col).compile(bind).string\\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\\n if col.default:\\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\\n if not col.nullable:\\n sql += ' NOT NULL'\\n print 'executing sql: ' + sql\\n conn.execute(sql)\\n\\n # Workaround to ensure updated DBs start with \\\"False\\\" in ignore column\\n if list(col_to_create)[0] == 'ignore':\\n sessionmaker = get_sessionmaker(bind.url.database)\\n session = sessionmaker()\\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\\n items = session.query(query_object).all()\\n for item in items:\\n item.ignore = False\\n session.flush()\\n\\n if col_to_delete:\\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\\n \\\"\\\"\\\"\\n BEGIN TRANSACTION;\\n CREATE TEMPORARY TABLE t1_backup(a,b);\\n INSERT INTO t1_backup SELECT a,b FROM t1;\\n DROP TABLE t1;\\n CREATE TABLE t1(a,b);\\n INSERT INTO t1 SELECT a,b FROM t1_backup;\\n DROP TABLE t1_backup;\\n COMMIT;\\n \\\"\\\"\\\"\",\n \"def compute_schema_updates(self):\\n data = self.client._perform_json(\\n \\\"GET\\\", \\\"/projects/%s/recipes/%s/schema-update\\\" % (self.project_key, self.recipe_name))\\n return RequiredSchemaUpdates(self, data)\",\n \"def has_desired_schema(self):\\n if self._new_table == self._old_table:\\n if not self.rebuild:\\n log.info(\\\"Table already has the desired schema. \\\")\\n return True\\n else:\\n log.info(\\n \\\"Table already has the desired schema. However \\\"\\n \\\"--rebuild is specified, doing a rebuild instead\\\"\\n )\\n return False\\n return False\",\n \"def modify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\\n\\n return provision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)\",\n \"def merge_schema(self, schema):\\n super(BooleanAttributeSchema, self).merge_schema(schema)\\n self.values.update(schema.values)\",\n \"def update(self):\\n current = LazyRegister(self.db)\\n current.render()\\n cur = self.db.cursor()\\n for table in self.tables:\\n if table in current.tables:\\n additions, removals = current.tables[table].migrate(self.tables[table])\\n for addition in additions:\\n cur.execute(\\\"\\\"\\\"ALTER TABLE %s ADD COLUMN %s\\\"\\\"\\\" % (\\n table, addition[1].get_sql()\\n ))\\n print('Added column: ', addition[0])\\n for removal in removals:\\n #cur.execute(\\\"\\\"\\\"ALTER TABLE %s DROP COLUMN %s\\\"\\\"\\\" % (\\n # table, removal[0]\\n #))\\n #print('Removed column: ', removal[0])\\n print('Did not removed column: ', removal[0])\\n else:\\n schema = self.tables[table].get_create_table_sql()\\n cur.execute(schema)\\n print('Added table %s' % table)\",\n \"def schema(self, schema):\\n self._schema = schema\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def upgrade():\\n op.execute(\\n f\\\"\\\"\\\"\\n ALTER TABLE\\n {config.CLEAN_SCHEMA}.forecasts\\n RENAME COLUMN\\n training_horizon\\n TO\\n train_horizon;\\n \\\"\\\"\\\",\\n ) # noqa:WPS355\",\n \"def update_schema(self, engine_name, schema):\\n endpoint = \\\"engines/{}/schema\\\".format(engine_name)\\n data = json.dumps(schema)\\n return self.swiftype_session.request('post', endpoint, data=data)\",\n \"def filter_schema(schema):\\n for column, column_schema in schema.iteritems():\\n if column_schema.get(CARDINALITY):\\n del column_schema[CARDINALITY]\\n schema[column] = column_schema\\n\\n return schema\",\n \"def set_schema(self, schema, set_num_columns=True):\\n update_dict = {self.SCHEMA: schema}\\n\\n if set_num_columns:\\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\\n\\n self.update(update_dict)\",\n \"def finalizeSchema(schema, folderish=False, moveDiscussion=True):\\n schema.moveField('businessOldLocation', after='workLocations')\\n schema.moveField('foldermanagers', after='businessOldLocation')\\n# schema.moveField('bound_licences', after='isTransferOfLicence')\\n schema.moveField('rubrics', after='folderCategory')\\n schema.moveField('description', after='additionalLegalConditions')\\n schema.moveField('referenceFT', after='referenceDGATLP')\\n schema.moveField('isTransferOfLicence', after='referenceFT')\\n\\n return schema\",\n \"def _alter_field(\\n self,\\n model,\\n old_field,\\n new_field,\\n old_type,\\n new_type,\\n old_db_params,\\n new_db_params,\\n strict=False,\\n ):\\n\\n super()._alter_field(\\n model,\\n old_field,\\n new_field,\\n old_type,\\n new_type,\\n old_db_params,\\n new_db_params,\\n strict,\\n )\\n\\n # If the pkey was dropped in the previous distribute migration,\\n # foreign key constraints didn't previously exists so django does not\\n # recreated them.\\n # Here we test if we are in this case\\n if isinstance(new_field, TenantForeignKey) and new_field.db_constraint:\\n from_model = get_model_by_db_table(model._meta.db_table)\\n fk_names = self._constraint_names(\\n model, [new_field.column], foreign_key=True\\n ) + self._constraint_names(\\n model,\\n [new_field.column, get_tenant_column(from_model)],\\n foreign_key=True,\\n )\\n if not fk_names:\\n self.execute(\\n self._create_fk_sql(\\n model, new_field, \\\"_fk_%(to_table)s_%(to_column)s\\\"\\n )\\n )\",\n \"def merge_attribute_schema(self, attr_schema):\\n name = attr_schema.name\\n if name not in self.schema:\\n self.schema[name] = attr_schema\\n else:\\n self.schema[name].merge_schema(attr_schema)\",\n \"def setAllColumns(self, newAllColumns):\\n \\n pass\",\n \"def _clean_up_columns(\\n self):\\n self.log.debug('starting the ``_clean_up_columns`` method')\\n\\n tableName = self.dbTableName\\n\\n print \\\"cleaning up %(tableName)s columns\\\" % locals()\\n\\n sqlQuery = u\\\"\\\"\\\"\\n set sql_mode=\\\"STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION\\\";\\n \\\"\\\"\\\" % locals()\\n writequery(\\n log=self.log,\\n sqlQuery=sqlQuery,\\n dbConn=self.cataloguesDbConn,\\n )\\n\\n sqlQuery = u\\\"\\\"\\\"\\n update %(tableName)s set dist_mod_err = null where dist_mod_err = 0;\\n update %(tableName)s set dist_in_ned_flag = null where dist_in_ned_flag = \\\"\\\";\\n update %(tableName)s set notes = null where notes = \\\"\\\";\\n update %(tableName)s set redshift = null where redshift = 0;\\n update %(tableName)s set dist_derived_from_sn = null where dist_derived_from_sn = \\\"\\\";\\n update %(tableName)s set hubble_const = null where hubble_const = 0;\\n update %(tableName)s set lmc_mod = null where lmc_mod = 0;\\n update %(tableName)s set master_row = 0;\\n update %(tableName)s set master_row = 1 where primaryId in (select * from (select distinct primaryId from %(tableName)s group by galaxy_index_id) as alias);\\n \\\"\\\"\\\" % locals()\\n writequery(\\n log=self.log,\\n sqlQuery=sqlQuery,\\n dbConn=self.cataloguesDbConn,\\n )\\n\\n self.log.debug('completed the ``_clean_up_columns`` method')\\n return None\",\n \"def apply_to(self, df: pd.DataFrame) -> pd.DataFrame:\\n schema_names = self.names\\n data_columns = df.columns\\n\\n assert len(schema_names) == len(\\n data_columns\\n ), \\\"schema column count does not match input data column count\\\"\\n\\n for column, dtype in zip(data_columns, self.types):\\n pandas_dtype = dtype.to_pandas()\\n\\n col = df[column]\\n col_dtype = col.dtype\\n\\n try:\\n not_equal = pandas_dtype != col_dtype\\n except TypeError:\\n # ugh, we can't compare dtypes coming from pandas,\\n # assume not equal\\n not_equal = True\\n\\n if not_equal or not dtype.is_primitive():\\n new_col = convert(col_dtype, dtype, col)\\n else:\\n new_col = col\\n df[column] = new_col\\n\\n # return data with the schema's columns which may be different than the\\n # input columns\\n df.columns = schema_names\\n return df\",\n \"def generate_altered_fields(self):\\n result = super(MigrationAutodetector, self).generate_altered_fields()\\n self.generate_sql_changes()\\n return result\",\n \"def apply_patch():\\n assert BaseDatabaseSchemaEditor is not None\\n\\n def _create_unique_sql(self, *args, **kwargs):\\n from django.db.backends.ddl_references import IndexName\\n\\n statement = orig_create_unique_sql(self, *args, **kwargs)\\n\\n if statement is not None:\\n index_name = statement.parts['name']\\n\\n if (isinstance(index_name, IndexName) and\\n index_name.create_index_name == self._create_index_name):\\n # The result will be unquoted. Let's quote it.\\n index_name.create_index_name = lambda *args, **kwargs: \\\\\\n self.quote_name(self._create_index_name(*args, **kwargs))\\n\\n return statement\\n\\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql\",\n \"def upgrade():\\n with op.batch_alter_table(\\\"slot_pool\\\") as batch_op:\\n batch_op.add_column(sa.Column(\\\"include_deferred\\\", sa.Boolean))\\n # Different databases support different literal for FALSE. This is fine.\\n op.execute(sa.text(f\\\"UPDATE slot_pool SET include_deferred = {sa.false().compile(op.get_bind())}\\\"))\\n with op.batch_alter_table(\\\"slot_pool\\\") as batch_op:\\n batch_op.alter_column(\\\"include_deferred\\\", existing_type=sa.Boolean, nullable=False)\",\n \"def db_schema_32():\\n with old_db_schema(\\\"32\\\"):\\n yield\",\n \"def update_table_columns(self, table_name, table):\\n table_definition = self._table_definitions[table_name]\\n new_columns = table.columns.difference(table_definition.c.keys())\\n new_column_types = {c: table.dtypes[c] for c in new_columns}\\n\\n allows_covariates = table_definition.name in [\\\"avgint\\\", \\\"data\\\"]\\n\\n good_prefixes = [\\\"c_\\\"]\\n if allows_covariates:\\n good_prefixes.append(\\\"x_\\\")\\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\\n if bad_column_names:\\n msg = f\\\"\\\"\\\"\\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\\n It allows additional comment columns, which must start 'c_'.\\\"\\\"\\\"\\n if allows_covariates:\\n msg += \\\" In addition it allows covariate columns, which must start with 'x_'.\\\"\\n msg += f\\\" You supplied columns that don't meet those requirements: {bad_column_names}\\\"\\n\\n raise ValueError(dedent(msg))\\n\\n add_columns_to_table(table_definition, new_column_types)\",\n \"def set_schema(self, schema):\\r\\n self.__schema = schema\",\n \"def extend_schema(\\n schema: GraphQLSchema,\\n document_ast: DocumentNode,\\n assume_valid=False,\\n assume_valid_sdl=False,\\n) -> GraphQLSchema:\\n assert_schema(schema)\\n\\n if not isinstance(document_ast, DocumentNode):\\n \\\"Must provide valid Document AST\\\"\\n\\n if not (assume_valid or assume_valid_sdl):\\n from ..validation.validate import assert_valid_sdl_extension\\n\\n assert_valid_sdl_extension(document_ast, schema)\\n\\n # Collect the type definitions and extensions found in the document.\\n type_defs: List[TypeDefinitionNode] = []\\n type_exts_map: Dict[str, Any] = defaultdict(list)\\n\\n # New directives and types are separate because a directives and types can have the\\n # same name. For example, a type named \\\"skip\\\".\\n directive_defs: List[DirectiveDefinitionNode] = []\\n\\n schema_def: Optional[SchemaDefinitionNode] = None\\n # Schema extensions are collected which may add additional operation types.\\n schema_exts: List[SchemaExtensionNode] = []\\n\\n for def_ in document_ast.definitions:\\n if isinstance(def_, SchemaDefinitionNode):\\n schema_def = def_\\n elif isinstance(def_, SchemaExtensionNode):\\n schema_exts.append(def_)\\n elif isinstance(def_, TypeDefinitionNode):\\n type_defs.append(def_)\\n elif isinstance(def_, TypeExtensionNode):\\n extended_type_name = def_.name.value\\n type_exts_map[extended_type_name].append(def_)\\n elif isinstance(def_, DirectiveDefinitionNode):\\n directive_defs.append(def_)\\n\\n # If this document contains no new types, extensions, or directives then return the\\n # same unmodified GraphQLSchema instance.\\n if (\\n not type_exts_map\\n and not type_defs\\n and not directive_defs\\n and not schema_exts\\n and not schema_def\\n ):\\n return schema\\n\\n # Below are functions used for producing this schema that have closed over this\\n # scope and have access to the schema, cache, and newly defined types.\\n\\n # noinspection PyTypeChecker,PyUnresolvedReferences\\n def replace_type(type_: GraphQLType) -> GraphQLType:\\n if is_list_type(type_):\\n return GraphQLList(replace_type(type_.of_type)) # type: ignore\\n if is_non_null_type(type_):\\n return GraphQLNonNull(replace_type(type_.of_type)) # type: ignore\\n return replace_named_type(type_) # type: ignore\\n\\n def replace_named_type(type_: GraphQLNamedType) -> GraphQLNamedType:\\n return type_map[type_.name]\\n\\n def get_maybe_type_by_name(type_name: Optional[str]) -> Optional[GraphQLNamedType]:\\n return type_map[type_name] if type_name else None\\n\\n def get_merged_directives() -> List[GraphQLDirective]:\\n if not schema.directives:\\n raise TypeError(\\\"schema must have default directives\\\")\\n\\n return list(\\n chain(\\n map(extend_directive, schema.directives),\\n map(ast_builder.build_directive, directive_defs),\\n )\\n )\\n\\n def extend_named_type(type_: GraphQLNamedType) -> GraphQLNamedType:\\n if is_introspection_type(type_) or is_specified_scalar_type(type_):\\n # Builtin types are not extended.\\n return type_\\n if is_scalar_type(type_):\\n type_ = cast(GraphQLScalarType, type_)\\n return extend_scalar_type(type_)\\n if is_object_type(type_):\\n type_ = cast(GraphQLObjectType, type_)\\n return extend_object_type(type_)\\n if is_interface_type(type_):\\n type_ = cast(GraphQLInterfaceType, type_)\\n return extend_interface_type(type_)\\n if is_union_type(type_):\\n type_ = cast(GraphQLUnionType, type_)\\n return extend_union_type(type_)\\n if is_enum_type(type_):\\n type_ = cast(GraphQLEnumType, type_)\\n return extend_enum_type(type_)\\n if is_input_object_type(type_):\\n type_ = cast(GraphQLInputObjectType, type_)\\n return extend_input_object_type(type_)\\n\\n # Not reachable. All possible types have been considered.\\n raise TypeError(f\\\"Unexpected type: '{inspect(type_)}'.\\\") # pragma: no cover\\n\\n def extend_directive(directive: GraphQLDirective) -> GraphQLDirective:\\n kwargs = directive.to_kwargs()\\n return GraphQLDirective( # type: ignore\\n **{\\n **kwargs,\\n \\\"args\\\": {name: extend_arg(arg) for name, arg in kwargs[\\\"args\\\"].items()},\\n }\\n )\\n\\n def extend_input_object_type(\\n type_: GraphQLInputObjectType\\n ) -> GraphQLInputObjectType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\\n\\n return GraphQLInputObjectType(\\n **{\\n **kwargs,\\n \\\"fields\\\": lambda: {\\n **{\\n name: GraphQLInputField( # type: ignore\\n **{**field.to_kwargs(), \\\"type_\\\": replace_type(field.type)}\\n )\\n for name, field in kwargs[\\\"fields\\\"].items()\\n },\\n **{\\n field.name.value: ast_builder.build_input_field(field)\\n for field in field_nodes\\n },\\n },\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_enum_type(type_: GraphQLEnumType) -> GraphQLEnumType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n value_nodes = chain.from_iterable(node.values or [] for node in extensions)\\n\\n return GraphQLEnumType(\\n **{\\n **kwargs,\\n \\\"values\\\": {\\n **kwargs[\\\"values\\\"],\\n **{\\n value.name.value: ast_builder.build_enum_value(value)\\n for value in value_nodes\\n },\\n },\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_scalar_type(type_: GraphQLScalarType) -> GraphQLScalarType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n\\n return GraphQLScalarType(\\n **{\\n **kwargs,\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_object_type(type_: GraphQLObjectType) -> GraphQLObjectType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n interface_nodes = chain.from_iterable(\\n node.interfaces or [] for node in extensions\\n )\\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\\n\\n return GraphQLObjectType(\\n **{\\n **kwargs,\\n \\\"interfaces\\\": lambda: [\\n replace_named_type(interface) for interface in kwargs[\\\"interfaces\\\"]\\n ]\\n # Note: While this could make early assertions to get the correctly\\n # typed values, that would throw immediately while type system\\n # validation with validate_schema will produce more actionable results.\\n + [ast_builder.get_named_type(node) for node in interface_nodes],\\n \\\"fields\\\": lambda: {\\n **{\\n name: extend_field(field)\\n for name, field in kwargs[\\\"fields\\\"].items()\\n },\\n **{\\n node.name.value: ast_builder.build_field(node)\\n for node in field_nodes\\n },\\n },\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_interface_type(type_: GraphQLInterfaceType) -> GraphQLInterfaceType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n field_nodes = chain.from_iterable(node.fields or [] for node in extensions)\\n\\n return GraphQLInterfaceType(\\n **{\\n **kwargs,\\n \\\"fields\\\": lambda: {\\n **{\\n name: extend_field(field)\\n for name, field in kwargs[\\\"fields\\\"].items()\\n },\\n **{\\n node.name.value: ast_builder.build_field(node)\\n for node in field_nodes\\n },\\n },\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_union_type(type_: GraphQLUnionType) -> GraphQLUnionType:\\n kwargs = type_.to_kwargs()\\n extensions = type_exts_map.get(kwargs[\\\"name\\\"], [])\\n type_nodes = chain.from_iterable(node.types or [] for node in extensions)\\n\\n return GraphQLUnionType(\\n **{\\n **kwargs,\\n \\\"types\\\": lambda: [\\n replace_named_type(member_type) for member_type in kwargs[\\\"types\\\"]\\n ]\\n # Note: While this could make early assertions to get the correctly\\n # typed values, that would throw immediately while type system\\n # validation with validate_schema will produce more actionable results.\\n + [ast_builder.get_named_type(node) for node in type_nodes],\\n \\\"extension_ast_nodes\\\": kwargs[\\\"extension_ast_nodes\\\"] + extensions,\\n }\\n )\\n\\n def extend_field(field: GraphQLField) -> GraphQLField:\\n return GraphQLField( # type: ignore\\n **{\\n **field.to_kwargs(),\\n \\\"type_\\\": replace_type(field.type),\\n \\\"args\\\": {name: extend_arg(arg) for name, arg in field.args.items()},\\n }\\n )\\n\\n def extend_arg(arg: GraphQLArgument) -> GraphQLArgument:\\n return GraphQLArgument( # type: ignore\\n **{**arg.to_kwargs(), \\\"type_\\\": replace_type(arg.type)}\\n )\\n\\n # noinspection PyShadowingNames\\n def resolve_type(type_name: str) -> GraphQLNamedType:\\n type_ = type_map.get(type_name)\\n if not type_:\\n raise TypeError(f\\\"Unknown type: '{type_name}'.\\\")\\n return type_\\n\\n ast_builder = ASTDefinitionBuilder(\\n assume_valid=assume_valid, resolve_type=resolve_type\\n )\\n\\n type_map = {node.name.value: ast_builder.build_type(node) for node in type_defs}\\n for existing_type_name, existing_type in schema.type_map.items():\\n type_map[existing_type_name] = extend_named_type(existing_type)\\n\\n # Get the extended root operation types.\\n operation_types: Dict[OperationType, Optional[str]] = {\\n OperationType.QUERY: schema.query_type.name if schema.query_type else None,\\n OperationType.MUTATION: schema.mutation_type.name\\n if schema.mutation_type\\n else None,\\n OperationType.SUBSCRIPTION: schema.subscription_type.name\\n if schema.subscription_type\\n else None,\\n }\\n\\n if schema_def:\\n for operation_type in schema_def.operation_types:\\n operation = operation_type.operation\\n operation_types[operation] = operation_type.type.name.value\\n\\n # Then, incorporate schema definition and all schema extensions.\\n for schema_ext in schema_exts:\\n if schema_ext.operation_types:\\n for operation_type in schema_ext.operation_types:\\n operation = operation_type.operation\\n operation_types[operation] = operation_type.type.name.value\\n\\n # Then produce and return a Schema with these types.\\n return GraphQLSchema( # type: ignore\\n # Note: While this could make early assertions to get the correctly\\n # typed values, that would throw immediately while type system\\n # validation with validateSchema() will produce more actionable results.\\n query=get_maybe_type_by_name(operation_types[OperationType.QUERY]),\\n mutation=get_maybe_type_by_name(operation_types[OperationType.MUTATION]),\\n subscription=get_maybe_type_by_name(\\n operation_types[OperationType.SUBSCRIPTION]\\n ),\\n types=list(type_map.values()),\\n directives=get_merged_directives(),\\n ast_node=schema_def or schema.ast_node,\\n extension_ast_nodes=(\\n (\\n schema.extension_ast_nodes\\n or cast(FrozenList[SchemaExtensionNode], FrozenList())\\n )\\n + schema_exts\\n )\\n or None,\\n )\",\n \"def test_compare_schemas_happypath(self):\\n status = schema_utils.compare_schemas(\\n self.base_schema,\\n self.base_schema\\n )\\n\\n assert status == schema_utils.Update.no_update\",\n \"def correct_db_schema_precision(\\n instance: Recorder,\\n table_object: type[DeclarativeBase],\\n schema_errors: set[str],\\n) -> None:\\n table_name = table_object.__tablename__\\n\\n if f\\\"{table_name}.double precision\\\" in schema_errors:\\n from ..migration import ( # pylint: disable=import-outside-toplevel\\n _modify_columns,\\n )\\n\\n precision_columns = _get_precision_column_types(table_object)\\n # Attempt to convert timestamp columns to µs precision\\n session_maker = instance.get_session\\n engine = instance.engine\\n assert engine is not None, \\\"Engine should be set\\\"\\n _modify_columns(\\n session_maker,\\n engine,\\n table_name,\\n [f\\\"{column} {DOUBLE_PRECISION_TYPE_SQL}\\\" for column in precision_columns],\\n )\",\n \"def _update(self, schema: 'Schema'):\\n for method in schema._get_methods():\\n if method.id in self:\\n raise ValueError(\\n f\\\"Duplicate method id for {method.method} id: {method.id}\\\"\\n )\\n\\n for combinator in schema._get_combinators():\\n if combinator.id in self:\\n raise ValueError(\\n f\\\"Duplicate combinator id for {combinator.predicate} \\\" +\\n f\\\"id: {combinator.id}\\\"\\n )\\n\\n self.constructors += schema.constructors\\n self.functions += schema.functions\\n\\n self._build_schema_data()\",\n \"def upgrade():\\n op.add_column(\\n 'wish', sa.Column(\\n 'admin_votes_num', sa.Integer(), server_default='0',\\n nullable=True))\\n op.add_column(\\n 'wish', sa.Column('real_votes_num', sa.Integer(), nullable=True))\\n op.execute('UPDATE wish SET real_votes_num = votes_num')\\n op.drop_column('wish', 'votes_num')\",\n \"def merge_schemas(self, old_schm, new_schm):\\n\\n old_schm_cols = [x['name'] for x in old_schm]\\n\\n for col in new_schm:\\n if type(col) == dict:\\n if col['name'] not in old_schm_cols:\\n old_schm.append(col)\\n \\n for count, old_col in enumerate(old_schm):\\n for meta in old_col:\\n if type(old_col[meta]) == list:\\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\\n if meta in new_col:\\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\\n \\n return old_schm\",\n \"def update_2xto30():\\r\\n if db_version > 300:\\r\\n log.debug('Database newer than schema version 300.')\\r\\n return # No update needed\\r\\n\\r\\n log.debug('Updating to schema 300.')\\r\\n QtSql.QSqlQuery('ALTER TABLE presentations RENAME TO presentations_old') # temporary table\\r\\n self.__create_presentations_table(PRESENTATIONS_SCHEMA_300)\\r\\n QtSql.QSqlQuery(\\\"\\\"\\\"INSERT INTO presentations\\r\\n SELECT Id, Title, Speaker, Description, Level, Event, Room, Time FROM presentations_old\\\"\\\"\\\")\\r\\n QtSql.QSqlQuery('DROP TABLE presentations_old')\",\n \"def _migrate_if_necessary(self, entries):\\r\\n entries = [\\r\\n self._migrate[entry.get('schema', 0)](self, entry)\\r\\n for entry in entries\\r\\n ]\\r\\n return entries\",\n \"def upgrade():\\n\\n conn = op.get_bind()\\n invalid_acr = get_invalid_acrs(conn, models_names)\\n\\n if invalid_acr:\\n invalid_acr_ids = [x.id for x in invalid_acr]\\n add_to_objects_without_revisions_bulk(conn,\\n invalid_acr_ids,\\n acr,\\n \\\"deleted\\\")\\n delete_invalid_acr(conn, models_names)\",\n \"def fix_all(self):\\n\\n altered_tables = {}\\n\\n for ingestible_db_conf in self.ingestible_db_conf_repo.get_ingestible_dbs():\\n target_db= ingestible_db_conf.target_db_name\\n db_type = ingestible_db_conf.db_type\\n self.logger.info(\\\"Fixing consistency for DB Type: %s, Target DB: %s\\\" % (db_type, target_db))\\n self.prepare_database(target_db)\\n consistency_checker = HiveConsistencyChecker(target_db, db_type)\\n\\n unused_tables = consistency_checker.get_unused_tables()\\n self.remove_unused_tables(unused_tables)\\n\\n new_tables = consistency_checker.get_new_tables()\\n self.create_new_tables(new_tables)\\n\\n inconsistent_tables = consistency_checker.get_inconsistent_tables()\\n self.fix_inconsistent_tables(inconsistent_tables, db_type)\\n\\n # Combine lists of inconsistent and unused tables\\n altered_tables[db_type] = map(lambda qualified_table: qualified_table.split(\\\".\\\")[1],\\n inconsistent_tables.keys() + unused_tables)\\n\\n self.logger.debug(\\\"Altered Tables: %s\\\" % altered_tables)\\n return altered_tables\",\n \"def setup_schema(self):\\n models.Base.metadata.create_all(self.session.bind)\",\n \"def schema_upgrades():\\n op.create_table('vpp_licenses',\\n sa.Column('license_id', sa.Integer(), nullable=False),\\n sa.Column('adam_id', sa.String(), nullable=True),\\n sa.Column('product_type', sa.Enum('Software', 'Application', 'Publication', name='vppproducttype'), nullable=True),\\n sa.Column('product_type_name', sa.String(), nullable=True),\\n sa.Column('pricing_param', sa.Enum('StandardQuality', 'HighQuality', name='vpppricingparam'), nullable=True),\\n sa.Column('is_irrevocable', sa.Boolean(), nullable=True),\\n sa.Column('user_id', sa.Integer(), nullable=True),\\n sa.Column('client_user_id', commandment.dbtypes.GUID(), nullable=True),\\n sa.Column('its_id_hash', sa.String(), nullable=True),\\n sa.ForeignKeyConstraint(['client_user_id'], ['vpp_users.client_user_id'], ),\\n sa.ForeignKeyConstraint(['user_id'], ['vpp_users.user_id'], ),\\n sa.PrimaryKeyConstraint('license_id')\\n )\",\n \"def same_schema(self):\\n return self._same_schema\",\n \"def enforce_constraints(self):\\n self.session.flush()\\n try:\\n self.session.execute('SET CONSTRAINTS ALL IMMEDIATE')\\n except DatabaseError:\\n handle_sqlalchemy_database_error()\",\n \"def resolve_schema(self, data):\\n if not isinstance(data, dict):\\n return\\n\\n # OAS 2 component or OAS 3 header\\n if \\\"schema\\\" in data:\\n data[\\\"schema\\\"] = self.openapi.resolve_schema_dict(data[\\\"schema\\\"])\\n # OAS 3 component except header\\n if self.openapi_version.major >= 3:\\n if \\\"content\\\" in data:\\n for content_type in data[\\\"content\\\"]:\\n schema = data[\\\"content\\\"][content_type][\\\"schema\\\"]\\n data[\\\"content\\\"][content_type][\\n \\\"schema\\\"\\n ] = self.openapi.resolve_schema_dict(schema)\",\n \"def finalizeSchema(schema, folderish=False, moveDiscussion=True):\\n schema.moveField('description', after='architects')\\n return schema\",\n \"def downgrade():\\n op.execute(\\n f\\\"\\\"\\\"\\n ALTER TABLE\\n {config.CLEAN_SCHEMA}.forecasts\\n RENAME COLUMN\\n train_horizon\\n TO\\n training_horizon;\\n \\\"\\\"\\\",\\n ) # noqa:WPS355\",\n \"def clone_schema(base_schema_name: str, new_schema_name: str, dry_run: bool = False):\\n check_schema_name(new_schema_name)\\n cursor = connection.cursor()\\n\\n # check if the clone_schema function already exists in the db\\n try:\\n cursor.execute(\\n \\\"SELECT 'public.clone_schema(text, text, public.cloneparms[])'::regprocedure\\\"\\n )\\n except ProgrammingError: # pragma: no cover\\n _create_clone_schema_function()\\n transaction.commit()\\n\\n try:\\n with transaction.atomic():\\n cursor.callproc(\\\"clone_schema\\\", [base_schema_name, new_schema_name, \\\"DATA\\\"])\\n cursor.close()\\n if dry_run:\\n raise DryRunException\\n except DryRunException:\\n cursor.close()\",\n \"def regenerate_constraints(self):\\n\\n # Let us not forget to remove fields that migh be empty by now\\n if hasattr(self, '_cons_kinds'):\\n for k in self._cons_kinds:\\n attrname = camel2underscores(k)\\n try:\\n delattr(self, attrname)\\n except AttributeError:\\n pass # The attribute may not have been set up yet\\n\\n _cons_kinds = defaultdict(DictList)\\n\\n for k, v in self._cons_dict.items():\\n _cons_kinds[v.__class__.__name__].append(v)\\n\\n for k in _cons_kinds:\\n attrname = camel2underscores(k)\\n setattr(self, attrname, _cons_kinds[k])\\n\\n self._cons_kinds = _cons_kinds\",\n \"def add_cols(self, source) :\\n\\n cols = source.get_cols()\\n types = source.get_types()\\n\\n new_cols = []\\n new_types = []\\n for i in range(len(cols)) :\\n if cols[i] not in self.cols :\\n new_cols.append(cols[i])\\n new_types.append(types[i])\\n self.cols.extend(new_cols)\\n self.types.extend(new_types)\\n\\n self._alter_table(new_cols, new_types)\\n\\n row_ids = self.get_values('__ROWID')\\n \\n for col in new_cols :\\n new_vals = source.get_values(col)\\n if len(row_ids) == 0 :\\n for val in new_vals :\\n self._insert_internal(['__ROWID', col], [0, val])\\n\\n row_ids = self.get_values('__ROWID')\\n\\n else :\\n binds = zip(new_vals, row_ids)\\n q = self._quoter(col)\\n sql_base = 'UPDATE \\\"%s\\\" SET \\\"%s\\\" = %s WHERE \\\"__ROWID\\\" = %%d' % (self.name, col, q)\\n cur = self.con.cursor()\\n for bind in binds :\\n if bind[0] :\\n update_sql = sql_base % (str(bind[0]), bind[1])\\n cur.execute(update_sql)\\n\\n self.version += 1\",\n \"def upgrade_to_14():\\n config.db.singletons.find_one_and_update(\\n {'_id': 'config', 'persistent.schema_path': {'$exists': True}},\\n {'$unset': {'persistent.schema_path': ''}})\",\n \"def upgrade_to_13():\\n config.db.singletons.find_one_and_update(\\n {'_id': 'config', 'persistent.schema_path': {'$exists': True}},\\n {'$unset': {'persistent.schema_path': ''}})\",\n \"def merge_schema(self, schema):\\n super(CategoricalAttributeSchema, self).merge_schema(schema)\\n self.categories.update(schema.categories)\",\n \"def deferred_to_columns_cb(self, target, model, fields):\\n table = model._meta.db_table\\n if table not in target:\\n target[table] = set()\\n for field in fields:\\n if not hasattr(field.column, \\\"columns\\\"):\\n target[table].add(field.column)\\n else:\\n target[table].update(field.column.columns)\",\n \"def upgrade_to_6():\\n\\n colls = config.db.collections.find({'modified': {'$type': 2}}) # type string\\n for c in colls:\\n fixed_mod = dateutil.parser.parse(c['modified'])\\n config.db.collections.update_one({'_id': c['_id']}, {'$set': {'modified': fixed_mod}})\",\n \"def _refactor_time_columns(write_cursor: 'DBCursor') -> None:\\n log.debug('Enter _refactor_time_columns')\\n write_cursor.execute('ALTER TABLE timed_balances RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE timed_location_data RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE trades RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE asset_movements RENAME COLUMN time TO timestamp')\\n log.debug('Exit _refactor_time_columns')\",\n \"def repair(self):\\n # self.add_cons_vars([x.constraint for x in self._cons_dict.values()])\\n # self.add_cons_vars([x.variable for x in self._var_dict.values()])\\n self._push_queue()\\n Model.repair(self)\\n self.regenerate_constraints()\\n self.regenerate_variables()\",\n \"def strict_startup(self):\\n self.load_up_initial_db(TIMESTAMP_PARSE_DICT)\\n self.clean()\\n self.add_numeric_cols()\",\n \"def upkeep(self) -> None:\\n if self.atype in ['REINFORCE', 'A2C']:\\n self._db.reset()\",\n \"def unmodify_schema(setup_path, names, lp, creds, reporter, ldif, msg):\\n\\n return deprovision_schema(setup_path, names, lp, creds, reporter, ldif, msg, True)\",\n \"def modify(self, fields=None, **fields_kwargs):\\n modified_fields = set()\\n fields = self.make_dict(fields, fields_kwargs)\\n fields = self._modify(fields)\\n for field_name, field_val in fields.items():\\n in_schema = field_name in self.schema.fields\\n if in_schema:\\n setattr(self, field_name, field_val)\\n modified_fields.add(field_name)\\n\\n return modified_fields\",\n \"def reset_modified(self):\\n self.modified_fields = set()\\n\\n # compensate for us not having knowledge of certain fields changing\\n for field_name, field in self.schema.normal_fields.items():\\n if isinstance(field, ObjectField):\\n self.modified_fields.add(field_name)\",\n \"def migrate(env):\\n registry = env['registry']\\n settings = registry.settings\\n readonly_backends = ('storage', 'permission')\\n readonly_mode = asbool(settings.get('readonly', False))\\n\\n for backend in ('cache', 'storage', 'permission'):\\n if hasattr(registry, backend):\\n if readonly_mode and backend in readonly_backends:\\n message = ('Cannot migrate the %s backend while '\\n 'in readonly mode.' % backend)\\n warnings.warn(message)\\n else:\\n getattr(registry, backend).initialize_schema()\",\n \"def ibis_schema_apply_to(schema, df):\\n\\n for column, dtype in schema.items():\\n pandas_dtype = dtype.to_pandas()\\n if isinstance(dtype, dt.Interval):\\n df[column] = df[column].values.astype(pandas_dtype)\\n else:\\n df[column] = df[column].astype(pandas_dtype, errors='ignore')\\n\\n if PY2 and dtype == dt.string:\\n df[column] = df[column].str.decode('utf-8', errors='ignore')\\n\\n return df\",\n \"def _rewrite_project(self, node: saldag.Project):\\n\\n selected_cols = node.selected_cols\\n\\n for in_col, out_col in zip(selected_cols, node.out_rel.columns):\\n out_col.coll_sets |= copy.deepcopy(in_col.coll_sets)\",\n \"def update(self, schema: ISchema) -> ISchema:\\n schema = super().update(schema)\\n\\n schema = cast(EventSchema, schema)\\n if not schema.Active and schema.Sport > 0:\\n self.select('ID', 'Sport', 'Active').filter(\\n 'Sport', Operators.Equals, schema.Sport,\\n ).filter('Active', Operators.Equals, 1)\\n result = self.execute()\\n if not result:\\n sm = SportModel()\\n sport = sm.find(schema.Sport)\\n sport = cast(SportSchema, sport)\\n sport.Active = False\\n sm.update(sport)\\n return schema\",\n \"def test_can_update_risk_type_schema(self):\\n risk_type = self.create_risk_type()\\n for r in risk_type.schema:\\n if r['field_type'] == 'text':\\n r['field_type'] = 'textarea'\\n break\\n\\n response = self.client.put(\\n f'/api/v0/risk-types/{risk_type.id}/',\\n data={\\n 'type_name': 'New Risk Type',\\n 'schema': risk_type.schema,\\n }, format='json')\\n risk_type.refresh_from_db()\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\\n self.assertEqual(risk_type.schema[0].get('field_type'), 'textarea')\",\n \"def upgrade():\\n op.add_column(\\n 'assessments',\\n sa.Column(\\n 'assessment_type',\\n sa.String(length=250),\\n nullable=False,\\n server_default=\\\"Control\\\",\\n )\\n )\\n # Change CA help text \\\"Assessment type\\\" to \\\"Assessment Category\\\"\\n op.execute(\\n 'UPDATE custom_attribute_definitions '\\n 'SET helptext = \\\"Assessment Category\\\" '\\n 'WHERE helptext = \\\"Assessment type\\\" '\\n 'AND definition_type = \\\"assessment\\\" AND title = \\\"Type\\\";'\\n )\",\n \"def migrate(env, dry_run=False):\\n registry = env['registry']\\n settings = registry.settings\\n readonly_backends = ('storage', 'permission')\\n readonly_mode = asbool(settings.get('readonly', False))\\n\\n for backend in ('cache', 'storage', 'permission'):\\n if hasattr(registry, backend):\\n if readonly_mode and backend in readonly_backends:\\n message = ('Cannot migrate the %s backend while '\\n 'in readonly mode.' % backend)\\n logger.error(message)\\n else:\\n getattr(registry, backend).initialize_schema(dry_run=dry_run)\",\n \"def _prepare_schema(self):\\n schema = DaskSchema(self.schema_name)\\n\\n if not self.tables:\\n logger.warning(\\\"No tables are registered.\\\")\\n\\n for name, dc in self.tables.items():\\n table = DaskTable(name)\\n df = dc.df\\n logger.debug(\\n f\\\"Adding table '{name}' to schema with columns: {list(df.columns)}\\\"\\n )\\n for column in df.columns:\\n data_type = df[column].dtype\\n sql_data_type = python_to_sql_type(data_type)\\n\\n table.addColumn(column, sql_data_type)\\n\\n schema.addTable(table)\\n\\n if not self.functions:\\n logger.debug(\\\"No custom functions defined.\\\")\\n\\n for function_description in self.function_list:\\n name = function_description.name\\n sql_return_type = python_to_sql_type(function_description.return_type)\\n if function_description.aggregation:\\n logger.debug(f\\\"Adding function '{name}' to schema as aggregation.\\\")\\n dask_function = DaskAggregateFunction(name, sql_return_type)\\n else:\\n logger.debug(f\\\"Adding function '{name}' to schema as scalar function.\\\")\\n dask_function = DaskScalarFunction(name, sql_return_type)\\n\\n dask_function = self._add_parameters_from_description(\\n function_description, dask_function\\n )\\n\\n schema.addFunction(dask_function)\\n\\n return schema\",\n \"def _create_schema(self):\\n self._conn.executescript(self._db_schema)\",\n \"def _create_clone_schema_function():\\n with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), \\\"clone_schema.sql\\\")) as f:\\n CLONE_SCHEMA_FUNCTION = (\\n f.read()\\n .replace(\\\"RAISE NOTICE ' source schema\\\", \\\"RAISE EXCEPTION ' source schema\\\")\\n .replace(\\\"RAISE NOTICE ' dest schema\\\", \\\"RAISE EXCEPTION ' dest schema\\\")\\n )\\n\\n cursor = connection.cursor()\\n cursor.execute(CLONE_SCHEMA_FUNCTION)\\n cursor.close()\",\n \"def test_compare_schemas_major(self):\\n status = schema_utils.compare_schemas(\\n self.base_schema,\\n self.major_removed_value\\n )\\n\\n assert status == schema_utils.Update.major\",\n \"def extend_schema(schema, documentAST=None):\\n\\n assert isinstance(schema, GraphQLSchema), \\\"Must provide valid GraphQLSchema\\\"\\n assert documentAST and isinstance(\\n documentAST, ast.Document\\n ), \\\"Must provide valid Document AST\\\"\\n\\n # Collect the type definitions and extensions found in the document.\\n type_definition_map = {}\\n type_extensions_map = defaultdict(list)\\n\\n for _def in documentAST.definitions:\\n if isinstance(\\n _def,\\n (\\n ast.ObjectTypeDefinition,\\n ast.InterfaceTypeDefinition,\\n ast.EnumTypeDefinition,\\n ast.UnionTypeDefinition,\\n ast.ScalarTypeDefinition,\\n ast.InputObjectTypeDefinition,\\n ),\\n ):\\n # Sanity check that none of the defined types conflict with the\\n # schema's existing types.\\n type_name = _def.name.value\\n if schema.get_type(type_name):\\n raise GraphQLError(\\n (\\n 'Type \\\"{}\\\" already exists in the schema. It cannot also '\\n + \\\"be defined in this type definition.\\\"\\n ).format(type_name),\\n [_def],\\n )\\n\\n type_definition_map[type_name] = _def\\n elif isinstance(_def, ast.TypeExtensionDefinition):\\n # Sanity check that this type extension exists within the\\n # schema's existing types.\\n extended_type_name = _def.definition.name.value\\n existing_type = schema.get_type(extended_type_name)\\n if not existing_type:\\n raise GraphQLError(\\n (\\n 'Cannot extend type \\\"{}\\\" because it does not '\\n + \\\"exist in the existing schema.\\\"\\n ).format(extended_type_name),\\n [_def.definition],\\n )\\n if not isinstance(existing_type, GraphQLObjectType):\\n raise GraphQLError(\\n 'Cannot extend non-object type \\\"{}\\\".'.format(extended_type_name),\\n [_def.definition],\\n )\\n\\n type_extensions_map[extended_type_name].append(_def)\\n\\n # Below are functions used for producing this schema that have closed over\\n # this scope and have access to the schema, cache, and newly defined types.\\n\\n def get_type_from_def(type_def):\\n type = _get_named_type(type_def.name)\\n assert type, \\\"Invalid schema\\\"\\n return type\\n\\n def get_type_from_AST(astNode):\\n type = _get_named_type(astNode.name.value)\\n if not type:\\n raise GraphQLError(\\n (\\n 'Unknown type: \\\"{}\\\". Ensure that this type exists '\\n + \\\"either in the original schema, or is added in a type definition.\\\"\\n ).format(astNode.name.value),\\n [astNode],\\n )\\n return type\\n\\n # Given a name, returns a type from either the existing schema or an\\n # added type.\\n def _get_named_type(typeName):\\n cached_type_def = type_def_cache.get(typeName)\\n if cached_type_def:\\n return cached_type_def\\n\\n existing_type = schema.get_type(typeName)\\n if existing_type:\\n type_def = extend_type(existing_type)\\n type_def_cache[typeName] = type_def\\n return type_def\\n\\n type_ast = type_definition_map.get(typeName)\\n if type_ast:\\n type_def = build_type(type_ast)\\n type_def_cache[typeName] = type_def\\n return type_def\\n\\n # Given a type's introspection result, construct the correct\\n # GraphQLType instance.\\n def extend_type(type):\\n if isinstance(type, GraphQLObjectType):\\n return extend_object_type(type)\\n if isinstance(type, GraphQLInterfaceType):\\n return extend_interface_type(type)\\n if isinstance(type, GraphQLUnionType):\\n return extend_union_type(type)\\n return type\\n\\n def extend_object_type(type):\\n return GraphQLObjectType(\\n name=type.name,\\n description=type.description,\\n interfaces=lambda: extend_implemented_interfaces(type),\\n fields=lambda: extend_field_map(type),\\n )\\n\\n def extend_interface_type(type):\\n return GraphQLInterfaceType(\\n name=type.name,\\n description=type.description,\\n fields=lambda: extend_field_map(type),\\n resolve_type=cannot_execute_client_schema,\\n )\\n\\n def extend_union_type(type):\\n return GraphQLUnionType(\\n name=type.name,\\n description=type.description,\\n types=list(map(get_type_from_def, type.types)),\\n resolve_type=cannot_execute_client_schema,\\n )\\n\\n def extend_implemented_interfaces(type):\\n interfaces = list(map(get_type_from_def, type.interfaces))\\n\\n # If there are any extensions to the interfaces, apply those here.\\n extensions = type_extensions_map[type.name]\\n for extension in extensions:\\n for namedType in extension.definition.interfaces:\\n interface_name = namedType.name.value\\n if any([_def.name == interface_name for _def in interfaces]):\\n raise GraphQLError(\\n (\\n 'Type \\\"{}\\\" already implements \\\"{}\\\". '\\n + \\\"It cannot also be implemented in this type extension.\\\"\\n ).format(type.name, interface_name),\\n [namedType],\\n )\\n interfaces.append(get_type_from_AST(namedType))\\n\\n return interfaces\\n\\n def extend_field_map(type):\\n new_field_map = OrderedDict()\\n old_field_map = type.fields\\n for field_name, field in old_field_map.items():\\n new_field_map[field_name] = GraphQLField(\\n extend_field_type(field.type),\\n description=field.description,\\n deprecation_reason=field.deprecation_reason,\\n args=field.args,\\n resolver=cannot_execute_client_schema,\\n )\\n\\n # If there are any extensions to the fields, apply those here.\\n extensions = type_extensions_map[type.name]\\n for extension in extensions:\\n for field in extension.definition.fields:\\n field_name = field.name.value\\n if field_name in old_field_map:\\n raise GraphQLError(\\n (\\n 'Field \\\"{}.{}\\\" already exists in the '\\n + \\\"schema. It cannot also be defined in this type extension.\\\"\\n ).format(type.name, field_name),\\n [field],\\n )\\n new_field_map[field_name] = GraphQLField(\\n build_field_type(field.type),\\n args=build_input_values(field.arguments),\\n resolver=cannot_execute_client_schema,\\n )\\n\\n return new_field_map\\n\\n def extend_field_type(type):\\n if isinstance(type, GraphQLList):\\n return GraphQLList(extend_field_type(type.of_type))\\n if isinstance(type, GraphQLNonNull):\\n return GraphQLNonNull(extend_field_type(type.of_type))\\n return get_type_from_def(type)\\n\\n def build_type(type_ast):\\n _type_build = {\\n ast.ObjectTypeDefinition: build_object_type,\\n ast.InterfaceTypeDefinition: build_interface_type,\\n ast.UnionTypeDefinition: build_union_type,\\n ast.ScalarTypeDefinition: build_scalar_type,\\n ast.EnumTypeDefinition: build_enum_type,\\n ast.InputObjectTypeDefinition: build_input_object_type,\\n }\\n func = _type_build.get(type(type_ast))\\n if func:\\n return func(type_ast)\\n\\n def build_object_type(type_ast):\\n return GraphQLObjectType(\\n type_ast.name.value,\\n interfaces=lambda: build_implemented_interfaces(type_ast),\\n fields=lambda: build_field_map(type_ast),\\n )\\n\\n def build_interface_type(type_ast):\\n return GraphQLInterfaceType(\\n type_ast.name.value,\\n fields=lambda: build_field_map(type_ast),\\n resolve_type=cannot_execute_client_schema,\\n )\\n\\n def build_union_type(type_ast):\\n return GraphQLUnionType(\\n type_ast.name.value,\\n types=list(map(get_type_from_AST, type_ast.types)),\\n resolve_type=cannot_execute_client_schema,\\n )\\n\\n def build_scalar_type(type_ast):\\n return GraphQLScalarType(\\n type_ast.name.value,\\n serialize=lambda *args, **kwargs: None,\\n # Note: validation calls the parse functions to determine if a\\n # literal value is correct. Returning null would cause use of custom\\n # scalars to always fail validation. Returning false causes them to\\n # always pass validation.\\n parse_value=lambda *args, **kwargs: False,\\n parse_literal=lambda *args, **kwargs: False,\\n )\\n\\n def build_enum_type(type_ast):\\n return GraphQLEnumType(\\n type_ast.name.value,\\n values={v.name.value: GraphQLEnumValue() for v in type_ast.values},\\n )\\n\\n def build_input_object_type(type_ast):\\n return GraphQLInputObjectType(\\n type_ast.name.value,\\n fields=lambda: build_input_values(type_ast.fields, GraphQLInputObjectField),\\n )\\n\\n def build_implemented_interfaces(type_ast):\\n return list(map(get_type_from_AST, type_ast.interfaces))\\n\\n def build_field_map(type_ast):\\n return {\\n field.name.value: GraphQLField(\\n build_field_type(field.type),\\n args=build_input_values(field.arguments),\\n resolver=cannot_execute_client_schema,\\n )\\n for field in type_ast.fields\\n }\\n\\n def build_input_values(values, input_type=GraphQLArgument):\\n input_values = OrderedDict()\\n for value in values:\\n type = build_field_type(value.type)\\n input_values[value.name.value] = input_type(\\n type, default_value=value_from_ast(value.default_value, type)\\n )\\n return input_values\\n\\n def build_field_type(type_ast):\\n if isinstance(type_ast, ast.ListType):\\n return GraphQLList(build_field_type(type_ast.type))\\n if isinstance(type_ast, ast.NonNullType):\\n return GraphQLNonNull(build_field_type(type_ast.type))\\n return get_type_from_AST(type_ast)\\n\\n # If this document contains no new types, then return the same unmodified\\n # GraphQLSchema instance.\\n if not type_extensions_map and not type_definition_map:\\n return schema\\n\\n # A cache to use to store the actual GraphQLType definition objects by name.\\n # Initialize to the GraphQL built in scalars and introspection types. All\\n # functions below are inline so that this type def cache is within the scope\\n # of the closure.\\n\\n type_def_cache = {\\n \\\"String\\\": GraphQLString,\\n \\\"Int\\\": GraphQLInt,\\n \\\"Float\\\": GraphQLFloat,\\n \\\"Boolean\\\": GraphQLBoolean,\\n \\\"ID\\\": GraphQLID,\\n \\\"__Schema\\\": __Schema,\\n \\\"__Directive\\\": __Directive,\\n \\\"__DirectiveLocation\\\": __DirectiveLocation,\\n \\\"__Type\\\": __Type,\\n \\\"__Field\\\": __Field,\\n \\\"__InputValue\\\": __InputValue,\\n \\\"__EnumValue\\\": __EnumValue,\\n \\\"__TypeKind\\\": __TypeKind,\\n }\\n\\n # Get the root Query, Mutation, and Subscription types.\\n query_type = get_type_from_def(schema.get_query_type())\\n\\n existing_mutation_type = schema.get_mutation_type()\\n mutationType = (\\n existing_mutation_type and get_type_from_def(existing_mutation_type) or None\\n )\\n\\n existing_subscription_type = schema.get_subscription_type()\\n subscription_type = (\\n existing_subscription_type\\n and get_type_from_def(existing_subscription_type)\\n or None\\n )\\n\\n # Iterate through all types, getting the type definition for each, ensuring\\n # that any type not directly referenced by a field will get created.\\n types = [get_type_from_def(_def) for _def in schema.get_type_map().values()]\\n\\n # Do the same with new types, appending to the list of defined types.\\n types += [get_type_from_AST(_def) for _def in type_definition_map.values()]\\n\\n # Then produce and return a Schema with these types.\\n return GraphQLSchema(\\n query=query_type,\\n mutation=mutationType,\\n subscription=subscription_type,\\n # Copy directives.\\n directives=schema.get_directives(),\\n types=types,\\n )\",\n \"def _swapcolumns(self):\\n return self.reindex_axis([self.columns[1], self.columns[0]], axis=1)\",\n \"def _load_schema(self, mode=\\\"staging\\\"):\\n\\n self._check_mode(mode)\\n\\n json_path = self.table_folder / f\\\"schema-{mode}.json\\\"\\n columns = self.table_config[\\\"columns\\\"]\\n\\n if mode == \\\"staging\\\":\\n new_columns = []\\n for c in columns:\\n # case is_in_staging are None then must be True\\n is_in_staging = (\\n True if c.get(\\\"is_in_staging\\\") is None else c[\\\"is_in_staging\\\"]\\n )\\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\\n if is_in_staging and not c.get(\\\"is_partition\\\"):\\n c[\\\"type\\\"] = \\\"STRING\\\"\\n new_columns.append(c)\\n\\n del columns\\n columns = new_columns\\n\\n elif mode == \\\"prod\\\":\\n schema = self._get_table_obj(mode).schema\\n\\n # get field names for fields at schema and at table_config.yaml\\n column_names = [c[\\\"name\\\"] for c in columns]\\n schema_names = [s.name for s in schema]\\n\\n # check if there are mismatched fields\\n not_in_columns = [name for name in schema_names if name not in column_names]\\n not_in_schema = [name for name in column_names if name not in schema_names]\\n\\n # raise if field is not in table_config\\n if not_in_columns:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in table_config.yaml. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_columns,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # raise if field is not in schema\\n if not_in_schema:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in publish.sql. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_schema,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # if field is in schema, get field_type and field_mode\\n for c in columns:\\n for s in schema:\\n if c[\\\"name\\\"] == s.name:\\n c[\\\"type\\\"] = s.field_type\\n c[\\\"mode\\\"] = s.mode\\n break\\n ## force utf-8, write schema_{mode}.json\\n json.dump(columns, (json_path).open(\\\"w\\\", encoding=\\\"utf-8\\\"))\\n\\n # load new created schema\\n return self.client[f\\\"bigquery_{mode}\\\"].schema_from_json(str(json_path))\",\n \"async def reload_database(self, schema='conf/schema.sql'):\\n with open(schema) as schema:\\n await self.dao.build((schema.read()))\",\n \"def upgrade():\\n op.execute(\\n \\\"\\\"\\\"\\n insert ignore into relationships (\\n modified_by_id,\\n created_at,\\n updated_at,\\n source_id,\\n source_type,\\n destination_id,\\n destination_type\\n )\\n select\\n modified_by_id,\\n created_at,\\n updated_at,\\n parent_id as source_id,\\n parent_type as source_type,\\n child_id as destination_id,\\n child_type as destination_type\\n from snapshots\\n \\\"\\\"\\\"\\n )\",\n \"def upgrade_to_py3(self):\\n # Rewrite database metadata pickles to force to version 3.\\n for name, (id, attrs, idx) in self._object_types.items():\\n self._db_query(\\\"UPDATE types SET attrs_pickle=?, idx_pickle=? WHERE id=?\\\", (self._pickle(attrs), self._pickle(idx), id))\\n for name, ivtidx in self._inverted_indexes.items():\\n self._db_query(\\\"UPDATE inverted_indexes SET value=? WHERE name=? AND attr=?\\\", (self._pickle(ivtidx), name, 'definition'))\\n self.commit()\\n self._readonly = False\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7231359","0.7089279","0.65710247","0.6482866","0.64562935","0.61638325","0.61030746","0.5923907","0.5808623","0.5721755","0.56536114","0.56280774","0.56276286","0.5590315","0.5581879","0.55440784","0.5543209","0.55420613","0.5536027","0.55306125","0.55029225","0.54575","0.5431088","0.54255265","0.5394251","0.5375789","0.5367753","0.5357313","0.5336318","0.5328095","0.5278523","0.52771056","0.52656645","0.52656645","0.52656645","0.52209383","0.5218055","0.52002794","0.51970035","0.51930255","0.51924634","0.5184683","0.51577127","0.5151599","0.51475465","0.51405257","0.5139874","0.513891","0.51383835","0.5136204","0.5116184","0.50896347","0.508401","0.5082808","0.50731707","0.5038522","0.49948877","0.49718288","0.4968792","0.49658614","0.49541888","0.49411947","0.49195436","0.49037525","0.49031138","0.48992842","0.4892197","0.48897704","0.48810467","0.48694217","0.486147","0.4859146","0.48515552","0.483281","0.4822995","0.4821257","0.48161238","0.48121506","0.48110282","0.48067328","0.48044786","0.48014674","0.4797127","0.47816378","0.47792447","0.47722372","0.47709516","0.47657466","0.47617412","0.4757309","0.47540647","0.47444832","0.47422335","0.47422227","0.47393706","0.47351882","0.47344276","0.47135434","0.47040495","0.46960893"],"string":"[\n \"0.7231359\",\n \"0.7089279\",\n \"0.65710247\",\n \"0.6482866\",\n \"0.64562935\",\n \"0.61638325\",\n \"0.61030746\",\n \"0.5923907\",\n \"0.5808623\",\n \"0.5721755\",\n \"0.56536114\",\n \"0.56280774\",\n \"0.56276286\",\n \"0.5590315\",\n \"0.5581879\",\n \"0.55440784\",\n \"0.5543209\",\n \"0.55420613\",\n \"0.5536027\",\n \"0.55306125\",\n \"0.55029225\",\n \"0.54575\",\n \"0.5431088\",\n \"0.54255265\",\n \"0.5394251\",\n \"0.5375789\",\n \"0.5367753\",\n \"0.5357313\",\n \"0.5336318\",\n \"0.5328095\",\n \"0.5278523\",\n \"0.52771056\",\n \"0.52656645\",\n \"0.52656645\",\n \"0.52656645\",\n \"0.52209383\",\n \"0.5218055\",\n \"0.52002794\",\n \"0.51970035\",\n \"0.51930255\",\n \"0.51924634\",\n \"0.5184683\",\n \"0.51577127\",\n \"0.5151599\",\n \"0.51475465\",\n \"0.51405257\",\n \"0.5139874\",\n \"0.513891\",\n \"0.51383835\",\n \"0.5136204\",\n \"0.5116184\",\n \"0.50896347\",\n \"0.508401\",\n \"0.5082808\",\n \"0.50731707\",\n \"0.5038522\",\n \"0.49948877\",\n \"0.49718288\",\n \"0.4968792\",\n \"0.49658614\",\n \"0.49541888\",\n \"0.49411947\",\n \"0.49195436\",\n \"0.49037525\",\n \"0.49031138\",\n \"0.48992842\",\n \"0.4892197\",\n \"0.48897704\",\n \"0.48810467\",\n \"0.48694217\",\n \"0.486147\",\n \"0.4859146\",\n \"0.48515552\",\n \"0.483281\",\n \"0.4822995\",\n \"0.4821257\",\n \"0.48161238\",\n \"0.48121506\",\n \"0.48110282\",\n \"0.48067328\",\n \"0.48044786\",\n \"0.48014674\",\n \"0.4797127\",\n \"0.47816378\",\n \"0.47792447\",\n \"0.47722372\",\n \"0.47709516\",\n \"0.47657466\",\n \"0.47617412\",\n \"0.4757309\",\n \"0.47540647\",\n \"0.47444832\",\n \"0.47422335\",\n \"0.47422227\",\n \"0.47393706\",\n \"0.47351882\",\n \"0.47344276\",\n \"0.47135434\",\n \"0.47040495\",\n \"0.46960893\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6559085"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":2290,"cells":{"query":{"kind":"string","value":"Change mode to `NULLABLE` for columns in existing schema. Tries set mode on existing columns in orig_schema_map to `NULLABLE`. Raises SchemaUpdateError if column is not found in orig_schema_map."},"document":{"kind":"string","value":"def _GetRelaxedCols(relaxed_columns, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for col in relaxed_columns:\n if col in orig_schema_map:\n updated_schema_map[col].mode = 'NULLABLE'\n else:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n return updated_schema_map"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\n old_info = old_schema_entry['info']\n new_info = new_schema_entry['info']\n old_mode = old_info['mode']\n old_name = old_info['name']\n old_type = old_info['type']\n old_status = old_schema_entry['status']\n new_mode = new_info['mode']\n new_name = new_info['name']\n new_type = new_info['type']\n new_status = new_schema_entry['status']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # If the old field is a REQUIRED primitive (which could only have come\n # from an existing schema), the new field can be either a\n # NULLABLE(filled) or a NULLABLE(unfilled).\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\n # If the new field is filled, then retain the REQUIRED.\n if new_schema_entry['filled']:\n return old_mode\n else:\n # The new field is not filled (i.e. an empty or null field).\n # If --infer_mode is active, then we allow the REQUIRED to\n # revert back to NULLABLE.\n if self.infer_mode:\n return new_mode\n else:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode.'\n ' cannot convert to NULLABLE because infer_schema not'\n ' set:'\n f' old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n elif old_mode != new_mode:\n self.log_error(\n f'Ignoring non-RECORD field with mismatched mode: '\n f'old=({old_status},{full_old_name},{old_mode},'\n f'{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},'\n f'{new_type})'\n )\n return None\n return old_mode","def nullable(self):\n _columns = []\n if not isinstance(self._last_column, list):\n _columns = [self._last_column]\n\n for column in _columns:\n column.nullable()\n return self","def filter_schema(schema):\n for column, column_schema in schema.iteritems():\n if column_schema.get(CARDINALITY):\n del column_schema[CARDINALITY]\n schema[column] = column_schema\n\n return schema","def _delete_null_columns(self):\r\n ds = DeleteStatement(self.column_family_name)\r\n deleted_fields = False\r\n for _, v in self.instance._values.items():\r\n col = v.column\r\n if v.deleted:\r\n ds.add_field(col.db_field_name)\r\n deleted_fields = True\r\n elif isinstance(col, Map):\r\n uc = MapDeleteClause(col.db_field_name, v.value, v.previous_value)\r\n if uc.get_context_size() > 0:\r\n ds.add_field(uc)\r\n deleted_fields = True\r\n\r\n if deleted_fields:\r\n for name, col in self.model._primary_keys.items():\r\n ds.add_where_clause(WhereClause(\r\n col.db_field_name,\r\n EqualsOperator(),\r\n col.to_database(getattr(self.instance, name))\r\n ))\r\n self._execute(ds)","def ProcessSchemaUpdate(ref, args, request):\n table = request.table\n relaxed_columns = args.relax_columns\n if not table.schema and not relaxed_columns: # if not updating schema,\n return request # then just return.\n\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\n ref.Name(),\n ref.projectId)\n\n new_schema_columns = table.schema\n updated_fields = _GetUpdatedSchema(original_schema,\n new_schema_columns,\n relaxed_columns)\n\n table_schema_type = GetApiMessage('TableSchema')\n request.table.schema = table_schema_type(fields=updated_fields)\n\n return request","def merge_schema_entry(\n self,\n old_schema_entry,\n new_schema_entry,\n base_path=None,\n ):\n if not old_schema_entry:\n return new_schema_entry\n\n # If the new schema is None, return immediately.\n if not new_schema_entry:\n return new_schema_entry\n\n # If a field value is missing, permanently set 'filled' to False.\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\n old_schema_entry['filled'] = False\n new_schema_entry['filled'] = False\n\n old_status = old_schema_entry['status']\n new_status = new_schema_entry['status']\n\n # new 'soft' does not clobber old 'hard'\n if old_status == 'hard' and new_status == 'soft':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n old_schema_entry['info']['mode'] = mode\n return old_schema_entry\n\n # new 'hard' clobbers old 'soft'\n if old_status == 'soft' and new_status == 'hard':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n new_schema_entry['info']['mode'] = mode\n return new_schema_entry\n\n # Verify that it's soft->soft or hard->hard\n if old_status != new_status:\n raise Exception(\n f'Unexpected schema_entry type, this should never happen: '\n f'old ({old_status}); new ({new_status})'\n )\n\n old_info = old_schema_entry['info']\n old_name = old_info['name']\n old_type = old_info['type']\n old_mode = old_info['mode']\n new_info = new_schema_entry['info']\n new_name = new_info['name']\n new_type = new_info['type']\n new_mode = new_info['mode']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # Defensive check, names should always be the same.\n if old_name != new_name:\n if old_name.lower() != new_name.lower():\n raise Exception(\n 'Unexpected difference in name, should never happen:'\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\n )\n else:\n # preserve old name if case is different\n new_info['name'] = old_info['name']\n\n # Recursively merge in the subfields of a RECORD, allowing\n # NULLABLE to become REPEATED (because 'bq load' allows it).\n if old_type == 'RECORD' and new_type == 'RECORD':\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\n # 'bq load' allows it.\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\n old_info['mode'] = 'REPEATED'\n self.log_error(\n f'Converting schema for \"{full_old_name}\" from '\n 'NULLABLE RECORD into REPEATED RECORD'\n )\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\n # TODO: Maybe remove this warning output. It was helpful during\n # development, but maybe it's just natural.\n self.log_error(\n f'Leaving schema for \"{full_old_name}\" as REPEATED RECORD'\n )\n\n # RECORD type needs a recursive merging of sub-fields. We merge into\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\n # can be modified in situ.\n old_fields = old_info['fields']\n new_fields = new_info['fields']\n for key, new_entry in new_fields.items():\n old_entry = old_fields.get(key)\n new_base_path = json_full_path(base_path, old_name)\n old_fields[key] = self.merge_schema_entry(\n old_schema_entry=old_entry,\n new_schema_entry=new_entry,\n base_path=new_base_path,\n )\n return old_schema_entry\n\n new_mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if new_mode is None:\n return None\n new_schema_entry['info']['mode'] = new_mode\n\n # For all other types...\n if old_type != new_type:\n # Check that the converted types are compatible.\n candidate_type = convert_type(old_type, new_type)\n if not candidate_type:\n self.log_error(\n f'Ignoring field with mismatched type: '\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\n )\n return None\n\n new_info['type'] = candidate_type\n return new_schema_entry","def remove_null_fields(self):\n with open(self.schema_path, 'r') as file_obj:\n schema_data = yaml.safe_load(file_obj)\n schema_fields = schema_data.get('mapping').keys()\n for field in schema_fields:\n # We want to keep 'false' and 0 values, and avoid removing fields that are required in the schema.\n if field in self.data and self.data[field] in (None, '', [], {}) and \\\n not schema_data.get('mapping', {}).get(field, {}).get('required'):\n self.data.pop(field)","def modify_bigquery_schema(self, schema, info_keys):\n # type: (bigquery.TableSchema, Set[str]) -> None","def merge_schema(self, schema):\n self.validate_schema(schema)\n\n if self.exclusive is False:\n self.exclusive = schema.exclusive\n\n if self.default is None:\n self.default = schema.default","def _patch_schema(self):\n fields = get_json()['data']['attributes'].keys()\n return make_entity_schema(\n self.SCHEMA, self.RESOURCE_NAME,\n make_data_schema(\n self.SCHEMA, id_required=True,\n only=fields, partial=True\n )\n )","def drop_null(self, how: Literal[\"any\", \"all\"] = \"any\"):\n # TODO only flat columns supported...\n assert self._dtype is not None\n res = Scope._EmptyColumn(self._dtype.constructor(nullable=False))\n if how == \"any\":\n for i in self:\n if not self._has_any_null(i):\n res._append(i)\n elif how == \"all\":\n for i in self:\n if not self._has_all_null(i):\n res._append(i)\n return res._finalize()","def correct_db_schema_precision(\n instance: Recorder,\n table_object: type[DeclarativeBase],\n schema_errors: set[str],\n) -> None:\n table_name = table_object.__tablename__\n\n if f\"{table_name}.double precision\" in schema_errors:\n from ..migration import ( # pylint: disable=import-outside-toplevel\n _modify_columns,\n )\n\n precision_columns = _get_precision_column_types(table_object)\n # Attempt to convert timestamp columns to µs precision\n session_maker = instance.get_session\n engine = instance.engine\n assert engine is not None, \"Engine should be set\"\n _modify_columns(\n session_maker,\n engine,\n table_name,\n [f\"{column} {DOUBLE_PRECISION_TYPE_SQL}\" for column in precision_columns],\n )","def _add_to_schema(self, new: dict):\n self._defaults.update(new)\n self._migrate()","def is_nullable(schema_obj):\n\n if isinstance(schema_obj, schema.Field):\n return schema_obj.is_nullable\n return False","def setNullAllowed(self, onlyNullAllowed):\n self._onlyNullAllowed = onlyNullAllowed","def nullify(self):\n self._original_values.clear()\n self._modified_values.clear()\n self._extra_record_data.clear()\n self._references.clear()\n for mtm in self._mtm_referencelist:\n self._mtm_referencelist[mtm].parentobjectid = None\n for chl in self._child_referencelist:\n self._child_referencelist[chl].clear() \n self._ismodified = False\n self._hasdata = False\n self._astxt = \"(null)\"\n if self._table: \n for f in self._table:\n self._original_values[f.name] = None","def set_sql_mode(self):\n self.execute_sql(\n sql.set_session_variable(\"sql_mode\"),\n (\"STRICT_ALL_TABLES,NO_AUTO_VALUE_ON_ZERO\",),\n )","def is_nullable(self) -> bool: # pragma: no cover\n pass","def _AddNewColsToSchema(new_fields, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for new_field in new_fields:\n if new_field.name in orig_schema_map:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n updated_schema_map[new_field.name] = new_field\n return updated_schema_map","def fillna_mode(data, columns, verbose=True):\n for col in columns:\n fill_val = data[col].mode()[0]\n if verbose: print('Filling ' + col + ' with: ' + fill_val)\n data[col].fillna(fill_val, inplace=True)","def update_table_columns(self, table_name, table):\n table_definition = self._table_definitions[table_name]\n new_columns = table.columns.difference(table_definition.c.keys())\n new_column_types = {c: table.dtypes[c] for c in new_columns}\n\n allows_covariates = table_definition.name in [\"avgint\", \"data\"]\n\n good_prefixes = [\"c_\"]\n if allows_covariates:\n good_prefixes.append(\"x_\")\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\n if bad_column_names:\n msg = f\"\"\"\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\n It allows additional comment columns, which must start 'c_'.\"\"\"\n if allows_covariates:\n msg += \" In addition it allows covariate columns, which must start with 'x_'.\"\n msg += f\" You supplied columns that don't meet those requirements: {bad_column_names}\"\n\n raise ValueError(dedent(msg))\n\n add_columns_to_table(table_definition, new_column_types)","def _copy_custom_attributes(self, column):\n\n column._fk = self._fk\n column._fk_on_update = self._fk_on_update\n column._fk_on_delete = self._fk_on_delete\n\n super()._copy_custom_attributes(column)","async def upgradeSchema(self) -> None:","def _GetUpdatedSchema(\n original_schema,\n new_columns=None,\n relaxed_columns=None):\n orig_field_map = (\n {f.name: f for f in original_schema.fields} if original_schema else {})\n\n if relaxed_columns:\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\n\n if new_columns:\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\n\n return sorted(orig_field_map.values(), key=lambda x: x.name)","def reset_schema_defs():\n SCHEMA_DEFS.clear()\n SCHEMA_DEFS.update((typ, typ) for typ in PRIMITIVE_TYPES)","def replace(self, dictionary):\n for column in self.__table__.columns.keys():\n setattr(self, column, None)\n self.from_dict(dictionary)","def _fillna_meta_cols(self):\n for col_name, fill_value in self._fillna.items():\n if col_name in self._hybrid_meta.columns:\n self._hybrid_meta[col_name].fillna(fill_value, inplace=True)\n else:\n self.__warn_missing_col(col_name, action='fill')\n\n self._hybrid_meta[self.__solar_rpi_n].fillna(-1, inplace=True)\n self._hybrid_meta[self.__wind_rpi_n].fillna(-1, inplace=True)","def update_records(cursor,table_schema,table_name,column_name,value):\n update_records = \"UPDATE \" + table_schema + \".\" + table_name + \" SET \" + column_name + \"='\" + value + \"' WHERE COALESCE(\" + column_name + \",'')='';\"\n cursor.execute(update_records)","def _set_editable_mode(self):\n dist = self.distribution\n build = dist.get_command_obj(\"build\")\n for cmd_name in build.get_sub_commands():\n cmd = dist.get_command_obj(cmd_name)\n if hasattr(cmd, \"editable_mode\"):\n cmd.editable_mode = True\n elif hasattr(cmd, \"inplace\"):\n cmd.inplace = True # backward compatibility with distutils","def test_null_update_deletes_column(self):\n partition = uuid4()\n for i in range(5):\n TestQueryUpdateModel.create(partition=partition, cluster=i, count=i, text=str(i))\n\n # sanity check\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\n self.assertEqual(row.cluster, i)\n self.assertEqual(row.count, i)\n self.assertEqual(row.text, str(i))\n\n # perform update\n TestQueryUpdateModel.objects(partition=partition, cluster=3).update(text=None)\n\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\n self.assertEqual(row.cluster, i)\n self.assertEqual(row.count, i)\n self.assertEqual(row.text, None if i == 3 else str(i))","def update(self, force=False):\n if (self.__fields is None) or force:\n self.__fields = [f for f in self.dbms.fields(self.table, self.db)]","def _encode_nullable(data_type, obj, alias_validators, old_style, for_msgpack):\n if obj is not None:\n return _json_compat_obj_encode_helper(\n data_type.validator, obj, alias_validators, old_style, for_msgpack)\n else:\n return None","def reinitToNull(self):\n for sAttr in self.getDataAttributes():\n setattr(self, sAttr, None);\n return self;","def set_null(self, /, *defaults: Any, **kwargs: Any) -> \"fn\":\n return self._mod.set_null(self._func, *defaults, **kwargs)","def get_nullable():\n changes = True\n while changes:\n changes = False\n for p in PRODUCTION_LIST:\n if not symbol_for_str(p.left).is_nullable:\n if p.right[0] == 'null':\n symbol_for_str(p.left).is_nullable = True\n changes = True\n continue\n else:\n right_is_nullable = symbol_for_str(p.right[0]).is_nullable\n # For X -> Y1 ... YN, Nullable(X) = Nullable(Y1) &\n # Nullable(Y2) ... & Nullable(YN)\n for r in p.right[1:]:\n if r.startswith('P'):\n continue\n right_is_nullable = right_is_nullable & symbol_for_str(\n r).is_nullable\n\n if right_is_nullable:\n changes = True\n symbol_for_str(p.left).is_nullable = True","def __null_check(self, record_attribute, attribute_schema):\n if attribute_schema[NULLABLE_KEY]:\n return True\n elif record_attribute is not None:\n return True\n else:\n IS_VALID_FILE = False\n return False","def _prepend_none_dimension(features):\n if features:\n modified_features = dict(features) # Create a copy to modify\n for key, feature in features.items():\n if isinstance(feature, FixedLenSequenceFeature):\n if not feature.allow_missing:\n raise ValueError(\"Unsupported: FixedLenSequenceFeature requires \"\n \"allow_missing to be True.\")\n modified_features[key] = FixedLenSequenceFeature(\n [None] + list(feature.shape),\n feature.dtype,\n feature.allow_missing,\n feature.default_value)\n return modified_features\n else:\n return features","def add_schema_attribute(self):\n schema_id = self.file.options['schema_id_attr']\n if self.sdef['df'] and self.file.options['include_schema_id']:\n # Normal defined entity\n ns = self.sdef['ns']\n id = self.sdef['id']\n schema = ns + \":\" + id\n self.attributes[schema_id] = {'value': schema}\n elif self.file.options['flag_custom_nodes']:\n self.attributes[schema_id] = {'value': 'custom'}","def build_schema(self, dframe, overwrite=False, set_num_columns=True):\n new_schema = self.schema.rebuild(dframe, overwrite)\n self.set_schema(new_schema,\n set_num_columns=(set_num_columns or overwrite))","def fix_incremental(meta, bind):\n meta.create_all(bind=bind, checkfirst=True)\n ref = inspect(bind)\n for table in meta.sorted_tables:\n orm_cols = set(col.name for col in table.c)\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\n col_to_create = orm_cols - ref_cols\n col_to_delete = ref_cols - orm_cols\n if col_to_create:\n print table.name, 'has diff to create', col_to_create\n with bind.begin() as conn:\n for col_name in col_to_create:\n col = table.c.get(col_name)\n column_sql = CreateColumn(col).compile(bind).string\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\n if col.default:\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\n if not col.nullable:\n sql += ' NOT NULL'\n print 'executing sql: ' + sql\n conn.execute(sql)\n\n # Workaround to ensure updated DBs start with \"False\" in ignore column\n if list(col_to_create)[0] == 'ignore':\n sessionmaker = get_sessionmaker(bind.url.database)\n session = sessionmaker()\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\n items = session.query(query_object).all()\n for item in items:\n item.ignore = False\n session.flush()\n\n if col_to_delete:\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\n \"\"\"\n BEGIN TRANSACTION;\n CREATE TEMPORARY TABLE t1_backup(a,b);\n INSERT INTO t1_backup SELECT a,b FROM t1;\n DROP TABLE t1;\n CREATE TABLE t1(a,b);\n INSERT INTO t1 SELECT a,b FROM t1_backup;\n DROP TABLE t1_backup;\n COMMIT;\n \"\"\"","def update_schema(self, new_schema):\n return self.conn.update_schema(new_schema)","def reformat(self, newformat):\n # check whether the column is defined\n if self._defined:\n # get the appropriate null-format\n nullformat = self._get_nullformat(newformat)\n # set the new formats\n self._format = [newformat, nullformat]\n else:\n # first the column type must be defined\n raise Exception('The data type of this column is not yet defined!')","def _copy_custom_attributes(self, column):\n\n column.min_length = self.min_length\n column.max_length = self.max_length\n column.allow_blank = self.allow_blank\n column.allow_whitespace = self.allow_whitespace\n\n super()._copy_custom_attributes(column)","def allows_auto_pk_0(self):\n return \"NO_AUTO_VALUE_ON_ZERO\" in self.connection.sql_mode","def correct_db_schema_utf8(\n instance: Recorder, table_object: type[DeclarativeBase], schema_errors: set[str]\n) -> None:\n table_name = table_object.__tablename__\n if (\n f\"{table_name}.4-byte UTF-8\" in schema_errors\n or f\"{table_name}.utf8mb4_unicode_ci\" in schema_errors\n ):\n from ..migration import ( # pylint: disable=import-outside-toplevel\n _correct_table_character_set_and_collation,\n )\n\n _correct_table_character_set_and_collation(table_name, instance.get_session)","def apply_patch():\n assert BaseDatabaseSchemaEditor is not None\n\n def _create_unique_sql(self, *args, **kwargs):\n from django.db.backends.ddl_references import IndexName\n\n statement = orig_create_unique_sql(self, *args, **kwargs)\n\n if statement is not None:\n index_name = statement.parts['name']\n\n if (isinstance(index_name, IndexName) and\n index_name.create_index_name == self._create_index_name):\n # The result will be unquoted. Let's quote it.\n index_name.create_index_name = lambda *args, **kwargs: \\\n self.quote_name(self._create_index_name(*args, **kwargs))\n\n return statement\n\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql","def to_json_schema(\n schema: Dict[str, Any], *, nullable_name: str, copy: bool = True, is_response_schema: bool = False\n) -> Dict[str, Any]:\n if copy:\n schema = fast_deepcopy(schema)\n if schema.get(nullable_name) is True:\n del schema[nullable_name]\n schema = {\"anyOf\": [schema, {\"type\": \"null\"}]}\n schema_type = schema.get(\"type\")\n if schema_type == \"file\":\n schema[\"type\"] = \"string\"\n schema[\"format\"] = \"binary\"\n if schema_type == \"object\":\n if is_response_schema:\n # Write-only properties should not occur in responses\n rewrite_properties(schema, is_write_only)\n else:\n # Read-only properties should not occur in requests\n rewrite_properties(schema, is_read_only)\n return schema","def test_build_schema_no_update(self):\n metadata = schema_utils.build_metadata(\n self.dummy_schema,\n self.fake_metadata,\n schema_utils.Update.no_update,\n )\n assert metadata == self.fake_metadata","def test_columns_set_to_all_columns_when_none(self):\n\n df = d.create_df_1()\n\n x = BaseTransformer(columns=None)\n\n x.columns_set_or_check(X=df)\n\n h.assert_equal_dispatch(\n expected=list(df.columns.values),\n actual=x.columns,\n msg=\"x.columns set when None\",\n )","def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\n name = to_safe_name(col_schema['name'])\n return bigquery.SchemaField(\n name,\n col_schema.get('type'),\n col_schema.get('mode', 'NULLABLE'),\n col_schema.get('description', '')\n )","def _load_schema(self, mode=\"staging\"):\n\n self._check_mode(mode)\n\n json_path = self.table_folder / f\"schema-{mode}.json\"\n columns = self.table_config[\"columns\"]\n\n if mode == \"staging\":\n new_columns = []\n for c in columns:\n # case is_in_staging are None then must be True\n is_in_staging = (\n True if c.get(\"is_in_staging\") is None else c[\"is_in_staging\"]\n )\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\n if is_in_staging and not c.get(\"is_partition\"):\n c[\"type\"] = \"STRING\"\n new_columns.append(c)\n\n del columns\n columns = new_columns\n\n elif mode == \"prod\":\n schema = self._get_table_obj(mode).schema\n\n # get field names for fields at schema and at table_config.yaml\n column_names = [c[\"name\"] for c in columns]\n schema_names = [s.name for s in schema]\n\n # check if there are mismatched fields\n not_in_columns = [name for name in schema_names if name not in column_names]\n not_in_schema = [name for name in column_names if name not in schema_names]\n\n # raise if field is not in table_config\n if not_in_columns:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in table_config.yaml. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_columns,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # raise if field is not in schema\n if not_in_schema:\n raise BaseDosDadosException(\n \"Column {error_columns} was not found in publish.sql. Are you sure that \"\n \"all your column names between table_config.yaml, publish.sql and \"\n \"{project_id}.{dataset_id}.{table_id} are the same?\".format(\n error_columns=not_in_schema,\n project_id=self.table_config[\"project_id_prod\"],\n dataset_id=self.table_config[\"dataset_id\"],\n table_id=self.table_config[\"table_id\"],\n )\n )\n\n # if field is in schema, get field_type and field_mode\n for c in columns:\n for s in schema:\n if c[\"name\"] == s.name:\n c[\"type\"] = s.field_type\n c[\"mode\"] = s.mode\n break\n ## force utf-8, write schema_{mode}.json\n json.dump(columns, (json_path).open(\"w\", encoding=\"utf-8\"))\n\n # load new created schema\n return self.client[f\"bigquery_{mode}\"].schema_from_json(str(json_path))","def initialize_schema(self, dry_run=False):\n if not dry_run:\n self.flush()","def _decode_nullable(\n data_type, obj, alias_validators, strict, old_style, for_msgpack):\n if obj is not None:\n return _json_compat_obj_decode_helper(\n data_type.validator, obj, alias_validators, strict, old_style,\n for_msgpack)\n else:\n return None","def _parse_fixed_length_data(self, original_record, column, null_table):\n column_name = column.col_name_str\n # Boolean fields are encoded in the null table\n if column.type == TYPE_BOOLEAN:\n if column.column_id > len(null_table):\n logging.error(f\"Failed to parse bool field, Column not found in null_table column: {column_name} ,\"\n f\" column id: {column.column_id} , null_table: {null_table}\")\n return\n\n parsed_type = null_table[column.column_id]\n else:\n\n if column.fixed_offset > len(original_record):\n logging.error(f\"Column offset is bigger than the length of the record {column.fixed_offset}\")\n return\n record = original_record[column.fixed_offset:]\n parsed_type = parse_type(column.type, record, version=self.version)\n\n if not null_table[column.column_id] and column.type != TYPE_BOOLEAN:\n self.parsed_table[column_name].append(\"\")\n else:\n self.parsed_table[column_name].append(parsed_type)","def rev_ensure_column(v,initial_shape):\n if initial_shape: # check that the tuple is nonempty\n v.shape = initial_shape \n \n return v","def test_null_update_deletes_column(self):\r\n partition = uuid4()\r\n for i in range(5):\r\n TestQueryUpdateModel.create(partition=partition, cluster=i, count=i, text=str(i))\r\n\r\n # sanity check\r\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\r\n assert row.cluster == i\r\n assert row.count == i\r\n assert row.text == str(i)\r\n\r\n # perform update\r\n TestQueryUpdateModel.objects(partition=partition, cluster=3).update(text=None)\r\n\r\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\r\n assert row.cluster == i\r\n assert row.count == i\r\n assert row.text == (None if i == 3 else str(i))","def test_update_risk_field_to_null(self, field, field_name):\n risk = factories.RiskFactory()\n\n response = self.api.put(risk, risk.id, {\n field: None,\n })\n\n self.assert400(response)\n self.assertEqual(response.json[\"message\"],\n field_name + \" for the object is not specified\")\n risk = db.session.query(all_models.Risk).get(risk.id)\n self.assertIsNotNone(risk.external_id)","def _base_schema(self, data_schema: Callable[[bool], StructType]) -> StructType:\n return StructType([\n StructField(\"id\", StringType(), False),\n StructField(\"op\", StringType(), False),\n StructField(\"ts\", LongType(), False),\n StructField(\"data\", data_schema(False), True),\n StructField(\"set\", data_schema(True), True),\n ])","def flatten_schema_map(\n schema_map,\n keep_nulls=False,\n sorted_schema=True,\n infer_mode=False,\n input_format='json',\n):\n if not isinstance(schema_map, dict):\n raise Exception(\n f\"Unexpected type '{type(schema_map)}' for schema_map\"\n )\n\n # Build the BigQuery schema from the internal 'schema_map'.\n schema = []\n map_items = sorted(schema_map.items()) if sorted_schema \\\n else schema_map.items()\n for name, meta in map_items:\n # Skip over fields which have been explicitly removed\n if not meta:\n continue\n\n status = meta['status']\n filled = meta['filled']\n info = meta['info']\n\n # Schema entries with a status of 'soft' are caused by 'null' or\n # empty fields. Don't print those out if the 'keep_nulls' flag is\n # False.\n if status == 'soft' and not keep_nulls:\n continue\n\n # Copy the 'info' dictionary into the schema dict, preserving the\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\n # keeps these sorted, so we created them in sorted order using an\n # OrderedDict, so they should preserve order here too.\n new_info = OrderedDict()\n for key, value in info.items():\n if key == 'fields':\n if not value:\n # Create a dummy attribute for an empty RECORD to make\n # the BigQuery importer happy.\n new_value = [\n OrderedDict([\n ('mode', 'NULLABLE'),\n ('name', '__unknown__'),\n ('type', 'STRING'),\n ])\n ]\n else:\n # Recursively flatten the sub-fields of a RECORD entry.\n new_value = flatten_schema_map(\n schema_map=value,\n keep_nulls=keep_nulls,\n sorted_schema=sorted_schema,\n infer_mode=infer_mode,\n input_format=input_format\n )\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\n new_value = value[1:]\n elif key == 'mode':\n # 'infer_mode' to set a field as REQUIRED is supported for only\n # input_format = 'csv' because the header line gives us the\n # complete list of fields to be expected in the CSV file. In\n # JSON data files, certain fields will often be completely\n # missing instead of being set to 'null' or \"\". If the field is\n # not even present, then it becomes incredibly difficult (not\n # impossible, but more effort than I want to expend right now)\n # to figure out which fields are missing so that we can mark the\n # appropriate schema entries with 'filled=False'.\n #\n # The --infer_mode option is activated only for\n # input_format == 'csv' in this function, which allows us to\n # overload the --infer_mode flag to mean that a REQUIRED mode of\n # an existing schema can transition to a NULLABLE mode.\n if (infer_mode and value == 'NULLABLE' and filled\n and input_format == 'csv'):\n new_value = 'REQUIRED'\n else:\n new_value = value\n else:\n new_value = value\n new_info[key] = new_value\n schema.append(new_info)\n return schema","def is_field_nullable(\n nullable: Optional[bool],\n default: Any,\n server_default: Any,\n pydantic_only: Optional[bool],\n) -> bool:\n if nullable is None:\n return (\n default is not None\n or server_default is not None\n or (pydantic_only is not None and pydantic_only)\n )\n return nullable","def update_writables(self, record_id, fields, typecast=False):\n \n cols = self.writable_columns\n cols_dict = { col['name']: col for col in cols }\n writable_fields = { k : v for k, v in fields.items() if k in cols_dict}\n \n Airtable.update(self, record_id, writable_fields, typecast)","def before_update(mapper, conn, target):\n if isinstance(target, Column):\n raise TypeError('Got a column instead of a table')\n\n if target.id_ is None:\n dataset_id = ObjectNumber.parse(target.d_id)\n target.id_ = str(TableNumber(dataset_id, target.sequence_id))","def _is_nullable(self) -> bool:\n return self.__nullable","def set_schema(self, schema):\r\n self.__schema = schema","def _set_default_edit_fields(self):\n default_edit_fields = []\n\n for col in self.table.get_column_names():\n req = False\n if col[-3:].lower() == '_id':\n # foreign key\n req = True\n \n dict_template = self._get_field_list_dict()\n \n dict_template['name'] = '{}'.format(col)\n dict_template['label'] = '{}'.format(col).replace('_',' ').title()\n dict_template['type'] = 'text'\n try:\n dict_template['type'] = '{}'.format(self.table.get_column_type(col))\n except KeyError:\n pass\n dict_template['req'] = req\n \n default_edit_fields.append(dict_template)\n \n return default_edit_fields","def set_schema(self, schema, set_num_columns=True):\n update_dict = {self.SCHEMA: schema}\n\n if set_num_columns:\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\n\n self.update(update_dict)","def _clean_up_columns(\n self):\n self.log.debug('starting the ``_clean_up_columns`` method')\n\n tableName = self.dbTableName\n\n print \"cleaning up %(tableName)s columns\" % locals()\n\n sqlQuery = u\"\"\"\n set sql_mode=\"STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION\";\n \"\"\" % locals()\n writequery(\n log=self.log,\n sqlQuery=sqlQuery,\n dbConn=self.cataloguesDbConn,\n )\n\n sqlQuery = u\"\"\"\n update %(tableName)s set dist_mod_err = null where dist_mod_err = 0;\n update %(tableName)s set dist_in_ned_flag = null where dist_in_ned_flag = \"\";\n update %(tableName)s set notes = null where notes = \"\";\n update %(tableName)s set redshift = null where redshift = 0;\n update %(tableName)s set dist_derived_from_sn = null where dist_derived_from_sn = \"\";\n update %(tableName)s set hubble_const = null where hubble_const = 0;\n update %(tableName)s set lmc_mod = null where lmc_mod = 0;\n update %(tableName)s set master_row = 0;\n update %(tableName)s set master_row = 1 where primaryId in (select * from (select distinct primaryId from %(tableName)s group by galaxy_index_id) as alias);\n \"\"\" % locals()\n writequery(\n log=self.log,\n sqlQuery=sqlQuery,\n dbConn=self.cataloguesDbConn,\n )\n\n self.log.debug('completed the ``_clean_up_columns`` method')\n return None","def test_can_update_risk_type_schema(self):\n risk_type = self.create_risk_type()\n for r in risk_type.schema:\n if r['field_type'] == 'text':\n r['field_type'] = 'textarea'\n break\n\n response = self.client.put(\n f'/api/v0/risk-types/{risk_type.id}/',\n data={\n 'type_name': 'New Risk Type',\n 'schema': risk_type.schema,\n }, format='json')\n risk_type.refresh_from_db()\n self.assertEqual(response.status_code, status.HTTP_200_OK)\n self.assertEqual(risk_type.schema[0].get('field_type'), 'textarea')","def test_updates_from_none(self):\r\n m = TestMapModel.create(int_map=None)\r\n expected = {1: uuid4()}\r\n m.int_map = expected\r\n m.save()\r\n\r\n m2 = TestMapModel.get(partition=m.partition)\r\n assert m2.int_map == expected\r\n\r\n m2.int_map = None\r\n m2.save()\r\n m3 = TestMapModel.get(partition=m.partition)\r\n assert m3.int_map != expected","def convertToParamNull(self):\n for sAttr in self.getDataAttributes():\n oValue = getattr(self, sAttr);\n oNewValue = self._convertAttributeToParamNull(sAttr, oValue);\n if oValue != oNewValue:\n setattr(self, sAttr, oNewValue);\n return self;","def _write_local_schema_file(self, cursor):\n schema = []\n tmp_schema_file_handle = NamedTemporaryFile(delete=True)\n if self.schema is not None and isinstance(self.schema, string_types):\n schema = self.schema\n tmp_schema_file_handle.write(schema)\n else:\n if self.schema is not None and isinstance(self.schema, list):\n schema = self.schema\n else:\n for field in cursor.description:\n # See PEP 249 for details about the description tuple.\n field_name = field[0]\n field_type = self.type_map(field[1])\n # Always allow TIMESTAMP to be nullable. MySQLdb returns None types\n # for required fields because some MySQL timestamps can't be\n # represented by Python's datetime (e.g. 0000-00-00 00:00:00).\n if field[6] or field_type == 'TIMESTAMP':\n field_mode = 'NULLABLE'\n else:\n field_mode = 'REQUIRED'\n schema.append({\n 'name': field_name,\n 'type': field_type,\n 'mode': field_mode,\n })\n s = json.dumps(schema, tmp_schema_file_handle, sort_keys=True)\n if PY3:\n s = s.encode('utf-8')\n tmp_schema_file_handle.write(s)\n\n self.log.info('Using schema for %s: %s', self.schema_filename, schema)\n return {self.schema_filename: tmp_schema_file_handle}","def modify_tbl(self):\n debug = False\n dd = mg.DATADETS_OBJ\n orig_tblname = dd.tbl\n ## other (i.e. not the sofa_id) field details\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\n if debug:\n print('oth_name_types to feed into '\n f'make_strict_typing_tbl {oth_name_types}')\n try: ## 1 way or other must do strict_cleanup()\n make_strict_typing_tbl(\n orig_tblname, oth_name_types, self.settings_data)\n except sqlite.IntegrityError as e: #@UndefinedVariable\n if debug: print(b.ue(e))\n strict_cleanup(restore_tblname=orig_tblname)\n raise FldMismatchException\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n raise Exception('Problem making strictly-typed table.'\n f'\\nCaused by error: {b.ue(e)}')\n copy_orig_tbl(orig_tblname)\n wipe_tbl(orig_tblname)\n final_name = self.tblname_lst[0] ## may have been renamed\n try:\n make_redesigned_tbl(final_name, oth_name_types)\n strict_cleanup(restore_tblname=final_name)\n dd.set_tbl(tbl=final_name)\n except Exception as e:\n strict_cleanup(restore_tblname=orig_tblname)\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\n dd.set_tbl(tbl=orig_tblname)\n raise Exception('Problem making redesigned table.'\n f'\\nCaused by error: {b.ue(e)}')\n wipe_tbl(mg.TMP_TBLNAME2)","def generate_altered_fields(self):\n result = super(MigrationAutodetector, self).generate_altered_fields()\n self.generate_sql_changes()\n return result","def dim_col_imputation(self, columns):\n for column in columns:\n if column in self.col_with_nulls:\n if not self._pandas_flag:\n mode = self.data_frame.select(column).toPandas().mode().values[0][0]\n self.data_frame = self.data_frame.fillna({ column:mode })\n else:\n self.data_frame[column] = self.mode_impute(self.data_frame[column])\n self.data_change_dict['ModeImputeCols'].append(column)","def test_update_from_none(self):\r\n ctx = {}\r\n col = columns.Set(columns.Integer, db_field=\"TEST\")\r\n statements = col.get_update_statement({1, 2, 3, 4}, None, ctx)\r\n\r\n #only one variable /statement should be generated\r\n assert len(ctx) == 1\r\n assert len(statements) == 1\r\n\r\n assert ctx.values()[0].value == {1, 2, 3, 4}\r\n assert statements[0] == '\"TEST\" = :{}'.format(ctx.keys()[0])","def _migrate_0(self, entry):\r\n if 'name' not in entry['_id']:\r\n entry_id = entry['_id']\r\n entry_id = bson.son.SON([\r\n ('org', entry_id['org']),\r\n ('course', entry_id['course']),\r\n ])\r\n self.location_map.remove({'_id': entry_id})\r\n return None\r\n\r\n # add schema, org, offering, etc, remove old fields\r\n entry['schema'] = 0\r\n entry.pop('course_id', None)\r\n entry.pop('lower_course_id', None)\r\n old_course_id = SlashSeparatedCourseKey(entry['_id']['org'], entry['_id']['course'], entry['_id']['name'])\r\n entry['org'] = old_course_id.org\r\n entry['offering'] = old_course_id.offering.replace('/', '+')\r\n return self._migrate_1(entry, True)","def is_nullable_type(self):\n raise exceptions.NotImplementedError()","def merge_attribute_schema(self, attr_schema):\n name = attr_schema.name\n if name not in self.schema:\n self.schema[name] = attr_schema\n else:\n self.schema[name].merge_schema(attr_schema)","def deferred_to_columns_cb(self, target, model, fields):\n table = model._meta.db_table\n if table not in target:\n target[table] = set()\n for field in fields:\n if not hasattr(field.column, \"columns\"):\n target[table].add(field.column)\n else:\n target[table].update(field.column.columns)","def _null_set_rel_pos(self, rel_pos):\n self.get_sp_rel_pos = self._null_get_rel_pos","def convertFromParamNull(self):\n for sAttr in self.getDataAttributes():\n oValue = getattr(self, sAttr);\n oNewValue = self._convertAttributeFromParamNull(sAttr, oValue);\n if oValue != oNewValue:\n setattr(self, sAttr, oNewValue);\n return self;","def test_update_field_to_null(self, field, field_name):\n control = factories.ControlFactory()\n\n response = self.api.put(control, control.id, {field: None})\n\n self.assert400(response)\n self.assertEqual(response.json[\"message\"],\n field_name + \" for the object is not specified\")\n control = db.session.query(all_models.Control).get(control.id)\n self.assertIsNotNone(control.external_id)","def DEADempty_fix_table():\n sqlnuke = \"delete from fix\"\n conf.Cur.execute(sqlnuke)\n conf.Con.commit()","def _migrate_if_necessary(self, entries):\r\n entries = [\r\n self._migrate[entry.get('schema', 0)](self, entry)\r\n for entry in entries\r\n ]\r\n return entries","def column_empty_like_same_mask(column, dtype):\n data = cuda.device_array(shape=len(column), dtype=dtype)\n params = dict(data=Buffer(data))\n if column.has_null_mask:\n params.update(mask=column.nullmask)\n return Column(**params)","def update(self, schema: ISchema) -> ISchema:\n schema = super().update(schema)\n\n schema = cast(EventSchema, schema)\n if not schema.Active and schema.Sport > 0:\n self.select('ID', 'Sport', 'Active').filter(\n 'Sport', Operators.Equals, schema.Sport,\n ).filter('Active', Operators.Equals, 1)\n result = self.execute()\n if not result:\n sm = SportModel()\n sport = sm.find(schema.Sport)\n sport = cast(SportSchema, sport)\n sport.Active = False\n sm.update(sport)\n return schema","def isNullable(self):\n if self.isPrimaryKey():\n return False\n else:\n return self._nullable","def apply_to(self, df: pd.DataFrame) -> pd.DataFrame:\n schema_names = self.names\n data_columns = df.columns\n\n assert len(schema_names) == len(\n data_columns\n ), \"schema column count does not match input data column count\"\n\n for column, dtype in zip(data_columns, self.types):\n pandas_dtype = dtype.to_pandas()\n\n col = df[column]\n col_dtype = col.dtype\n\n try:\n not_equal = pandas_dtype != col_dtype\n except TypeError:\n # ugh, we can't compare dtypes coming from pandas,\n # assume not equal\n not_equal = True\n\n if not_equal or not dtype.is_primitive():\n new_col = convert(col_dtype, dtype, col)\n else:\n new_col = col\n df[column] = new_col\n\n # return data with the schema's columns which may be different than the\n # input columns\n df.columns = schema_names\n return df","def columns_setup(self):\n self.required = None\n self.addition = None\n self.deletion = None\n self.retention = None\n self.rename = None","def test_empty_cols_allowed(self):\n self.test_table.allow_empty_columns = True\n self.test_table.change_header(Path=1, SectionType=3, Value=4)\n self.assertEqual(self.test_table._header, [\"Path\", None, \"SectionType\",\n \"Value\"])","def on_doctype_update():\n\tif not frappe.db.sql(\"\"\"show index from `tabDefaultValue`\n\t\twhere Key_name=\"defaultvalue_parent_defkey_index\" \"\"\"):\n\t\tfrappe.db.commit()\n\t\tfrappe.db.sql(\"\"\"alter table `tabDefaultValue`\n\t\t\tadd index defaultvalue_parent_defkey_index(parent, defkey)\"\"\")\n\n\tif not frappe.db.sql(\"\"\"show index from `tabDefaultValue`\n\t\twhere Key_name=\"defaultvalue_parent_parenttype_index\" \"\"\"):\n\t\tfrappe.db.commit()\n\t\tfrappe.db.sql(\"\"\"alter table `tabDefaultValue`\n\t\t\tadd index defaultvalue_parent_parenttype_index(parent, parenttype)\"\"\")","def change_col_type(df,schema):\n d = {'int':IntegerType(),'str':StringType(),'float':FloatType(),'bool':BooleanType()}\n \n for c,t in schema.items():\n df = df.withColumn(c,col(c).cast(d[t]))\n return df","def is_nullable(self):\n return self._is_nullable","def getSchemaMap(self):\n\t\trSchemaMap = {}\n\t\tfor schemaName in self.schemaList:\n\t\t\tmodeList = [str(tKey) for tKey in self.schemaList[schemaName].modes.keys()]\n\n\t\t\tif len(modeList) == 1 and None in self.schemaList[schemaName].modes:\n\t\t\t\trSchemaMap[schemaName] = 0\n\t\t\telse:\n\t\t\t\trSchemaMap[schemaName] = modeList\n\n\t\treturn rSchemaMap","def before_insert(mapper, conn, target):\n\n #from identity import ObjectNumber\n #assert not target.fk_vid or not ObjectNumber.parse(target.fk_vid).revision\n\n if target.sequence_id is None:\n # In case this happens in multi-process mode\n conn.execute(\"BEGIN IMMEDIATE\")\n sql = text(\n '''SELECT max(c_sequence_id)+1 FROM columns WHERE c_t_id = :tid''')\n\n max_id, = conn.execute(sql, tid=target.t_id).fetchone()\n\n if not max_id:\n max_id = 1\n\n target.sequence_id = max_id\n\n Column.before_update(mapper, conn, target)","def set_default_values_as_needed(self):\n if self.verbose:\n click.echo('Updating required default values')\n for field in ARGUMENTS_DEFAULT_VALUES:\n if self.__class__.__name__ in ARGUMENTS_DEFAULT_VALUES[field][1]:\n self.data[field] = ARGUMENTS_DEFAULT_VALUES[field][0]","def reset_modified(self):\n self.modified_fields = set()\n\n # compensate for us not having knowledge of certain fields changing\n for field_name, field in self.schema.normal_fields.items():\n if isinstance(field, ObjectField):\n self.modified_fields.add(field_name)","def s3_table_set_before_write(cls, table):\n\n update_default = cls.s3_table_name_update_default\n\n table._before_insert.append(update_default)\n table._before_update.append(lambda s, data: update_default(data))","def standardize(self, options: ParameterSetSchema) -> \"Parameters\":\n replace_dict = {}\n for key, val in asdict(self).items():\n dimensions = (val.shape[0], getattr(options, key).degree + 1)\n val_new = np.zeros(dimensions)\n max_dimension = (np.minimum(val.shape[1], dimensions[1]))\n val_new[:, :max_dimension] = val[:, :max_dimension]\n replace_dict.update({key: val_new})\n return replace(self, **replace_dict)","def changenonetoNone(s):\r\n if s=='None':\r\n return None\r\n else:\r\n return s"],"string":"[\n \"def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\\n old_info = old_schema_entry['info']\\n new_info = new_schema_entry['info']\\n old_mode = old_info['mode']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_status = old_schema_entry['status']\\n new_mode = new_info['mode']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_status = new_schema_entry['status']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # If the old field is a REQUIRED primitive (which could only have come\\n # from an existing schema), the new field can be either a\\n # NULLABLE(filled) or a NULLABLE(unfilled).\\n if old_mode == 'REQUIRED' and new_mode == 'NULLABLE':\\n # If the new field is filled, then retain the REQUIRED.\\n if new_schema_entry['filled']:\\n return old_mode\\n else:\\n # The new field is not filled (i.e. an empty or null field).\\n # If --infer_mode is active, then we allow the REQUIRED to\\n # revert back to NULLABLE.\\n if self.infer_mode:\\n return new_mode\\n else:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode.'\\n ' cannot convert to NULLABLE because infer_schema not'\\n ' set:'\\n f' old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n elif old_mode != new_mode:\\n self.log_error(\\n f'Ignoring non-RECORD field with mismatched mode: '\\n f'old=({old_status},{full_old_name},{old_mode},'\\n f'{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},'\\n f'{new_type})'\\n )\\n return None\\n return old_mode\",\n \"def nullable(self):\\n _columns = []\\n if not isinstance(self._last_column, list):\\n _columns = [self._last_column]\\n\\n for column in _columns:\\n column.nullable()\\n return self\",\n \"def filter_schema(schema):\\n for column, column_schema in schema.iteritems():\\n if column_schema.get(CARDINALITY):\\n del column_schema[CARDINALITY]\\n schema[column] = column_schema\\n\\n return schema\",\n \"def _delete_null_columns(self):\\r\\n ds = DeleteStatement(self.column_family_name)\\r\\n deleted_fields = False\\r\\n for _, v in self.instance._values.items():\\r\\n col = v.column\\r\\n if v.deleted:\\r\\n ds.add_field(col.db_field_name)\\r\\n deleted_fields = True\\r\\n elif isinstance(col, Map):\\r\\n uc = MapDeleteClause(col.db_field_name, v.value, v.previous_value)\\r\\n if uc.get_context_size() > 0:\\r\\n ds.add_field(uc)\\r\\n deleted_fields = True\\r\\n\\r\\n if deleted_fields:\\r\\n for name, col in self.model._primary_keys.items():\\r\\n ds.add_where_clause(WhereClause(\\r\\n col.db_field_name,\\r\\n EqualsOperator(),\\r\\n col.to_database(getattr(self.instance, name))\\r\\n ))\\r\\n self._execute(ds)\",\n \"def ProcessSchemaUpdate(ref, args, request):\\n table = request.table\\n relaxed_columns = args.relax_columns\\n if not table.schema and not relaxed_columns: # if not updating schema,\\n return request # then just return.\\n\\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\\n ref.Name(),\\n ref.projectId)\\n\\n new_schema_columns = table.schema\\n updated_fields = _GetUpdatedSchema(original_schema,\\n new_schema_columns,\\n relaxed_columns)\\n\\n table_schema_type = GetApiMessage('TableSchema')\\n request.table.schema = table_schema_type(fields=updated_fields)\\n\\n return request\",\n \"def merge_schema_entry(\\n self,\\n old_schema_entry,\\n new_schema_entry,\\n base_path=None,\\n ):\\n if not old_schema_entry:\\n return new_schema_entry\\n\\n # If the new schema is None, return immediately.\\n if not new_schema_entry:\\n return new_schema_entry\\n\\n # If a field value is missing, permanently set 'filled' to False.\\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\\n old_schema_entry['filled'] = False\\n new_schema_entry['filled'] = False\\n\\n old_status = old_schema_entry['status']\\n new_status = new_schema_entry['status']\\n\\n # new 'soft' does not clobber old 'hard'\\n if old_status == 'hard' and new_status == 'soft':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n old_schema_entry['info']['mode'] = mode\\n return old_schema_entry\\n\\n # new 'hard' clobbers old 'soft'\\n if old_status == 'soft' and new_status == 'hard':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n new_schema_entry['info']['mode'] = mode\\n return new_schema_entry\\n\\n # Verify that it's soft->soft or hard->hard\\n if old_status != new_status:\\n raise Exception(\\n f'Unexpected schema_entry type, this should never happen: '\\n f'old ({old_status}); new ({new_status})'\\n )\\n\\n old_info = old_schema_entry['info']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_mode = old_info['mode']\\n new_info = new_schema_entry['info']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_mode = new_info['mode']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # Defensive check, names should always be the same.\\n if old_name != new_name:\\n if old_name.lower() != new_name.lower():\\n raise Exception(\\n 'Unexpected difference in name, should never happen:'\\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\\n )\\n else:\\n # preserve old name if case is different\\n new_info['name'] = old_info['name']\\n\\n # Recursively merge in the subfields of a RECORD, allowing\\n # NULLABLE to become REPEATED (because 'bq load' allows it).\\n if old_type == 'RECORD' and new_type == 'RECORD':\\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\\n # 'bq load' allows it.\\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\\n old_info['mode'] = 'REPEATED'\\n self.log_error(\\n f'Converting schema for \\\"{full_old_name}\\\" from '\\n 'NULLABLE RECORD into REPEATED RECORD'\\n )\\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\\n # TODO: Maybe remove this warning output. It was helpful during\\n # development, but maybe it's just natural.\\n self.log_error(\\n f'Leaving schema for \\\"{full_old_name}\\\" as REPEATED RECORD'\\n )\\n\\n # RECORD type needs a recursive merging of sub-fields. We merge into\\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\\n # can be modified in situ.\\n old_fields = old_info['fields']\\n new_fields = new_info['fields']\\n for key, new_entry in new_fields.items():\\n old_entry = old_fields.get(key)\\n new_base_path = json_full_path(base_path, old_name)\\n old_fields[key] = self.merge_schema_entry(\\n old_schema_entry=old_entry,\\n new_schema_entry=new_entry,\\n base_path=new_base_path,\\n )\\n return old_schema_entry\\n\\n new_mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if new_mode is None:\\n return None\\n new_schema_entry['info']['mode'] = new_mode\\n\\n # For all other types...\\n if old_type != new_type:\\n # Check that the converted types are compatible.\\n candidate_type = convert_type(old_type, new_type)\\n if not candidate_type:\\n self.log_error(\\n f'Ignoring field with mismatched type: '\\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\\n )\\n return None\\n\\n new_info['type'] = candidate_type\\n return new_schema_entry\",\n \"def remove_null_fields(self):\\n with open(self.schema_path, 'r') as file_obj:\\n schema_data = yaml.safe_load(file_obj)\\n schema_fields = schema_data.get('mapping').keys()\\n for field in schema_fields:\\n # We want to keep 'false' and 0 values, and avoid removing fields that are required in the schema.\\n if field in self.data and self.data[field] in (None, '', [], {}) and \\\\\\n not schema_data.get('mapping', {}).get(field, {}).get('required'):\\n self.data.pop(field)\",\n \"def modify_bigquery_schema(self, schema, info_keys):\\n # type: (bigquery.TableSchema, Set[str]) -> None\",\n \"def merge_schema(self, schema):\\n self.validate_schema(schema)\\n\\n if self.exclusive is False:\\n self.exclusive = schema.exclusive\\n\\n if self.default is None:\\n self.default = schema.default\",\n \"def _patch_schema(self):\\n fields = get_json()['data']['attributes'].keys()\\n return make_entity_schema(\\n self.SCHEMA, self.RESOURCE_NAME,\\n make_data_schema(\\n self.SCHEMA, id_required=True,\\n only=fields, partial=True\\n )\\n )\",\n \"def drop_null(self, how: Literal[\\\"any\\\", \\\"all\\\"] = \\\"any\\\"):\\n # TODO only flat columns supported...\\n assert self._dtype is not None\\n res = Scope._EmptyColumn(self._dtype.constructor(nullable=False))\\n if how == \\\"any\\\":\\n for i in self:\\n if not self._has_any_null(i):\\n res._append(i)\\n elif how == \\\"all\\\":\\n for i in self:\\n if not self._has_all_null(i):\\n res._append(i)\\n return res._finalize()\",\n \"def correct_db_schema_precision(\\n instance: Recorder,\\n table_object: type[DeclarativeBase],\\n schema_errors: set[str],\\n) -> None:\\n table_name = table_object.__tablename__\\n\\n if f\\\"{table_name}.double precision\\\" in schema_errors:\\n from ..migration import ( # pylint: disable=import-outside-toplevel\\n _modify_columns,\\n )\\n\\n precision_columns = _get_precision_column_types(table_object)\\n # Attempt to convert timestamp columns to µs precision\\n session_maker = instance.get_session\\n engine = instance.engine\\n assert engine is not None, \\\"Engine should be set\\\"\\n _modify_columns(\\n session_maker,\\n engine,\\n table_name,\\n [f\\\"{column} {DOUBLE_PRECISION_TYPE_SQL}\\\" for column in precision_columns],\\n )\",\n \"def _add_to_schema(self, new: dict):\\n self._defaults.update(new)\\n self._migrate()\",\n \"def is_nullable(schema_obj):\\n\\n if isinstance(schema_obj, schema.Field):\\n return schema_obj.is_nullable\\n return False\",\n \"def setNullAllowed(self, onlyNullAllowed):\\n self._onlyNullAllowed = onlyNullAllowed\",\n \"def nullify(self):\\n self._original_values.clear()\\n self._modified_values.clear()\\n self._extra_record_data.clear()\\n self._references.clear()\\n for mtm in self._mtm_referencelist:\\n self._mtm_referencelist[mtm].parentobjectid = None\\n for chl in self._child_referencelist:\\n self._child_referencelist[chl].clear() \\n self._ismodified = False\\n self._hasdata = False\\n self._astxt = \\\"(null)\\\"\\n if self._table: \\n for f in self._table:\\n self._original_values[f.name] = None\",\n \"def set_sql_mode(self):\\n self.execute_sql(\\n sql.set_session_variable(\\\"sql_mode\\\"),\\n (\\\"STRICT_ALL_TABLES,NO_AUTO_VALUE_ON_ZERO\\\",),\\n )\",\n \"def is_nullable(self) -> bool: # pragma: no cover\\n pass\",\n \"def _AddNewColsToSchema(new_fields, orig_schema_map):\\n updated_schema_map = orig_schema_map.copy()\\n for new_field in new_fields:\\n if new_field.name in orig_schema_map:\\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\\n updated_schema_map[new_field.name] = new_field\\n return updated_schema_map\",\n \"def fillna_mode(data, columns, verbose=True):\\n for col in columns:\\n fill_val = data[col].mode()[0]\\n if verbose: print('Filling ' + col + ' with: ' + fill_val)\\n data[col].fillna(fill_val, inplace=True)\",\n \"def update_table_columns(self, table_name, table):\\n table_definition = self._table_definitions[table_name]\\n new_columns = table.columns.difference(table_definition.c.keys())\\n new_column_types = {c: table.dtypes[c] for c in new_columns}\\n\\n allows_covariates = table_definition.name in [\\\"avgint\\\", \\\"data\\\"]\\n\\n good_prefixes = [\\\"c_\\\"]\\n if allows_covariates:\\n good_prefixes.append(\\\"x_\\\")\\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\\n if bad_column_names:\\n msg = f\\\"\\\"\\\"\\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\\n It allows additional comment columns, which must start 'c_'.\\\"\\\"\\\"\\n if allows_covariates:\\n msg += \\\" In addition it allows covariate columns, which must start with 'x_'.\\\"\\n msg += f\\\" You supplied columns that don't meet those requirements: {bad_column_names}\\\"\\n\\n raise ValueError(dedent(msg))\\n\\n add_columns_to_table(table_definition, new_column_types)\",\n \"def _copy_custom_attributes(self, column):\\n\\n column._fk = self._fk\\n column._fk_on_update = self._fk_on_update\\n column._fk_on_delete = self._fk_on_delete\\n\\n super()._copy_custom_attributes(column)\",\n \"async def upgradeSchema(self) -> None:\",\n \"def _GetUpdatedSchema(\\n original_schema,\\n new_columns=None,\\n relaxed_columns=None):\\n orig_field_map = (\\n {f.name: f for f in original_schema.fields} if original_schema else {})\\n\\n if relaxed_columns:\\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\\n\\n if new_columns:\\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\\n\\n return sorted(orig_field_map.values(), key=lambda x: x.name)\",\n \"def reset_schema_defs():\\n SCHEMA_DEFS.clear()\\n SCHEMA_DEFS.update((typ, typ) for typ in PRIMITIVE_TYPES)\",\n \"def replace(self, dictionary):\\n for column in self.__table__.columns.keys():\\n setattr(self, column, None)\\n self.from_dict(dictionary)\",\n \"def _fillna_meta_cols(self):\\n for col_name, fill_value in self._fillna.items():\\n if col_name in self._hybrid_meta.columns:\\n self._hybrid_meta[col_name].fillna(fill_value, inplace=True)\\n else:\\n self.__warn_missing_col(col_name, action='fill')\\n\\n self._hybrid_meta[self.__solar_rpi_n].fillna(-1, inplace=True)\\n self._hybrid_meta[self.__wind_rpi_n].fillna(-1, inplace=True)\",\n \"def update_records(cursor,table_schema,table_name,column_name,value):\\n update_records = \\\"UPDATE \\\" + table_schema + \\\".\\\" + table_name + \\\" SET \\\" + column_name + \\\"='\\\" + value + \\\"' WHERE COALESCE(\\\" + column_name + \\\",'')='';\\\"\\n cursor.execute(update_records)\",\n \"def _set_editable_mode(self):\\n dist = self.distribution\\n build = dist.get_command_obj(\\\"build\\\")\\n for cmd_name in build.get_sub_commands():\\n cmd = dist.get_command_obj(cmd_name)\\n if hasattr(cmd, \\\"editable_mode\\\"):\\n cmd.editable_mode = True\\n elif hasattr(cmd, \\\"inplace\\\"):\\n cmd.inplace = True # backward compatibility with distutils\",\n \"def test_null_update_deletes_column(self):\\n partition = uuid4()\\n for i in range(5):\\n TestQueryUpdateModel.create(partition=partition, cluster=i, count=i, text=str(i))\\n\\n # sanity check\\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\\n self.assertEqual(row.cluster, i)\\n self.assertEqual(row.count, i)\\n self.assertEqual(row.text, str(i))\\n\\n # perform update\\n TestQueryUpdateModel.objects(partition=partition, cluster=3).update(text=None)\\n\\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\\n self.assertEqual(row.cluster, i)\\n self.assertEqual(row.count, i)\\n self.assertEqual(row.text, None if i == 3 else str(i))\",\n \"def update(self, force=False):\\n if (self.__fields is None) or force:\\n self.__fields = [f for f in self.dbms.fields(self.table, self.db)]\",\n \"def _encode_nullable(data_type, obj, alias_validators, old_style, for_msgpack):\\n if obj is not None:\\n return _json_compat_obj_encode_helper(\\n data_type.validator, obj, alias_validators, old_style, for_msgpack)\\n else:\\n return None\",\n \"def reinitToNull(self):\\n for sAttr in self.getDataAttributes():\\n setattr(self, sAttr, None);\\n return self;\",\n \"def set_null(self, /, *defaults: Any, **kwargs: Any) -> \\\"fn\\\":\\n return self._mod.set_null(self._func, *defaults, **kwargs)\",\n \"def get_nullable():\\n changes = True\\n while changes:\\n changes = False\\n for p in PRODUCTION_LIST:\\n if not symbol_for_str(p.left).is_nullable:\\n if p.right[0] == 'null':\\n symbol_for_str(p.left).is_nullable = True\\n changes = True\\n continue\\n else:\\n right_is_nullable = symbol_for_str(p.right[0]).is_nullable\\n # For X -> Y1 ... YN, Nullable(X) = Nullable(Y1) &\\n # Nullable(Y2) ... & Nullable(YN)\\n for r in p.right[1:]:\\n if r.startswith('P'):\\n continue\\n right_is_nullable = right_is_nullable & symbol_for_str(\\n r).is_nullable\\n\\n if right_is_nullable:\\n changes = True\\n symbol_for_str(p.left).is_nullable = True\",\n \"def __null_check(self, record_attribute, attribute_schema):\\n if attribute_schema[NULLABLE_KEY]:\\n return True\\n elif record_attribute is not None:\\n return True\\n else:\\n IS_VALID_FILE = False\\n return False\",\n \"def _prepend_none_dimension(features):\\n if features:\\n modified_features = dict(features) # Create a copy to modify\\n for key, feature in features.items():\\n if isinstance(feature, FixedLenSequenceFeature):\\n if not feature.allow_missing:\\n raise ValueError(\\\"Unsupported: FixedLenSequenceFeature requires \\\"\\n \\\"allow_missing to be True.\\\")\\n modified_features[key] = FixedLenSequenceFeature(\\n [None] + list(feature.shape),\\n feature.dtype,\\n feature.allow_missing,\\n feature.default_value)\\n return modified_features\\n else:\\n return features\",\n \"def add_schema_attribute(self):\\n schema_id = self.file.options['schema_id_attr']\\n if self.sdef['df'] and self.file.options['include_schema_id']:\\n # Normal defined entity\\n ns = self.sdef['ns']\\n id = self.sdef['id']\\n schema = ns + \\\":\\\" + id\\n self.attributes[schema_id] = {'value': schema}\\n elif self.file.options['flag_custom_nodes']:\\n self.attributes[schema_id] = {'value': 'custom'}\",\n \"def build_schema(self, dframe, overwrite=False, set_num_columns=True):\\n new_schema = self.schema.rebuild(dframe, overwrite)\\n self.set_schema(new_schema,\\n set_num_columns=(set_num_columns or overwrite))\",\n \"def fix_incremental(meta, bind):\\n meta.create_all(bind=bind, checkfirst=True)\\n ref = inspect(bind)\\n for table in meta.sorted_tables:\\n orm_cols = set(col.name for col in table.c)\\n ref_cols = set(col['name'] for col in ref.get_columns(table.name))\\n col_to_create = orm_cols - ref_cols\\n col_to_delete = ref_cols - orm_cols\\n if col_to_create:\\n print table.name, 'has diff to create', col_to_create\\n with bind.begin() as conn:\\n for col_name in col_to_create:\\n col = table.c.get(col_name)\\n column_sql = CreateColumn(col).compile(bind).string\\n sql = 'ALTER TABLE {} ADD COLUMN {}'.format(table.name, column_sql)\\n if col.default:\\n sql += ' DEFAULT {!r}'.format(col.default.arg) # can break when a pickle type has callable default.\\n if not col.nullable:\\n sql += ' NOT NULL'\\n print 'executing sql: ' + sql\\n conn.execute(sql)\\n\\n # Workaround to ensure updated DBs start with \\\"False\\\" in ignore column\\n if list(col_to_create)[0] == 'ignore':\\n sessionmaker = get_sessionmaker(bind.url.database)\\n session = sessionmaker()\\n query_object = {'dttrialdff0s': DTTrialDff0, 'trials': Trial}[table.name]\\n items = session.query(query_object).all()\\n for item in items:\\n item.ignore = False\\n session.flush()\\n\\n if col_to_delete:\\n print table.name, 'has diff to delete', col_to_delete, 'maybe later version.'\\n \\\"\\\"\\\"\\n BEGIN TRANSACTION;\\n CREATE TEMPORARY TABLE t1_backup(a,b);\\n INSERT INTO t1_backup SELECT a,b FROM t1;\\n DROP TABLE t1;\\n CREATE TABLE t1(a,b);\\n INSERT INTO t1 SELECT a,b FROM t1_backup;\\n DROP TABLE t1_backup;\\n COMMIT;\\n \\\"\\\"\\\"\",\n \"def update_schema(self, new_schema):\\n return self.conn.update_schema(new_schema)\",\n \"def reformat(self, newformat):\\n # check whether the column is defined\\n if self._defined:\\n # get the appropriate null-format\\n nullformat = self._get_nullformat(newformat)\\n # set the new formats\\n self._format = [newformat, nullformat]\\n else:\\n # first the column type must be defined\\n raise Exception('The data type of this column is not yet defined!')\",\n \"def _copy_custom_attributes(self, column):\\n\\n column.min_length = self.min_length\\n column.max_length = self.max_length\\n column.allow_blank = self.allow_blank\\n column.allow_whitespace = self.allow_whitespace\\n\\n super()._copy_custom_attributes(column)\",\n \"def allows_auto_pk_0(self):\\n return \\\"NO_AUTO_VALUE_ON_ZERO\\\" in self.connection.sql_mode\",\n \"def correct_db_schema_utf8(\\n instance: Recorder, table_object: type[DeclarativeBase], schema_errors: set[str]\\n) -> None:\\n table_name = table_object.__tablename__\\n if (\\n f\\\"{table_name}.4-byte UTF-8\\\" in schema_errors\\n or f\\\"{table_name}.utf8mb4_unicode_ci\\\" in schema_errors\\n ):\\n from ..migration import ( # pylint: disable=import-outside-toplevel\\n _correct_table_character_set_and_collation,\\n )\\n\\n _correct_table_character_set_and_collation(table_name, instance.get_session)\",\n \"def apply_patch():\\n assert BaseDatabaseSchemaEditor is not None\\n\\n def _create_unique_sql(self, *args, **kwargs):\\n from django.db.backends.ddl_references import IndexName\\n\\n statement = orig_create_unique_sql(self, *args, **kwargs)\\n\\n if statement is not None:\\n index_name = statement.parts['name']\\n\\n if (isinstance(index_name, IndexName) and\\n index_name.create_index_name == self._create_index_name):\\n # The result will be unquoted. Let's quote it.\\n index_name.create_index_name = lambda *args, **kwargs: \\\\\\n self.quote_name(self._create_index_name(*args, **kwargs))\\n\\n return statement\\n\\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql\",\n \"def to_json_schema(\\n schema: Dict[str, Any], *, nullable_name: str, copy: bool = True, is_response_schema: bool = False\\n) -> Dict[str, Any]:\\n if copy:\\n schema = fast_deepcopy(schema)\\n if schema.get(nullable_name) is True:\\n del schema[nullable_name]\\n schema = {\\\"anyOf\\\": [schema, {\\\"type\\\": \\\"null\\\"}]}\\n schema_type = schema.get(\\\"type\\\")\\n if schema_type == \\\"file\\\":\\n schema[\\\"type\\\"] = \\\"string\\\"\\n schema[\\\"format\\\"] = \\\"binary\\\"\\n if schema_type == \\\"object\\\":\\n if is_response_schema:\\n # Write-only properties should not occur in responses\\n rewrite_properties(schema, is_write_only)\\n else:\\n # Read-only properties should not occur in requests\\n rewrite_properties(schema, is_read_only)\\n return schema\",\n \"def test_build_schema_no_update(self):\\n metadata = schema_utils.build_metadata(\\n self.dummy_schema,\\n self.fake_metadata,\\n schema_utils.Update.no_update,\\n )\\n assert metadata == self.fake_metadata\",\n \"def test_columns_set_to_all_columns_when_none(self):\\n\\n df = d.create_df_1()\\n\\n x = BaseTransformer(columns=None)\\n\\n x.columns_set_or_check(X=df)\\n\\n h.assert_equal_dispatch(\\n expected=list(df.columns.values),\\n actual=x.columns,\\n msg=\\\"x.columns set when None\\\",\\n )\",\n \"def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\\n name = to_safe_name(col_schema['name'])\\n return bigquery.SchemaField(\\n name,\\n col_schema.get('type'),\\n col_schema.get('mode', 'NULLABLE'),\\n col_schema.get('description', '')\\n )\",\n \"def _load_schema(self, mode=\\\"staging\\\"):\\n\\n self._check_mode(mode)\\n\\n json_path = self.table_folder / f\\\"schema-{mode}.json\\\"\\n columns = self.table_config[\\\"columns\\\"]\\n\\n if mode == \\\"staging\\\":\\n new_columns = []\\n for c in columns:\\n # case is_in_staging are None then must be True\\n is_in_staging = (\\n True if c.get(\\\"is_in_staging\\\") is None else c[\\\"is_in_staging\\\"]\\n )\\n # append columns declared in table_config.yaml to schema only if is_in_staging: True\\n if is_in_staging and not c.get(\\\"is_partition\\\"):\\n c[\\\"type\\\"] = \\\"STRING\\\"\\n new_columns.append(c)\\n\\n del columns\\n columns = new_columns\\n\\n elif mode == \\\"prod\\\":\\n schema = self._get_table_obj(mode).schema\\n\\n # get field names for fields at schema and at table_config.yaml\\n column_names = [c[\\\"name\\\"] for c in columns]\\n schema_names = [s.name for s in schema]\\n\\n # check if there are mismatched fields\\n not_in_columns = [name for name in schema_names if name not in column_names]\\n not_in_schema = [name for name in column_names if name not in schema_names]\\n\\n # raise if field is not in table_config\\n if not_in_columns:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in table_config.yaml. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_columns,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # raise if field is not in schema\\n if not_in_schema:\\n raise BaseDosDadosException(\\n \\\"Column {error_columns} was not found in publish.sql. Are you sure that \\\"\\n \\\"all your column names between table_config.yaml, publish.sql and \\\"\\n \\\"{project_id}.{dataset_id}.{table_id} are the same?\\\".format(\\n error_columns=not_in_schema,\\n project_id=self.table_config[\\\"project_id_prod\\\"],\\n dataset_id=self.table_config[\\\"dataset_id\\\"],\\n table_id=self.table_config[\\\"table_id\\\"],\\n )\\n )\\n\\n # if field is in schema, get field_type and field_mode\\n for c in columns:\\n for s in schema:\\n if c[\\\"name\\\"] == s.name:\\n c[\\\"type\\\"] = s.field_type\\n c[\\\"mode\\\"] = s.mode\\n break\\n ## force utf-8, write schema_{mode}.json\\n json.dump(columns, (json_path).open(\\\"w\\\", encoding=\\\"utf-8\\\"))\\n\\n # load new created schema\\n return self.client[f\\\"bigquery_{mode}\\\"].schema_from_json(str(json_path))\",\n \"def initialize_schema(self, dry_run=False):\\n if not dry_run:\\n self.flush()\",\n \"def _decode_nullable(\\n data_type, obj, alias_validators, strict, old_style, for_msgpack):\\n if obj is not None:\\n return _json_compat_obj_decode_helper(\\n data_type.validator, obj, alias_validators, strict, old_style,\\n for_msgpack)\\n else:\\n return None\",\n \"def _parse_fixed_length_data(self, original_record, column, null_table):\\n column_name = column.col_name_str\\n # Boolean fields are encoded in the null table\\n if column.type == TYPE_BOOLEAN:\\n if column.column_id > len(null_table):\\n logging.error(f\\\"Failed to parse bool field, Column not found in null_table column: {column_name} ,\\\"\\n f\\\" column id: {column.column_id} , null_table: {null_table}\\\")\\n return\\n\\n parsed_type = null_table[column.column_id]\\n else:\\n\\n if column.fixed_offset > len(original_record):\\n logging.error(f\\\"Column offset is bigger than the length of the record {column.fixed_offset}\\\")\\n return\\n record = original_record[column.fixed_offset:]\\n parsed_type = parse_type(column.type, record, version=self.version)\\n\\n if not null_table[column.column_id] and column.type != TYPE_BOOLEAN:\\n self.parsed_table[column_name].append(\\\"\\\")\\n else:\\n self.parsed_table[column_name].append(parsed_type)\",\n \"def rev_ensure_column(v,initial_shape):\\n if initial_shape: # check that the tuple is nonempty\\n v.shape = initial_shape \\n \\n return v\",\n \"def test_null_update_deletes_column(self):\\r\\n partition = uuid4()\\r\\n for i in range(5):\\r\\n TestQueryUpdateModel.create(partition=partition, cluster=i, count=i, text=str(i))\\r\\n\\r\\n # sanity check\\r\\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\\r\\n assert row.cluster == i\\r\\n assert row.count == i\\r\\n assert row.text == str(i)\\r\\n\\r\\n # perform update\\r\\n TestQueryUpdateModel.objects(partition=partition, cluster=3).update(text=None)\\r\\n\\r\\n for i, row in enumerate(TestQueryUpdateModel.objects(partition=partition)):\\r\\n assert row.cluster == i\\r\\n assert row.count == i\\r\\n assert row.text == (None if i == 3 else str(i))\",\n \"def test_update_risk_field_to_null(self, field, field_name):\\n risk = factories.RiskFactory()\\n\\n response = self.api.put(risk, risk.id, {\\n field: None,\\n })\\n\\n self.assert400(response)\\n self.assertEqual(response.json[\\\"message\\\"],\\n field_name + \\\" for the object is not specified\\\")\\n risk = db.session.query(all_models.Risk).get(risk.id)\\n self.assertIsNotNone(risk.external_id)\",\n \"def _base_schema(self, data_schema: Callable[[bool], StructType]) -> StructType:\\n return StructType([\\n StructField(\\\"id\\\", StringType(), False),\\n StructField(\\\"op\\\", StringType(), False),\\n StructField(\\\"ts\\\", LongType(), False),\\n StructField(\\\"data\\\", data_schema(False), True),\\n StructField(\\\"set\\\", data_schema(True), True),\\n ])\",\n \"def flatten_schema_map(\\n schema_map,\\n keep_nulls=False,\\n sorted_schema=True,\\n infer_mode=False,\\n input_format='json',\\n):\\n if not isinstance(schema_map, dict):\\n raise Exception(\\n f\\\"Unexpected type '{type(schema_map)}' for schema_map\\\"\\n )\\n\\n # Build the BigQuery schema from the internal 'schema_map'.\\n schema = []\\n map_items = sorted(schema_map.items()) if sorted_schema \\\\\\n else schema_map.items()\\n for name, meta in map_items:\\n # Skip over fields which have been explicitly removed\\n if not meta:\\n continue\\n\\n status = meta['status']\\n filled = meta['filled']\\n info = meta['info']\\n\\n # Schema entries with a status of 'soft' are caused by 'null' or\\n # empty fields. Don't print those out if the 'keep_nulls' flag is\\n # False.\\n if status == 'soft' and not keep_nulls:\\n continue\\n\\n # Copy the 'info' dictionary into the schema dict, preserving the\\n # ordering of the 'field', 'mode', 'name', 'type' elements. 'bq load'\\n # keeps these sorted, so we created them in sorted order using an\\n # OrderedDict, so they should preserve order here too.\\n new_info = OrderedDict()\\n for key, value in info.items():\\n if key == 'fields':\\n if not value:\\n # Create a dummy attribute for an empty RECORD to make\\n # the BigQuery importer happy.\\n new_value = [\\n OrderedDict([\\n ('mode', 'NULLABLE'),\\n ('name', '__unknown__'),\\n ('type', 'STRING'),\\n ])\\n ]\\n else:\\n # Recursively flatten the sub-fields of a RECORD entry.\\n new_value = flatten_schema_map(\\n schema_map=value,\\n keep_nulls=keep_nulls,\\n sorted_schema=sorted_schema,\\n infer_mode=infer_mode,\\n input_format=input_format\\n )\\n elif key == 'type' and value in ['QINTEGER', 'QFLOAT', 'QBOOLEAN']:\\n # Convert QINTEGER -> INTEGER, similarly for QFLOAT and QBOOLEAN\\n new_value = value[1:]\\n elif key == 'mode':\\n # 'infer_mode' to set a field as REQUIRED is supported for only\\n # input_format = 'csv' because the header line gives us the\\n # complete list of fields to be expected in the CSV file. In\\n # JSON data files, certain fields will often be completely\\n # missing instead of being set to 'null' or \\\"\\\". If the field is\\n # not even present, then it becomes incredibly difficult (not\\n # impossible, but more effort than I want to expend right now)\\n # to figure out which fields are missing so that we can mark the\\n # appropriate schema entries with 'filled=False'.\\n #\\n # The --infer_mode option is activated only for\\n # input_format == 'csv' in this function, which allows us to\\n # overload the --infer_mode flag to mean that a REQUIRED mode of\\n # an existing schema can transition to a NULLABLE mode.\\n if (infer_mode and value == 'NULLABLE' and filled\\n and input_format == 'csv'):\\n new_value = 'REQUIRED'\\n else:\\n new_value = value\\n else:\\n new_value = value\\n new_info[key] = new_value\\n schema.append(new_info)\\n return schema\",\n \"def is_field_nullable(\\n nullable: Optional[bool],\\n default: Any,\\n server_default: Any,\\n pydantic_only: Optional[bool],\\n) -> bool:\\n if nullable is None:\\n return (\\n default is not None\\n or server_default is not None\\n or (pydantic_only is not None and pydantic_only)\\n )\\n return nullable\",\n \"def update_writables(self, record_id, fields, typecast=False):\\n \\n cols = self.writable_columns\\n cols_dict = { col['name']: col for col in cols }\\n writable_fields = { k : v for k, v in fields.items() if k in cols_dict}\\n \\n Airtable.update(self, record_id, writable_fields, typecast)\",\n \"def before_update(mapper, conn, target):\\n if isinstance(target, Column):\\n raise TypeError('Got a column instead of a table')\\n\\n if target.id_ is None:\\n dataset_id = ObjectNumber.parse(target.d_id)\\n target.id_ = str(TableNumber(dataset_id, target.sequence_id))\",\n \"def _is_nullable(self) -> bool:\\n return self.__nullable\",\n \"def set_schema(self, schema):\\r\\n self.__schema = schema\",\n \"def _set_default_edit_fields(self):\\n default_edit_fields = []\\n\\n for col in self.table.get_column_names():\\n req = False\\n if col[-3:].lower() == '_id':\\n # foreign key\\n req = True\\n \\n dict_template = self._get_field_list_dict()\\n \\n dict_template['name'] = '{}'.format(col)\\n dict_template['label'] = '{}'.format(col).replace('_',' ').title()\\n dict_template['type'] = 'text'\\n try:\\n dict_template['type'] = '{}'.format(self.table.get_column_type(col))\\n except KeyError:\\n pass\\n dict_template['req'] = req\\n \\n default_edit_fields.append(dict_template)\\n \\n return default_edit_fields\",\n \"def set_schema(self, schema, set_num_columns=True):\\n update_dict = {self.SCHEMA: schema}\\n\\n if set_num_columns:\\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\\n\\n self.update(update_dict)\",\n \"def _clean_up_columns(\\n self):\\n self.log.debug('starting the ``_clean_up_columns`` method')\\n\\n tableName = self.dbTableName\\n\\n print \\\"cleaning up %(tableName)s columns\\\" % locals()\\n\\n sqlQuery = u\\\"\\\"\\\"\\n set sql_mode=\\\"STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION\\\";\\n \\\"\\\"\\\" % locals()\\n writequery(\\n log=self.log,\\n sqlQuery=sqlQuery,\\n dbConn=self.cataloguesDbConn,\\n )\\n\\n sqlQuery = u\\\"\\\"\\\"\\n update %(tableName)s set dist_mod_err = null where dist_mod_err = 0;\\n update %(tableName)s set dist_in_ned_flag = null where dist_in_ned_flag = \\\"\\\";\\n update %(tableName)s set notes = null where notes = \\\"\\\";\\n update %(tableName)s set redshift = null where redshift = 0;\\n update %(tableName)s set dist_derived_from_sn = null where dist_derived_from_sn = \\\"\\\";\\n update %(tableName)s set hubble_const = null where hubble_const = 0;\\n update %(tableName)s set lmc_mod = null where lmc_mod = 0;\\n update %(tableName)s set master_row = 0;\\n update %(tableName)s set master_row = 1 where primaryId in (select * from (select distinct primaryId from %(tableName)s group by galaxy_index_id) as alias);\\n \\\"\\\"\\\" % locals()\\n writequery(\\n log=self.log,\\n sqlQuery=sqlQuery,\\n dbConn=self.cataloguesDbConn,\\n )\\n\\n self.log.debug('completed the ``_clean_up_columns`` method')\\n return None\",\n \"def test_can_update_risk_type_schema(self):\\n risk_type = self.create_risk_type()\\n for r in risk_type.schema:\\n if r['field_type'] == 'text':\\n r['field_type'] = 'textarea'\\n break\\n\\n response = self.client.put(\\n f'/api/v0/risk-types/{risk_type.id}/',\\n data={\\n 'type_name': 'New Risk Type',\\n 'schema': risk_type.schema,\\n }, format='json')\\n risk_type.refresh_from_db()\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\\n self.assertEqual(risk_type.schema[0].get('field_type'), 'textarea')\",\n \"def test_updates_from_none(self):\\r\\n m = TestMapModel.create(int_map=None)\\r\\n expected = {1: uuid4()}\\r\\n m.int_map = expected\\r\\n m.save()\\r\\n\\r\\n m2 = TestMapModel.get(partition=m.partition)\\r\\n assert m2.int_map == expected\\r\\n\\r\\n m2.int_map = None\\r\\n m2.save()\\r\\n m3 = TestMapModel.get(partition=m.partition)\\r\\n assert m3.int_map != expected\",\n \"def convertToParamNull(self):\\n for sAttr in self.getDataAttributes():\\n oValue = getattr(self, sAttr);\\n oNewValue = self._convertAttributeToParamNull(sAttr, oValue);\\n if oValue != oNewValue:\\n setattr(self, sAttr, oNewValue);\\n return self;\",\n \"def _write_local_schema_file(self, cursor):\\n schema = []\\n tmp_schema_file_handle = NamedTemporaryFile(delete=True)\\n if self.schema is not None and isinstance(self.schema, string_types):\\n schema = self.schema\\n tmp_schema_file_handle.write(schema)\\n else:\\n if self.schema is not None and isinstance(self.schema, list):\\n schema = self.schema\\n else:\\n for field in cursor.description:\\n # See PEP 249 for details about the description tuple.\\n field_name = field[0]\\n field_type = self.type_map(field[1])\\n # Always allow TIMESTAMP to be nullable. MySQLdb returns None types\\n # for required fields because some MySQL timestamps can't be\\n # represented by Python's datetime (e.g. 0000-00-00 00:00:00).\\n if field[6] or field_type == 'TIMESTAMP':\\n field_mode = 'NULLABLE'\\n else:\\n field_mode = 'REQUIRED'\\n schema.append({\\n 'name': field_name,\\n 'type': field_type,\\n 'mode': field_mode,\\n })\\n s = json.dumps(schema, tmp_schema_file_handle, sort_keys=True)\\n if PY3:\\n s = s.encode('utf-8')\\n tmp_schema_file_handle.write(s)\\n\\n self.log.info('Using schema for %s: %s', self.schema_filename, schema)\\n return {self.schema_filename: tmp_schema_file_handle}\",\n \"def modify_tbl(self):\\n debug = False\\n dd = mg.DATADETS_OBJ\\n orig_tblname = dd.tbl\\n ## other (i.e. not the sofa_id) field details\\n oth_name_types = getdata.get_oth_name_types(self.settings_data)\\n if debug:\\n print('oth_name_types to feed into '\\n f'make_strict_typing_tbl {oth_name_types}')\\n try: ## 1 way or other must do strict_cleanup()\\n make_strict_typing_tbl(\\n orig_tblname, oth_name_types, self.settings_data)\\n except sqlite.IntegrityError as e: #@UndefinedVariable\\n if debug: print(b.ue(e))\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise FldMismatchException\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n raise Exception('Problem making strictly-typed table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n copy_orig_tbl(orig_tblname)\\n wipe_tbl(orig_tblname)\\n final_name = self.tblname_lst[0] ## may have been renamed\\n try:\\n make_redesigned_tbl(final_name, oth_name_types)\\n strict_cleanup(restore_tblname=final_name)\\n dd.set_tbl(tbl=final_name)\\n except Exception as e:\\n strict_cleanup(restore_tblname=orig_tblname)\\n restore_copy_tbl(orig_tblname) ## effectively removes tmp_tbl 2\\n dd.set_tbl(tbl=orig_tblname)\\n raise Exception('Problem making redesigned table.'\\n f'\\\\nCaused by error: {b.ue(e)}')\\n wipe_tbl(mg.TMP_TBLNAME2)\",\n \"def generate_altered_fields(self):\\n result = super(MigrationAutodetector, self).generate_altered_fields()\\n self.generate_sql_changes()\\n return result\",\n \"def dim_col_imputation(self, columns):\\n for column in columns:\\n if column in self.col_with_nulls:\\n if not self._pandas_flag:\\n mode = self.data_frame.select(column).toPandas().mode().values[0][0]\\n self.data_frame = self.data_frame.fillna({ column:mode })\\n else:\\n self.data_frame[column] = self.mode_impute(self.data_frame[column])\\n self.data_change_dict['ModeImputeCols'].append(column)\",\n \"def test_update_from_none(self):\\r\\n ctx = {}\\r\\n col = columns.Set(columns.Integer, db_field=\\\"TEST\\\")\\r\\n statements = col.get_update_statement({1, 2, 3, 4}, None, ctx)\\r\\n\\r\\n #only one variable /statement should be generated\\r\\n assert len(ctx) == 1\\r\\n assert len(statements) == 1\\r\\n\\r\\n assert ctx.values()[0].value == {1, 2, 3, 4}\\r\\n assert statements[0] == '\\\"TEST\\\" = :{}'.format(ctx.keys()[0])\",\n \"def _migrate_0(self, entry):\\r\\n if 'name' not in entry['_id']:\\r\\n entry_id = entry['_id']\\r\\n entry_id = bson.son.SON([\\r\\n ('org', entry_id['org']),\\r\\n ('course', entry_id['course']),\\r\\n ])\\r\\n self.location_map.remove({'_id': entry_id})\\r\\n return None\\r\\n\\r\\n # add schema, org, offering, etc, remove old fields\\r\\n entry['schema'] = 0\\r\\n entry.pop('course_id', None)\\r\\n entry.pop('lower_course_id', None)\\r\\n old_course_id = SlashSeparatedCourseKey(entry['_id']['org'], entry['_id']['course'], entry['_id']['name'])\\r\\n entry['org'] = old_course_id.org\\r\\n entry['offering'] = old_course_id.offering.replace('/', '+')\\r\\n return self._migrate_1(entry, True)\",\n \"def is_nullable_type(self):\\n raise exceptions.NotImplementedError()\",\n \"def merge_attribute_schema(self, attr_schema):\\n name = attr_schema.name\\n if name not in self.schema:\\n self.schema[name] = attr_schema\\n else:\\n self.schema[name].merge_schema(attr_schema)\",\n \"def deferred_to_columns_cb(self, target, model, fields):\\n table = model._meta.db_table\\n if table not in target:\\n target[table] = set()\\n for field in fields:\\n if not hasattr(field.column, \\\"columns\\\"):\\n target[table].add(field.column)\\n else:\\n target[table].update(field.column.columns)\",\n \"def _null_set_rel_pos(self, rel_pos):\\n self.get_sp_rel_pos = self._null_get_rel_pos\",\n \"def convertFromParamNull(self):\\n for sAttr in self.getDataAttributes():\\n oValue = getattr(self, sAttr);\\n oNewValue = self._convertAttributeFromParamNull(sAttr, oValue);\\n if oValue != oNewValue:\\n setattr(self, sAttr, oNewValue);\\n return self;\",\n \"def test_update_field_to_null(self, field, field_name):\\n control = factories.ControlFactory()\\n\\n response = self.api.put(control, control.id, {field: None})\\n\\n self.assert400(response)\\n self.assertEqual(response.json[\\\"message\\\"],\\n field_name + \\\" for the object is not specified\\\")\\n control = db.session.query(all_models.Control).get(control.id)\\n self.assertIsNotNone(control.external_id)\",\n \"def DEADempty_fix_table():\\n sqlnuke = \\\"delete from fix\\\"\\n conf.Cur.execute(sqlnuke)\\n conf.Con.commit()\",\n \"def _migrate_if_necessary(self, entries):\\r\\n entries = [\\r\\n self._migrate[entry.get('schema', 0)](self, entry)\\r\\n for entry in entries\\r\\n ]\\r\\n return entries\",\n \"def column_empty_like_same_mask(column, dtype):\\n data = cuda.device_array(shape=len(column), dtype=dtype)\\n params = dict(data=Buffer(data))\\n if column.has_null_mask:\\n params.update(mask=column.nullmask)\\n return Column(**params)\",\n \"def update(self, schema: ISchema) -> ISchema:\\n schema = super().update(schema)\\n\\n schema = cast(EventSchema, schema)\\n if not schema.Active and schema.Sport > 0:\\n self.select('ID', 'Sport', 'Active').filter(\\n 'Sport', Operators.Equals, schema.Sport,\\n ).filter('Active', Operators.Equals, 1)\\n result = self.execute()\\n if not result:\\n sm = SportModel()\\n sport = sm.find(schema.Sport)\\n sport = cast(SportSchema, sport)\\n sport.Active = False\\n sm.update(sport)\\n return schema\",\n \"def isNullable(self):\\n if self.isPrimaryKey():\\n return False\\n else:\\n return self._nullable\",\n \"def apply_to(self, df: pd.DataFrame) -> pd.DataFrame:\\n schema_names = self.names\\n data_columns = df.columns\\n\\n assert len(schema_names) == len(\\n data_columns\\n ), \\\"schema column count does not match input data column count\\\"\\n\\n for column, dtype in zip(data_columns, self.types):\\n pandas_dtype = dtype.to_pandas()\\n\\n col = df[column]\\n col_dtype = col.dtype\\n\\n try:\\n not_equal = pandas_dtype != col_dtype\\n except TypeError:\\n # ugh, we can't compare dtypes coming from pandas,\\n # assume not equal\\n not_equal = True\\n\\n if not_equal or not dtype.is_primitive():\\n new_col = convert(col_dtype, dtype, col)\\n else:\\n new_col = col\\n df[column] = new_col\\n\\n # return data with the schema's columns which may be different than the\\n # input columns\\n df.columns = schema_names\\n return df\",\n \"def columns_setup(self):\\n self.required = None\\n self.addition = None\\n self.deletion = None\\n self.retention = None\\n self.rename = None\",\n \"def test_empty_cols_allowed(self):\\n self.test_table.allow_empty_columns = True\\n self.test_table.change_header(Path=1, SectionType=3, Value=4)\\n self.assertEqual(self.test_table._header, [\\\"Path\\\", None, \\\"SectionType\\\",\\n \\\"Value\\\"])\",\n \"def on_doctype_update():\\n\\tif not frappe.db.sql(\\\"\\\"\\\"show index from `tabDefaultValue`\\n\\t\\twhere Key_name=\\\"defaultvalue_parent_defkey_index\\\" \\\"\\\"\\\"):\\n\\t\\tfrappe.db.commit()\\n\\t\\tfrappe.db.sql(\\\"\\\"\\\"alter table `tabDefaultValue`\\n\\t\\t\\tadd index defaultvalue_parent_defkey_index(parent, defkey)\\\"\\\"\\\")\\n\\n\\tif not frappe.db.sql(\\\"\\\"\\\"show index from `tabDefaultValue`\\n\\t\\twhere Key_name=\\\"defaultvalue_parent_parenttype_index\\\" \\\"\\\"\\\"):\\n\\t\\tfrappe.db.commit()\\n\\t\\tfrappe.db.sql(\\\"\\\"\\\"alter table `tabDefaultValue`\\n\\t\\t\\tadd index defaultvalue_parent_parenttype_index(parent, parenttype)\\\"\\\"\\\")\",\n \"def change_col_type(df,schema):\\n d = {'int':IntegerType(),'str':StringType(),'float':FloatType(),'bool':BooleanType()}\\n \\n for c,t in schema.items():\\n df = df.withColumn(c,col(c).cast(d[t]))\\n return df\",\n \"def is_nullable(self):\\n return self._is_nullable\",\n \"def getSchemaMap(self):\\n\\t\\trSchemaMap = {}\\n\\t\\tfor schemaName in self.schemaList:\\n\\t\\t\\tmodeList = [str(tKey) for tKey in self.schemaList[schemaName].modes.keys()]\\n\\n\\t\\t\\tif len(modeList) == 1 and None in self.schemaList[schemaName].modes:\\n\\t\\t\\t\\trSchemaMap[schemaName] = 0\\n\\t\\t\\telse:\\n\\t\\t\\t\\trSchemaMap[schemaName] = modeList\\n\\n\\t\\treturn rSchemaMap\",\n \"def before_insert(mapper, conn, target):\\n\\n #from identity import ObjectNumber\\n #assert not target.fk_vid or not ObjectNumber.parse(target.fk_vid).revision\\n\\n if target.sequence_id is None:\\n # In case this happens in multi-process mode\\n conn.execute(\\\"BEGIN IMMEDIATE\\\")\\n sql = text(\\n '''SELECT max(c_sequence_id)+1 FROM columns WHERE c_t_id = :tid''')\\n\\n max_id, = conn.execute(sql, tid=target.t_id).fetchone()\\n\\n if not max_id:\\n max_id = 1\\n\\n target.sequence_id = max_id\\n\\n Column.before_update(mapper, conn, target)\",\n \"def set_default_values_as_needed(self):\\n if self.verbose:\\n click.echo('Updating required default values')\\n for field in ARGUMENTS_DEFAULT_VALUES:\\n if self.__class__.__name__ in ARGUMENTS_DEFAULT_VALUES[field][1]:\\n self.data[field] = ARGUMENTS_DEFAULT_VALUES[field][0]\",\n \"def reset_modified(self):\\n self.modified_fields = set()\\n\\n # compensate for us not having knowledge of certain fields changing\\n for field_name, field in self.schema.normal_fields.items():\\n if isinstance(field, ObjectField):\\n self.modified_fields.add(field_name)\",\n \"def s3_table_set_before_write(cls, table):\\n\\n update_default = cls.s3_table_name_update_default\\n\\n table._before_insert.append(update_default)\\n table._before_update.append(lambda s, data: update_default(data))\",\n \"def standardize(self, options: ParameterSetSchema) -> \\\"Parameters\\\":\\n replace_dict = {}\\n for key, val in asdict(self).items():\\n dimensions = (val.shape[0], getattr(options, key).degree + 1)\\n val_new = np.zeros(dimensions)\\n max_dimension = (np.minimum(val.shape[1], dimensions[1]))\\n val_new[:, :max_dimension] = val[:, :max_dimension]\\n replace_dict.update({key: val_new})\\n return replace(self, **replace_dict)\",\n \"def changenonetoNone(s):\\r\\n if s=='None':\\r\\n return None\\r\\n else:\\r\\n return s\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.581769","0.5178056","0.5142687","0.5107475","0.50148743","0.4938137","0.49304643","0.4709507","0.4704251","0.4693166","0.46439534","0.460573","0.45949084","0.4564342","0.45579243","0.44939494","0.4487079","0.44671857","0.44571728","0.44475183","0.44284815","0.44273856","0.4420121","0.44103774","0.4398482","0.4389953","0.43886152","0.43481353","0.4338426","0.43361387","0.43354636","0.4328191","0.432072","0.43179303","0.43146068","0.43080887","0.43002936","0.42834532","0.42733145","0.42574638","0.4256291","0.42553374","0.42515603","0.42507502","0.42487434","0.42222852","0.4220983","0.42181864","0.4215106","0.4207957","0.42077914","0.42056474","0.42030367","0.41983145","0.4197902","0.4193015","0.4184039","0.41691354","0.4166196","0.4161701","0.41562364","0.4149698","0.41378924","0.41359726","0.41308078","0.41205308","0.41057402","0.4103443","0.40973568","0.4094938","0.40752518","0.40581706","0.40564007","0.40423664","0.40393743","0.4038854","0.4034126","0.40301055","0.40212595","0.4020144","0.40148473","0.40145954","0.40142488","0.40111858","0.4004962","0.3997657","0.39896274","0.39865515","0.39862368","0.3969516","0.39657027","0.39650917","0.39629957","0.39604303","0.39579844","0.39570943","0.39489138","0.39434963","0.39393175","0.39359477"],"string":"[\n \"0.581769\",\n \"0.5178056\",\n \"0.5142687\",\n \"0.5107475\",\n \"0.50148743\",\n \"0.4938137\",\n \"0.49304643\",\n \"0.4709507\",\n \"0.4704251\",\n \"0.4693166\",\n \"0.46439534\",\n \"0.460573\",\n \"0.45949084\",\n \"0.4564342\",\n \"0.45579243\",\n \"0.44939494\",\n \"0.4487079\",\n \"0.44671857\",\n \"0.44571728\",\n \"0.44475183\",\n \"0.44284815\",\n \"0.44273856\",\n \"0.4420121\",\n \"0.44103774\",\n \"0.4398482\",\n \"0.4389953\",\n \"0.43886152\",\n \"0.43481353\",\n \"0.4338426\",\n \"0.43361387\",\n \"0.43354636\",\n \"0.4328191\",\n \"0.432072\",\n \"0.43179303\",\n \"0.43146068\",\n \"0.43080887\",\n \"0.43002936\",\n \"0.42834532\",\n \"0.42733145\",\n \"0.42574638\",\n \"0.4256291\",\n \"0.42553374\",\n \"0.42515603\",\n \"0.42507502\",\n \"0.42487434\",\n \"0.42222852\",\n \"0.4220983\",\n \"0.42181864\",\n \"0.4215106\",\n \"0.4207957\",\n \"0.42077914\",\n \"0.42056474\",\n \"0.42030367\",\n \"0.41983145\",\n \"0.4197902\",\n \"0.4193015\",\n \"0.4184039\",\n \"0.41691354\",\n \"0.4166196\",\n \"0.4161701\",\n \"0.41562364\",\n \"0.4149698\",\n \"0.41378924\",\n \"0.41359726\",\n \"0.41308078\",\n \"0.41205308\",\n \"0.41057402\",\n \"0.4103443\",\n \"0.40973568\",\n \"0.4094938\",\n \"0.40752518\",\n \"0.40581706\",\n \"0.40564007\",\n \"0.40423664\",\n \"0.40393743\",\n \"0.4038854\",\n \"0.4034126\",\n \"0.40301055\",\n \"0.40212595\",\n \"0.4020144\",\n \"0.40148473\",\n \"0.40145954\",\n \"0.40142488\",\n \"0.40111858\",\n \"0.4004962\",\n \"0.3997657\",\n \"0.39896274\",\n \"0.39865515\",\n \"0.39862368\",\n \"0.3969516\",\n \"0.39657027\",\n \"0.39650917\",\n \"0.39629957\",\n \"0.39604303\",\n \"0.39579844\",\n \"0.39570943\",\n \"0.39489138\",\n \"0.39434963\",\n \"0.39393175\",\n \"0.39359477\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.637235"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2291,"cells":{"query":{"kind":"string","value":"Add new columns to an existing schema. Tries add new fields to an existing schema. Raises SchemaUpdateError if column already exists in the orig_schema_map."},"document":{"kind":"string","value":"def _AddNewColsToSchema(new_fields, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for new_field in new_fields:\n if new_field.name in orig_schema_map:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n updated_schema_map[new_field.name] = new_field\n return updated_schema_map"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add_column(self, schema):\n self[schema.name] = schema.copy()","def _add_to_schema(self, new: dict):\n self._defaults.update(new)\n self._migrate()","def _GetRelaxedCols(relaxed_columns, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for col in relaxed_columns:\n if col in orig_schema_map:\n updated_schema_map[col].mode = 'NULLABLE'\n else:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n return updated_schema_map","def _GetUpdatedSchema(\n original_schema,\n new_columns=None,\n relaxed_columns=None):\n orig_field_map = (\n {f.name: f for f in original_schema.fields} if original_schema else {})\n\n if relaxed_columns:\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\n\n if new_columns:\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\n\n return sorted(orig_field_map.values(), key=lambda x: x.name)","def add_cols(self, source) :\n\n cols = source.get_cols()\n types = source.get_types()\n\n new_cols = []\n new_types = []\n for i in range(len(cols)) :\n if cols[i] not in self.cols :\n new_cols.append(cols[i])\n new_types.append(types[i])\n self.cols.extend(new_cols)\n self.types.extend(new_types)\n\n self._alter_table(new_cols, new_types)\n\n row_ids = self.get_values('__ROWID')\n \n for col in new_cols :\n new_vals = source.get_values(col)\n if len(row_ids) == 0 :\n for val in new_vals :\n self._insert_internal(['__ROWID', col], [0, val])\n\n row_ids = self.get_values('__ROWID')\n\n else :\n binds = zip(new_vals, row_ids)\n q = self._quoter(col)\n sql_base = 'UPDATE \"%s\" SET \"%s\" = %s WHERE \"__ROWID\" = %%d' % (self.name, col, q)\n cur = self.con.cursor()\n for bind in binds :\n if bind[0] :\n update_sql = sql_base % (str(bind[0]), bind[1])\n cur.execute(update_sql)\n\n self.version += 1","def update_table_columns(self, table_name, table):\n table_definition = self._table_definitions[table_name]\n new_columns = table.columns.difference(table_definition.c.keys())\n new_column_types = {c: table.dtypes[c] for c in new_columns}\n\n allows_covariates = table_definition.name in [\"avgint\", \"data\"]\n\n good_prefixes = [\"c_\"]\n if allows_covariates:\n good_prefixes.append(\"x_\")\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\n if bad_column_names:\n msg = f\"\"\"\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\n It allows additional comment columns, which must start 'c_'.\"\"\"\n if allows_covariates:\n msg += \" In addition it allows covariate columns, which must start with 'x_'.\"\n msg += f\" You supplied columns that don't meet those requirements: {bad_column_names}\"\n\n raise ValueError(dedent(msg))\n\n add_columns_to_table(table_definition, new_column_types)","def test_add_column(self):\n name_column = Varchar()\n name_column._meta.name = \"name\"\n\n genre_column = Varchar()\n genre_column._meta.name = \"genre\"\n\n schema: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[name_column, genre_column],\n )\n ]\n schema_snapshot: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[name_column],\n )\n ]\n\n schema_differ = SchemaDiffer(\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\"y\"\n )\n\n self.assertTrue(len(schema_differ.add_columns.statements) == 1)\n self.assertEqual(\n schema_differ.add_columns.statements[0],\n \"manager.add_column(table_class_name='Band', tablename='band', column_name='genre', db_column_name='genre', column_class_name='Varchar', column_class=Varchar, params={'length': 255, 'default': '', 'null': False, 'primary_key': False, 'unique': False, 'index': False, 'index_method': IndexMethod.btree, 'choices': None, 'db_column_name': None})\", # noqa\n )","def update(self):\n current = LazyRegister(self.db)\n current.render()\n cur = self.db.cursor()\n for table in self.tables:\n if table in current.tables:\n additions, removals = current.tables[table].migrate(self.tables[table])\n for addition in additions:\n cur.execute(\"\"\"ALTER TABLE %s ADD COLUMN %s\"\"\" % (\n table, addition[1].get_sql()\n ))\n print('Added column: ', addition[0])\n for removal in removals:\n #cur.execute(\"\"\"ALTER TABLE %s DROP COLUMN %s\"\"\" % (\n # table, removal[0]\n #))\n #print('Removed column: ', removal[0])\n print('Did not removed column: ', removal[0])\n else:\n schema = self.tables[table].get_create_table_sql()\n cur.execute(schema)\n print('Added table %s' % table)","def add_columns(self, table, col_data, col_type):\n conn = psycopg2.connect(self.name, sslmode='require')\n c = conn.cursor()\n for data, typ in zip(col_data, col_type):\n c.execute(\"ALTER TABLE {tn} ADD COLUMN {cn} {ct}\".\n format(tn=table, cn=data, ct=typ))\n conn.commit() \n conn.close()","def add_table_column(self, schema, column):\n if not column[\"name\"] or not constants.NAME_RX.match(column[\"name\"]):\n raise ValueError(\"invalid column name\")\n if utils.name_in_nocase(column[\"name\"], [c[\"name\"] for c in schema[\"columns\"]]):\n raise ValueError(\"non-unique column name\")\n if column[\"type\"] not in constants.COLUMN_TYPES:\n raise ValueError(\"invalid column type\")\n sql = (\n f'''ALTER TABLE \"{schema['name']}\"'''\n f\"\"\" ADD COLUMN \"{column['name']}\" {column['type']}\"\"\"\n )\n if column.get(\"notnull\"):\n notnull = [\"NOT NULL\"]\n if column[\"type\"] == constants.INTEGER:\n notnull.append(\"DEFAULT 0\")\n elif column[\"type\"] == constants.REAL:\n notnull.append(\"DEFAULT 0.0\")\n elif column[\"type\"] in (constants.TEXT, constants.BLOB):\n notnull.append(\"DEFAULT ''\")\n sql += \" \" + \" \".join(notnull)\n self.dbcnx.execute(sql)\n schema[\"columns\"].append(column)\n self.update_table(schema)","def add_column_to_staging_table(cursor,table_schema,table_name,column_name):\n if not check_if_column_exists(cursor, table_schema, table_name, column_name):\n add_column = \"ALTER TABLE \" + table_schema + \".\" + table_name + \" ADD COLUMN \" + column_name + \" text;\"\n cursor.execute(add_column)","def add_schema_fields(self, fields):\n if not fields:\n return\n\n data = json.dumps(fields)\n\n try:\n return self.client.post(\n self._get_collection_url('schema/fields'),\n body=data\n )\n except solr_errors.SolrError as e:\n raise solr_errors.SolrSchemaUpdateError(fields, message=e.args[0])","def add_column_into_target_sf(self, tap_type, table, new_column):\n self.run_query_target_snowflake(\n f'ALTER TABLE ppw_e2e_tap_{tap_type}{self.sf_schema_postfix}.{table} ADD {new_column[\"name\"]} int'\n )\n self.run_query_target_snowflake(\n f'UPDATE ppw_e2e_tap_{tap_type}{self.sf_schema_postfix}.{table}'\n f' SET {new_column[\"name\"]}={new_column[\"value\"]} WHERE 1=1'\n )","def update_schema(self, new_schema):\n return self.conn.update_schema(new_schema)","def add_feature_columns(self, feature_columns: typing.List[str]):\n self.feature_columns += feature_columns","def _addColumn(self, table, column, init_data):\n\t\tcommand = \"ALTER TABLE \" + table + \" ADD COLUMN \" + str(column) + \" \" + getSQLiteType(init_data)\n\t\ttry:\n\t\t\tself._run_command(command)\n\t\texcept sqlite3.OperationalError:\n\t\t\tprint(\"Column \" + str(column) + \" already exists!\")","def __append_columns(self, new_dataframe):\n self.dataframe = pd.merge(self.dataframe, new_dataframe)","def newColumn (layer,FieldName,DataType):\n # Check if field already exists\n if layer.fields().indexFromName(FieldName)==-1:\n caps = layer.dataProvider().capabilities()\n if caps & QgsVectorDataProvider.AddAttributes:\n res = layer.dataProvider().addAttributes([QgsField(FieldName,DataType)])\n print(\"New field \\\"{}\\\" added\".format(FieldName))\n # Update to propagate the changes\n layer.updateFields()\n else:\n print(\"Field \\\"{}\\\" already exists.\".format(FieldName))","def rename_column(self, original_column_name, new_column_name):\n self.renames.append((original_column_name, new_column_name))\n if not self.column_exists(new_column_name):\n super(MigrationTable, self).rename_column(original_column_name, new_column_name)","def _add_hybrid_cols(self):\n for new_col_name, method in HYBRID_METHODS.items():\n out = method(self)\n if out is not None:\n try:\n self._hybrid_meta[new_col_name] = out\n except ValueError as e:\n msg = (\"Unable to add {!r} column to hybrid meta. The \"\n \"following exception was raised when adding \"\n \"the data output by '{}': {!r}.\")\n w = msg.format(new_col_name, method.__name__, e)\n logger.warning(w)\n warn(w, OutputWarning)","def ProcessSchemaUpdate(ref, args, request):\n table = request.table\n relaxed_columns = args.relax_columns\n if not table.schema and not relaxed_columns: # if not updating schema,\n return request # then just return.\n\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\n ref.Name(),\n ref.projectId)\n\n new_schema_columns = table.schema\n updated_fields = _GetUpdatedSchema(original_schema,\n new_schema_columns,\n relaxed_columns)\n\n table_schema_type = GetApiMessage('TableSchema')\n request.table.schema = table_schema_type(fields=updated_fields)\n\n return request","def add_column_into_source(self, tap_type, table, new_column):\n run_query_method = getattr(self, f'run_query_tap_{tap_type}')\n run_query_method(\n f'ALTER TABLE {table} ADD {new_column[\"name\"]} int'\n )\n run_query_method(\n f'UPDATE {table} set {new_column[\"name\"]}={new_column[\"value\"]} where 1=1'\n )","def update(self, other):\n # Check if any columns will remain with their original length. If so\n # also check if the lengths of the tables are the same.\n self._dirty = True\n nrows = other.number_of_rows()\n\n if (other._columns and\n set(self._columns) - set(other._columns) and\n other.number_of_rows() != self.number_of_rows()):\n\n raise ValueError('Can not add columns of length {}'\n ' to table of length {}'.format(\n other.number_of_rows(),\n self.number_of_rows()))\n\n for name, column in other._columns.items():\n self._set_column_column_nocheck(name, column, nrows)\n\n self.set_table_attributes(other.get_table_attributes())\n self.set_name(other.get_name())","def create_column(self, new_column, dtype):\n self.logger.debug(\"[%u] Ready to add column %s\" %\n (os.getpid(), new_column))\n ddl = \"\"\"\n ALTER TABLE {schema}.{table}\n ADD COLUMN IF NOT EXISTS {col} {type}\n \"\"\"\n # TODO Replace by execute_ddl func and test it\n with get_sink_connection_string(self) as conn:\n with conn.cursor() as cursor:\n cursor.execute(ddl.format(schema=self.config['schema'],\n table=self.config['table'],\n col=new_column,\n type=dtype))\n self.logger.debug(\"[%u] Column %s has been added\" %\n (os.getpid(), new_column))","def modify_bigquery_schema(self, schema, info_keys):\n # type: (bigquery.TableSchema, Set[str]) -> None","def add_col(self, colname, n_batch=5000, debug=False):\n\n if debug: print(\"Create new column {col}\".format(col=colname))\n # Alter table add column\n #\n alter_query = '''\n ALTER TABLE \"{tablename}\"\n ADD COLUMN \"{colname}\" {datatype};\n '''.format(tablename=self.get_carto_tablename(),\n colname=colname,\n datatype=datatype_map(str(self.dtypes[colname])))\n if debug: print(alter_query)\n\n # add column\n resp = self.carto_sql_client.send(alter_query)\n if debug: print(resp)\n\n # update all the values in that column\n #\n # NOTE: fails if colval is 'inf' or some other exceptional Python\n # or NumPy type\n n_items = len(self[colname])\n update_query = '''\n UPDATE \"{tablename}\"\n SET \"{colname}\" = {colval}\n WHERE \"cartodb_id\" = {cartodb_id};\n '''\n queries = []\n\n for row_num, item in enumerate(self[colname].iteritems()):\n # if debug: print(item)\n pgtype = dtype_to_pgtype(self[colname].dtype, colname)\n temp_query = update_query.format(\n tablename=self.get_carto_tablename(),\n colname=colname,\n colval=numpy_val_to_pg_val(item[1], pgtype),\n cartodb_id=item[0]).strip()\n queries.append(temp_query)\n if (len(queries) == n_batch) or (row_num == n_items - 1):\n output_query = '\\n'.join(queries)\n if debug: print(output_query)\n if debug: print(\"Num chars in query: {}\".format(len(output_query)))\n resp = self.carto_sql_client.send(output_query)\n queries = []\n\n return None","def AddColumns(sqlite_file, table_name):\r\n columns = ['cf_direct_parent','cf_kingdom','cf_superclass',\\\r\n 'cf_class','cf_subclass','cf_intermediate_0','cf_intermediate_1',\\\r\n 'cf_intermediate_2','cf_intermediate_3','cf_intermediate_4',\\\r\n 'cf_intermediate_5','cf_molecular_framework','cf_alternative_parents',\\\r\n 'cf_substituents', 'cf_description']\r\n column_type = 'TEXT'\r\n # Connecting to the database file\r\n conn = sqlite3.connect(sqlite_file) # Connecting to the database\r\n c = conn.cursor() # Adding a cursor to interact with the database\r\n # Adding new column, if it does not exist yet, without a row value\r\n for new_column_name in columns:\r\n try:\r\n c.execute(\"ALTER TABLE {tn} ADD COLUMN '{cn}' {ct}\"\\\r\n .format(tn=table_name, cn=new_column_name, ct=column_type))\r\n print(\"Column created: {cn}\".format(cn=new_column_name))\r\n except sqlite3.OperationalError:\r\n print(\"Column already exists: {cn}\".format(cn=new_column_name))\r\n conn.commit()\r\n conn.close()\r\n return None","def rename_columns(self, col):\n try:\n self.cleaned_data.columns = col\n except Exception as e:\n raise e","def addCommonExtraColumn(self, req, study_id, found_extra_table, column_name, data_type, description):\n debug = False\n common_extra_table_name = None\n min_column_count = None\n quoted_column_name = '\"{0}\"'.format(column_name.upper())\n \n if 'SAMPLE' in found_extra_table:\n common_extra_table_name = 'COMMON_EXTRA_SAMPLE'\n min_column_count = 2\n elif 'PREP' in found_extra_table:\n common_extra_table_name = 'COMMON_EXTRA_PREP'\n min_column_count = 3\n \n if common_extra_table_name == None:\n raise Exception('Error: Could not determine the common extra table name. The found extra table is: %s' % found_extra_table)\n \n # Set the database data type:\n database_data_type = ''\n if data_type == 'text' or database_data_type == 'range':\n database_data_type = 'varchar2(4000)'\n elif data_type == 'numeric':\n database_data_type = 'int'\n elif data_type == 'date':\n database_data_type = 'date'\n \n if database_data_type == '':\n raise Exception('Could not determine common extra column data type.')\n\n # Create the column if it doesn't already exist\n statement = \"\"\"\n select count(*) \n from all_tab_columns \n where column_name = '{0}' \n and table_name = '{1}'\n \"\"\".format(column_name.upper(), common_extra_table_name)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con = self.getMetadataDatabaseConnection()\n results = con.cursor().execute(statement).fetchone()\n if results[0] == 0:\n statement = 'alter table %s add %s %s' % (common_extra_table_name, quoted_column_name, database_data_type)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n \n # Copy the data found in the found extra_table\n if common_extra_table_name == 'COMMON_EXTRA_SAMPLE':\n statement = \"\"\"\n MERGE INTO common_extra_sample e\n USING (\n SELECT sample_id, {0}\n FROM {1}\n ) x\n ON (e.sample_id = x.sample_id)\n WHEN MATCHED THEN \n UPDATE SET e.{0} = x.{0}\n WHEN NOT MATCHED THEN \n INSERT (e.sample_id, e.{0})\n VALUES (x.sample_id, x.{0})\n \"\"\".format(quoted_column_name, found_extra_table)\n else:\n statement = \"\"\"\n MERGE INTO common_extra_prep e\n USING (\n SELECT sample_id, row_number, {0}\n FROM {1}\n ) x\n ON (e.sample_id = x.sample_id and e.row_number = x.row_number)\n WHEN MATCHED THEN \n UPDATE SET e.{0} = x.{0}\n WHEN NOT MATCHED THEN \n INSERT (e.sample_id, e.row_number, e.{0})\n VALUES (x.sample_id, x.row_number, x.{0})\n \"\"\".format(quoted_column_name, found_extra_table)\n \n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n statement = 'commit'\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n \n # Remove the column from the found extra table. If it's the last custom column in the table, remove the table\n statement = \"select count(*) from all_tab_columns where table_name = '%s'\" % (found_extra_table)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n results = con.cursor().execute(statement).fetchone()\n if results[0] <= min_column_count:\n statement = 'drop table %s' % (found_extra_table)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n else:\n statement = 'alter table %s drop column %s' % (found_extra_table, quoted_column_name)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n \n # Clean up references in study_actual_columns\n extra_table_study_id = found_extra_table.split('_')[2]\n\n statement = \"\"\"\n update study_actual_columns \n set table_name = '\"{0}\"' \n where study_id = {1} \n and table_name = '\"{2}\"'\n \"\"\".format(common_extra_table_name, extra_table_study_id, found_extra_table)\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)\n statement = 'commit'\n if debug:\n req.write('<pre>' + statement + '</pre><br/>')\n con.cursor().execute(statement)","def addSchemaFile(self, newSchemaFile):\n\t\tself.schemaFile.append(newSchemaFile)","def test_rename_column(self):\n name_column = Varchar()\n name_column._meta.name = \"name\"\n\n title_column = Varchar()\n title_column._meta.name = \"title\"\n\n schema: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[name_column],\n )\n ]\n schema_snapshot: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[title_column],\n )\n ]\n\n schema_differ = SchemaDiffer(\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\"y\"\n )\n\n self.assertTrue(len(schema_differ.rename_columns.statements) == 1)\n self.assertEqual(\n schema_differ.rename_columns.statements[0],\n \"manager.rename_column(table_class_name='Band', tablename='band', old_column_name='title', new_column_name='name', old_db_column_name='title', new_db_column_name='name')\", # noqa\n )","def _alter_table(self, names, types) :\n\n cur = self.con.cursor()\n for i in range(min(len(names), len(types))) :\n alter_sql = 'ALTER TABLE \"%s\" ADD COLUMN \"%s\" %s' % (self.name, names[i], types[i])\n cur.execute(alter_sql)","def _check_columns(\n schema_errors: set[str],\n stored: Mapping,\n expected: Mapping,\n columns: Iterable[str],\n table_name: str,\n supports: str,\n) -> None:\n for column in columns:\n if stored[column] == expected[column]:\n continue\n schema_errors.add(f\"{table_name}.{supports}\")\n _LOGGER.error(\n \"Column %s in database table %s does not support %s (stored=%s != expected=%s)\",\n column,\n table_name,\n supports,\n stored[column],\n expected[column],\n )","def add_column(self, table_name: str, column) -> None:\n sql = 'ALTER TABLE ' + table_name + ' ADD COLUMN ' + column.to_sql()\n self.cursor.execute(sql)","def addcolumn(self, column):\n if column not in self.headersindex:\n database = managers.database_manager.get_database(self.owner_id, self.database_id)\n cur = database.get_connection().cursor()\n cur.execute(\"ALTER TABLE \\'%s\\' ADD COLUMN %s\" % (self.name, column.to_declaration()))","def __update_feature_table_columns(self):\n self.__init_table()\n\n feature_dict_sorted_keys = feature_extractor_definition.keys()\n feature_dict_sorted_keys.sort()\n for key in feature_dict_sorted_keys:\n if not self.__has_feature_column(key):\n self.__add_feature_column(key, feature_extractor_definition[key])","def add_new_cols(cat, prefix=\"\", floatcols=None, boolcols=None):\n\t\n\tif floatcols != None:\n\t\tfor col in floatcols:\n\t\t\tcat.add_column(astropy.table.MaskedColumn(name=prefix+col, dtype=float, length=len(cat)))\n\t\t\tcat[prefix+col].mask = [True] * len(cat)\n\tif boolcols != None:\n\t\tfor col in boolcols:\n\t\t\tcat.add_column(astropy.table.MaskedColumn(name=prefix+col, dtype=bool, length=len(cat)))\n\t\t\tcat[prefix+col].mask = [True] * len(cat)","def _add_necessary_columns(args, custom_columns):\n # we need to add the variant's chrom, start and gene if \n # not already there.\n if custom_columns.find(\"gene\") < 0:\n custom_columns += \", gene\"\n if custom_columns.find(\"start\") < 0:\n custom_columns += \", start\"\n \n return custom_columns","def save_column_mappings(request):\n body = json.loads(request.body)\n import_file = ImportFile.objects.get(pk=body.get('import_file_id'))\n organization = import_file.import_record.super_organization\n mappings = body.get('mappings', [])\n for mapping in mappings:\n dest_field, raw_field = mapping\n if dest_field == '':\n dest_field = None\n\n dest_cols = _column_fields_to_columns(dest_field, organization)\n raw_cols = _column_fields_to_columns(raw_field, organization)\n try:\n column_mapping, created = ColumnMapping.objects.get_or_create(\n super_organization=organization,\n column_raw__in=raw_cols,\n )\n except ColumnMapping.MultipleObjectsReturned:\n # handle the special edge-case where remove dupes doesn't get\n # called by ``get_or_create``\n ColumnMapping.objects.filter(\n super_organization=organization,\n column_raw__in=raw_cols,\n ).delete()\n column_mapping, created = ColumnMapping.objects.get_or_create(\n super_organization=organization,\n column_raw__in=raw_cols,\n )\n\n # Clear out the column_raw and column mapped relationships.\n column_mapping.column_raw.clear()\n column_mapping.column_mapped.clear()\n\n # Add all that we got back from the interface back in the M2M rel.\n [column_mapping.column_raw.add(raw_col) for raw_col in raw_cols]\n if dest_cols is not None:\n [\n column_mapping.column_mapped.add(dest_col)\n for dest_col in dest_cols\n ]\n\n column_mapping.user = request.user\n column_mapping.save()\n\n return {'status': 'success'}","def columns(self, new_columns: ColumnT) -> None:\n new_columns2: ndarray = init.check_column_validity(new_columns)\n len_new: int = len(new_columns2)\n len_old: int = len(self._columns)\n if len_new != len_old:\n raise ValueError(f'There are {len_old} columns in the DataFrame. '\n f'You provided {len_new}.')\n\n new_column_info: ColInfoT = {}\n for old_col, new_col in zip(self._columns, new_columns2):\n new_column_info[new_col] = utils.Column(*self._column_info[old_col].values)\n\n self._column_info = new_column_info\n self._columns = new_columns2","def add_column(self, colspec):\n if colspec.name == DEFAULT_COLUMN_NAME or colspec.name in self.columns.keys():\n raise Exception(\"Column {} already exists.\".format(colspec.name))\n\n self.info.add_column(colspec.name, colspec.video, colspec.dtype)","def test_add_column(self):\n self.spy_on(DataGrid.add_column)\n\n DataGridColumnsHook(extension=self.extension,\n datagrid_cls=DataGrid,\n columns=[Column(id='sandbox')])\n\n self.assertTrue(DataGrid.add_column.called)","def modify(self, fields=None, **fields_kwargs):\n modified_fields = set()\n fields = self.make_dict(fields, fields_kwargs)\n fields = self._modify(fields)\n for field_name, field_val in fields.items():\n in_schema = field_name in self.schema.fields\n if in_schema:\n setattr(self, field_name, field_val)\n modified_fields.add(field_name)\n\n return modified_fields","def merge_attribute_schema(self, attr_schema):\n name = attr_schema.name\n if name not in self.schema:\n self.schema[name] = attr_schema\n else:\n self.schema[name].merge_schema(attr_schema)","def _addcolumns(self, columnname, columndata=\"\"):\n self[columnname] = columndata","def parse_migration_columns(\n self, tablename: str, migration_columns: ColumnParametersSchema\n ):\n try:\n update = self.check_table(tablename)\n\n for col in migration_columns:\n self.source_column = col.sourceColumn\n self.destination_column = col.destinationColumn\n self.dest_options = col.destinationColumn.options.dict()\n\n self._parse_fk(tablename, self.dest_options.pop(\"foreign_key\"))\n column_type = self._parse_column_type()\n\n col = Column(self.destination_column.name, column_type, **self.dest_options)\n if update:\n if not self.check_column(tablename, self.destination_column.name):\n # self.add_alter_column(tablename, {\"column_name\": self.destination_column.name,\"type\":column_type,\"options\":{**self.dest_options}})\n # else:\n self.add_updated_table(tablename, col)\n else:\n self.add_created_table(tablename, col)\n except Exception as err:\n logger.error(\"parse_migration_columns [error] -> %s\" % err)","def add_col2tab(con_db, cur_db, tab_name, col_name, col_type):\n\n # Iterate through all existing column names of the database table using\n # the PRAGMA table_info command\n for row in cur_db.execute(f'PRAGMA table_info({tab_name})'):\n\n # If the column exists: exit the function\n if row[1] == col_name:\n break\n\n # If the column is not existing yet, add the new column\n else:\n cur_db.execute(f'ALTER TABLE {tab_name} ' \\\n f'ADD COLUMN {col_name} {col_type}')\n con_db.commit()","async def upgradeSchema(self) -> None:","def AddColumn(self, column):\n self.columns.append(column)\n self.column_dict[column.column_id] = column","def append_columns(cls, columns, grid=None, grid_url=None):\n grid_id = parse_grid_id_args(grid, grid_url)\n\n grid_ops.ensure_uploaded(grid_id)\n\n # Verify unique column names\n column_names = [c.name for c in columns]\n if grid:\n existing_column_names = [c.name for c in grid]\n column_names.extend(existing_column_names)\n duplicate_name = utils.get_first_duplicate(column_names)\n if duplicate_name:\n err = exceptions.NON_UNIQUE_COLUMN_MESSAGE.format(duplicate_name)\n raise exceptions.InputError(err)\n\n # This is sorta gross, we need to double-encode this.\n body = {\"cols\": _json.dumps(columns, cls=PlotlyJSONEncoder)}\n fid = grid_id\n response = v2.grids.col_create(fid, body)\n parsed_content = response.json()\n\n cls._fill_in_response_column_ids(columns, parsed_content[\"cols\"], fid)\n\n if grid:\n grid.extend(columns)","def _format_meta_pre_merge(self):\n self.__col_name_map = {\n ColNameFormatter.fmt(c): c\n for c in self.data.solar_meta.columns.values\n }\n\n self._rename_cols(self.data.solar_meta, prefix=SOLAR_PREFIX)\n self._rename_cols(self.data.wind_meta, prefix=WIND_PREFIX)\n\n self._save_rep_prof_index_internally()","def rename_columns(columns, mapper, keep_original):\n for name, rename in mapper.items():\n if name in columns:\n columns[rename] = org_copy.deepcopy(columns[name])\n if 'parent' in columns[name]:\n parents = columns[name]['parent']\n else:\n parents = {}\n if not keep_original: del columns[name]\n columns[rename]['name'] = rename\n for parent_name, parent_spec in list(parents.items()):\n new_parent_map = {}\n if parent_name in mapper:\n new_name = mapper[parent_name]\n new_parent_map[new_name] = parent_spec\n columns[rename]['parent'] = new_parent_map\n if columns[rename].get('values'):\n values = columns[rename]['values']\n if isinstance(values, str):\n if values in mapper:\n columns[rename]['values'] = mapper[values]","def _ensure_schema_has_covariates(self, x_underscore_columns):\n previous_rename = self.covariate_rename\n if set(x_underscore_columns) == set(previous_rename.values()):\n return\n # Only rewrite schema if the x_<integer> list has changed.\n # because the schema depends on the number of covariates, not\n # their names.\n covariate_columns = list(x_underscore_columns)\n # ASCII sorting isn't correct b/c x_11 is before x_2.\n covariate_columns.sort(key=lambda x: int(x[2:]))\n for create_name in [\"data\", \"avgint\"]:\n empty = self.dismod_file.empty_table(create_name)\n without = [c for c in empty.columns if not c.startswith(\"x_\")]\n # The wrapper needs these columns to have a dtype of Real.\n empty = empty[without].assign(**{cname: np.empty((0,), dtype=np.float) for cname in covariate_columns})\n self.dismod_file.update_table_columns(create_name, empty)\n if getattr(self.dismod_file, create_name).empty:\n CODELOG.debug(f\"Writing empty {create_name} table with columns {covariate_columns}\")\n setattr(self.dismod_file, create_name, empty)\n else:\n CODELOG.debug(f\"Adding to {create_name} table schema the columns {covariate_columns}\")","def add_column(self, name, type):\n raise NotImplementedError(\n \"Please implement the 'add_column' method in a derived class.\")","def merge(self, other: Schema) -> Schema:\n if duplicates := self.keys() & other.keys():\n raise IntegrityError(f'Duplicate column name(s): {duplicates}')\n return self.__class__({**self, **other})","def build_schema(self, dframe, overwrite=False, set_num_columns=True):\n new_schema = self.schema.rebuild(dframe, overwrite)\n self.set_schema(new_schema,\n set_num_columns=(set_num_columns or overwrite))","def upgrade_alter_table(self, db, tablename, colname, coltype):\n try:\n cursor = db.cursor()\n cursor.execute(\"select %s from %s\" % (colname,tablename))\n except Exception, e:\n self.log.debug(\"upgrade_alter_table: %s\", e)\n cursor = db.cursor()\n alter = \"ALTER TABLE %s add column %s %s\" % (tablename, colname,\n coltype)\n cursor.execute(alter)","def merge_schemas(self, old_schm, new_schm):\n\n old_schm_cols = [x['name'] for x in old_schm]\n\n for col in new_schm:\n if type(col) == dict:\n if col['name'] not in old_schm_cols:\n old_schm.append(col)\n \n for count, old_col in enumerate(old_schm):\n for meta in old_col:\n if type(old_col[meta]) == list:\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\n if meta in new_col:\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\n \n return old_schm","def _get_and_validate_schema_mapping(schema1, schema2, strict=False):\n\n len_schema1 = len(schema1)\n len_schema2 = len(schema2)\n\n # If both non-empty, must be same length\n if 0 < len_schema1 != len_schema2 > 0:\n raise ValueError(\"Attempted to merge profiles with different \"\n \"numbers of columns\")\n\n # In the case of __add__ with one of the schemas not initialized\n if strict and (len_schema1 == 0 or len_schema2 == 0):\n raise ValueError(\"Cannot merge empty profiles.\")\n\n # In the case of _update_from_chunk with uninitialized schema\n if not strict and len_schema2 == 0:\n return {col_ind: col_ind for col_ind_list in schema1.values()\n for col_ind in col_ind_list}\n\n # Map indices in schema1 to indices in schema2\n schema_mapping = dict()\n\n for key in schema1:\n # Pandas columns are int by default, but need to fuzzy match strs\n if isinstance(key, str):\n key = key.lower()\n if key not in schema2:\n raise ValueError(\"Columns do not match, cannot update \"\n \"or merge profiles.\")\n\n elif len(schema1[key]) != len(schema2[key]):\n raise ValueError(f\"Different number of columns detected for \"\n f\"'{key}', cannot update or merge profiles.\")\n\n is_duplicate_col = len(schema1[key]) > 1\n for schema1_col_ind, schema2_col_ind in zip(schema1[key],\n schema2[key]):\n if is_duplicate_col and (schema1_col_ind != schema2_col_ind):\n raise ValueError(f\"Different column indices under \"\n f\"duplicate name '{key}', cannot update \"\n f\"or merge unless schema is identical.\")\n schema_mapping[schema1_col_ind] = schema2_col_ind\n\n return schema_mapping","def ensure_internal_schema_updated(self):\n if self._internal_schema_updated:\n return\n if internalmigrations.needs_upgrading(self):\n assert not self._in_transaction\n with self.lock():\n internalmigrations.upgrade(self)\n self.connection.commit()\n self._internal_schema_updated = True","def _refactor_time_columns(write_cursor: 'DBCursor') -> None:\n log.debug('Enter _refactor_time_columns')\n write_cursor.execute('ALTER TABLE timed_balances RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE timed_location_data RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE trades RENAME COLUMN time TO timestamp')\n write_cursor.execute('ALTER TABLE asset_movements RENAME COLUMN time TO timestamp')\n log.debug('Exit _refactor_time_columns')","def test_new_columns(self):\n rename = '{}*'\n expected = (list(self.df.columns) +\n list(rename.format(f) for f in self.formants))\n actual = self.normalizer(rename=rename, **self.kwargs).normalize(\n self.df).columns\n\n expected = sorted(expected)\n actual = sorted(actual)\n self.assertListEqual(actual, expected)","def addcolumn(self, colname, coldata):\n if len(coldata) != len(self):\n raise ValueError,\"Column length must match catalog length\"\n\n #Most of the bookkeeping is the same as for an empty column\n self.addemptycolumn(colname,coldata.dtype)\n\n #and then we reset the column to contain the actual data\n setattr(self,colname,coldata)","def insert_column(self, tb_name, column_name, data_type):\n sentences = f\"\"\"\n ALTER TABLE {tb_name} ADD COLUMN {column_name} {data_type};\n \"\"\"\n print(sentences)\n self.commit(sentences)","def get_column_definitions(self, schema, table, connection=None):\n raise NotImplementedError","def addColumn(self, name, column):\n self.columnNames.append(name)\n self.addColumnValues(column)","def merge_schema(self, schema):\n for _, attr_schema in schema.iter_attributes():\n self.merge_attribute_schema(attr_schema)","def update_column(self, xmldata):\n columns = managers.request_manager.get_request().session().value(\"columns\")\n headers = managers.request_manager.get_request().session().value(\"headers\")\n if not columns:\n return False\n if xmldata:\n # Parsing of column declaration\n dom = parseString(xmldata.encode(\"UTF-8\"))\n column = dom.getElementsByTagName(\"column\")[0]\n name = un_quote(column.getAttribute(\"name\"))\n if not name:\n return False\n declaration = name\n constraints = {}\n cid = column.getAttribute(\"id\")\n type = column.getAttribute(\"type\")\n if not type or type == \"INTEGER\" or type == \"REAL\" or type == \"TEXT\" or type == \"BLOB\":\n constraints[\"type\"] = type\n if column.getAttribute(\"notnull\") == \"true\":\n constraints[\"not null\"] = True\n if column.getAttribute(\"primary\") == \"true\":\n if column.getAttribute(\"autoincrement\") == \"true\":\n constraints[\"primary key\"] = \"autoincrement\"\n else:\n constraints[\"primary key\"] = True\n if column.getAttribute(\"unique\") == \"true\":\n constraints[\"unique\"] = True\n\n if column.getAttribute(\"default\") and column.getAttribute(\"default\") != \"\" and column.getAttribute(\"default\") != \"NULL\":\n constraints[\"default\"] = column.getAttribute(\"default\")\n\n column_obj = VDOM_db_column(name, constraints)\n column_obj.id = cid\n\n # praparing SQL code\n old_column = None\n for col in columns:\n if columns[col].id == cid:\n old_column = columns[col]\n break\n if not old_column:\n return False\n\n newtable = \"%s_new(\" % self.name\n oldtable = \"%s(\" % self.name\n for col in headers:\n if oldtable[-1] != \"(\":\n oldtable += \", \"\n oldtable += columns[col].to_declaration()\n\n if columns[col].id == cid:\n if newtable[-1] != \"(\":\n newtable += \", \"\n newtable += column_obj.to_declaration()\n\n else:\n if newtable[-1] != \"(\":\n newtable += \", \"\n newtable += columns[col].to_declaration()\n newtable += \")\"\n if newtable[-2] == \"(\":\n return False\n newcols = []\n newcols.extend(headers)\n newcols.remove(old_column.name)\n newcols_decl = \"\"\n for ctr in newcols:\n newcols_decl += \", `%s`\" % ctr\n\n sql = \"\"\"BEGIN TRANSACTION;\nCREATE TABLE %(newtable)s;\nINSERT INTO `%(newtablename)s` (%(newcols)s) SELECT %(newcols)s FROM `%(oldtablename)s`;\nDROP TABLE `%(oldtablename)s`;\nALTER TABLE `%(newtablename)s` RENAME TO `%(oldtablename)s`;\nEND TRANSACTION;\"\"\" % {\"newtable\": newtable, \"newtablename\": self.name + \"_new\", \"oldtablename\": self.name, \"newcols\": newcols_decl[2:]}\n query = VDOM_sql_query(self.owner_id, self.database_id, sql, None, True)\n query.commit()\n columns.pop(old_column.name)\n columns[column_obj.name] = column_obj\n managers.request_manager.get_request().session().value(\"columns\", columns)\n self.restore_structure()\n return True","def addStudyActualColumn(self, study_id, column_name, table_name):\n try:\n con = self.getMetadataDatabaseConnection()\n con.cursor().callproc('qiime_assets.add_study_actual_column', [study_id, column_name, table_name])\n except Exception, e: \n raise Exception('Exception caught in addStudyActualColumns(): %s.\\nThe error is: %s' % (type(e), e))","def add_column(self, col_name, definition):\n if not self.column_exists(col_name):\n self.execute(self.commands.add_column(self.name, col_name, definition))","def addcolumn_from_xml(self, xmldata):\n num_added = 0\n if xmldata:\n dom = parseString(xmldata.encode(\"UTF-8\"))\n for column in dom.getElementsByTagName(\"column\"):\n columns = managers.request_manager.get_request().session().value(\"columns\")\n if not columns:\n columns = self.parse_declaration()\n name = un_quote(column.getAttribute(\"name\"))\n if not name:\n continue\n if name in columns:\n continue # column already exists\n declaration = name\n constraints = {}\n cid = column.getAttribute(\"id\")\n type = column.getAttribute(\"type\")\n if not type or type == \"INTEGER\" or type == \"REAL\" or type == \"TEXT\" or type == \"BLOB\":\n constraints[\"type\"] = type\n if column.getAttribute(\"notnull\") == \"true\":\n constraints[\"not null\"] = True\n if column.getAttribute(\"primary\") == \"true\":\n if column.getAttribute(\"autoincrement\") == \"true\":\n constraints[\"primary key\"] = \"autoincrement\"\n else:\n constraints[\"primary key\"] = True\n if column.getAttribute(\"unique\") == \"true\":\n constraints[\"unique\"] = True\n\n if column.getAttribute(\"default\") and column.getAttribute(\"default\") != \"\" and column.getAttribute(\"default\") != \"NULL\":\n constraints[\"default\"] = column.getAttribute(\"default\")\n\n column_obj = VDOM_db_column(name, constraints)\n column_obj.id = cid\n columns[name] = column_obj\n self.addcolumn(column_obj)\n managers.request_manager.get_request().session().value(\"columns\", columns)\n num_added += 1\n return num_added","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\n return False","def add_latclonc_to_db(self):\n \n # add new columns\n try:\n command =\"ALTER TABLE {tb} ADD COLUMN latc TEXT\".format(tb=self.table_name) \n self.conn.cursor.execute(command)\n except:\n # pass if the column latc exists\n pass\n try:\n command =\"ALTER TABLE {tb} ADD COLUMN lonc TEXT\".format(tb=self.table_name) \n self.conn.cursor.execute(command)\n except:\n # pass if the column lonc exists\n pass\n\n # iterate through tvals of the self.sites\n sdtm = self.stm\n for ii, st in enumerate(self.sites):\n if ii == len(self.sites)-1:\n edtm = self.etm\n else:\n edtm = st.tval\n command = \"SELECT rowid, slist, vel, frang, rsep, datetime FROM {tb} WHERE (DATETIME(datetime)>'{sdtm}' and\\\n DATETIME(datetime)<='{edtm}') ORDER BY datetime\".format(tb=self.table_name,\\\n sdtm=str(sdtm), edtm=str(edtm))\n self.conn.cursor.execute(command)\n rows = self.conn.cursor.fetchall() \n if rows != []:\n rowid, slist, vel, frang_old, rsep_old, date_time_old = rows[0]\n\n # calculate latc_all and lonc_all in 'geo' coords\n latc_all, lonc_all = calc_latc_lonc(self.sites[ii], self.bmnum, frang_old, rsep_old, \n altitude=300., elevation=None, coord_alt=0.,\n coords=\"geo\", date_time=None)\n for row in rows:\n rowid, slist, vel, frang, rsep, date_time = row\n if (frang, rsep) != (frang_old, rsep_old):\n latc_all, lonc_all = calc_latc_lonc(self.sites[ii], self.bmnum, frang, rsep, \n altitude=300., elevation=None, coord_alt=0.,\n coords=\"geo\", date_time=None)\n\n \n frang_old, rsep_old = frang, rsep\n\n # convert from string to float\n slist = [int(float(x)) for x in slist.split(\",\")]\n vel = [float(x) for x in vel.split(\",\")]\n\n # exclude the slist values beyond maxgate and their correspinding velocities\n vel = [vel[i] for i in range(len(vel)) if slist[i] < st.maxgate]\n slist = [s for s in slist if s < st.maxgate]\n\n # extract latc and lonc values\n latc = [latc_all[s] for s in slist]\n lonc = [lonc_all[s] for s in slist]\n\n # convert to comma seperated text\n slist = \",\".join([str(x) for x in slist])\n vel = \",\".join([str(round(x,2)) for x in vel])\n latc = \",\".join([str(round(x,2)) for x in latc])\n lonc = \",\".join([str(round(x,2)) for x in lonc])\n\n # update the table\n command = \"UPDATE {tb} SET slist='{slist}', vel='{vel}',\\\n latc='{latc}', lonc='{lonc}' WHERE rowid=={rowid}\".\\\n format(tb=self.table_name, slist=slist, vel=vel,\\\n latc=latc, lonc=lonc, rowid=rowid)\n self.conn.cursor.execute(command)\n\n # update sdtm\n sdtm = edtm\n\n # commit the data into the db\n self.conn._commit()\n\n # close db connection\n self.conn._close_connection()\n \n return","def _insert_into_new_columns(self, commit, mapping_index):\n for i in range(self.num_new_columns):\n if self.new_columns[i].commit == commit:\n self.mapping[mapping_index] = i\n return mapping_index + 2\n\n # This commit isn't already in new_columns. Add it.\n column = Column(commit, self._find_commit_color(commit))\n self.new_columns[self.num_new_columns] = column\n self.mapping[mapping_index] = self.num_new_columns\n self.num_new_columns += 1\n return mapping_index + 2","def setAllColumns(self, newAllColumns):\n \n pass","def deferred_to_columns_cb(self, target, model, fields):\n table = model._meta.db_table\n if table not in target:\n target[table] = set()\n for field in fields:\n if not hasattr(field.column, \"columns\"):\n target[table].add(field.column)\n else:\n target[table].update(field.column.columns)","def addTableColumn(self, tablename, columnname, columntype):\n\n # Check if the table exists\n if tablename in self.getTableNames():\n\n # Check that the column does not already exist\n if columnname not in self.getColumnNames(tablename):\n\n #Allow columnames with spaces\n columnname = '`'+columnname+'`'\n\n \"\"\"# Fit characters to the allowed format if necessary\n fmt = ''\n if (self.connector == 'mysql' and\n ('TEXT' in columntype or 'VARCHAR' in columntype) and\n not ('CHARACTER SET' in columntype or\n 'utf8mb4' in columntype)):\n\n # We enforze utf8mb4 for mysql\n fmt = ' CHARACTER SET utf8mb4'\n\n\n sqlcmd = ('ALTER TABLE ' + tablename + ' ADD COLUMN ' +\n columnname + ' ' + columntype + fmt)\"\"\"\n sqlcmd = ('ALTER TABLE ' + tablename + ' ADD COLUMN ' +\n columnname + ' ' + columntype) \n self._c.execute(sqlcmd)\n\n # Commit changes\n self._conn.commit()\n\n else:\n print((\"WARNING: Column {0} already exists in table {1}.\"\n ).format(columnname, tablename))\n\n else:\n print('Error adding column to table. Please, select a valid ' +\n 'table name from the list')\n print(self.getTableNames())\n\n return","def _insert_column(self, column_name, column_type, table, params=None, overwrite=False, after_col=None, verbose=True):\n \n not_null = ''\n auto_increment = ''\n \n if params != None and 'not_null' in params:\n not_null = 'NOT NULL'\n \n \n if params != None and 'auto_increment' in params:\n auto_increment = \"AUTO_INCREMENT\"\n \n \n ADD_COLUMN_COMMAND = \"ALTER TABLE {0} ADD {1} {2} {3} {4}\".format(table, column_name, column_type, not_null, auto_increment)\n \n if (after_col != None and type(after_col) is str):\n ADD_COLUMN_COMMAND += \" AFTER {0} \".format(after_col)\n \n \n self.cursor.execute(ADD_COLUMN_COMMAND)\n \n if verbose: \n print(\"Adding the column '{0}' to the table '{1}'...\".format(column_name, table))\n print(\"\\t\" + ADD_COLUMN_COMMAND) \n \n \n if params != None and 'foreign_key' in params:\n \n if 'references' not in params:\n raise InvalidParameterError\n \n referenced_table = params['references'].split('(')[0]\n referenced_column = params['references'].split('(')[1][:-1] \n \n \n if (not self.check_table(referenced_table, verbose=False)):\n raise(TableNotFoundError)\n \n \n if (not self.check_column(referenced_column, referenced_table, verbose=False)):\n raise(ColumnNotFoundError)\n \n \n ADD_FOREIGN_KEY_COMMAND = \"ALTER TABLE {0} ADD FOREIGN KEY ({1}) REFERENCES {2}({3})\".format(table, column_name, referenced_table, referenced_column)\n \n \n if verbose: \n print(\"\\t\" + ADD_FOREIGN_KEY_COMMAND) \n \n self.cursor.execute(ADD_FOREIGN_KEY_COMMAND)","def addExtraColumnMetadata(self, study_id, table_level, column_name, description, data_type):\n try:\n con = self.getMetadataDatabaseConnection()\n con.cursor().callproc('qiime_assets.extra_column_metadata_insert', [study_id, table_level, \n column_name, description, data_type])\n except Exception, e: \n raise Exception('Exception caught in addExtraColumnMetadata(): {0}.\\nThe error is: {1}.\\nstudy_id: \\\n {2}\\ntable_level: {3}\\ncolumn_name: {4}\\ndescription: {5}\\n data_type: {6}'.format(type(e), e, \\\n str(study_id), str(table_level), str(column_name), str(description), str(data_type)))","def test_dummydb_add_data_to_table_wrong_column_name(self):\n db = DummyDB()\n columns = {\n \"one\": int,\n \"two\": str,\n \"three\": bool,\n }\n db.create_table(\"new_table\", columns)\n result = db.select(\"new_table\", four=1)","def generate_altered_fields(self):\n result = super(MigrationAutodetector, self).generate_altered_fields()\n self.generate_sql_changes()\n return result","def add_col(self):\r\n reader = csv.reader(open(self.in_csvfile, newline=''))\r\n rows = list(reader)\r\n rows[0].append(self.col_name)\r\n for i in range(1, len(rows)):\r\n rows[i].append(self.cell_filler(rows[i]))\r\n writer = csv.writer(open(self.out_csvfile, 'w', newline=''))\r\n writer.writerows(rows)","def has_desired_schema(self):\n if self._new_table == self._old_table:\n if not self.rebuild:\n log.info(\"Table already has the desired schema. \")\n return True\n else:\n log.info(\n \"Table already has the desired schema. However \"\n \"--rebuild is specified, doing a rebuild instead\"\n )\n return False\n return False","def _add_cols(df: pandas.DataFrame, scope = (globals(), locals())) -> None:\n command : str = input(\"\\nAdd a column:\\n\")\n if command.lower() in ['n', 'no', 'quit()', 'exit', 'return']:\n return\n\n col_name : str = command[ \\\n re.search(r'[\\w\\.\\(\\)]+', command).start(): \\\n re.search(r'[\\w\\.\\(\\)]+', command).end() \\\n ]\n # new column's name\n\n arg : str = command[re.search(r'[=,;]', command).end():]\n # the new column's \"function\"\n ref_cols = re.findall(r'(?<=\\{)\\w[\\w\\.\\(\\)]*(?=\\})', arg)\n # df column names that are referenced to create new columns\n\n for i in range(len(ref_cols)):\n arg = re.sub(\n f'{{{ref_cols[i]}}}',\n f'df[\\'{ref_cols[i]}\\']',\n arg\n )\n # substituting references\n\n scope[0].update(globals())\n scope[1].update(locals())\n\n col_arg = eval(arg, scope[0], scope[1])\n # pandas.Series for type checking\n df[col_name] = col_arg\n # creating column\n\n more : str = input(\"\\nWould you like to add more columns?\\n\")\n if more.lower() in ['y', 'yes', 'continue', 'true']:\n return _add_cols(df)\n return","def merge_schema_entry(\n self,\n old_schema_entry,\n new_schema_entry,\n base_path=None,\n ):\n if not old_schema_entry:\n return new_schema_entry\n\n # If the new schema is None, return immediately.\n if not new_schema_entry:\n return new_schema_entry\n\n # If a field value is missing, permanently set 'filled' to False.\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\n old_schema_entry['filled'] = False\n new_schema_entry['filled'] = False\n\n old_status = old_schema_entry['status']\n new_status = new_schema_entry['status']\n\n # new 'soft' does not clobber old 'hard'\n if old_status == 'hard' and new_status == 'soft':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n old_schema_entry['info']['mode'] = mode\n return old_schema_entry\n\n # new 'hard' clobbers old 'soft'\n if old_status == 'soft' and new_status == 'hard':\n mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if mode is None:\n return None\n new_schema_entry['info']['mode'] = mode\n return new_schema_entry\n\n # Verify that it's soft->soft or hard->hard\n if old_status != new_status:\n raise Exception(\n f'Unexpected schema_entry type, this should never happen: '\n f'old ({old_status}); new ({new_status})'\n )\n\n old_info = old_schema_entry['info']\n old_name = old_info['name']\n old_type = old_info['type']\n old_mode = old_info['mode']\n new_info = new_schema_entry['info']\n new_name = new_info['name']\n new_type = new_info['type']\n new_mode = new_info['mode']\n\n full_old_name = json_full_path(base_path, old_name)\n full_new_name = json_full_path(base_path, new_name)\n\n # Defensive check, names should always be the same.\n if old_name != new_name:\n if old_name.lower() != new_name.lower():\n raise Exception(\n 'Unexpected difference in name, should never happen:'\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\n )\n else:\n # preserve old name if case is different\n new_info['name'] = old_info['name']\n\n # Recursively merge in the subfields of a RECORD, allowing\n # NULLABLE to become REPEATED (because 'bq load' allows it).\n if old_type == 'RECORD' and new_type == 'RECORD':\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\n # 'bq load' allows it.\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\n old_info['mode'] = 'REPEATED'\n self.log_error(\n f'Converting schema for \"{full_old_name}\" from '\n 'NULLABLE RECORD into REPEATED RECORD'\n )\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\n # TODO: Maybe remove this warning output. It was helpful during\n # development, but maybe it's just natural.\n self.log_error(\n f'Leaving schema for \"{full_old_name}\" as REPEATED RECORD'\n )\n\n # RECORD type needs a recursive merging of sub-fields. We merge into\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\n # can be modified in situ.\n old_fields = old_info['fields']\n new_fields = new_info['fields']\n for key, new_entry in new_fields.items():\n old_entry = old_fields.get(key)\n new_base_path = json_full_path(base_path, old_name)\n old_fields[key] = self.merge_schema_entry(\n old_schema_entry=old_entry,\n new_schema_entry=new_entry,\n base_path=new_base_path,\n )\n return old_schema_entry\n\n new_mode = self.merge_mode(old_schema_entry,\n new_schema_entry,\n base_path)\n if new_mode is None:\n return None\n new_schema_entry['info']['mode'] = new_mode\n\n # For all other types...\n if old_type != new_type:\n # Check that the converted types are compatible.\n candidate_type = convert_type(old_type, new_type)\n if not candidate_type:\n self.log_error(\n f'Ignoring field with mismatched type: '\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\n )\n return None\n\n new_info['type'] = candidate_type\n return new_schema_entry","def build_column_mapping(raw_columns, dest_columns, previous_mapping=None, map_args=None,\n default_mappings=None, thresh=0):\n\n return MappingColumns(raw_columns, dest_columns, previous_mapping=previous_mapping,\n map_args=map_args, default_mappings=default_mappings,\n threshold=thresh).final_mappings","def _modify_fields(usecols, dtype, badcols):\n for col in badcols:\n usecols = [badcols[col] if uc == col else uc for uc in usecols]\n try:\n dtype[badcols[col]] = dtype.pop(col)\n except KeyError:\n pass\n return usecols, dtype","def add_schema(self, schema, db):\n self._dbs[schema.typename] = db\n return None","def addColumnsToFile(filename, columns, add_before_original=True):\n\ttempFile = \"TEMP.tmp\"\n\toutFile = open(tempFile, \"w\")\n\tinFile = open(filename, \"r\")\n\tcolumns = listR.toList(columns)\n\tindex = 0\n\taLine = inFile.readline()\n\twhile aLine:\n\t\tif add_before_original:\n\t\t\toutFile.write(columns[index] + aLine)\n\t\telse:\n\t\t\toutFile.write(aLine + columns[index])\n\t\tindex = listR.next(columns, index)\n\t\taLine = inFile.readline()\n\tinFile.close\n\toutFile.close()\n\tcopy(tempFile, filename)","def rename_column(self, table_name, old, new):\r\n self._remake_table(table_name, renames={old: new})","def _prepare_schema(self):\n schema = DaskSchema(self.schema_name)\n\n if not self.tables:\n logger.warning(\"No tables are registered.\")\n\n for name, dc in self.tables.items():\n table = DaskTable(name)\n df = dc.df\n logger.debug(\n f\"Adding table '{name}' to schema with columns: {list(df.columns)}\"\n )\n for column in df.columns:\n data_type = df[column].dtype\n sql_data_type = python_to_sql_type(data_type)\n\n table.addColumn(column, sql_data_type)\n\n schema.addTable(table)\n\n if not self.functions:\n logger.debug(\"No custom functions defined.\")\n\n for function_description in self.function_list:\n name = function_description.name\n sql_return_type = python_to_sql_type(function_description.return_type)\n if function_description.aggregation:\n logger.debug(f\"Adding function '{name}' to schema as aggregation.\")\n dask_function = DaskAggregateFunction(name, sql_return_type)\n else:\n logger.debug(f\"Adding function '{name}' to schema as scalar function.\")\n dask_function = DaskScalarFunction(name, sql_return_type)\n\n dask_function = self._add_parameters_from_description(\n function_description, dask_function\n )\n\n schema.addFunction(dask_function)\n\n return schema","def apply_patch():\n assert BaseDatabaseSchemaEditor is not None\n\n def _create_unique_sql(self, *args, **kwargs):\n from django.db.backends.ddl_references import IndexName\n\n statement = orig_create_unique_sql(self, *args, **kwargs)\n\n if statement is not None:\n index_name = statement.parts['name']\n\n if (isinstance(index_name, IndexName) and\n index_name.create_index_name == self._create_index_name):\n # The result will be unquoted. Let's quote it.\n index_name.create_index_name = lambda *args, **kwargs: \\\n self.quote_name(self._create_index_name(*args, **kwargs))\n\n return statement\n\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql"],"string":"[\n \"def add_column(self, schema):\\n self[schema.name] = schema.copy()\",\n \"def _add_to_schema(self, new: dict):\\n self._defaults.update(new)\\n self._migrate()\",\n \"def _GetRelaxedCols(relaxed_columns, orig_schema_map):\\n updated_schema_map = orig_schema_map.copy()\\n for col in relaxed_columns:\\n if col in orig_schema_map:\\n updated_schema_map[col].mode = 'NULLABLE'\\n else:\\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\\n return updated_schema_map\",\n \"def _GetUpdatedSchema(\\n original_schema,\\n new_columns=None,\\n relaxed_columns=None):\\n orig_field_map = (\\n {f.name: f for f in original_schema.fields} if original_schema else {})\\n\\n if relaxed_columns:\\n orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)\\n\\n if new_columns:\\n orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)\\n\\n return sorted(orig_field_map.values(), key=lambda x: x.name)\",\n \"def add_cols(self, source) :\\n\\n cols = source.get_cols()\\n types = source.get_types()\\n\\n new_cols = []\\n new_types = []\\n for i in range(len(cols)) :\\n if cols[i] not in self.cols :\\n new_cols.append(cols[i])\\n new_types.append(types[i])\\n self.cols.extend(new_cols)\\n self.types.extend(new_types)\\n\\n self._alter_table(new_cols, new_types)\\n\\n row_ids = self.get_values('__ROWID')\\n \\n for col in new_cols :\\n new_vals = source.get_values(col)\\n if len(row_ids) == 0 :\\n for val in new_vals :\\n self._insert_internal(['__ROWID', col], [0, val])\\n\\n row_ids = self.get_values('__ROWID')\\n\\n else :\\n binds = zip(new_vals, row_ids)\\n q = self._quoter(col)\\n sql_base = 'UPDATE \\\"%s\\\" SET \\\"%s\\\" = %s WHERE \\\"__ROWID\\\" = %%d' % (self.name, col, q)\\n cur = self.con.cursor()\\n for bind in binds :\\n if bind[0] :\\n update_sql = sql_base % (str(bind[0]), bind[1])\\n cur.execute(update_sql)\\n\\n self.version += 1\",\n \"def update_table_columns(self, table_name, table):\\n table_definition = self._table_definitions[table_name]\\n new_columns = table.columns.difference(table_definition.c.keys())\\n new_column_types = {c: table.dtypes[c] for c in new_columns}\\n\\n allows_covariates = table_definition.name in [\\\"avgint\\\", \\\"data\\\"]\\n\\n good_prefixes = [\\\"c_\\\"]\\n if allows_covariates:\\n good_prefixes.append(\\\"x_\\\")\\n bad_column_names = [c for c in new_columns if c[:2] not in good_prefixes]\\n if bad_column_names:\\n msg = f\\\"\\\"\\\"\\n Table '{table_definition.name}' has these columns {list(table_definition.c.keys())}.\\n It allows additional comment columns, which must start 'c_'.\\\"\\\"\\\"\\n if allows_covariates:\\n msg += \\\" In addition it allows covariate columns, which must start with 'x_'.\\\"\\n msg += f\\\" You supplied columns that don't meet those requirements: {bad_column_names}\\\"\\n\\n raise ValueError(dedent(msg))\\n\\n add_columns_to_table(table_definition, new_column_types)\",\n \"def test_add_column(self):\\n name_column = Varchar()\\n name_column._meta.name = \\\"name\\\"\\n\\n genre_column = Varchar()\\n genre_column._meta.name = \\\"genre\\\"\\n\\n schema: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[name_column, genre_column],\\n )\\n ]\\n schema_snapshot: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[name_column],\\n )\\n ]\\n\\n schema_differ = SchemaDiffer(\\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\\\"y\\\"\\n )\\n\\n self.assertTrue(len(schema_differ.add_columns.statements) == 1)\\n self.assertEqual(\\n schema_differ.add_columns.statements[0],\\n \\\"manager.add_column(table_class_name='Band', tablename='band', column_name='genre', db_column_name='genre', column_class_name='Varchar', column_class=Varchar, params={'length': 255, 'default': '', 'null': False, 'primary_key': False, 'unique': False, 'index': False, 'index_method': IndexMethod.btree, 'choices': None, 'db_column_name': None})\\\", # noqa\\n )\",\n \"def update(self):\\n current = LazyRegister(self.db)\\n current.render()\\n cur = self.db.cursor()\\n for table in self.tables:\\n if table in current.tables:\\n additions, removals = current.tables[table].migrate(self.tables[table])\\n for addition in additions:\\n cur.execute(\\\"\\\"\\\"ALTER TABLE %s ADD COLUMN %s\\\"\\\"\\\" % (\\n table, addition[1].get_sql()\\n ))\\n print('Added column: ', addition[0])\\n for removal in removals:\\n #cur.execute(\\\"\\\"\\\"ALTER TABLE %s DROP COLUMN %s\\\"\\\"\\\" % (\\n # table, removal[0]\\n #))\\n #print('Removed column: ', removal[0])\\n print('Did not removed column: ', removal[0])\\n else:\\n schema = self.tables[table].get_create_table_sql()\\n cur.execute(schema)\\n print('Added table %s' % table)\",\n \"def add_columns(self, table, col_data, col_type):\\n conn = psycopg2.connect(self.name, sslmode='require')\\n c = conn.cursor()\\n for data, typ in zip(col_data, col_type):\\n c.execute(\\\"ALTER TABLE {tn} ADD COLUMN {cn} {ct}\\\".\\n format(tn=table, cn=data, ct=typ))\\n conn.commit() \\n conn.close()\",\n \"def add_table_column(self, schema, column):\\n if not column[\\\"name\\\"] or not constants.NAME_RX.match(column[\\\"name\\\"]):\\n raise ValueError(\\\"invalid column name\\\")\\n if utils.name_in_nocase(column[\\\"name\\\"], [c[\\\"name\\\"] for c in schema[\\\"columns\\\"]]):\\n raise ValueError(\\\"non-unique column name\\\")\\n if column[\\\"type\\\"] not in constants.COLUMN_TYPES:\\n raise ValueError(\\\"invalid column type\\\")\\n sql = (\\n f'''ALTER TABLE \\\"{schema['name']}\\\"'''\\n f\\\"\\\"\\\" ADD COLUMN \\\"{column['name']}\\\" {column['type']}\\\"\\\"\\\"\\n )\\n if column.get(\\\"notnull\\\"):\\n notnull = [\\\"NOT NULL\\\"]\\n if column[\\\"type\\\"] == constants.INTEGER:\\n notnull.append(\\\"DEFAULT 0\\\")\\n elif column[\\\"type\\\"] == constants.REAL:\\n notnull.append(\\\"DEFAULT 0.0\\\")\\n elif column[\\\"type\\\"] in (constants.TEXT, constants.BLOB):\\n notnull.append(\\\"DEFAULT ''\\\")\\n sql += \\\" \\\" + \\\" \\\".join(notnull)\\n self.dbcnx.execute(sql)\\n schema[\\\"columns\\\"].append(column)\\n self.update_table(schema)\",\n \"def add_column_to_staging_table(cursor,table_schema,table_name,column_name):\\n if not check_if_column_exists(cursor, table_schema, table_name, column_name):\\n add_column = \\\"ALTER TABLE \\\" + table_schema + \\\".\\\" + table_name + \\\" ADD COLUMN \\\" + column_name + \\\" text;\\\"\\n cursor.execute(add_column)\",\n \"def add_schema_fields(self, fields):\\n if not fields:\\n return\\n\\n data = json.dumps(fields)\\n\\n try:\\n return self.client.post(\\n self._get_collection_url('schema/fields'),\\n body=data\\n )\\n except solr_errors.SolrError as e:\\n raise solr_errors.SolrSchemaUpdateError(fields, message=e.args[0])\",\n \"def add_column_into_target_sf(self, tap_type, table, new_column):\\n self.run_query_target_snowflake(\\n f'ALTER TABLE ppw_e2e_tap_{tap_type}{self.sf_schema_postfix}.{table} ADD {new_column[\\\"name\\\"]} int'\\n )\\n self.run_query_target_snowflake(\\n f'UPDATE ppw_e2e_tap_{tap_type}{self.sf_schema_postfix}.{table}'\\n f' SET {new_column[\\\"name\\\"]}={new_column[\\\"value\\\"]} WHERE 1=1'\\n )\",\n \"def update_schema(self, new_schema):\\n return self.conn.update_schema(new_schema)\",\n \"def add_feature_columns(self, feature_columns: typing.List[str]):\\n self.feature_columns += feature_columns\",\n \"def _addColumn(self, table, column, init_data):\\n\\t\\tcommand = \\\"ALTER TABLE \\\" + table + \\\" ADD COLUMN \\\" + str(column) + \\\" \\\" + getSQLiteType(init_data)\\n\\t\\ttry:\\n\\t\\t\\tself._run_command(command)\\n\\t\\texcept sqlite3.OperationalError:\\n\\t\\t\\tprint(\\\"Column \\\" + str(column) + \\\" already exists!\\\")\",\n \"def __append_columns(self, new_dataframe):\\n self.dataframe = pd.merge(self.dataframe, new_dataframe)\",\n \"def newColumn (layer,FieldName,DataType):\\n # Check if field already exists\\n if layer.fields().indexFromName(FieldName)==-1:\\n caps = layer.dataProvider().capabilities()\\n if caps & QgsVectorDataProvider.AddAttributes:\\n res = layer.dataProvider().addAttributes([QgsField(FieldName,DataType)])\\n print(\\\"New field \\\\\\\"{}\\\\\\\" added\\\".format(FieldName))\\n # Update to propagate the changes\\n layer.updateFields()\\n else:\\n print(\\\"Field \\\\\\\"{}\\\\\\\" already exists.\\\".format(FieldName))\",\n \"def rename_column(self, original_column_name, new_column_name):\\n self.renames.append((original_column_name, new_column_name))\\n if not self.column_exists(new_column_name):\\n super(MigrationTable, self).rename_column(original_column_name, new_column_name)\",\n \"def _add_hybrid_cols(self):\\n for new_col_name, method in HYBRID_METHODS.items():\\n out = method(self)\\n if out is not None:\\n try:\\n self._hybrid_meta[new_col_name] = out\\n except ValueError as e:\\n msg = (\\\"Unable to add {!r} column to hybrid meta. The \\\"\\n \\\"following exception was raised when adding \\\"\\n \\\"the data output by '{}': {!r}.\\\")\\n w = msg.format(new_col_name, method.__name__, e)\\n logger.warning(w)\\n warn(w, OutputWarning)\",\n \"def ProcessSchemaUpdate(ref, args, request):\\n table = request.table\\n relaxed_columns = args.relax_columns\\n if not table.schema and not relaxed_columns: # if not updating schema,\\n return request # then just return.\\n\\n original_schema = _TryGetCurrentSchema(ref.Parent().Name(),\\n ref.Name(),\\n ref.projectId)\\n\\n new_schema_columns = table.schema\\n updated_fields = _GetUpdatedSchema(original_schema,\\n new_schema_columns,\\n relaxed_columns)\\n\\n table_schema_type = GetApiMessage('TableSchema')\\n request.table.schema = table_schema_type(fields=updated_fields)\\n\\n return request\",\n \"def add_column_into_source(self, tap_type, table, new_column):\\n run_query_method = getattr(self, f'run_query_tap_{tap_type}')\\n run_query_method(\\n f'ALTER TABLE {table} ADD {new_column[\\\"name\\\"]} int'\\n )\\n run_query_method(\\n f'UPDATE {table} set {new_column[\\\"name\\\"]}={new_column[\\\"value\\\"]} where 1=1'\\n )\",\n \"def update(self, other):\\n # Check if any columns will remain with their original length. If so\\n # also check if the lengths of the tables are the same.\\n self._dirty = True\\n nrows = other.number_of_rows()\\n\\n if (other._columns and\\n set(self._columns) - set(other._columns) and\\n other.number_of_rows() != self.number_of_rows()):\\n\\n raise ValueError('Can not add columns of length {}'\\n ' to table of length {}'.format(\\n other.number_of_rows(),\\n self.number_of_rows()))\\n\\n for name, column in other._columns.items():\\n self._set_column_column_nocheck(name, column, nrows)\\n\\n self.set_table_attributes(other.get_table_attributes())\\n self.set_name(other.get_name())\",\n \"def create_column(self, new_column, dtype):\\n self.logger.debug(\\\"[%u] Ready to add column %s\\\" %\\n (os.getpid(), new_column))\\n ddl = \\\"\\\"\\\"\\n ALTER TABLE {schema}.{table}\\n ADD COLUMN IF NOT EXISTS {col} {type}\\n \\\"\\\"\\\"\\n # TODO Replace by execute_ddl func and test it\\n with get_sink_connection_string(self) as conn:\\n with conn.cursor() as cursor:\\n cursor.execute(ddl.format(schema=self.config['schema'],\\n table=self.config['table'],\\n col=new_column,\\n type=dtype))\\n self.logger.debug(\\\"[%u] Column %s has been added\\\" %\\n (os.getpid(), new_column))\",\n \"def modify_bigquery_schema(self, schema, info_keys):\\n # type: (bigquery.TableSchema, Set[str]) -> None\",\n \"def add_col(self, colname, n_batch=5000, debug=False):\\n\\n if debug: print(\\\"Create new column {col}\\\".format(col=colname))\\n # Alter table add column\\n #\\n alter_query = '''\\n ALTER TABLE \\\"{tablename}\\\"\\n ADD COLUMN \\\"{colname}\\\" {datatype};\\n '''.format(tablename=self.get_carto_tablename(),\\n colname=colname,\\n datatype=datatype_map(str(self.dtypes[colname])))\\n if debug: print(alter_query)\\n\\n # add column\\n resp = self.carto_sql_client.send(alter_query)\\n if debug: print(resp)\\n\\n # update all the values in that column\\n #\\n # NOTE: fails if colval is 'inf' or some other exceptional Python\\n # or NumPy type\\n n_items = len(self[colname])\\n update_query = '''\\n UPDATE \\\"{tablename}\\\"\\n SET \\\"{colname}\\\" = {colval}\\n WHERE \\\"cartodb_id\\\" = {cartodb_id};\\n '''\\n queries = []\\n\\n for row_num, item in enumerate(self[colname].iteritems()):\\n # if debug: print(item)\\n pgtype = dtype_to_pgtype(self[colname].dtype, colname)\\n temp_query = update_query.format(\\n tablename=self.get_carto_tablename(),\\n colname=colname,\\n colval=numpy_val_to_pg_val(item[1], pgtype),\\n cartodb_id=item[0]).strip()\\n queries.append(temp_query)\\n if (len(queries) == n_batch) or (row_num == n_items - 1):\\n output_query = '\\\\n'.join(queries)\\n if debug: print(output_query)\\n if debug: print(\\\"Num chars in query: {}\\\".format(len(output_query)))\\n resp = self.carto_sql_client.send(output_query)\\n queries = []\\n\\n return None\",\n \"def AddColumns(sqlite_file, table_name):\\r\\n columns = ['cf_direct_parent','cf_kingdom','cf_superclass',\\\\\\r\\n 'cf_class','cf_subclass','cf_intermediate_0','cf_intermediate_1',\\\\\\r\\n 'cf_intermediate_2','cf_intermediate_3','cf_intermediate_4',\\\\\\r\\n 'cf_intermediate_5','cf_molecular_framework','cf_alternative_parents',\\\\\\r\\n 'cf_substituents', 'cf_description']\\r\\n column_type = 'TEXT'\\r\\n # Connecting to the database file\\r\\n conn = sqlite3.connect(sqlite_file) # Connecting to the database\\r\\n c = conn.cursor() # Adding a cursor to interact with the database\\r\\n # Adding new column, if it does not exist yet, without a row value\\r\\n for new_column_name in columns:\\r\\n try:\\r\\n c.execute(\\\"ALTER TABLE {tn} ADD COLUMN '{cn}' {ct}\\\"\\\\\\r\\n .format(tn=table_name, cn=new_column_name, ct=column_type))\\r\\n print(\\\"Column created: {cn}\\\".format(cn=new_column_name))\\r\\n except sqlite3.OperationalError:\\r\\n print(\\\"Column already exists: {cn}\\\".format(cn=new_column_name))\\r\\n conn.commit()\\r\\n conn.close()\\r\\n return None\",\n \"def rename_columns(self, col):\\n try:\\n self.cleaned_data.columns = col\\n except Exception as e:\\n raise e\",\n \"def addCommonExtraColumn(self, req, study_id, found_extra_table, column_name, data_type, description):\\n debug = False\\n common_extra_table_name = None\\n min_column_count = None\\n quoted_column_name = '\\\"{0}\\\"'.format(column_name.upper())\\n \\n if 'SAMPLE' in found_extra_table:\\n common_extra_table_name = 'COMMON_EXTRA_SAMPLE'\\n min_column_count = 2\\n elif 'PREP' in found_extra_table:\\n common_extra_table_name = 'COMMON_EXTRA_PREP'\\n min_column_count = 3\\n \\n if common_extra_table_name == None:\\n raise Exception('Error: Could not determine the common extra table name. The found extra table is: %s' % found_extra_table)\\n \\n # Set the database data type:\\n database_data_type = ''\\n if data_type == 'text' or database_data_type == 'range':\\n database_data_type = 'varchar2(4000)'\\n elif data_type == 'numeric':\\n database_data_type = 'int'\\n elif data_type == 'date':\\n database_data_type = 'date'\\n \\n if database_data_type == '':\\n raise Exception('Could not determine common extra column data type.')\\n\\n # Create the column if it doesn't already exist\\n statement = \\\"\\\"\\\"\\n select count(*) \\n from all_tab_columns \\n where column_name = '{0}' \\n and table_name = '{1}'\\n \\\"\\\"\\\".format(column_name.upper(), common_extra_table_name)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con = self.getMetadataDatabaseConnection()\\n results = con.cursor().execute(statement).fetchone()\\n if results[0] == 0:\\n statement = 'alter table %s add %s %s' % (common_extra_table_name, quoted_column_name, database_data_type)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n \\n # Copy the data found in the found extra_table\\n if common_extra_table_name == 'COMMON_EXTRA_SAMPLE':\\n statement = \\\"\\\"\\\"\\n MERGE INTO common_extra_sample e\\n USING (\\n SELECT sample_id, {0}\\n FROM {1}\\n ) x\\n ON (e.sample_id = x.sample_id)\\n WHEN MATCHED THEN \\n UPDATE SET e.{0} = x.{0}\\n WHEN NOT MATCHED THEN \\n INSERT (e.sample_id, e.{0})\\n VALUES (x.sample_id, x.{0})\\n \\\"\\\"\\\".format(quoted_column_name, found_extra_table)\\n else:\\n statement = \\\"\\\"\\\"\\n MERGE INTO common_extra_prep e\\n USING (\\n SELECT sample_id, row_number, {0}\\n FROM {1}\\n ) x\\n ON (e.sample_id = x.sample_id and e.row_number = x.row_number)\\n WHEN MATCHED THEN \\n UPDATE SET e.{0} = x.{0}\\n WHEN NOT MATCHED THEN \\n INSERT (e.sample_id, e.row_number, e.{0})\\n VALUES (x.sample_id, x.row_number, x.{0})\\n \\\"\\\"\\\".format(quoted_column_name, found_extra_table)\\n \\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n statement = 'commit'\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n \\n # Remove the column from the found extra table. If it's the last custom column in the table, remove the table\\n statement = \\\"select count(*) from all_tab_columns where table_name = '%s'\\\" % (found_extra_table)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n results = con.cursor().execute(statement).fetchone()\\n if results[0] <= min_column_count:\\n statement = 'drop table %s' % (found_extra_table)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n else:\\n statement = 'alter table %s drop column %s' % (found_extra_table, quoted_column_name)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n \\n # Clean up references in study_actual_columns\\n extra_table_study_id = found_extra_table.split('_')[2]\\n\\n statement = \\\"\\\"\\\"\\n update study_actual_columns \\n set table_name = '\\\"{0}\\\"' \\n where study_id = {1} \\n and table_name = '\\\"{2}\\\"'\\n \\\"\\\"\\\".format(common_extra_table_name, extra_table_study_id, found_extra_table)\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\\n statement = 'commit'\\n if debug:\\n req.write('<pre>' + statement + '</pre><br/>')\\n con.cursor().execute(statement)\",\n \"def addSchemaFile(self, newSchemaFile):\\n\\t\\tself.schemaFile.append(newSchemaFile)\",\n \"def test_rename_column(self):\\n name_column = Varchar()\\n name_column._meta.name = \\\"name\\\"\\n\\n title_column = Varchar()\\n title_column._meta.name = \\\"title\\\"\\n\\n schema: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[name_column],\\n )\\n ]\\n schema_snapshot: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[title_column],\\n )\\n ]\\n\\n schema_differ = SchemaDiffer(\\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\\\"y\\\"\\n )\\n\\n self.assertTrue(len(schema_differ.rename_columns.statements) == 1)\\n self.assertEqual(\\n schema_differ.rename_columns.statements[0],\\n \\\"manager.rename_column(table_class_name='Band', tablename='band', old_column_name='title', new_column_name='name', old_db_column_name='title', new_db_column_name='name')\\\", # noqa\\n )\",\n \"def _alter_table(self, names, types) :\\n\\n cur = self.con.cursor()\\n for i in range(min(len(names), len(types))) :\\n alter_sql = 'ALTER TABLE \\\"%s\\\" ADD COLUMN \\\"%s\\\" %s' % (self.name, names[i], types[i])\\n cur.execute(alter_sql)\",\n \"def _check_columns(\\n schema_errors: set[str],\\n stored: Mapping,\\n expected: Mapping,\\n columns: Iterable[str],\\n table_name: str,\\n supports: str,\\n) -> None:\\n for column in columns:\\n if stored[column] == expected[column]:\\n continue\\n schema_errors.add(f\\\"{table_name}.{supports}\\\")\\n _LOGGER.error(\\n \\\"Column %s in database table %s does not support %s (stored=%s != expected=%s)\\\",\\n column,\\n table_name,\\n supports,\\n stored[column],\\n expected[column],\\n )\",\n \"def add_column(self, table_name: str, column) -> None:\\n sql = 'ALTER TABLE ' + table_name + ' ADD COLUMN ' + column.to_sql()\\n self.cursor.execute(sql)\",\n \"def addcolumn(self, column):\\n if column not in self.headersindex:\\n database = managers.database_manager.get_database(self.owner_id, self.database_id)\\n cur = database.get_connection().cursor()\\n cur.execute(\\\"ALTER TABLE \\\\'%s\\\\' ADD COLUMN %s\\\" % (self.name, column.to_declaration()))\",\n \"def __update_feature_table_columns(self):\\n self.__init_table()\\n\\n feature_dict_sorted_keys = feature_extractor_definition.keys()\\n feature_dict_sorted_keys.sort()\\n for key in feature_dict_sorted_keys:\\n if not self.__has_feature_column(key):\\n self.__add_feature_column(key, feature_extractor_definition[key])\",\n \"def add_new_cols(cat, prefix=\\\"\\\", floatcols=None, boolcols=None):\\n\\t\\n\\tif floatcols != None:\\n\\t\\tfor col in floatcols:\\n\\t\\t\\tcat.add_column(astropy.table.MaskedColumn(name=prefix+col, dtype=float, length=len(cat)))\\n\\t\\t\\tcat[prefix+col].mask = [True] * len(cat)\\n\\tif boolcols != None:\\n\\t\\tfor col in boolcols:\\n\\t\\t\\tcat.add_column(astropy.table.MaskedColumn(name=prefix+col, dtype=bool, length=len(cat)))\\n\\t\\t\\tcat[prefix+col].mask = [True] * len(cat)\",\n \"def _add_necessary_columns(args, custom_columns):\\n # we need to add the variant's chrom, start and gene if \\n # not already there.\\n if custom_columns.find(\\\"gene\\\") < 0:\\n custom_columns += \\\", gene\\\"\\n if custom_columns.find(\\\"start\\\") < 0:\\n custom_columns += \\\", start\\\"\\n \\n return custom_columns\",\n \"def save_column_mappings(request):\\n body = json.loads(request.body)\\n import_file = ImportFile.objects.get(pk=body.get('import_file_id'))\\n organization = import_file.import_record.super_organization\\n mappings = body.get('mappings', [])\\n for mapping in mappings:\\n dest_field, raw_field = mapping\\n if dest_field == '':\\n dest_field = None\\n\\n dest_cols = _column_fields_to_columns(dest_field, organization)\\n raw_cols = _column_fields_to_columns(raw_field, organization)\\n try:\\n column_mapping, created = ColumnMapping.objects.get_or_create(\\n super_organization=organization,\\n column_raw__in=raw_cols,\\n )\\n except ColumnMapping.MultipleObjectsReturned:\\n # handle the special edge-case where remove dupes doesn't get\\n # called by ``get_or_create``\\n ColumnMapping.objects.filter(\\n super_organization=organization,\\n column_raw__in=raw_cols,\\n ).delete()\\n column_mapping, created = ColumnMapping.objects.get_or_create(\\n super_organization=organization,\\n column_raw__in=raw_cols,\\n )\\n\\n # Clear out the column_raw and column mapped relationships.\\n column_mapping.column_raw.clear()\\n column_mapping.column_mapped.clear()\\n\\n # Add all that we got back from the interface back in the M2M rel.\\n [column_mapping.column_raw.add(raw_col) for raw_col in raw_cols]\\n if dest_cols is not None:\\n [\\n column_mapping.column_mapped.add(dest_col)\\n for dest_col in dest_cols\\n ]\\n\\n column_mapping.user = request.user\\n column_mapping.save()\\n\\n return {'status': 'success'}\",\n \"def columns(self, new_columns: ColumnT) -> None:\\n new_columns2: ndarray = init.check_column_validity(new_columns)\\n len_new: int = len(new_columns2)\\n len_old: int = len(self._columns)\\n if len_new != len_old:\\n raise ValueError(f'There are {len_old} columns in the DataFrame. '\\n f'You provided {len_new}.')\\n\\n new_column_info: ColInfoT = {}\\n for old_col, new_col in zip(self._columns, new_columns2):\\n new_column_info[new_col] = utils.Column(*self._column_info[old_col].values)\\n\\n self._column_info = new_column_info\\n self._columns = new_columns2\",\n \"def add_column(self, colspec):\\n if colspec.name == DEFAULT_COLUMN_NAME or colspec.name in self.columns.keys():\\n raise Exception(\\\"Column {} already exists.\\\".format(colspec.name))\\n\\n self.info.add_column(colspec.name, colspec.video, colspec.dtype)\",\n \"def test_add_column(self):\\n self.spy_on(DataGrid.add_column)\\n\\n DataGridColumnsHook(extension=self.extension,\\n datagrid_cls=DataGrid,\\n columns=[Column(id='sandbox')])\\n\\n self.assertTrue(DataGrid.add_column.called)\",\n \"def modify(self, fields=None, **fields_kwargs):\\n modified_fields = set()\\n fields = self.make_dict(fields, fields_kwargs)\\n fields = self._modify(fields)\\n for field_name, field_val in fields.items():\\n in_schema = field_name in self.schema.fields\\n if in_schema:\\n setattr(self, field_name, field_val)\\n modified_fields.add(field_name)\\n\\n return modified_fields\",\n \"def merge_attribute_schema(self, attr_schema):\\n name = attr_schema.name\\n if name not in self.schema:\\n self.schema[name] = attr_schema\\n else:\\n self.schema[name].merge_schema(attr_schema)\",\n \"def _addcolumns(self, columnname, columndata=\\\"\\\"):\\n self[columnname] = columndata\",\n \"def parse_migration_columns(\\n self, tablename: str, migration_columns: ColumnParametersSchema\\n ):\\n try:\\n update = self.check_table(tablename)\\n\\n for col in migration_columns:\\n self.source_column = col.sourceColumn\\n self.destination_column = col.destinationColumn\\n self.dest_options = col.destinationColumn.options.dict()\\n\\n self._parse_fk(tablename, self.dest_options.pop(\\\"foreign_key\\\"))\\n column_type = self._parse_column_type()\\n\\n col = Column(self.destination_column.name, column_type, **self.dest_options)\\n if update:\\n if not self.check_column(tablename, self.destination_column.name):\\n # self.add_alter_column(tablename, {\\\"column_name\\\": self.destination_column.name,\\\"type\\\":column_type,\\\"options\\\":{**self.dest_options}})\\n # else:\\n self.add_updated_table(tablename, col)\\n else:\\n self.add_created_table(tablename, col)\\n except Exception as err:\\n logger.error(\\\"parse_migration_columns [error] -> %s\\\" % err)\",\n \"def add_col2tab(con_db, cur_db, tab_name, col_name, col_type):\\n\\n # Iterate through all existing column names of the database table using\\n # the PRAGMA table_info command\\n for row in cur_db.execute(f'PRAGMA table_info({tab_name})'):\\n\\n # If the column exists: exit the function\\n if row[1] == col_name:\\n break\\n\\n # If the column is not existing yet, add the new column\\n else:\\n cur_db.execute(f'ALTER TABLE {tab_name} ' \\\\\\n f'ADD COLUMN {col_name} {col_type}')\\n con_db.commit()\",\n \"async def upgradeSchema(self) -> None:\",\n \"def AddColumn(self, column):\\n self.columns.append(column)\\n self.column_dict[column.column_id] = column\",\n \"def append_columns(cls, columns, grid=None, grid_url=None):\\n grid_id = parse_grid_id_args(grid, grid_url)\\n\\n grid_ops.ensure_uploaded(grid_id)\\n\\n # Verify unique column names\\n column_names = [c.name for c in columns]\\n if grid:\\n existing_column_names = [c.name for c in grid]\\n column_names.extend(existing_column_names)\\n duplicate_name = utils.get_first_duplicate(column_names)\\n if duplicate_name:\\n err = exceptions.NON_UNIQUE_COLUMN_MESSAGE.format(duplicate_name)\\n raise exceptions.InputError(err)\\n\\n # This is sorta gross, we need to double-encode this.\\n body = {\\\"cols\\\": _json.dumps(columns, cls=PlotlyJSONEncoder)}\\n fid = grid_id\\n response = v2.grids.col_create(fid, body)\\n parsed_content = response.json()\\n\\n cls._fill_in_response_column_ids(columns, parsed_content[\\\"cols\\\"], fid)\\n\\n if grid:\\n grid.extend(columns)\",\n \"def _format_meta_pre_merge(self):\\n self.__col_name_map = {\\n ColNameFormatter.fmt(c): c\\n for c in self.data.solar_meta.columns.values\\n }\\n\\n self._rename_cols(self.data.solar_meta, prefix=SOLAR_PREFIX)\\n self._rename_cols(self.data.wind_meta, prefix=WIND_PREFIX)\\n\\n self._save_rep_prof_index_internally()\",\n \"def rename_columns(columns, mapper, keep_original):\\n for name, rename in mapper.items():\\n if name in columns:\\n columns[rename] = org_copy.deepcopy(columns[name])\\n if 'parent' in columns[name]:\\n parents = columns[name]['parent']\\n else:\\n parents = {}\\n if not keep_original: del columns[name]\\n columns[rename]['name'] = rename\\n for parent_name, parent_spec in list(parents.items()):\\n new_parent_map = {}\\n if parent_name in mapper:\\n new_name = mapper[parent_name]\\n new_parent_map[new_name] = parent_spec\\n columns[rename]['parent'] = new_parent_map\\n if columns[rename].get('values'):\\n values = columns[rename]['values']\\n if isinstance(values, str):\\n if values in mapper:\\n columns[rename]['values'] = mapper[values]\",\n \"def _ensure_schema_has_covariates(self, x_underscore_columns):\\n previous_rename = self.covariate_rename\\n if set(x_underscore_columns) == set(previous_rename.values()):\\n return\\n # Only rewrite schema if the x_<integer> list has changed.\\n # because the schema depends on the number of covariates, not\\n # their names.\\n covariate_columns = list(x_underscore_columns)\\n # ASCII sorting isn't correct b/c x_11 is before x_2.\\n covariate_columns.sort(key=lambda x: int(x[2:]))\\n for create_name in [\\\"data\\\", \\\"avgint\\\"]:\\n empty = self.dismod_file.empty_table(create_name)\\n without = [c for c in empty.columns if not c.startswith(\\\"x_\\\")]\\n # The wrapper needs these columns to have a dtype of Real.\\n empty = empty[without].assign(**{cname: np.empty((0,), dtype=np.float) for cname in covariate_columns})\\n self.dismod_file.update_table_columns(create_name, empty)\\n if getattr(self.dismod_file, create_name).empty:\\n CODELOG.debug(f\\\"Writing empty {create_name} table with columns {covariate_columns}\\\")\\n setattr(self.dismod_file, create_name, empty)\\n else:\\n CODELOG.debug(f\\\"Adding to {create_name} table schema the columns {covariate_columns}\\\")\",\n \"def add_column(self, name, type):\\n raise NotImplementedError(\\n \\\"Please implement the 'add_column' method in a derived class.\\\")\",\n \"def merge(self, other: Schema) -> Schema:\\n if duplicates := self.keys() & other.keys():\\n raise IntegrityError(f'Duplicate column name(s): {duplicates}')\\n return self.__class__({**self, **other})\",\n \"def build_schema(self, dframe, overwrite=False, set_num_columns=True):\\n new_schema = self.schema.rebuild(dframe, overwrite)\\n self.set_schema(new_schema,\\n set_num_columns=(set_num_columns or overwrite))\",\n \"def upgrade_alter_table(self, db, tablename, colname, coltype):\\n try:\\n cursor = db.cursor()\\n cursor.execute(\\\"select %s from %s\\\" % (colname,tablename))\\n except Exception, e:\\n self.log.debug(\\\"upgrade_alter_table: %s\\\", e)\\n cursor = db.cursor()\\n alter = \\\"ALTER TABLE %s add column %s %s\\\" % (tablename, colname,\\n coltype)\\n cursor.execute(alter)\",\n \"def merge_schemas(self, old_schm, new_schm):\\n\\n old_schm_cols = [x['name'] for x in old_schm]\\n\\n for col in new_schm:\\n if type(col) == dict:\\n if col['name'] not in old_schm_cols:\\n old_schm.append(col)\\n \\n for count, old_col in enumerate(old_schm):\\n for meta in old_col:\\n if type(old_col[meta]) == list:\\n if old_col['name'] in [pot_new_col['name'] for pot_new_col in new_schm]:\\n new_col = [pot_new_col for pot_new_col in new_schm if pot_new_col['name'] == old_col['name']][0]\\n if meta in new_col:\\n old_schm[count][meta] = self.merge_schemas(old_col[meta], new_col[meta])\\n \\n return old_schm\",\n \"def _get_and_validate_schema_mapping(schema1, schema2, strict=False):\\n\\n len_schema1 = len(schema1)\\n len_schema2 = len(schema2)\\n\\n # If both non-empty, must be same length\\n if 0 < len_schema1 != len_schema2 > 0:\\n raise ValueError(\\\"Attempted to merge profiles with different \\\"\\n \\\"numbers of columns\\\")\\n\\n # In the case of __add__ with one of the schemas not initialized\\n if strict and (len_schema1 == 0 or len_schema2 == 0):\\n raise ValueError(\\\"Cannot merge empty profiles.\\\")\\n\\n # In the case of _update_from_chunk with uninitialized schema\\n if not strict and len_schema2 == 0:\\n return {col_ind: col_ind for col_ind_list in schema1.values()\\n for col_ind in col_ind_list}\\n\\n # Map indices in schema1 to indices in schema2\\n schema_mapping = dict()\\n\\n for key in schema1:\\n # Pandas columns are int by default, but need to fuzzy match strs\\n if isinstance(key, str):\\n key = key.lower()\\n if key not in schema2:\\n raise ValueError(\\\"Columns do not match, cannot update \\\"\\n \\\"or merge profiles.\\\")\\n\\n elif len(schema1[key]) != len(schema2[key]):\\n raise ValueError(f\\\"Different number of columns detected for \\\"\\n f\\\"'{key}', cannot update or merge profiles.\\\")\\n\\n is_duplicate_col = len(schema1[key]) > 1\\n for schema1_col_ind, schema2_col_ind in zip(schema1[key],\\n schema2[key]):\\n if is_duplicate_col and (schema1_col_ind != schema2_col_ind):\\n raise ValueError(f\\\"Different column indices under \\\"\\n f\\\"duplicate name '{key}', cannot update \\\"\\n f\\\"or merge unless schema is identical.\\\")\\n schema_mapping[schema1_col_ind] = schema2_col_ind\\n\\n return schema_mapping\",\n \"def ensure_internal_schema_updated(self):\\n if self._internal_schema_updated:\\n return\\n if internalmigrations.needs_upgrading(self):\\n assert not self._in_transaction\\n with self.lock():\\n internalmigrations.upgrade(self)\\n self.connection.commit()\\n self._internal_schema_updated = True\",\n \"def _refactor_time_columns(write_cursor: 'DBCursor') -> None:\\n log.debug('Enter _refactor_time_columns')\\n write_cursor.execute('ALTER TABLE timed_balances RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE timed_location_data RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE trades RENAME COLUMN time TO timestamp')\\n write_cursor.execute('ALTER TABLE asset_movements RENAME COLUMN time TO timestamp')\\n log.debug('Exit _refactor_time_columns')\",\n \"def test_new_columns(self):\\n rename = '{}*'\\n expected = (list(self.df.columns) +\\n list(rename.format(f) for f in self.formants))\\n actual = self.normalizer(rename=rename, **self.kwargs).normalize(\\n self.df).columns\\n\\n expected = sorted(expected)\\n actual = sorted(actual)\\n self.assertListEqual(actual, expected)\",\n \"def addcolumn(self, colname, coldata):\\n if len(coldata) != len(self):\\n raise ValueError,\\\"Column length must match catalog length\\\"\\n\\n #Most of the bookkeeping is the same as for an empty column\\n self.addemptycolumn(colname,coldata.dtype)\\n\\n #and then we reset the column to contain the actual data\\n setattr(self,colname,coldata)\",\n \"def insert_column(self, tb_name, column_name, data_type):\\n sentences = f\\\"\\\"\\\"\\n ALTER TABLE {tb_name} ADD COLUMN {column_name} {data_type};\\n \\\"\\\"\\\"\\n print(sentences)\\n self.commit(sentences)\",\n \"def get_column_definitions(self, schema, table, connection=None):\\n raise NotImplementedError\",\n \"def addColumn(self, name, column):\\n self.columnNames.append(name)\\n self.addColumnValues(column)\",\n \"def merge_schema(self, schema):\\n for _, attr_schema in schema.iter_attributes():\\n self.merge_attribute_schema(attr_schema)\",\n \"def update_column(self, xmldata):\\n columns = managers.request_manager.get_request().session().value(\\\"columns\\\")\\n headers = managers.request_manager.get_request().session().value(\\\"headers\\\")\\n if not columns:\\n return False\\n if xmldata:\\n # Parsing of column declaration\\n dom = parseString(xmldata.encode(\\\"UTF-8\\\"))\\n column = dom.getElementsByTagName(\\\"column\\\")[0]\\n name = un_quote(column.getAttribute(\\\"name\\\"))\\n if not name:\\n return False\\n declaration = name\\n constraints = {}\\n cid = column.getAttribute(\\\"id\\\")\\n type = column.getAttribute(\\\"type\\\")\\n if not type or type == \\\"INTEGER\\\" or type == \\\"REAL\\\" or type == \\\"TEXT\\\" or type == \\\"BLOB\\\":\\n constraints[\\\"type\\\"] = type\\n if column.getAttribute(\\\"notnull\\\") == \\\"true\\\":\\n constraints[\\\"not null\\\"] = True\\n if column.getAttribute(\\\"primary\\\") == \\\"true\\\":\\n if column.getAttribute(\\\"autoincrement\\\") == \\\"true\\\":\\n constraints[\\\"primary key\\\"] = \\\"autoincrement\\\"\\n else:\\n constraints[\\\"primary key\\\"] = True\\n if column.getAttribute(\\\"unique\\\") == \\\"true\\\":\\n constraints[\\\"unique\\\"] = True\\n\\n if column.getAttribute(\\\"default\\\") and column.getAttribute(\\\"default\\\") != \\\"\\\" and column.getAttribute(\\\"default\\\") != \\\"NULL\\\":\\n constraints[\\\"default\\\"] = column.getAttribute(\\\"default\\\")\\n\\n column_obj = VDOM_db_column(name, constraints)\\n column_obj.id = cid\\n\\n # praparing SQL code\\n old_column = None\\n for col in columns:\\n if columns[col].id == cid:\\n old_column = columns[col]\\n break\\n if not old_column:\\n return False\\n\\n newtable = \\\"%s_new(\\\" % self.name\\n oldtable = \\\"%s(\\\" % self.name\\n for col in headers:\\n if oldtable[-1] != \\\"(\\\":\\n oldtable += \\\", \\\"\\n oldtable += columns[col].to_declaration()\\n\\n if columns[col].id == cid:\\n if newtable[-1] != \\\"(\\\":\\n newtable += \\\", \\\"\\n newtable += column_obj.to_declaration()\\n\\n else:\\n if newtable[-1] != \\\"(\\\":\\n newtable += \\\", \\\"\\n newtable += columns[col].to_declaration()\\n newtable += \\\")\\\"\\n if newtable[-2] == \\\"(\\\":\\n return False\\n newcols = []\\n newcols.extend(headers)\\n newcols.remove(old_column.name)\\n newcols_decl = \\\"\\\"\\n for ctr in newcols:\\n newcols_decl += \\\", `%s`\\\" % ctr\\n\\n sql = \\\"\\\"\\\"BEGIN TRANSACTION;\\nCREATE TABLE %(newtable)s;\\nINSERT INTO `%(newtablename)s` (%(newcols)s) SELECT %(newcols)s FROM `%(oldtablename)s`;\\nDROP TABLE `%(oldtablename)s`;\\nALTER TABLE `%(newtablename)s` RENAME TO `%(oldtablename)s`;\\nEND TRANSACTION;\\\"\\\"\\\" % {\\\"newtable\\\": newtable, \\\"newtablename\\\": self.name + \\\"_new\\\", \\\"oldtablename\\\": self.name, \\\"newcols\\\": newcols_decl[2:]}\\n query = VDOM_sql_query(self.owner_id, self.database_id, sql, None, True)\\n query.commit()\\n columns.pop(old_column.name)\\n columns[column_obj.name] = column_obj\\n managers.request_manager.get_request().session().value(\\\"columns\\\", columns)\\n self.restore_structure()\\n return True\",\n \"def addStudyActualColumn(self, study_id, column_name, table_name):\\n try:\\n con = self.getMetadataDatabaseConnection()\\n con.cursor().callproc('qiime_assets.add_study_actual_column', [study_id, column_name, table_name])\\n except Exception, e: \\n raise Exception('Exception caught in addStudyActualColumns(): %s.\\\\nThe error is: %s' % (type(e), e))\",\n \"def add_column(self, col_name, definition):\\n if not self.column_exists(col_name):\\n self.execute(self.commands.add_column(self.name, col_name, definition))\",\n \"def addcolumn_from_xml(self, xmldata):\\n num_added = 0\\n if xmldata:\\n dom = parseString(xmldata.encode(\\\"UTF-8\\\"))\\n for column in dom.getElementsByTagName(\\\"column\\\"):\\n columns = managers.request_manager.get_request().session().value(\\\"columns\\\")\\n if not columns:\\n columns = self.parse_declaration()\\n name = un_quote(column.getAttribute(\\\"name\\\"))\\n if not name:\\n continue\\n if name in columns:\\n continue # column already exists\\n declaration = name\\n constraints = {}\\n cid = column.getAttribute(\\\"id\\\")\\n type = column.getAttribute(\\\"type\\\")\\n if not type or type == \\\"INTEGER\\\" or type == \\\"REAL\\\" or type == \\\"TEXT\\\" or type == \\\"BLOB\\\":\\n constraints[\\\"type\\\"] = type\\n if column.getAttribute(\\\"notnull\\\") == \\\"true\\\":\\n constraints[\\\"not null\\\"] = True\\n if column.getAttribute(\\\"primary\\\") == \\\"true\\\":\\n if column.getAttribute(\\\"autoincrement\\\") == \\\"true\\\":\\n constraints[\\\"primary key\\\"] = \\\"autoincrement\\\"\\n else:\\n constraints[\\\"primary key\\\"] = True\\n if column.getAttribute(\\\"unique\\\") == \\\"true\\\":\\n constraints[\\\"unique\\\"] = True\\n\\n if column.getAttribute(\\\"default\\\") and column.getAttribute(\\\"default\\\") != \\\"\\\" and column.getAttribute(\\\"default\\\") != \\\"NULL\\\":\\n constraints[\\\"default\\\"] = column.getAttribute(\\\"default\\\")\\n\\n column_obj = VDOM_db_column(name, constraints)\\n column_obj.id = cid\\n columns[name] = column_obj\\n self.addcolumn(column_obj)\\n managers.request_manager.get_request().session().value(\\\"columns\\\", columns)\\n num_added += 1\\n return num_added\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def AppendCols(self, numCols=1): # real signature unknown; restored from __doc__\\n return False\",\n \"def add_latclonc_to_db(self):\\n \\n # add new columns\\n try:\\n command =\\\"ALTER TABLE {tb} ADD COLUMN latc TEXT\\\".format(tb=self.table_name) \\n self.conn.cursor.execute(command)\\n except:\\n # pass if the column latc exists\\n pass\\n try:\\n command =\\\"ALTER TABLE {tb} ADD COLUMN lonc TEXT\\\".format(tb=self.table_name) \\n self.conn.cursor.execute(command)\\n except:\\n # pass if the column lonc exists\\n pass\\n\\n # iterate through tvals of the self.sites\\n sdtm = self.stm\\n for ii, st in enumerate(self.sites):\\n if ii == len(self.sites)-1:\\n edtm = self.etm\\n else:\\n edtm = st.tval\\n command = \\\"SELECT rowid, slist, vel, frang, rsep, datetime FROM {tb} WHERE (DATETIME(datetime)>'{sdtm}' and\\\\\\n DATETIME(datetime)<='{edtm}') ORDER BY datetime\\\".format(tb=self.table_name,\\\\\\n sdtm=str(sdtm), edtm=str(edtm))\\n self.conn.cursor.execute(command)\\n rows = self.conn.cursor.fetchall() \\n if rows != []:\\n rowid, slist, vel, frang_old, rsep_old, date_time_old = rows[0]\\n\\n # calculate latc_all and lonc_all in 'geo' coords\\n latc_all, lonc_all = calc_latc_lonc(self.sites[ii], self.bmnum, frang_old, rsep_old, \\n altitude=300., elevation=None, coord_alt=0.,\\n coords=\\\"geo\\\", date_time=None)\\n for row in rows:\\n rowid, slist, vel, frang, rsep, date_time = row\\n if (frang, rsep) != (frang_old, rsep_old):\\n latc_all, lonc_all = calc_latc_lonc(self.sites[ii], self.bmnum, frang, rsep, \\n altitude=300., elevation=None, coord_alt=0.,\\n coords=\\\"geo\\\", date_time=None)\\n\\n \\n frang_old, rsep_old = frang, rsep\\n\\n # convert from string to float\\n slist = [int(float(x)) for x in slist.split(\\\",\\\")]\\n vel = [float(x) for x in vel.split(\\\",\\\")]\\n\\n # exclude the slist values beyond maxgate and their correspinding velocities\\n vel = [vel[i] for i in range(len(vel)) if slist[i] < st.maxgate]\\n slist = [s for s in slist if s < st.maxgate]\\n\\n # extract latc and lonc values\\n latc = [latc_all[s] for s in slist]\\n lonc = [lonc_all[s] for s in slist]\\n\\n # convert to comma seperated text\\n slist = \\\",\\\".join([str(x) for x in slist])\\n vel = \\\",\\\".join([str(round(x,2)) for x in vel])\\n latc = \\\",\\\".join([str(round(x,2)) for x in latc])\\n lonc = \\\",\\\".join([str(round(x,2)) for x in lonc])\\n\\n # update the table\\n command = \\\"UPDATE {tb} SET slist='{slist}', vel='{vel}',\\\\\\n latc='{latc}', lonc='{lonc}' WHERE rowid=={rowid}\\\".\\\\\\n format(tb=self.table_name, slist=slist, vel=vel,\\\\\\n latc=latc, lonc=lonc, rowid=rowid)\\n self.conn.cursor.execute(command)\\n\\n # update sdtm\\n sdtm = edtm\\n\\n # commit the data into the db\\n self.conn._commit()\\n\\n # close db connection\\n self.conn._close_connection()\\n \\n return\",\n \"def _insert_into_new_columns(self, commit, mapping_index):\\n for i in range(self.num_new_columns):\\n if self.new_columns[i].commit == commit:\\n self.mapping[mapping_index] = i\\n return mapping_index + 2\\n\\n # This commit isn't already in new_columns. Add it.\\n column = Column(commit, self._find_commit_color(commit))\\n self.new_columns[self.num_new_columns] = column\\n self.mapping[mapping_index] = self.num_new_columns\\n self.num_new_columns += 1\\n return mapping_index + 2\",\n \"def setAllColumns(self, newAllColumns):\\n \\n pass\",\n \"def deferred_to_columns_cb(self, target, model, fields):\\n table = model._meta.db_table\\n if table not in target:\\n target[table] = set()\\n for field in fields:\\n if not hasattr(field.column, \\\"columns\\\"):\\n target[table].add(field.column)\\n else:\\n target[table].update(field.column.columns)\",\n \"def addTableColumn(self, tablename, columnname, columntype):\\n\\n # Check if the table exists\\n if tablename in self.getTableNames():\\n\\n # Check that the column does not already exist\\n if columnname not in self.getColumnNames(tablename):\\n\\n #Allow columnames with spaces\\n columnname = '`'+columnname+'`'\\n\\n \\\"\\\"\\\"# Fit characters to the allowed format if necessary\\n fmt = ''\\n if (self.connector == 'mysql' and\\n ('TEXT' in columntype or 'VARCHAR' in columntype) and\\n not ('CHARACTER SET' in columntype or\\n 'utf8mb4' in columntype)):\\n\\n # We enforze utf8mb4 for mysql\\n fmt = ' CHARACTER SET utf8mb4'\\n\\n\\n sqlcmd = ('ALTER TABLE ' + tablename + ' ADD COLUMN ' +\\n columnname + ' ' + columntype + fmt)\\\"\\\"\\\"\\n sqlcmd = ('ALTER TABLE ' + tablename + ' ADD COLUMN ' +\\n columnname + ' ' + columntype) \\n self._c.execute(sqlcmd)\\n\\n # Commit changes\\n self._conn.commit()\\n\\n else:\\n print((\\\"WARNING: Column {0} already exists in table {1}.\\\"\\n ).format(columnname, tablename))\\n\\n else:\\n print('Error adding column to table. Please, select a valid ' +\\n 'table name from the list')\\n print(self.getTableNames())\\n\\n return\",\n \"def _insert_column(self, column_name, column_type, table, params=None, overwrite=False, after_col=None, verbose=True):\\n \\n not_null = ''\\n auto_increment = ''\\n \\n if params != None and 'not_null' in params:\\n not_null = 'NOT NULL'\\n \\n \\n if params != None and 'auto_increment' in params:\\n auto_increment = \\\"AUTO_INCREMENT\\\"\\n \\n \\n ADD_COLUMN_COMMAND = \\\"ALTER TABLE {0} ADD {1} {2} {3} {4}\\\".format(table, column_name, column_type, not_null, auto_increment)\\n \\n if (after_col != None and type(after_col) is str):\\n ADD_COLUMN_COMMAND += \\\" AFTER {0} \\\".format(after_col)\\n \\n \\n self.cursor.execute(ADD_COLUMN_COMMAND)\\n \\n if verbose: \\n print(\\\"Adding the column '{0}' to the table '{1}'...\\\".format(column_name, table))\\n print(\\\"\\\\t\\\" + ADD_COLUMN_COMMAND) \\n \\n \\n if params != None and 'foreign_key' in params:\\n \\n if 'references' not in params:\\n raise InvalidParameterError\\n \\n referenced_table = params['references'].split('(')[0]\\n referenced_column = params['references'].split('(')[1][:-1] \\n \\n \\n if (not self.check_table(referenced_table, verbose=False)):\\n raise(TableNotFoundError)\\n \\n \\n if (not self.check_column(referenced_column, referenced_table, verbose=False)):\\n raise(ColumnNotFoundError)\\n \\n \\n ADD_FOREIGN_KEY_COMMAND = \\\"ALTER TABLE {0} ADD FOREIGN KEY ({1}) REFERENCES {2}({3})\\\".format(table, column_name, referenced_table, referenced_column)\\n \\n \\n if verbose: \\n print(\\\"\\\\t\\\" + ADD_FOREIGN_KEY_COMMAND) \\n \\n self.cursor.execute(ADD_FOREIGN_KEY_COMMAND)\",\n \"def addExtraColumnMetadata(self, study_id, table_level, column_name, description, data_type):\\n try:\\n con = self.getMetadataDatabaseConnection()\\n con.cursor().callproc('qiime_assets.extra_column_metadata_insert', [study_id, table_level, \\n column_name, description, data_type])\\n except Exception, e: \\n raise Exception('Exception caught in addExtraColumnMetadata(): {0}.\\\\nThe error is: {1}.\\\\nstudy_id: \\\\\\n {2}\\\\ntable_level: {3}\\\\ncolumn_name: {4}\\\\ndescription: {5}\\\\n data_type: {6}'.format(type(e), e, \\\\\\n str(study_id), str(table_level), str(column_name), str(description), str(data_type)))\",\n \"def test_dummydb_add_data_to_table_wrong_column_name(self):\\n db = DummyDB()\\n columns = {\\n \\\"one\\\": int,\\n \\\"two\\\": str,\\n \\\"three\\\": bool,\\n }\\n db.create_table(\\\"new_table\\\", columns)\\n result = db.select(\\\"new_table\\\", four=1)\",\n \"def generate_altered_fields(self):\\n result = super(MigrationAutodetector, self).generate_altered_fields()\\n self.generate_sql_changes()\\n return result\",\n \"def add_col(self):\\r\\n reader = csv.reader(open(self.in_csvfile, newline=''))\\r\\n rows = list(reader)\\r\\n rows[0].append(self.col_name)\\r\\n for i in range(1, len(rows)):\\r\\n rows[i].append(self.cell_filler(rows[i]))\\r\\n writer = csv.writer(open(self.out_csvfile, 'w', newline=''))\\r\\n writer.writerows(rows)\",\n \"def has_desired_schema(self):\\n if self._new_table == self._old_table:\\n if not self.rebuild:\\n log.info(\\\"Table already has the desired schema. \\\")\\n return True\\n else:\\n log.info(\\n \\\"Table already has the desired schema. However \\\"\\n \\\"--rebuild is specified, doing a rebuild instead\\\"\\n )\\n return False\\n return False\",\n \"def _add_cols(df: pandas.DataFrame, scope = (globals(), locals())) -> None:\\n command : str = input(\\\"\\\\nAdd a column:\\\\n\\\")\\n if command.lower() in ['n', 'no', 'quit()', 'exit', 'return']:\\n return\\n\\n col_name : str = command[ \\\\\\n re.search(r'[\\\\w\\\\.\\\\(\\\\)]+', command).start(): \\\\\\n re.search(r'[\\\\w\\\\.\\\\(\\\\)]+', command).end() \\\\\\n ]\\n # new column's name\\n\\n arg : str = command[re.search(r'[=,;]', command).end():]\\n # the new column's \\\"function\\\"\\n ref_cols = re.findall(r'(?<=\\\\{)\\\\w[\\\\w\\\\.\\\\(\\\\)]*(?=\\\\})', arg)\\n # df column names that are referenced to create new columns\\n\\n for i in range(len(ref_cols)):\\n arg = re.sub(\\n f'{{{ref_cols[i]}}}',\\n f'df[\\\\'{ref_cols[i]}\\\\']',\\n arg\\n )\\n # substituting references\\n\\n scope[0].update(globals())\\n scope[1].update(locals())\\n\\n col_arg = eval(arg, scope[0], scope[1])\\n # pandas.Series for type checking\\n df[col_name] = col_arg\\n # creating column\\n\\n more : str = input(\\\"\\\\nWould you like to add more columns?\\\\n\\\")\\n if more.lower() in ['y', 'yes', 'continue', 'true']:\\n return _add_cols(df)\\n return\",\n \"def merge_schema_entry(\\n self,\\n old_schema_entry,\\n new_schema_entry,\\n base_path=None,\\n ):\\n if not old_schema_entry:\\n return new_schema_entry\\n\\n # If the new schema is None, return immediately.\\n if not new_schema_entry:\\n return new_schema_entry\\n\\n # If a field value is missing, permanently set 'filled' to False.\\n if not new_schema_entry['filled'] or not old_schema_entry['filled']:\\n old_schema_entry['filled'] = False\\n new_schema_entry['filled'] = False\\n\\n old_status = old_schema_entry['status']\\n new_status = new_schema_entry['status']\\n\\n # new 'soft' does not clobber old 'hard'\\n if old_status == 'hard' and new_status == 'soft':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n old_schema_entry['info']['mode'] = mode\\n return old_schema_entry\\n\\n # new 'hard' clobbers old 'soft'\\n if old_status == 'soft' and new_status == 'hard':\\n mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if mode is None:\\n return None\\n new_schema_entry['info']['mode'] = mode\\n return new_schema_entry\\n\\n # Verify that it's soft->soft or hard->hard\\n if old_status != new_status:\\n raise Exception(\\n f'Unexpected schema_entry type, this should never happen: '\\n f'old ({old_status}); new ({new_status})'\\n )\\n\\n old_info = old_schema_entry['info']\\n old_name = old_info['name']\\n old_type = old_info['type']\\n old_mode = old_info['mode']\\n new_info = new_schema_entry['info']\\n new_name = new_info['name']\\n new_type = new_info['type']\\n new_mode = new_info['mode']\\n\\n full_old_name = json_full_path(base_path, old_name)\\n full_new_name = json_full_path(base_path, new_name)\\n\\n # Defensive check, names should always be the same.\\n if old_name != new_name:\\n if old_name.lower() != new_name.lower():\\n raise Exception(\\n 'Unexpected difference in name, should never happen:'\\n f' old_name ({full_old_name}) != new_name ({full_new_name})'\\n )\\n else:\\n # preserve old name if case is different\\n new_info['name'] = old_info['name']\\n\\n # Recursively merge in the subfields of a RECORD, allowing\\n # NULLABLE to become REPEATED (because 'bq load' allows it).\\n if old_type == 'RECORD' and new_type == 'RECORD':\\n # Allow NULLABLE RECORD to be upgraded to REPEATED RECORD because\\n # 'bq load' allows it.\\n if old_mode == 'NULLABLE' and new_mode == 'REPEATED':\\n old_info['mode'] = 'REPEATED'\\n self.log_error(\\n f'Converting schema for \\\"{full_old_name}\\\" from '\\n 'NULLABLE RECORD into REPEATED RECORD'\\n )\\n elif old_mode == 'REPEATED' and new_mode == 'NULLABLE':\\n # TODO: Maybe remove this warning output. It was helpful during\\n # development, but maybe it's just natural.\\n self.log_error(\\n f'Leaving schema for \\\"{full_old_name}\\\" as REPEATED RECORD'\\n )\\n\\n # RECORD type needs a recursive merging of sub-fields. We merge into\\n # the 'old_schema_entry' which assumes that the 'old_schema_entry'\\n # can be modified in situ.\\n old_fields = old_info['fields']\\n new_fields = new_info['fields']\\n for key, new_entry in new_fields.items():\\n old_entry = old_fields.get(key)\\n new_base_path = json_full_path(base_path, old_name)\\n old_fields[key] = self.merge_schema_entry(\\n old_schema_entry=old_entry,\\n new_schema_entry=new_entry,\\n base_path=new_base_path,\\n )\\n return old_schema_entry\\n\\n new_mode = self.merge_mode(old_schema_entry,\\n new_schema_entry,\\n base_path)\\n if new_mode is None:\\n return None\\n new_schema_entry['info']['mode'] = new_mode\\n\\n # For all other types...\\n if old_type != new_type:\\n # Check that the converted types are compatible.\\n candidate_type = convert_type(old_type, new_type)\\n if not candidate_type:\\n self.log_error(\\n f'Ignoring field with mismatched type: '\\n f'old=({old_status},{full_old_name},{old_mode},{old_type});'\\n f' new=({new_status},{full_new_name},{new_mode},{new_type})'\\n )\\n return None\\n\\n new_info['type'] = candidate_type\\n return new_schema_entry\",\n \"def build_column_mapping(raw_columns, dest_columns, previous_mapping=None, map_args=None,\\n default_mappings=None, thresh=0):\\n\\n return MappingColumns(raw_columns, dest_columns, previous_mapping=previous_mapping,\\n map_args=map_args, default_mappings=default_mappings,\\n threshold=thresh).final_mappings\",\n \"def _modify_fields(usecols, dtype, badcols):\\n for col in badcols:\\n usecols = [badcols[col] if uc == col else uc for uc in usecols]\\n try:\\n dtype[badcols[col]] = dtype.pop(col)\\n except KeyError:\\n pass\\n return usecols, dtype\",\n \"def add_schema(self, schema, db):\\n self._dbs[schema.typename] = db\\n return None\",\n \"def addColumnsToFile(filename, columns, add_before_original=True):\\n\\ttempFile = \\\"TEMP.tmp\\\"\\n\\toutFile = open(tempFile, \\\"w\\\")\\n\\tinFile = open(filename, \\\"r\\\")\\n\\tcolumns = listR.toList(columns)\\n\\tindex = 0\\n\\taLine = inFile.readline()\\n\\twhile aLine:\\n\\t\\tif add_before_original:\\n\\t\\t\\toutFile.write(columns[index] + aLine)\\n\\t\\telse:\\n\\t\\t\\toutFile.write(aLine + columns[index])\\n\\t\\tindex = listR.next(columns, index)\\n\\t\\taLine = inFile.readline()\\n\\tinFile.close\\n\\toutFile.close()\\n\\tcopy(tempFile, filename)\",\n \"def rename_column(self, table_name, old, new):\\r\\n self._remake_table(table_name, renames={old: new})\",\n \"def _prepare_schema(self):\\n schema = DaskSchema(self.schema_name)\\n\\n if not self.tables:\\n logger.warning(\\\"No tables are registered.\\\")\\n\\n for name, dc in self.tables.items():\\n table = DaskTable(name)\\n df = dc.df\\n logger.debug(\\n f\\\"Adding table '{name}' to schema with columns: {list(df.columns)}\\\"\\n )\\n for column in df.columns:\\n data_type = df[column].dtype\\n sql_data_type = python_to_sql_type(data_type)\\n\\n table.addColumn(column, sql_data_type)\\n\\n schema.addTable(table)\\n\\n if not self.functions:\\n logger.debug(\\\"No custom functions defined.\\\")\\n\\n for function_description in self.function_list:\\n name = function_description.name\\n sql_return_type = python_to_sql_type(function_description.return_type)\\n if function_description.aggregation:\\n logger.debug(f\\\"Adding function '{name}' to schema as aggregation.\\\")\\n dask_function = DaskAggregateFunction(name, sql_return_type)\\n else:\\n logger.debug(f\\\"Adding function '{name}' to schema as scalar function.\\\")\\n dask_function = DaskScalarFunction(name, sql_return_type)\\n\\n dask_function = self._add_parameters_from_description(\\n function_description, dask_function\\n )\\n\\n schema.addFunction(dask_function)\\n\\n return schema\",\n \"def apply_patch():\\n assert BaseDatabaseSchemaEditor is not None\\n\\n def _create_unique_sql(self, *args, **kwargs):\\n from django.db.backends.ddl_references import IndexName\\n\\n statement = orig_create_unique_sql(self, *args, **kwargs)\\n\\n if statement is not None:\\n index_name = statement.parts['name']\\n\\n if (isinstance(index_name, IndexName) and\\n index_name.create_index_name == self._create_index_name):\\n # The result will be unquoted. Let's quote it.\\n index_name.create_index_name = lambda *args, **kwargs: \\\\\\n self.quote_name(self._create_index_name(*args, **kwargs))\\n\\n return statement\\n\\n orig_create_unique_sql = BaseDatabaseSchemaEditor._create_unique_sql\\n BaseDatabaseSchemaEditor._create_unique_sql = _create_unique_sql\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6689222","0.6531303","0.60537446","0.6039341","0.60350144","0.5883875","0.5845651","0.5813085","0.5690668","0.5641946","0.56057465","0.54915494","0.54909086","0.5434344","0.542425","0.5340224","0.53072643","0.5284575","0.52605635","0.5229555","0.52235705","0.5215396","0.51270014","0.5114374","0.5099848","0.5091163","0.50850743","0.5079301","0.5066776","0.5061453","0.5058868","0.50537986","0.50251365","0.50063413","0.5003117","0.49837986","0.49823472","0.4980061","0.49774334","0.49630207","0.49608415","0.49564832","0.49248683","0.49137408","0.49054983","0.4888428","0.48686206","0.48596603","0.48417622","0.48306552","0.48175353","0.47841254","0.47764885","0.47700122","0.47664386","0.47572923","0.47393766","0.47371304","0.4725905","0.4722962","0.47181255","0.47132292","0.4712522","0.47057188","0.47056517","0.46860245","0.46845675","0.46844116","0.46684757","0.46683952","0.46643776","0.46638516","0.46638516","0.46638516","0.46638516","0.46638516","0.46638516","0.46638516","0.46638516","0.46638516","0.4663825","0.4663445","0.46563223","0.4647813","0.46442434","0.4643868","0.46406853","0.46243957","0.46223035","0.4617757","0.46147448","0.46147442","0.46130097","0.45996097","0.45981187","0.45927855","0.45847002","0.4576712","0.4568765","0.45627815"],"string":"[\n \"0.6689222\",\n \"0.6531303\",\n \"0.60537446\",\n \"0.6039341\",\n \"0.60350144\",\n \"0.5883875\",\n \"0.5845651\",\n \"0.5813085\",\n \"0.5690668\",\n \"0.5641946\",\n \"0.56057465\",\n \"0.54915494\",\n \"0.54909086\",\n \"0.5434344\",\n \"0.542425\",\n \"0.5340224\",\n \"0.53072643\",\n \"0.5284575\",\n \"0.52605635\",\n \"0.5229555\",\n \"0.52235705\",\n \"0.5215396\",\n \"0.51270014\",\n \"0.5114374\",\n \"0.5099848\",\n \"0.5091163\",\n \"0.50850743\",\n \"0.5079301\",\n \"0.5066776\",\n \"0.5061453\",\n \"0.5058868\",\n \"0.50537986\",\n \"0.50251365\",\n \"0.50063413\",\n \"0.5003117\",\n \"0.49837986\",\n \"0.49823472\",\n \"0.4980061\",\n \"0.49774334\",\n \"0.49630207\",\n \"0.49608415\",\n \"0.49564832\",\n \"0.49248683\",\n \"0.49137408\",\n \"0.49054983\",\n \"0.4888428\",\n \"0.48686206\",\n \"0.48596603\",\n \"0.48417622\",\n \"0.48306552\",\n \"0.48175353\",\n \"0.47841254\",\n \"0.47764885\",\n \"0.47700122\",\n \"0.47664386\",\n \"0.47572923\",\n \"0.47393766\",\n \"0.47371304\",\n \"0.4725905\",\n \"0.4722962\",\n \"0.47181255\",\n \"0.47132292\",\n \"0.4712522\",\n \"0.47057188\",\n \"0.47056517\",\n \"0.46860245\",\n \"0.46845675\",\n \"0.46844116\",\n \"0.46684757\",\n \"0.46683952\",\n \"0.46643776\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.46638516\",\n \"0.4663825\",\n \"0.4663445\",\n \"0.46563223\",\n \"0.4647813\",\n \"0.46442434\",\n \"0.4643868\",\n \"0.46406853\",\n \"0.46243957\",\n \"0.46223035\",\n \"0.4617757\",\n \"0.46147448\",\n \"0.46147442\",\n \"0.46130097\",\n \"0.45996097\",\n \"0.45981187\",\n \"0.45927855\",\n \"0.45847002\",\n \"0.4576712\",\n \"0.4568765\",\n \"0.45627815\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.82155335"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2292,"cells":{"query":{"kind":"string","value":"Validate a resource of the given type with specified ID already exists."},"document":{"kind":"string","value":"def _DatasetExists(dataset_id, project_id):\n client = GetApiClient()\n service = client.datasets\n get_request_type = GetApiMessage('BigqueryDatasetsGetRequest')\n get_request = get_request_type(datasetId=dataset_id, projectId=project_id)\n try:\n service.Get(get_request)\n return True\n except apitools_exceptions.HttpNotFoundError:\n log.info('Dataset with id [{}:{}] not found.'.format(\n project_id, dataset_id))\n\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_id_already_exists(self) -> None:\n with pytest.raises(IntegrityError):\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\n 'description': 'A new filter type.'})","def check_id(self, id):","def testValidateId(self):\n #create a different person and try to use their id\n self.directory.invokeFactory(type_name=\"FSDPerson\",id=\"def456\",firstName=\"Joe\",lastName=\"Blow\")\n self.failUnless('def456' in self.person.validate_id('def456'))\n #create a different content object and try to use its id\n self.directory.invokeFactory(\"Document\", \"mydoc\")\n self.failUnless('mydoc' in self.person.validate_id('mydoc'))","def check_repost_exists(type, id):\n \n try:\n soundcloud.get('/e1/me/{}_reposts/{}'.format(type, id))\n return True\n except HTTPError as e:\n if e.response.status_code == 404:\n db.mark_as_deleted(type, id)\n return False\n else:\n raise","def test_resource_id(self):\n resource_id = '1234-1234-1234'\n\n # resource id does not exist\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 404)\n\n # create a resource ID\n resp = self.app.post(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 201)\n\n # resource id exists\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # cannot create twice\n resp = self.app.post(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 409)\n\n # delete resource id\n resp = self.app.delete(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # resource id does not exist\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 404)","def ResourceExists(self, name):\n pass","def assert_has(self, type_id, message=''):\n if self.first_by_id(type_id):\n return\n raise AssertionError(message)","def does_resource_exist(resource):\n try:\n resource.load()\n return True\n except botocore.exceptions.ClientError as e:\n if e.response['Error']['Code'] == 'ValidationError':\n return False\n else:\n raise e","def check_action_type_exists(\n action_type_id: int\n) -> None:\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\n raise errors.ActionTypeDoesNotExistError()","def check_id_existence(self, id:str):\n\n oc_prefix = id[:(id.index(':')+1)]\n\n if oc_prefix == 'doi:':\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\n if oc_prefix == 'isbn:':\n vldt = isbn.ISBNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'issn:':\n vldt = issn.ISSNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'orcid:':\n vldt = orcid.ORCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmcid:':\n vldt = pmcid.PMCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmid:':\n vldt = pmid.PMIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'ror:':\n vldt = ror.RORManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'url:':\n vldt = url.URLManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'viaf:':\n vldt = viaf.ViafManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikidata:':\n vldt = wikidata.WikidataManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikipedia:':\n vldt = wikipedia.WikipediaManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))","def test_create_id_type(self):\n self.assertIsInstance(Rectangle.create().id, int)","def test_duplicate_flavorids_fail(self):\n flavorid = 'flavor1'\n instance_types.create('name one', 256, 1, 120, 200, flavorid)\n self.assertRaises(exception.InstanceTypeIdExists,\n instance_types.create,\n 'name two', 256, 1, 120, 200, flavorid)","def test_difference_id(self):\n self.assertFalse(\n self.factory.create_type('iphone') is self.factory.create_type(\n 'iphone'))","def validate_id(cls, id: str) -> ObjectId:\n return ObjectId(id)","def test_id_missing(self) -> None:\n with pytest.raises(NotFound):\n ObservationType.from_id(-1)","def check_unique_element_id(cls, instance, element_id):\n if not element_id:\n return\n try:\n element_ids = instance.placeholder.page.cascadepage.glossary['element_ids'][instance.language]\n except (AttributeError, KeyError, ObjectDoesNotExist):\n return\n else:\n for key, value in element_ids.items():\n if str(key) != str(instance.pk) and element_id == value:\n msg = _(\"The element ID '{}' is not unique for this page.\")\n raise ValidationError(msg.format(element_id))","def test_duplicate_id(self):\n with self.assertRaises(ValueError):\n REANATemplate(\n workflow_spec={},\n parameters=[\n pd.parameter_declaration('A', index=1),\n pd.parameter_declaration('B'),\n pd.parameter_declaration('C'),\n pd.parameter_declaration('A', index=2),\n pd.parameter_declaration('E', index=1)\n ],\n validate=True\n )","def test_create_resource(self):\n test_resource = ResourceTypeName.get() # the name of the resource type to create\n\n # the resource type should not exist yet\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 404)\n\n # create the resource type\n resp = self.app.post(f'/v1/resource/{test_resource}', data=json.dumps({'actions': ['tr:action1']}),\n headers=admin_headers)\n self.assertEqual(resp.status_code, 201)\n\n # the resource type exists\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # delete the resource type\n resp = self.app.delete(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # the resource type should not exist\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 404)","def _validate_create(context, db_api, create_data, model_name):\n ipaddrlist = utils.get_addresses(create_data['ip_address'])\n\n if not ipaddrlist:\n errors = (_(\"Failed to register (%s)\" +\n \". The (%s) IP Address (%s) could not \"\n \"be resolved.\")\n % (model_name, model_name, create_data['ip_address']))\n raise exception.AddressResolutionFailure(reason=errors)\n LOG.info(\"IP/FQDN for the \" + model_name + \" %s is %s\" % (\n create_data['ip_address'],\n ipaddrlist))\n try:\n get_all = getattr(db_api, \"get_all_%ss\" % model_name)\n res_data = get_all(context)\n if not res_data:\n # No registered resources\n LOG.info(\"No registered %s\" % model_name)\n return\n except Exception:\n errors = (_(\"Failed to retrieve data for (%s) %s\")\n % (model_name, create_data.get('ip_address')))\n raise exception.InternalFailure(reason=errors)\n name = create_data.get(\"name\")\n valid_name = _validate_duplicate_names(res_data, name)\n if not valid_name:\n msg = (_(\"Two different (%s) with same \"\n \"name cannot be registered\") % model_name)\n raise exception.ResourceExists(reason=msg)\n registered_data = []\n for data in res_data:\n registered_data.append(data['ip_address'])\n\n if set(ipaddrlist).intersection(set(registered_data)):\n errors = (_(\"(%s) by ip_address (%s) already exists.\")\n % (model_name, create_data['ip_address']))\n raise exception.ResourceExists(reason=errors)","def test_will_not_get_instance_type_with_bad_id(self):\n self.assertRaises(exception.InstanceTypeNotFound,\n instance_types.get_instance_type, 'asdf')","def test_check_resource(self):\n s1 = System()\n b1 = Books(\"1984\", \"George Orwell\", \"Harvill Secker\", \"1949\", \"0123456789123\")\n self.assertEqual(s1.check_resource(b1), False)\n s1.add_resource(b1)\n self.assertEqual(s1.check_resource(b1), True)","def resourceExists(node, name = None, resourceType = PROP_RESOURCE_TYPE_RESOURCE):\n \n exists = False\n if not node:\n return exists\n try:\n myResourceType = \"\"\n if name:\n # make sure it's unicode:\n if not isinstance(name, str):\n name = name.decode(sys.getfilesystemencoding())\n url = node.url\n if url.endswith(\"/\"):\n url = url + name\n else:\n url = url + \"/\" + name\n newNode = ResourceStorer(url, node.connection)\n element = newNode.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\n else: # name is \"None\":\n element = node.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\n \n if len(element.children) > 0:\n myResourceType = element.children[0].name\n if resourceType == myResourceType or resourceType == PROP_RESOURCE_TYPE_RESOURCE:\n exists = True\n else:\n exists = False\n except WebdavError as wderr:\n if wderr.code == CODE_NOT_FOUND:\n # node doesn't exist -> exists = False:\n exists = False\n else:\n # another exception occured -> \"re-raise\" it:\n raise\n return exists","def is_resource_id(schema_obj):\n\n if isinstance(schema_obj, schema.Field):\n return is_resource_id(schema_obj.metadata)\n elif isinstance(schema_obj, schema.Struct):\n return schema_obj.full_name == 'weave.common.ResourceId'\n return False","def is_existing_object(did):\n if not d1_gmn.app.did.is_existing_object(did):\n raise d1_common.types.exceptions.NotFound(\n 0,\n \"Identifier is {}. Expected a Persistent ID (PID) for an existing \"\n 'object. id=\"{}\"'.format(d1_gmn.app.did.classify_identifier(did), did),\n identifier=did,\n )","def test_will_not_get_instance_type_by_unknown_id(self):\n self.assertRaises(exception.InstanceTypeNotFound,\n instance_types.get_instance_type, 10000)","def validate_id(ctx, param, value):\r\n try:\r\n if value is None:\r\n return None\r\n obj = optiga.Object(int(value, base=16))\r\n obj = obj.meta\r\n return int(value, base=16)\r\n except (ValueError, TypeError, OSError) as no_object:\r\n raise click.BadParameter(\"Object ID doesn't exist. Please align with the Objects map\") from no_object","def taco_test_put_error_requires_id(self):\n body = '{ \"id\": 400, \"name\": \"item_new\", \"content\": \"after test update\" }'\n env = self.get_env('PUT', '/item', body=body)\n webapi_start(env, lambda status, response_headers: self.assertEqual(status, '501'))","def _create_resource(resource, **options):\n global _existing\n\n if _existing[resource]:\n print('{r} {k}:{v} already exists with id {i}.'.format(\n r=resource,\n k=args.tag,\n v=args.role,\n i=_existing[resource].id\n ))\n return True\n\n print('{v} a {r} with parameters: {p}...'.format(\n v='Would create' if dry else 'Creating',\n r=resource,\n p=str(options)\n ))\n\n if dry:\n return True\n\n # All easy cases out of the way, we now need to actually create something.\n r = None\n try:\n r = getattr(ec2, definitions[resource].create)(** options)\n # In some cases (instance) a list is returned instead of one item. Quack!\n try:\n r = r[0]\n except:\n pass\n _tag_resource(r)\n print('... {r} id {i} created.'.format(\n r=resource,\n i=r.id\n ))\n _existing[resource] = r\n return True\n except Exception as e:\n if r is None:\n print('Could not create resource {r}.'.format(\n r=resource\n ))\n traceback.print_exc()\n else:\n print('Could not tag resource {r}, id {i}.'.format(\n r=resource,\n i=r.id\n ))\n traceback.print_exc()\n _destroy_resource(resource)\n return False","def validate_identifier(self, identifier):\n pass","def needs_unique_instance(type_):\n return type_ in unique_instance_types","def _validate_call_id(self, call_id):\n\n self._validate_required_data(call_id, self.CALL_ID)\n\n query = CallRecord.objects.filter(call_id=call_id)\n\n if query.exists():\n raise NotAcceptable(\n detail='Call id is already in use. Please, choose another')","def identify_id(id: str) -> bool:\n return validate_handle(id)","def test_create_id_identity(self):\n self.assertIs(Rectangle.create(id=True).id, True)\n self.assertIs(Rectangle.create(id=type).id, type)\n self.assertIs(Rectangle.create(id=None).id, None)","def validate_user_id(self, value):\n if not User.objects.filter(id=value).exists():\n raise serializers.ValidationError('User with this id does not exist.')\n return value","def validate(self):\n # Validate all mandatory keys are present\n if not self.mandatory_keys.issubset(set(self.resource)):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] miss a \"\n \"mandatory key. Please check the model.\" % (\n self.__class__.MODEL_TYPE,\n self.id))\n\n # Validate the resource does not contains extra keys\n if not set(self.resource).issubset(self.keys):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] contains \"\n \"extra keys. Please check the model.\" % (\n self.__class__.MODEL_TYPE,\n self.id))\n\n # Validate the resource value type\n for key, value in self.resource.items():\n if not isinstance(value, self.__class__.MODEL[key][0]):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data type (expected: %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][0]))\n # For str type validate the content as according the regex\n if self.__class__.MODEL[key][0] is str:\n if not re.match(self.__class__.MODEL[key][1], value):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data content (expected match : %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][1]))\n # For list type validate the content as according the regex\n if self.__class__.MODEL[key][0] is list:\n if not all([re.match(self.__class__.MODEL[key][1], v)\n for v in value]):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data content (expected match : %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][1]))","def test_check_input_id(self):\n r3 = Rectangle(10, 2, 0, 0, 12)\n self.assertEqual(r3.id, 12)","def resource(\n name: str,\n *,\n mime_type: str,\n parent_folder_id: drive_api.ResourceID,\n drive_service: Optional[discovery.Resource] = None,\n) -> drive_api.ResourceID:\n command = request(\n name,\n mime_type=mime_type,\n parent_folder_id=parent_folder_id,\n drive_service=drive_service,\n )\n result = command.execute()\n new_id: drive_api.ResourceID = result.get(\"id\")\n return new_id","def test_bad_id(self):\n r1 = Square(10, 2)\n self.assertEqual(r1.id, 1)\n\n r2 = Square(2, 10)\n self.assertEqual(r2.id, 2)","def validatePredefinedType(self, type: int) -> bool:\n ...","def validate_resources(self, folder, resources):\r\n self.validate_files_exist(folder, resources)\r\n self.validate_no_duplicate_paths(resources)","def __validateResourceStateEntry(self, resource: Dict[str, str]):\n if AZ_RESOURCE_ID not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (\n self.fullName, AZ_RESOURCE_ID))\n if SID not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (self.fullName, SID))\n if ARM_TYPE not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (self.fullName, ARM_TYPE))","def validate_id(self, value):\n try:\n Tutor.objects.get(pk=value)\n except Tutor.DoesNotExist:\n raise serializers.ValidationError('Tutor object with id \\'{}\\' does not exist.'.format(value))\n return value","def test_readable_id_invalid(readable_id_value):\n program = ProgramFactory.build(readable_id=readable_id_value)\n with pytest.raises(ValidationError):\n program.save()\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\n with pytest.raises(ValidationError):\n course.save()","def test_api_update_book_with_id_does_not_exist(self):\n\n\t\tlogin_data = self.login_test_user()\n\t\ttoken = login_data['auth_token']\n\n\t\tbook = self.client.put(\n\t\t\tf'{URL_BOOKS}/1',\n\t\t\theaders=dict(Authorization=f'Bearer {token}'),\n\t\t\tcontent_type='application/json',\n\t\t\tdata=json.dumps(\n\t\t\t\tdict(\n\t\t\t\t\ttitle='updated book'\n\t\t\t\t)\n\t\t\t)\n\t\t)\n\n\t\tbook_res = json.loads(book.data.decode())\n\t\tself.assertTrue(book_res['message'] == 'book with id 1 does not exist')\n\t\tself.assertTrue(book_res['status'] == 'error')","def test_check_id(self):\n r1 = Rectangle(2, 10)\n r2 = Rectangle(2, 10)\n r3 = Rectangle(2, 10)\n self.assertGreater(r2.id, r1.id)\n self.assertGreater(r3.id, r2.id)","def create_resource(self, resource, resource_data, resource_type, **kwargs):\n if not isinstance(resource, Resource):\n raise KeyError(\"'resource' should be an instance of Resource\")\n if not isinstance(resource_data, ResourceData) or not resource_data.value:\n raise KeyError(\n \"'resource_data' should be ResourceData with 'value' attribute\")\n if not isinstance(resource_type, ResourceType):\n raise KeyError(\"'resource_type' should be an instance of ResourceType\")\n if not kwargs or 'feed_id' not in kwargs:\n raise KeyError('Variable \"feed_id\" id mandatory field!')\n\n resource_id = urlquote(resource.id, safe='')\n r = self._post('entity/f;{}/resource'.format(kwargs['feed_id']),\n data={\"name\": resource.name, \"id\": resource.id,\n \"resourceTypePath\": \"rt;{}\"\n .format(resource_type.path.resource_type_id)})\n if r:\n r = self._post('entity/f;{}/r;{}/data'\n .format(kwargs['feed_id'], resource_id),\n data={'role': 'configuration', \"value\": resource_data.value})\n else:\n # if resource or it's data was not created correctly, delete resource\n self._delete('entity/f;{}/r;{}'.format(kwargs['feed_id'], resource_id))\n return r","def checkValidId(self, id, prep_id = False):\n new_id = unquote(id)\n if prep_id: new_id = self.prepId(id)\n try:\n globalCheckValidId(self, new_id)\n return True\n except Exception:\n return str(sys.exc_info()[1])","def resource_exists(self, resource):\n products = Product.select(self.env, where={'name' : resource.id})\n return bool(products)","def test_cannot_add_existing_asset_code(self):\n self.assertEqual(self.all_assets.count(), 1)\n asset_code = \"IC002\"\n new_asset = Asset(asset_code, \"SN001\")\n with self.assertRaises(ValidationError):\n new_asset.save()\n self.assertEqual(self.all_assets.count(), 1)","def send_error_missing_id(message, obj_type):\n return make_response(jsonify({\"validation_error\": {\n \"error\": 'Missing id',\n \"object_type\": obj_type,\n \"description\": message\n }}), 400)","def test_init_id_identity(self):\n self.assertIs(Rectangle(1, 1, id=True).id, True)\n self.assertIs(Rectangle(1, 1, id=type).id, type)","def id_exists(host_id: int,\n database_connection: mysql.connector.connect) -> bool:\n return validate_id(host_id, database_connection)","def _validate_duplicate_names(res_data, name, _id=None):\n if _id:\n for data in res_data:\n if data.get(\"name\") == name and data.get(\"id\") != _id:\n return False\n return True\n else:\n for data in res_data:\n if data.get(\"name\") == name:\n return False\n return True","def validate(self):\n try:\n # update _resource to have default values from the schema\n self._resource = self.schema(self._resource)\n except MultipleInvalid as e:\n errors = [format_error(err, self.resource_type) for err in e.errors]\n raise exceptions.ValidationError({'errors': errors})\n\n yield self.check_unique()","def _uniqueness_check(self, cls, unique_in = None, **attr):\n # under the same datasource, only 1 subsystem, 1 neuropil, 1 tract of the name can exist\n # under the same neuropil, only 1 neuron of the name can exist\n # multiple (collections of) synapses can exist between two neurons\n if cls == 'Species':\n tmp = self.sql_query(\n \"\"\"select from Species where (name = \"{name}\" or \"{name}\" in synonyms) and stage = \"{stage}\" and sex = \"{sex}\" \"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex']))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"Species {name} at {stage} stage ({sex}) already exists with rid = {rid}\"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = objs[0]._id))\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"Species {name} (as its synonym) at {stage} stage ({sex}) already exists with rid = {rid}, use name {formalname} instead\"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = obj._id, formalname = obj.name))\n elif cls == 'DataSource':\n objs = self.find_objs('DataSource', name=attr['name'], version=attr['version'])\n #if self.exists(cls, name = attr['name'], version = attr['version']):\n if len(objs):\n raise NodeAlreadyExistError(\"\"\"{} Node with attributes {} already exists with rid = {}\"\"\".format(\n cls, ', '.join([\"\"\"{} = {}\"\"\".format(key, value) \\\n for key, value in attr.items()]), objs[0]._id))\n elif cls == 'Neurotransmitter':\n tmp = self.sql_query(\n \"\"\"select from Neurotransmitter where name = \"{name}\" or \"{name}\" in synonyms\"\"\".format(\n name = attr['name']))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"Neurotransmitter {name} already exists with rid = {rid}\"\"\".format(\n name = attr['name'], rid = objs[0]._id))\n return objs\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"Neurotransmitter {name} (as its synonym) already exists with rid = {rid}, use name {formalname} instead\"\"\".format(\n name = attr['name'], rid = obj._id, formalname = obj.name))\n elif cls in ['Subsystem', 'Neuropil', 'Subregion', 'Tract']:\n # TODO: synonyms are not checked against existing names and synonyms\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where name = \"{name}\" or \"{name}\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'],\n ds = unique_in.name,\n version = unique_in.version, rid = objs[0]._id))\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'], formalname = obj.name,\n ds = unique_in.name,\n version = unique_in.version, rid = obj._id))\n # Alternatively, try:\n # tmp = self.sql_query(\n # \"\"\"select from {cls} where name = \"{name}\" or \"{name}\" in synonyms\"\"\".format(\n # cls = cls, name = attr['name']))\n # ds = tmp.owned_by(cls = 'DataSource').has(rid = datasource)\n # if len(ds):\n # tmp1 = tmp.has(name = attr['name'])\n # if len(tmp1.owned_by(cls = 'DataSource').has(rid = datasource)):\n # raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}\"\"\".format(\n # cls = cls, name = attr['name'],\n # ds = datasource.name,\n # version = datasource.version))\n # else:\n # all_synonym_objs = (tmp - tmp1).node_objs\n # for obj in objs:\n # if len(QueryWrapper.from_rids(obj._id).has(cls = 'DataSource').has(rid = datasource)):\n # raise NodeAlreadyExistError(\n # \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}\"\"\".format(\n # cls = cls, name = attr['name'], formalname = obj.name,\n # ds = datasource.name,\n # version = datasource.version))\n\n # Alternatively 2, try: (will be slow when it has a lot of Owns edges)\n # tmp = sql_query(\n # \"\"\"\n # select from (select expand(out('Owns')[@class = \"{cls}\"]) from {rid}) where name = \"{name}\" or \"{name}\" in synonyms\n # \"\"\"\n # )\n # elif cls in ['Subregion']:\n # if not isinstance(unique_in, models.Neuropil):\n # raise TypeError('To check the uniqueness of a {} instance, unique_in must be a Neuropil object'.format(cls))\n # tmp = self.sql_query(\n # \"\"\"select from (select from {cls} where name = \"{name}\" or \"{name}\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='ucls' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n # rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n # if len(tmp):\n # objs = tmp.node_objs\n # if attr['name'] in [obj.name for obj in objs]:\n # raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under Neuropil {ds}\"\"\".format(\n # cls = cls, name = attr['name'],\n # ds = unique_in.name))\n # else:\n # for obj in objs:\n # if name in obj.synonyms:\n # raise NodeAlreadyExistError(\n # \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under Neuropil {ds}\"\"\".format(\n # cls = cls, name = attr['name'], formalname = obj.name,\n # ds = unique_in.name))\n elif cls in ['Neuron', 'NeuronFragment']:\n # TODO: synonyms are not checked against existing names and synonyms\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where uname = \"{name}\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists with rid = {rid}, under DataSource {ds} version {version}\"\"\".format(\n cls = cls, name = attr['name'], rid = objs[0]._id,\n ds = unique_in.name,\n version = unique_in.version))\n elif cls == 'Circuit':\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where name = \"{name}\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'],\n ds = unique_in.name,\n version = unique_in.version, rid = objs[0]._id))\n elif cls == 'ArborizationData':\n if not isinstance(unique_in, (models.Neuron, models.Synapse)):\n raise TypeError('To check the uniqueness of a ArborizationData instance, unique_in must be a Neuron or a Synapse object')\n tmp = self.sql_query(\n \"\"\"select from (select expand(out(HasData)) from {rid}) where @class = 'ArborizationData' \"\"\".format(rid = unique_in._id))\n if len(tmp):\n raise NodeAlreadyExistError(\"\"\"ArborizationData already exists for {node} {uname} with rid = {rid}. Use NeuroArch.update_{node}_arborization to update the record\"\"\".format(\n node = unique_in.element_type.lower(), rid = tmp.node_objs[0]._id, uname = unique_in.uname))\n else:\n raise TypeError('Model type not understood.')\n return True","def is_resource(space, w_obj):\n return space.wrap(space.is_resource(w_obj))","def is_valid_pid_for_create(did):\n if not d1_gmn.app.did.is_valid_pid_for_create(did):\n raise d1_common.types.exceptions.IdentifierNotUnique(\n 0,\n 'Identifier is already in use as {}. did=\"{}\"'.format(\n d1_gmn.app.did.classify_identifier(did), did\n ),\n identifier=did,\n )","def test_validation_idaa_valid_and_exists(self):\n expected_discrepancies = 0\n\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][self.create_idaa_program_index]['fields'],\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\n )\n\n self.assertTrue(upload_program.is_valid())\n self.assertTrue(upload_program.tola_program_exists)\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)","def _check_for_preexisting_identifier(self, doi: Doi):\n # The database expects each field to be a list.\n query_criterias = {\"ids\": [doi.pds_identifier]}\n\n # Query database for rows with given id value.\n columns, rows = self._database_obj.select_latest_rows(query_criterias)\n\n for row in rows:\n existing_record = dict(zip(columns, row))\n\n if doi.doi != existing_record[\"doi\"]:\n raise IllegalDOIActionException(\n f\"There is already a DOI {existing_record['doi']} associated \"\n f\"with PDS identifier {doi.pds_identifier} \"\n f\"(status={existing_record['status']}).\\n\"\n f\"You cannot modify a DOI for an existing PDS identifier.\"\n )","def existence_validation(self, request, *args, **kwargs):\n lection_id = self.kwargs.get('lection_id')\n course_id = self.kwargs.get('course_id')\n lection = Lection.objects.filter(Q(course_id=course_id) & Q(id=lection_id)).first()\n error = {'error': f\"Either lection with ID{lection_id} doesn't belong to course with ID{course_id}, \"\n f\"or doesn't exist.\"}\n if lection:\n return method(self, request, *args, **kwargs)\n return Response(error, status=status.HTTP_403_FORBIDDEN)","def test_init_id_type(self):\n self.assertIsInstance(Rectangle(1, 1).id, int)\n self.assertIsInstance(Rectangle(1, 1, id=None).id, int)","def add_existing_key_fail(self, data):\n message = 'exists'\n rv = self.add_success(data)\n assert not in_response(rv, message)\n return self.add_fail(data, message)","def test_get_by_id_wrong_type(self):\n assert ExampleUserModel.get_by_id(\"xyz\") is None","def test_get_event_type_by_id_invalid_id(self):\n\t\trequest = self.client.get('/api/event_type/esper/0', follow=True)\n\t\tself.assertEqual(request.status_code, status.HTTP_400_BAD_REQUEST)","def test_resource_exists(self):\r\n\t\tself.assertTrue(self._configuration_.resources().has_key(\"AddWordTaskRepeat\") and self._configuration_.resources().has_key(\"RemoveWordTaskRepeat\"))","def test_register_subscription_existing_type(self):\n mock_type = Mock()\n bus = event_bus._event_bus\n bus._subscriptions[mock_type] = [\n EventSubscription(mock_type, lambda _: None)]\n new_subscription = EventSubscription(mock_type, lambda _: True)\n\n reg_id = event_bus.register_subscription(new_subscription)\n\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\n self.assertTrue(reg_id in bus._registration_id_map.keys())","def test_add_resource(self):\n s1 = System()\n b1 = Books(\"1984\", \"George Orwell\", \"Harvill Secker\", \"1949\", \"0123456789123\")\n self.assertNotIn(b1, s1.catalogue)\n s1.add_resource(b1)\n self.assertIn(b1, s1.catalogue)\n s1.add_resource(b1)\n self.assertEqual(len(s1.catalogue), 1)","def check_existed_did(self):\n for wallet in self.wallet_state_manager.wallets.values():\n if (\n wallet.type() == WalletType.DECENTRALIZED_ID\n and self.did_info.origin_coin.name() == wallet.did_info.origin_coin.name()\n ):\n self.log.warning(f\"DID {self.did_info.origin_coin} already existed, ignore the wallet creation.\")\n raise ValueError(\"Wallet already exists\")","def _resource_name_check(self, resource_name):\n return self._name_check(resource_name, 'resources')","def validate(self, entity_id):\n\n safe_entity = self.find_by_id(entity_id)\n if not safe_entity:\n raise EntityNotFound(\"The param_id = {} is not valid.\".format(entity_id))\n\n return safe_entity","def check_status(self, id):\n raise NotImplementedError()","def test_cannot_add_existing_serial_number(self):\n self.assertEqual(self.all_assets.count(), 1)\n serial_number = \"SN001\"\n new_asset = Asset(serial_number, \"SN001\")\n with self.assertRaises(ValidationError):\n new_asset.save()\n self.assertEqual(self.all_assets.count(), 1)","def delete_does_not_exist_fail(self, id_):\n assert is_404(self.get((id_, self.delete_url)))\n self.delete_fail(id_, 'does not exist')","def test_readable_id_valid(readable_id_value):\n program = ProgramFactory.build(readable_id=readable_id_value)\n program.save()\n assert program.id is not None\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\n course.save()\n assert course.id is not None","def validated_id(cls, name):\n if name:\n if name in cls._ids:\n return cls._ids[name]\n if cls.validated_name(name):\n if Accounts.exists(name):\n return cls.get_id(name)\n return None","def ResourceExists(resource_name, search_user_paths=True):\n try:\n ResourcePath(resource_name, search_user_paths)\n return True\n except ResourceNotFound:\n return False","def test_get_event_type_by_id_not_found(self):\n\t\tevent_type = EventType.objects.get(name=\"asd\")\n\t\trequest = self.client.get('/api/event_type/esper/' + str(event_type.id + 1), follow=True)\n\t\tself.assertEqual(request.status_code, status.HTTP_404_NOT_FOUND)","def test_create_with_bad_id(self):\n # Count the number of records before the save\n existing_records_count = Track.objects.all().count()\n post_data = {'source_type': 'spotify', 'source_id': 00}\n resp = self.api_client.post('/api/metadata/tracks/', data=post_data)\n data = json.loads(resp.content)\n new_records_count = Track.objects.all().count()\n\n # Ensure the request filed with a 404, and an error message is returned\n self.assertEqual(resp.status_code, 404)\n self.assertEqual(existing_records_count, new_records_count)\n self.assertEqual(data['detail'], u'The record could not be found.')","def is_resource(self, path):\n # type: (Text) -> bool\n raise FileNotFoundError","def validate_new_person(self, person_id):\n\n self.db_cursor.execute(\"\"\"SELECT COUNT(*) FROM Person WHERE id == %s\"\"\", (person_id,))\n ct = self.db_cursor.fetchone()\n ct = ct[0]\n if ct == 0:\n return False\n return True","async def test_create_invalid_field(self):\n data = {'id': 33, 'value': 'foo'}\n with self.assertRaises(InvalidResourceDetails) as cm:\n await self.resource.create(data)\n self.assertEqual(\n 'Error: \"id\": 33 is not a string: {\\'id\\': \\'\\'}',\n str(cm.exception))","def update_object_type(self, object_type=None):\n # Return Value\n # ------------\n # {success: true}\n #\n if not is_basic_identifier(object_type.name):\n raise BadRequest(\"Invalid object_type name: %s\" % object_type.name)\n if not is_yaml_string_valid(object_type.definition):\n raise BadRequest(\"Invalid YAML definition\")\n object_id, version = self.clients.resource_registry.update(object_type)\n return object_id","def find_by_id(cls, id):\n\t\tif id:\n\t\t\treturn cls.query.filter_by(id=id).first()\n\t\treturn {\n\t\t\t'message': 'id field is required',\n\t\t\t'status': 'Failed'\n\t\t\t}, 400","def validateID(id):\n\n if re.compile('[0-9]+').match(id) == None:\n output.completeOutputError(InvalidArgumentCount(descape =\"'%s' is not a valid Id. ID should be numeric with Length = '%s' \" \n\t\t\t% (id, lib.constants._ATTR_ID_LENGHT)))\n return -1\n else:\n # Check for the lenght \n counter = 0\n for char in id:\n counter += 1\n print counter , lib.constants._ATTR_ID_LENGHT\n if counter > lib.constants._ATTR_ID_LENGHT :\n output.completeOutputError(InvalidArgumentCount(descape =\"'%s' exceeded the given length i.e Max Length = '%s'\" % \n\t\t\t(id, lib.constants._ATTR_ID_LENGHT)))\n return -1\n else:\n return 0\n return 0","def test_id_uniqueness(self):\n user_2 = User()\n self.assertNotEqual(self.user_1.id, user_2.id)","def sanity_check(cls, data, ticket_id=None):\n if ticket_id is not None:\n ticket_id = int(ticket_id)\n ticket = DB_TICKET_TABLE.get(doc_id=ticket_id)\n if not ticket:\n flask_restful.abort(404, message=f\"ticket '{ticket_id}' not found!\")\n else:\n ticket = None\n\n # A custom validator to make sure the aportio ID remains unique\n def validate_aportio_id(aportio_id):\n if not isinstance(aportio_id, str):\n raise ValueError(\"expected string type for aportio ID\")\n TicketQuery = Query()\n ticket_with_aportio_id = DB_TICKET_TABLE.get(\n TicketQuery.aportio_id == aportio_id)\n if ticket_with_aportio_id and (ticket_with_aportio_id.doc_id != ticket_id):\n raise ValueError(f\"a ticket with aportio ID '{aportio_id}' \"\n f\"exists already\")\n return aportio_id\n\n # A custom validator for the short title\n def validate_short_title(text):\n return _str_len_check(text, cls.SHORT_TITLE_MIN_LEN, cls.SHORT_TITLE_MAX_LEN)\n\n # A custom validator for the long text\n def validate_long_text(text):\n return _str_len_check(text, cls.LONG_TEXT_MIN_LEN, cls.LONG_TEXT_MAX_LEN)\n\n # Perform some sanity checking of the provided attributes\n data = _dict_sanity_check(data,\n mandatory_keys = [\n (\"aportio_id\", validate_aportio_id),\n (\"customer_id\", Customer.exists),\n (\"short_title\", validate_short_title),\n (\"user_id\", User.exists),\n (\"status\", Ticket.valid_status),\n (\"classification\", Ticket.valid_classification),\n (\"long_text\", validate_long_text)\n ],\n optional_keys = [\n (\"custom_fields\", dict)\n ],\n obj=ticket)\n # Now check whether this user is even associated with that customer\n cust_id = data['customer_id']\n user_id = data['user_id']\n assoc_q = Query()\n assoc_data = DB_USER_CUSTOMER_RELS_TABLE.search((assoc_q.customer_id == cust_id) &\n (assoc_q.user_id == user_id))\n if not assoc_data:\n flask_restful.abort(400, message=f\"Bad Request - user '{user_id}' is not \"\n f\"associated with customer '{cust_id}'\")\n return data, ticket","def test_exists(self):\n with self.assertRaises(IncompetentQiitaDeveloperError):\n BaseSample.exists('SKM7.640188', SampleTemplate(1))","def test_validation_idaa_valid_and_does_not_exists(self):\n idaa_index = 1\n expected_discrepancies = 0\n\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][idaa_index]['fields'],\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\n )\n\n self.assertTrue(upload_program.is_valid())\n self.assertFalse(upload_program.tola_program_exists)\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)","def _check_id(self, keyword):\n if keyword not in self.request.data:\n return '{} parameter is missing'.format(keyword)\n \"\"\" Check if <keyword> parameter is not None \"\"\"\n if self.request.data[keyword] == '':\n return '{} ID cannot be None'.format(keyword)\n \"\"\" Check if <keyword> parameter is > 0 \"\"\"\n if int(self.request.data[keyword]) < 1:\n return '{} ID must be an integer > 0'.format(keyword)","def exists(self, obj):\n return False","def _check_subject_id(subject_id):\n if (subject_id and\n len(subject_id) > models.Subject.id.property.columns[\n 0].type.length):\n raise exception.SubjectNotFound()","def test_validate_post_existing_resource(client):\n response = client.post(\n '/user/',\n data=json.dumps({\n 'name': 'Jeff Knupp',\n 'email': 'jknupp@gmail.com',\n }),\n headers={'Content-Type': 'application/json'}\n )\n assert response.status_code == 400\n assert response.json['message'] == INVALID_ACTION_MESSAGE","def verify_object(self, data):\n rv = self.get(data[self.id_field])\n result = not is_404(rv)\n if result:\n for key, value in data:\n if not in_response(rv, value):\n return False\n return result","def validate_item_id(idx):\n item = ItemModel.query.get(idx)\n if item is None:\n raise NotFound(f'Item with id {idx} not found.')\n return item","def test_data_type_id(self):\n self.assertTrue(self.tester.data_type(ret_id=True), 2)","def check_person_existence(self, searched_person_id):\n self.__load_persons_from_file_into_memory()\n return super().check_person_existence(searched_person_id)","def check_instance(self, class_name, inst_id, stored_objects):\n '''get '<class_name>.id' to FileStorage.__objects key format'''\n instance = \"{}.{}\".format(class_name, inst_id)\n if instance not in stored_objects:\n \"\"\"given id does not exist\"\"\"\n print(\"** no instance found **\")\n instance = False\n return instance","def test_create_already_existing_campaign_fails(self):\n test_campaign = return_canned_campaign()\n self.test_org.campaign = [test_campaign]\n test_campaign.save()\n response = self.client.post(\n self.endpoint_url,\n json={\n \"logo\": test_campaign.logo,\n \"name\": test_campaign.name,\n \"organisations\": [self.test_org.id],\n \"url\": test_campaign.url,\n },\n headers={\"Authorization\": self.session_token},\n )\n response_body = response.get_json()\n self.assertEqual(response.status_code, 409)\n self.assertEqual(response_body[\"Error\"], \" Campaign name already exists\")\n self.assertEqual(response_body[\"SubCode\"], \"NameExists\")","def exists(self, Search_ID):\n if self.get_id(Search_ID) is None:\n return False\n else:\n return True","def validateID(self, id : int) -> int:\n # If ID is a string, ensure it can be casted to an int before casting and returning.\n if type(id) == str:\n if not lib.stringTyping.isInt(id):\n raise TypeError(\"user ID must be either int or string of digits\")\n return int(id)\n # If ID is not a string, nor an int, throw an error.\n elif type(id) != int:\n raise TypeError(\"user ID must be either int or string of digits\")\n # ID must be an int, so return it.\n return id","def id_exists(show_id: int,\n database_connection: mysql.connector.connect) -> bool:\n return validate_id(show_id, database_connection)"],"string":"[\n \"def test_id_already_exists(self) -> None:\\n with pytest.raises(IntegrityError):\\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\\n 'description': 'A new filter type.'})\",\n \"def check_id(self, id):\",\n \"def testValidateId(self):\\n #create a different person and try to use their id\\n self.directory.invokeFactory(type_name=\\\"FSDPerson\\\",id=\\\"def456\\\",firstName=\\\"Joe\\\",lastName=\\\"Blow\\\")\\n self.failUnless('def456' in self.person.validate_id('def456'))\\n #create a different content object and try to use its id\\n self.directory.invokeFactory(\\\"Document\\\", \\\"mydoc\\\")\\n self.failUnless('mydoc' in self.person.validate_id('mydoc'))\",\n \"def check_repost_exists(type, id):\\n \\n try:\\n soundcloud.get('/e1/me/{}_reposts/{}'.format(type, id))\\n return True\\n except HTTPError as e:\\n if e.response.status_code == 404:\\n db.mark_as_deleted(type, id)\\n return False\\n else:\\n raise\",\n \"def test_resource_id(self):\\n resource_id = '1234-1234-1234'\\n\\n # resource id does not exist\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\\n\\n # create a resource ID\\n resp = self.app.post(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 201)\\n\\n # resource id exists\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # cannot create twice\\n resp = self.app.post(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 409)\\n\\n # delete resource id\\n resp = self.app.delete(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # resource id does not exist\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\",\n \"def ResourceExists(self, name):\\n pass\",\n \"def assert_has(self, type_id, message=''):\\n if self.first_by_id(type_id):\\n return\\n raise AssertionError(message)\",\n \"def does_resource_exist(resource):\\n try:\\n resource.load()\\n return True\\n except botocore.exceptions.ClientError as e:\\n if e.response['Error']['Code'] == 'ValidationError':\\n return False\\n else:\\n raise e\",\n \"def check_action_type_exists(\\n action_type_id: int\\n) -> None:\\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\\n raise errors.ActionTypeDoesNotExistError()\",\n \"def check_id_existence(self, id:str):\\n\\n oc_prefix = id[:(id.index(':')+1)]\\n\\n if oc_prefix == 'doi:':\\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\\n if oc_prefix == 'isbn:':\\n vldt = isbn.ISBNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'issn:':\\n vldt = issn.ISSNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'orcid:':\\n vldt = orcid.ORCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmcid:':\\n vldt = pmcid.PMCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmid:':\\n vldt = pmid.PMIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'ror:':\\n vldt = ror.RORManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'url:':\\n vldt = url.URLManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'viaf:':\\n vldt = viaf.ViafManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikidata:':\\n vldt = wikidata.WikidataManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikipedia:':\\n vldt = wikipedia.WikipediaManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\",\n \"def test_create_id_type(self):\\n self.assertIsInstance(Rectangle.create().id, int)\",\n \"def test_duplicate_flavorids_fail(self):\\n flavorid = 'flavor1'\\n instance_types.create('name one', 256, 1, 120, 200, flavorid)\\n self.assertRaises(exception.InstanceTypeIdExists,\\n instance_types.create,\\n 'name two', 256, 1, 120, 200, flavorid)\",\n \"def test_difference_id(self):\\n self.assertFalse(\\n self.factory.create_type('iphone') is self.factory.create_type(\\n 'iphone'))\",\n \"def validate_id(cls, id: str) -> ObjectId:\\n return ObjectId(id)\",\n \"def test_id_missing(self) -> None:\\n with pytest.raises(NotFound):\\n ObservationType.from_id(-1)\",\n \"def check_unique_element_id(cls, instance, element_id):\\n if not element_id:\\n return\\n try:\\n element_ids = instance.placeholder.page.cascadepage.glossary['element_ids'][instance.language]\\n except (AttributeError, KeyError, ObjectDoesNotExist):\\n return\\n else:\\n for key, value in element_ids.items():\\n if str(key) != str(instance.pk) and element_id == value:\\n msg = _(\\\"The element ID '{}' is not unique for this page.\\\")\\n raise ValidationError(msg.format(element_id))\",\n \"def test_duplicate_id(self):\\n with self.assertRaises(ValueError):\\n REANATemplate(\\n workflow_spec={},\\n parameters=[\\n pd.parameter_declaration('A', index=1),\\n pd.parameter_declaration('B'),\\n pd.parameter_declaration('C'),\\n pd.parameter_declaration('A', index=2),\\n pd.parameter_declaration('E', index=1)\\n ],\\n validate=True\\n )\",\n \"def test_create_resource(self):\\n test_resource = ResourceTypeName.get() # the name of the resource type to create\\n\\n # the resource type should not exist yet\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\\n\\n # create the resource type\\n resp = self.app.post(f'/v1/resource/{test_resource}', data=json.dumps({'actions': ['tr:action1']}),\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 201)\\n\\n # the resource type exists\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # delete the resource type\\n resp = self.app.delete(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # the resource type should not exist\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\",\n \"def _validate_create(context, db_api, create_data, model_name):\\n ipaddrlist = utils.get_addresses(create_data['ip_address'])\\n\\n if not ipaddrlist:\\n errors = (_(\\\"Failed to register (%s)\\\" +\\n \\\". The (%s) IP Address (%s) could not \\\"\\n \\\"be resolved.\\\")\\n % (model_name, model_name, create_data['ip_address']))\\n raise exception.AddressResolutionFailure(reason=errors)\\n LOG.info(\\\"IP/FQDN for the \\\" + model_name + \\\" %s is %s\\\" % (\\n create_data['ip_address'],\\n ipaddrlist))\\n try:\\n get_all = getattr(db_api, \\\"get_all_%ss\\\" % model_name)\\n res_data = get_all(context)\\n if not res_data:\\n # No registered resources\\n LOG.info(\\\"No registered %s\\\" % model_name)\\n return\\n except Exception:\\n errors = (_(\\\"Failed to retrieve data for (%s) %s\\\")\\n % (model_name, create_data.get('ip_address')))\\n raise exception.InternalFailure(reason=errors)\\n name = create_data.get(\\\"name\\\")\\n valid_name = _validate_duplicate_names(res_data, name)\\n if not valid_name:\\n msg = (_(\\\"Two different (%s) with same \\\"\\n \\\"name cannot be registered\\\") % model_name)\\n raise exception.ResourceExists(reason=msg)\\n registered_data = []\\n for data in res_data:\\n registered_data.append(data['ip_address'])\\n\\n if set(ipaddrlist).intersection(set(registered_data)):\\n errors = (_(\\\"(%s) by ip_address (%s) already exists.\\\")\\n % (model_name, create_data['ip_address']))\\n raise exception.ResourceExists(reason=errors)\",\n \"def test_will_not_get_instance_type_with_bad_id(self):\\n self.assertRaises(exception.InstanceTypeNotFound,\\n instance_types.get_instance_type, 'asdf')\",\n \"def test_check_resource(self):\\n s1 = System()\\n b1 = Books(\\\"1984\\\", \\\"George Orwell\\\", \\\"Harvill Secker\\\", \\\"1949\\\", \\\"0123456789123\\\")\\n self.assertEqual(s1.check_resource(b1), False)\\n s1.add_resource(b1)\\n self.assertEqual(s1.check_resource(b1), True)\",\n \"def resourceExists(node, name = None, resourceType = PROP_RESOURCE_TYPE_RESOURCE):\\n \\n exists = False\\n if not node:\\n return exists\\n try:\\n myResourceType = \\\"\\\"\\n if name:\\n # make sure it's unicode:\\n if not isinstance(name, str):\\n name = name.decode(sys.getfilesystemencoding())\\n url = node.url\\n if url.endswith(\\\"/\\\"):\\n url = url + name\\n else:\\n url = url + \\\"/\\\" + name\\n newNode = ResourceStorer(url, node.connection)\\n element = newNode.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\\n else: # name is \\\"None\\\":\\n element = node.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\\n \\n if len(element.children) > 0:\\n myResourceType = element.children[0].name\\n if resourceType == myResourceType or resourceType == PROP_RESOURCE_TYPE_RESOURCE:\\n exists = True\\n else:\\n exists = False\\n except WebdavError as wderr:\\n if wderr.code == CODE_NOT_FOUND:\\n # node doesn't exist -> exists = False:\\n exists = False\\n else:\\n # another exception occured -> \\\"re-raise\\\" it:\\n raise\\n return exists\",\n \"def is_resource_id(schema_obj):\\n\\n if isinstance(schema_obj, schema.Field):\\n return is_resource_id(schema_obj.metadata)\\n elif isinstance(schema_obj, schema.Struct):\\n return schema_obj.full_name == 'weave.common.ResourceId'\\n return False\",\n \"def is_existing_object(did):\\n if not d1_gmn.app.did.is_existing_object(did):\\n raise d1_common.types.exceptions.NotFound(\\n 0,\\n \\\"Identifier is {}. Expected a Persistent ID (PID) for an existing \\\"\\n 'object. id=\\\"{}\\\"'.format(d1_gmn.app.did.classify_identifier(did), did),\\n identifier=did,\\n )\",\n \"def test_will_not_get_instance_type_by_unknown_id(self):\\n self.assertRaises(exception.InstanceTypeNotFound,\\n instance_types.get_instance_type, 10000)\",\n \"def validate_id(ctx, param, value):\\r\\n try:\\r\\n if value is None:\\r\\n return None\\r\\n obj = optiga.Object(int(value, base=16))\\r\\n obj = obj.meta\\r\\n return int(value, base=16)\\r\\n except (ValueError, TypeError, OSError) as no_object:\\r\\n raise click.BadParameter(\\\"Object ID doesn't exist. Please align with the Objects map\\\") from no_object\",\n \"def taco_test_put_error_requires_id(self):\\n body = '{ \\\"id\\\": 400, \\\"name\\\": \\\"item_new\\\", \\\"content\\\": \\\"after test update\\\" }'\\n env = self.get_env('PUT', '/item', body=body)\\n webapi_start(env, lambda status, response_headers: self.assertEqual(status, '501'))\",\n \"def _create_resource(resource, **options):\\n global _existing\\n\\n if _existing[resource]:\\n print('{r} {k}:{v} already exists with id {i}.'.format(\\n r=resource,\\n k=args.tag,\\n v=args.role,\\n i=_existing[resource].id\\n ))\\n return True\\n\\n print('{v} a {r} with parameters: {p}...'.format(\\n v='Would create' if dry else 'Creating',\\n r=resource,\\n p=str(options)\\n ))\\n\\n if dry:\\n return True\\n\\n # All easy cases out of the way, we now need to actually create something.\\n r = None\\n try:\\n r = getattr(ec2, definitions[resource].create)(** options)\\n # In some cases (instance) a list is returned instead of one item. Quack!\\n try:\\n r = r[0]\\n except:\\n pass\\n _tag_resource(r)\\n print('... {r} id {i} created.'.format(\\n r=resource,\\n i=r.id\\n ))\\n _existing[resource] = r\\n return True\\n except Exception as e:\\n if r is None:\\n print('Could not create resource {r}.'.format(\\n r=resource\\n ))\\n traceback.print_exc()\\n else:\\n print('Could not tag resource {r}, id {i}.'.format(\\n r=resource,\\n i=r.id\\n ))\\n traceback.print_exc()\\n _destroy_resource(resource)\\n return False\",\n \"def validate_identifier(self, identifier):\\n pass\",\n \"def needs_unique_instance(type_):\\n return type_ in unique_instance_types\",\n \"def _validate_call_id(self, call_id):\\n\\n self._validate_required_data(call_id, self.CALL_ID)\\n\\n query = CallRecord.objects.filter(call_id=call_id)\\n\\n if query.exists():\\n raise NotAcceptable(\\n detail='Call id is already in use. Please, choose another')\",\n \"def identify_id(id: str) -> bool:\\n return validate_handle(id)\",\n \"def test_create_id_identity(self):\\n self.assertIs(Rectangle.create(id=True).id, True)\\n self.assertIs(Rectangle.create(id=type).id, type)\\n self.assertIs(Rectangle.create(id=None).id, None)\",\n \"def validate_user_id(self, value):\\n if not User.objects.filter(id=value).exists():\\n raise serializers.ValidationError('User with this id does not exist.')\\n return value\",\n \"def validate(self):\\n # Validate all mandatory keys are present\\n if not self.mandatory_keys.issubset(set(self.resource)):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] miss a \\\"\\n \\\"mandatory key. Please check the model.\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id))\\n\\n # Validate the resource does not contains extra keys\\n if not set(self.resource).issubset(self.keys):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] contains \\\"\\n \\\"extra keys. Please check the model.\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id))\\n\\n # Validate the resource value type\\n for key, value in self.resource.items():\\n if not isinstance(value, self.__class__.MODEL[key][0]):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data type (expected: %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][0]))\\n # For str type validate the content as according the regex\\n if self.__class__.MODEL[key][0] is str:\\n if not re.match(self.__class__.MODEL[key][1], value):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data content (expected match : %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][1]))\\n # For list type validate the content as according the regex\\n if self.__class__.MODEL[key][0] is list:\\n if not all([re.match(self.__class__.MODEL[key][1], v)\\n for v in value]):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data content (expected match : %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][1]))\",\n \"def test_check_input_id(self):\\n r3 = Rectangle(10, 2, 0, 0, 12)\\n self.assertEqual(r3.id, 12)\",\n \"def resource(\\n name: str,\\n *,\\n mime_type: str,\\n parent_folder_id: drive_api.ResourceID,\\n drive_service: Optional[discovery.Resource] = None,\\n) -> drive_api.ResourceID:\\n command = request(\\n name,\\n mime_type=mime_type,\\n parent_folder_id=parent_folder_id,\\n drive_service=drive_service,\\n )\\n result = command.execute()\\n new_id: drive_api.ResourceID = result.get(\\\"id\\\")\\n return new_id\",\n \"def test_bad_id(self):\\n r1 = Square(10, 2)\\n self.assertEqual(r1.id, 1)\\n\\n r2 = Square(2, 10)\\n self.assertEqual(r2.id, 2)\",\n \"def validatePredefinedType(self, type: int) -> bool:\\n ...\",\n \"def validate_resources(self, folder, resources):\\r\\n self.validate_files_exist(folder, resources)\\r\\n self.validate_no_duplicate_paths(resources)\",\n \"def __validateResourceStateEntry(self, resource: Dict[str, str]):\\n if AZ_RESOURCE_ID not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (\\n self.fullName, AZ_RESOURCE_ID))\\n if SID not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (self.fullName, SID))\\n if ARM_TYPE not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (self.fullName, ARM_TYPE))\",\n \"def validate_id(self, value):\\n try:\\n Tutor.objects.get(pk=value)\\n except Tutor.DoesNotExist:\\n raise serializers.ValidationError('Tutor object with id \\\\'{}\\\\' does not exist.'.format(value))\\n return value\",\n \"def test_readable_id_invalid(readable_id_value):\\n program = ProgramFactory.build(readable_id=readable_id_value)\\n with pytest.raises(ValidationError):\\n program.save()\\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\\n with pytest.raises(ValidationError):\\n course.save()\",\n \"def test_api_update_book_with_id_does_not_exist(self):\\n\\n\\t\\tlogin_data = self.login_test_user()\\n\\t\\ttoken = login_data['auth_token']\\n\\n\\t\\tbook = self.client.put(\\n\\t\\t\\tf'{URL_BOOKS}/1',\\n\\t\\t\\theaders=dict(Authorization=f'Bearer {token}'),\\n\\t\\t\\tcontent_type='application/json',\\n\\t\\t\\tdata=json.dumps(\\n\\t\\t\\t\\tdict(\\n\\t\\t\\t\\t\\ttitle='updated book'\\n\\t\\t\\t\\t)\\n\\t\\t\\t)\\n\\t\\t)\\n\\n\\t\\tbook_res = json.loads(book.data.decode())\\n\\t\\tself.assertTrue(book_res['message'] == 'book with id 1 does not exist')\\n\\t\\tself.assertTrue(book_res['status'] == 'error')\",\n \"def test_check_id(self):\\n r1 = Rectangle(2, 10)\\n r2 = Rectangle(2, 10)\\n r3 = Rectangle(2, 10)\\n self.assertGreater(r2.id, r1.id)\\n self.assertGreater(r3.id, r2.id)\",\n \"def create_resource(self, resource, resource_data, resource_type, **kwargs):\\n if not isinstance(resource, Resource):\\n raise KeyError(\\\"'resource' should be an instance of Resource\\\")\\n if not isinstance(resource_data, ResourceData) or not resource_data.value:\\n raise KeyError(\\n \\\"'resource_data' should be ResourceData with 'value' attribute\\\")\\n if not isinstance(resource_type, ResourceType):\\n raise KeyError(\\\"'resource_type' should be an instance of ResourceType\\\")\\n if not kwargs or 'feed_id' not in kwargs:\\n raise KeyError('Variable \\\"feed_id\\\" id mandatory field!')\\n\\n resource_id = urlquote(resource.id, safe='')\\n r = self._post('entity/f;{}/resource'.format(kwargs['feed_id']),\\n data={\\\"name\\\": resource.name, \\\"id\\\": resource.id,\\n \\\"resourceTypePath\\\": \\\"rt;{}\\\"\\n .format(resource_type.path.resource_type_id)})\\n if r:\\n r = self._post('entity/f;{}/r;{}/data'\\n .format(kwargs['feed_id'], resource_id),\\n data={'role': 'configuration', \\\"value\\\": resource_data.value})\\n else:\\n # if resource or it's data was not created correctly, delete resource\\n self._delete('entity/f;{}/r;{}'.format(kwargs['feed_id'], resource_id))\\n return r\",\n \"def checkValidId(self, id, prep_id = False):\\n new_id = unquote(id)\\n if prep_id: new_id = self.prepId(id)\\n try:\\n globalCheckValidId(self, new_id)\\n return True\\n except Exception:\\n return str(sys.exc_info()[1])\",\n \"def resource_exists(self, resource):\\n products = Product.select(self.env, where={'name' : resource.id})\\n return bool(products)\",\n \"def test_cannot_add_existing_asset_code(self):\\n self.assertEqual(self.all_assets.count(), 1)\\n asset_code = \\\"IC002\\\"\\n new_asset = Asset(asset_code, \\\"SN001\\\")\\n with self.assertRaises(ValidationError):\\n new_asset.save()\\n self.assertEqual(self.all_assets.count(), 1)\",\n \"def send_error_missing_id(message, obj_type):\\n return make_response(jsonify({\\\"validation_error\\\": {\\n \\\"error\\\": 'Missing id',\\n \\\"object_type\\\": obj_type,\\n \\\"description\\\": message\\n }}), 400)\",\n \"def test_init_id_identity(self):\\n self.assertIs(Rectangle(1, 1, id=True).id, True)\\n self.assertIs(Rectangle(1, 1, id=type).id, type)\",\n \"def id_exists(host_id: int,\\n database_connection: mysql.connector.connect) -> bool:\\n return validate_id(host_id, database_connection)\",\n \"def _validate_duplicate_names(res_data, name, _id=None):\\n if _id:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name and data.get(\\\"id\\\") != _id:\\n return False\\n return True\\n else:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name:\\n return False\\n return True\",\n \"def validate(self):\\n try:\\n # update _resource to have default values from the schema\\n self._resource = self.schema(self._resource)\\n except MultipleInvalid as e:\\n errors = [format_error(err, self.resource_type) for err in e.errors]\\n raise exceptions.ValidationError({'errors': errors})\\n\\n yield self.check_unique()\",\n \"def _uniqueness_check(self, cls, unique_in = None, **attr):\\n # under the same datasource, only 1 subsystem, 1 neuropil, 1 tract of the name can exist\\n # under the same neuropil, only 1 neuron of the name can exist\\n # multiple (collections of) synapses can exist between two neurons\\n if cls == 'Species':\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from Species where (name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) and stage = \\\"{stage}\\\" and sex = \\\"{sex}\\\" \\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex']))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"Species {name} at {stage} stage ({sex}) already exists with rid = {rid}\\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = objs[0]._id))\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"Species {name} (as its synonym) at {stage} stage ({sex}) already exists with rid = {rid}, use name {formalname} instead\\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = obj._id, formalname = obj.name))\\n elif cls == 'DataSource':\\n objs = self.find_objs('DataSource', name=attr['name'], version=attr['version'])\\n #if self.exists(cls, name = attr['name'], version = attr['version']):\\n if len(objs):\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{} Node with attributes {} already exists with rid = {}\\\"\\\"\\\".format(\\n cls, ', '.join([\\\"\\\"\\\"{} = {}\\\"\\\"\\\".format(key, value) \\\\\\n for key, value in attr.items()]), objs[0]._id))\\n elif cls == 'Neurotransmitter':\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from Neurotransmitter where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\\"\\\"\\\".format(\\n name = attr['name']))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"Neurotransmitter {name} already exists with rid = {rid}\\\"\\\"\\\".format(\\n name = attr['name'], rid = objs[0]._id))\\n return objs\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"Neurotransmitter {name} (as its synonym) already exists with rid = {rid}, use name {formalname} instead\\\"\\\"\\\".format(\\n name = attr['name'], rid = obj._id, formalname = obj.name))\\n elif cls in ['Subsystem', 'Neuropil', 'Subregion', 'Tract']:\\n # TODO: synonyms are not checked against existing names and synonyms\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'],\\n ds = unique_in.name,\\n version = unique_in.version, rid = objs[0]._id))\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'], formalname = obj.name,\\n ds = unique_in.name,\\n version = unique_in.version, rid = obj._id))\\n # Alternatively, try:\\n # tmp = self.sql_query(\\n # \\\"\\\"\\\"select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name']))\\n # ds = tmp.owned_by(cls = 'DataSource').has(rid = datasource)\\n # if len(ds):\\n # tmp1 = tmp.has(name = attr['name'])\\n # if len(tmp1.owned_by(cls = 'DataSource').has(rid = datasource)):\\n # raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'],\\n # ds = datasource.name,\\n # version = datasource.version))\\n # else:\\n # all_synonym_objs = (tmp - tmp1).node_objs\\n # for obj in objs:\\n # if len(QueryWrapper.from_rids(obj._id).has(cls = 'DataSource').has(rid = datasource)):\\n # raise NodeAlreadyExistError(\\n # \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'], formalname = obj.name,\\n # ds = datasource.name,\\n # version = datasource.version))\\n\\n # Alternatively 2, try: (will be slow when it has a lot of Owns edges)\\n # tmp = sql_query(\\n # \\\"\\\"\\\"\\n # select from (select expand(out('Owns')[@class = \\\"{cls}\\\"]) from {rid}) where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\n # \\\"\\\"\\\"\\n # )\\n # elif cls in ['Subregion']:\\n # if not isinstance(unique_in, models.Neuropil):\\n # raise TypeError('To check the uniqueness of a {} instance, unique_in must be a Neuropil object'.format(cls))\\n # tmp = self.sql_query(\\n # \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='ucls' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n # rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n # if len(tmp):\\n # objs = tmp.node_objs\\n # if attr['name'] in [obj.name for obj in objs]:\\n # raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under Neuropil {ds}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'],\\n # ds = unique_in.name))\\n # else:\\n # for obj in objs:\\n # if name in obj.synonyms:\\n # raise NodeAlreadyExistError(\\n # \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under Neuropil {ds}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'], formalname = obj.name,\\n # ds = unique_in.name))\\n elif cls in ['Neuron', 'NeuronFragment']:\\n # TODO: synonyms are not checked against existing names and synonyms\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where uname = \\\"{name}\\\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists with rid = {rid}, under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'], rid = objs[0]._id,\\n ds = unique_in.name,\\n version = unique_in.version))\\n elif cls == 'Circuit':\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'],\\n ds = unique_in.name,\\n version = unique_in.version, rid = objs[0]._id))\\n elif cls == 'ArborizationData':\\n if not isinstance(unique_in, (models.Neuron, models.Synapse)):\\n raise TypeError('To check the uniqueness of a ArborizationData instance, unique_in must be a Neuron or a Synapse object')\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select expand(out(HasData)) from {rid}) where @class = 'ArborizationData' \\\"\\\"\\\".format(rid = unique_in._id))\\n if len(tmp):\\n raise NodeAlreadyExistError(\\\"\\\"\\\"ArborizationData already exists for {node} {uname} with rid = {rid}. Use NeuroArch.update_{node}_arborization to update the record\\\"\\\"\\\".format(\\n node = unique_in.element_type.lower(), rid = tmp.node_objs[0]._id, uname = unique_in.uname))\\n else:\\n raise TypeError('Model type not understood.')\\n return True\",\n \"def is_resource(space, w_obj):\\n return space.wrap(space.is_resource(w_obj))\",\n \"def is_valid_pid_for_create(did):\\n if not d1_gmn.app.did.is_valid_pid_for_create(did):\\n raise d1_common.types.exceptions.IdentifierNotUnique(\\n 0,\\n 'Identifier is already in use as {}. did=\\\"{}\\\"'.format(\\n d1_gmn.app.did.classify_identifier(did), did\\n ),\\n identifier=did,\\n )\",\n \"def test_validation_idaa_valid_and_exists(self):\\n expected_discrepancies = 0\\n\\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][self.create_idaa_program_index]['fields'],\\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\\n )\\n\\n self.assertTrue(upload_program.is_valid())\\n self.assertTrue(upload_program.tola_program_exists)\\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)\",\n \"def _check_for_preexisting_identifier(self, doi: Doi):\\n # The database expects each field to be a list.\\n query_criterias = {\\\"ids\\\": [doi.pds_identifier]}\\n\\n # Query database for rows with given id value.\\n columns, rows = self._database_obj.select_latest_rows(query_criterias)\\n\\n for row in rows:\\n existing_record = dict(zip(columns, row))\\n\\n if doi.doi != existing_record[\\\"doi\\\"]:\\n raise IllegalDOIActionException(\\n f\\\"There is already a DOI {existing_record['doi']} associated \\\"\\n f\\\"with PDS identifier {doi.pds_identifier} \\\"\\n f\\\"(status={existing_record['status']}).\\\\n\\\"\\n f\\\"You cannot modify a DOI for an existing PDS identifier.\\\"\\n )\",\n \"def existence_validation(self, request, *args, **kwargs):\\n lection_id = self.kwargs.get('lection_id')\\n course_id = self.kwargs.get('course_id')\\n lection = Lection.objects.filter(Q(course_id=course_id) & Q(id=lection_id)).first()\\n error = {'error': f\\\"Either lection with ID{lection_id} doesn't belong to course with ID{course_id}, \\\"\\n f\\\"or doesn't exist.\\\"}\\n if lection:\\n return method(self, request, *args, **kwargs)\\n return Response(error, status=status.HTTP_403_FORBIDDEN)\",\n \"def test_init_id_type(self):\\n self.assertIsInstance(Rectangle(1, 1).id, int)\\n self.assertIsInstance(Rectangle(1, 1, id=None).id, int)\",\n \"def add_existing_key_fail(self, data):\\n message = 'exists'\\n rv = self.add_success(data)\\n assert not in_response(rv, message)\\n return self.add_fail(data, message)\",\n \"def test_get_by_id_wrong_type(self):\\n assert ExampleUserModel.get_by_id(\\\"xyz\\\") is None\",\n \"def test_get_event_type_by_id_invalid_id(self):\\n\\t\\trequest = self.client.get('/api/event_type/esper/0', follow=True)\\n\\t\\tself.assertEqual(request.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def test_resource_exists(self):\\r\\n\\t\\tself.assertTrue(self._configuration_.resources().has_key(\\\"AddWordTaskRepeat\\\") and self._configuration_.resources().has_key(\\\"RemoveWordTaskRepeat\\\"))\",\n \"def test_register_subscription_existing_type(self):\\n mock_type = Mock()\\n bus = event_bus._event_bus\\n bus._subscriptions[mock_type] = [\\n EventSubscription(mock_type, lambda _: None)]\\n new_subscription = EventSubscription(mock_type, lambda _: True)\\n\\n reg_id = event_bus.register_subscription(new_subscription)\\n\\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\\n self.assertTrue(reg_id in bus._registration_id_map.keys())\",\n \"def test_add_resource(self):\\n s1 = System()\\n b1 = Books(\\\"1984\\\", \\\"George Orwell\\\", \\\"Harvill Secker\\\", \\\"1949\\\", \\\"0123456789123\\\")\\n self.assertNotIn(b1, s1.catalogue)\\n s1.add_resource(b1)\\n self.assertIn(b1, s1.catalogue)\\n s1.add_resource(b1)\\n self.assertEqual(len(s1.catalogue), 1)\",\n \"def check_existed_did(self):\\n for wallet in self.wallet_state_manager.wallets.values():\\n if (\\n wallet.type() == WalletType.DECENTRALIZED_ID\\n and self.did_info.origin_coin.name() == wallet.did_info.origin_coin.name()\\n ):\\n self.log.warning(f\\\"DID {self.did_info.origin_coin} already existed, ignore the wallet creation.\\\")\\n raise ValueError(\\\"Wallet already exists\\\")\",\n \"def _resource_name_check(self, resource_name):\\n return self._name_check(resource_name, 'resources')\",\n \"def validate(self, entity_id):\\n\\n safe_entity = self.find_by_id(entity_id)\\n if not safe_entity:\\n raise EntityNotFound(\\\"The param_id = {} is not valid.\\\".format(entity_id))\\n\\n return safe_entity\",\n \"def check_status(self, id):\\n raise NotImplementedError()\",\n \"def test_cannot_add_existing_serial_number(self):\\n self.assertEqual(self.all_assets.count(), 1)\\n serial_number = \\\"SN001\\\"\\n new_asset = Asset(serial_number, \\\"SN001\\\")\\n with self.assertRaises(ValidationError):\\n new_asset.save()\\n self.assertEqual(self.all_assets.count(), 1)\",\n \"def delete_does_not_exist_fail(self, id_):\\n assert is_404(self.get((id_, self.delete_url)))\\n self.delete_fail(id_, 'does not exist')\",\n \"def test_readable_id_valid(readable_id_value):\\n program = ProgramFactory.build(readable_id=readable_id_value)\\n program.save()\\n assert program.id is not None\\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\\n course.save()\\n assert course.id is not None\",\n \"def validated_id(cls, name):\\n if name:\\n if name in cls._ids:\\n return cls._ids[name]\\n if cls.validated_name(name):\\n if Accounts.exists(name):\\n return cls.get_id(name)\\n return None\",\n \"def ResourceExists(resource_name, search_user_paths=True):\\n try:\\n ResourcePath(resource_name, search_user_paths)\\n return True\\n except ResourceNotFound:\\n return False\",\n \"def test_get_event_type_by_id_not_found(self):\\n\\t\\tevent_type = EventType.objects.get(name=\\\"asd\\\")\\n\\t\\trequest = self.client.get('/api/event_type/esper/' + str(event_type.id + 1), follow=True)\\n\\t\\tself.assertEqual(request.status_code, status.HTTP_404_NOT_FOUND)\",\n \"def test_create_with_bad_id(self):\\n # Count the number of records before the save\\n existing_records_count = Track.objects.all().count()\\n post_data = {'source_type': 'spotify', 'source_id': 00}\\n resp = self.api_client.post('/api/metadata/tracks/', data=post_data)\\n data = json.loads(resp.content)\\n new_records_count = Track.objects.all().count()\\n\\n # Ensure the request filed with a 404, and an error message is returned\\n self.assertEqual(resp.status_code, 404)\\n self.assertEqual(existing_records_count, new_records_count)\\n self.assertEqual(data['detail'], u'The record could not be found.')\",\n \"def is_resource(self, path):\\n # type: (Text) -> bool\\n raise FileNotFoundError\",\n \"def validate_new_person(self, person_id):\\n\\n self.db_cursor.execute(\\\"\\\"\\\"SELECT COUNT(*) FROM Person WHERE id == %s\\\"\\\"\\\", (person_id,))\\n ct = self.db_cursor.fetchone()\\n ct = ct[0]\\n if ct == 0:\\n return False\\n return True\",\n \"async def test_create_invalid_field(self):\\n data = {'id': 33, 'value': 'foo'}\\n with self.assertRaises(InvalidResourceDetails) as cm:\\n await self.resource.create(data)\\n self.assertEqual(\\n 'Error: \\\"id\\\": 33 is not a string: {\\\\'id\\\\': \\\\'\\\\'}',\\n str(cm.exception))\",\n \"def update_object_type(self, object_type=None):\\n # Return Value\\n # ------------\\n # {success: true}\\n #\\n if not is_basic_identifier(object_type.name):\\n raise BadRequest(\\\"Invalid object_type name: %s\\\" % object_type.name)\\n if not is_yaml_string_valid(object_type.definition):\\n raise BadRequest(\\\"Invalid YAML definition\\\")\\n object_id, version = self.clients.resource_registry.update(object_type)\\n return object_id\",\n \"def find_by_id(cls, id):\\n\\t\\tif id:\\n\\t\\t\\treturn cls.query.filter_by(id=id).first()\\n\\t\\treturn {\\n\\t\\t\\t'message': 'id field is required',\\n\\t\\t\\t'status': 'Failed'\\n\\t\\t\\t}, 400\",\n \"def validateID(id):\\n\\n if re.compile('[0-9]+').match(id) == None:\\n output.completeOutputError(InvalidArgumentCount(descape =\\\"'%s' is not a valid Id. ID should be numeric with Length = '%s' \\\" \\n\\t\\t\\t% (id, lib.constants._ATTR_ID_LENGHT)))\\n return -1\\n else:\\n # Check for the lenght \\n counter = 0\\n for char in id:\\n counter += 1\\n print counter , lib.constants._ATTR_ID_LENGHT\\n if counter > lib.constants._ATTR_ID_LENGHT :\\n output.completeOutputError(InvalidArgumentCount(descape =\\\"'%s' exceeded the given length i.e Max Length = '%s'\\\" % \\n\\t\\t\\t(id, lib.constants._ATTR_ID_LENGHT)))\\n return -1\\n else:\\n return 0\\n return 0\",\n \"def test_id_uniqueness(self):\\n user_2 = User()\\n self.assertNotEqual(self.user_1.id, user_2.id)\",\n \"def sanity_check(cls, data, ticket_id=None):\\n if ticket_id is not None:\\n ticket_id = int(ticket_id)\\n ticket = DB_TICKET_TABLE.get(doc_id=ticket_id)\\n if not ticket:\\n flask_restful.abort(404, message=f\\\"ticket '{ticket_id}' not found!\\\")\\n else:\\n ticket = None\\n\\n # A custom validator to make sure the aportio ID remains unique\\n def validate_aportio_id(aportio_id):\\n if not isinstance(aportio_id, str):\\n raise ValueError(\\\"expected string type for aportio ID\\\")\\n TicketQuery = Query()\\n ticket_with_aportio_id = DB_TICKET_TABLE.get(\\n TicketQuery.aportio_id == aportio_id)\\n if ticket_with_aportio_id and (ticket_with_aportio_id.doc_id != ticket_id):\\n raise ValueError(f\\\"a ticket with aportio ID '{aportio_id}' \\\"\\n f\\\"exists already\\\")\\n return aportio_id\\n\\n # A custom validator for the short title\\n def validate_short_title(text):\\n return _str_len_check(text, cls.SHORT_TITLE_MIN_LEN, cls.SHORT_TITLE_MAX_LEN)\\n\\n # A custom validator for the long text\\n def validate_long_text(text):\\n return _str_len_check(text, cls.LONG_TEXT_MIN_LEN, cls.LONG_TEXT_MAX_LEN)\\n\\n # Perform some sanity checking of the provided attributes\\n data = _dict_sanity_check(data,\\n mandatory_keys = [\\n (\\\"aportio_id\\\", validate_aportio_id),\\n (\\\"customer_id\\\", Customer.exists),\\n (\\\"short_title\\\", validate_short_title),\\n (\\\"user_id\\\", User.exists),\\n (\\\"status\\\", Ticket.valid_status),\\n (\\\"classification\\\", Ticket.valid_classification),\\n (\\\"long_text\\\", validate_long_text)\\n ],\\n optional_keys = [\\n (\\\"custom_fields\\\", dict)\\n ],\\n obj=ticket)\\n # Now check whether this user is even associated with that customer\\n cust_id = data['customer_id']\\n user_id = data['user_id']\\n assoc_q = Query()\\n assoc_data = DB_USER_CUSTOMER_RELS_TABLE.search((assoc_q.customer_id == cust_id) &\\n (assoc_q.user_id == user_id))\\n if not assoc_data:\\n flask_restful.abort(400, message=f\\\"Bad Request - user '{user_id}' is not \\\"\\n f\\\"associated with customer '{cust_id}'\\\")\\n return data, ticket\",\n \"def test_exists(self):\\n with self.assertRaises(IncompetentQiitaDeveloperError):\\n BaseSample.exists('SKM7.640188', SampleTemplate(1))\",\n \"def test_validation_idaa_valid_and_does_not_exists(self):\\n idaa_index = 1\\n expected_discrepancies = 0\\n\\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][idaa_index]['fields'],\\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\\n )\\n\\n self.assertTrue(upload_program.is_valid())\\n self.assertFalse(upload_program.tola_program_exists)\\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)\",\n \"def _check_id(self, keyword):\\n if keyword not in self.request.data:\\n return '{} parameter is missing'.format(keyword)\\n \\\"\\\"\\\" Check if <keyword> parameter is not None \\\"\\\"\\\"\\n if self.request.data[keyword] == '':\\n return '{} ID cannot be None'.format(keyword)\\n \\\"\\\"\\\" Check if <keyword> parameter is > 0 \\\"\\\"\\\"\\n if int(self.request.data[keyword]) < 1:\\n return '{} ID must be an integer > 0'.format(keyword)\",\n \"def exists(self, obj):\\n return False\",\n \"def _check_subject_id(subject_id):\\n if (subject_id and\\n len(subject_id) > models.Subject.id.property.columns[\\n 0].type.length):\\n raise exception.SubjectNotFound()\",\n \"def test_validate_post_existing_resource(client):\\n response = client.post(\\n '/user/',\\n data=json.dumps({\\n 'name': 'Jeff Knupp',\\n 'email': 'jknupp@gmail.com',\\n }),\\n headers={'Content-Type': 'application/json'}\\n )\\n assert response.status_code == 400\\n assert response.json['message'] == INVALID_ACTION_MESSAGE\",\n \"def verify_object(self, data):\\n rv = self.get(data[self.id_field])\\n result = not is_404(rv)\\n if result:\\n for key, value in data:\\n if not in_response(rv, value):\\n return False\\n return result\",\n \"def validate_item_id(idx):\\n item = ItemModel.query.get(idx)\\n if item is None:\\n raise NotFound(f'Item with id {idx} not found.')\\n return item\",\n \"def test_data_type_id(self):\\n self.assertTrue(self.tester.data_type(ret_id=True), 2)\",\n \"def check_person_existence(self, searched_person_id):\\n self.__load_persons_from_file_into_memory()\\n return super().check_person_existence(searched_person_id)\",\n \"def check_instance(self, class_name, inst_id, stored_objects):\\n '''get '<class_name>.id' to FileStorage.__objects key format'''\\n instance = \\\"{}.{}\\\".format(class_name, inst_id)\\n if instance not in stored_objects:\\n \\\"\\\"\\\"given id does not exist\\\"\\\"\\\"\\n print(\\\"** no instance found **\\\")\\n instance = False\\n return instance\",\n \"def test_create_already_existing_campaign_fails(self):\\n test_campaign = return_canned_campaign()\\n self.test_org.campaign = [test_campaign]\\n test_campaign.save()\\n response = self.client.post(\\n self.endpoint_url,\\n json={\\n \\\"logo\\\": test_campaign.logo,\\n \\\"name\\\": test_campaign.name,\\n \\\"organisations\\\": [self.test_org.id],\\n \\\"url\\\": test_campaign.url,\\n },\\n headers={\\\"Authorization\\\": self.session_token},\\n )\\n response_body = response.get_json()\\n self.assertEqual(response.status_code, 409)\\n self.assertEqual(response_body[\\\"Error\\\"], \\\" Campaign name already exists\\\")\\n self.assertEqual(response_body[\\\"SubCode\\\"], \\\"NameExists\\\")\",\n \"def exists(self, Search_ID):\\n if self.get_id(Search_ID) is None:\\n return False\\n else:\\n return True\",\n \"def validateID(self, id : int) -> int:\\n # If ID is a string, ensure it can be casted to an int before casting and returning.\\n if type(id) == str:\\n if not lib.stringTyping.isInt(id):\\n raise TypeError(\\\"user ID must be either int or string of digits\\\")\\n return int(id)\\n # If ID is not a string, nor an int, throw an error.\\n elif type(id) != int:\\n raise TypeError(\\\"user ID must be either int or string of digits\\\")\\n # ID must be an int, so return it.\\n return id\",\n \"def id_exists(show_id: int,\\n database_connection: mysql.connector.connect) -> bool:\\n return validate_id(show_id, database_connection)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6422405","0.64173734","0.6142269","0.61312246","0.5939884","0.5908327","0.5880398","0.5806814","0.577634","0.5734848","0.5730072","0.56382006","0.55637","0.5501549","0.5488068","0.5485431","0.5476124","0.5466836","0.54339","0.5411698","0.5398409","0.5372584","0.53484315","0.53477323","0.5336371","0.5327411","0.5316241","0.5294655","0.5292505","0.52906764","0.5290138","0.52719474","0.52706325","0.52505064","0.5224689","0.5216522","0.5177424","0.5173158","0.5164601","0.51274157","0.51106805","0.5106305","0.50903237","0.5088144","0.50764173","0.5063056","0.5062557","0.50492555","0.50405514","0.5026922","0.5023985","0.5008982","0.50059426","0.5004298","0.5000435","0.49945658","0.49936256","0.49927726","0.4989894","0.49898884","0.49880224","0.49869823","0.49819273","0.49790868","0.49758255","0.49716154","0.49641553","0.49623126","0.49579415","0.49545392","0.49482954","0.49476528","0.49418265","0.49415585","0.4931851","0.49189654","0.49133888","0.4912833","0.49104878","0.49034798","0.4903424","0.4892134","0.48883384","0.4884316","0.48806715","0.48744503","0.48673403","0.48648918","0.48645955","0.48611632","0.48581317","0.4855877","0.48537856","0.48529413","0.48418126","0.48340088","0.482996","0.4826713","0.48135507","0.4812498","0.48092806"],"string":"[\n \"0.6422405\",\n \"0.64173734\",\n \"0.6142269\",\n \"0.61312246\",\n \"0.5939884\",\n \"0.5908327\",\n \"0.5880398\",\n \"0.5806814\",\n \"0.577634\",\n \"0.5734848\",\n \"0.5730072\",\n \"0.56382006\",\n \"0.55637\",\n \"0.5501549\",\n \"0.5488068\",\n \"0.5485431\",\n \"0.5476124\",\n \"0.5466836\",\n \"0.54339\",\n \"0.5411698\",\n \"0.5398409\",\n \"0.5372584\",\n \"0.53484315\",\n \"0.53477323\",\n \"0.5336371\",\n \"0.5327411\",\n \"0.5316241\",\n \"0.5294655\",\n \"0.5292505\",\n \"0.52906764\",\n \"0.5290138\",\n \"0.52719474\",\n \"0.52706325\",\n \"0.52505064\",\n \"0.5224689\",\n \"0.5216522\",\n \"0.5177424\",\n \"0.5173158\",\n \"0.5164601\",\n \"0.51274157\",\n \"0.51106805\",\n \"0.5106305\",\n \"0.50903237\",\n \"0.5088144\",\n \"0.50764173\",\n \"0.5063056\",\n \"0.5062557\",\n \"0.50492555\",\n \"0.50405514\",\n \"0.5026922\",\n \"0.5023985\",\n \"0.5008982\",\n \"0.50059426\",\n \"0.5004298\",\n \"0.5000435\",\n \"0.49945658\",\n \"0.49936256\",\n \"0.49927726\",\n \"0.4989894\",\n \"0.49898884\",\n \"0.49880224\",\n \"0.49869823\",\n \"0.49819273\",\n \"0.49790868\",\n \"0.49758255\",\n \"0.49716154\",\n \"0.49641553\",\n \"0.49623126\",\n \"0.49579415\",\n \"0.49545392\",\n \"0.49482954\",\n \"0.49476528\",\n \"0.49418265\",\n \"0.49415585\",\n \"0.4931851\",\n \"0.49189654\",\n \"0.49133888\",\n \"0.4912833\",\n \"0.49104878\",\n \"0.49034798\",\n \"0.4903424\",\n \"0.4892134\",\n \"0.48883384\",\n \"0.4884316\",\n \"0.48806715\",\n \"0.48744503\",\n \"0.48673403\",\n \"0.48648918\",\n \"0.48645955\",\n \"0.48611632\",\n \"0.48581317\",\n \"0.4855877\",\n \"0.48537856\",\n \"0.48529413\",\n \"0.48418126\",\n \"0.48340088\",\n \"0.482996\",\n \"0.4826713\",\n \"0.48135507\",\n \"0.4812498\",\n \"0.48092806\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":2293,"cells":{"query":{"kind":"string","value":"Validate a resource of the given type with specified ID already exists."},"document":{"kind":"string","value":"def _TableExists(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n get_request_type = GetApiMessage('BigqueryTablesGetRequest')\n get_request = get_request_type(datasetId=dataset_id, tableId=table_id,\n projectId=project_id)\n try:\n service.Get(get_request)\n return True\n except apitools_exceptions.HttpNotFoundError:\n log.info('Table with id [{}:{}:{}] not found.'.format(\n project_id, dataset_id, table_id))\n\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_id_already_exists(self) -> None:\n with pytest.raises(IntegrityError):\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\n 'description': 'A new filter type.'})","def check_id(self, id):","def testValidateId(self):\n #create a different person and try to use their id\n self.directory.invokeFactory(type_name=\"FSDPerson\",id=\"def456\",firstName=\"Joe\",lastName=\"Blow\")\n self.failUnless('def456' in self.person.validate_id('def456'))\n #create a different content object and try to use its id\n self.directory.invokeFactory(\"Document\", \"mydoc\")\n self.failUnless('mydoc' in self.person.validate_id('mydoc'))","def check_repost_exists(type, id):\n \n try:\n soundcloud.get('/e1/me/{}_reposts/{}'.format(type, id))\n return True\n except HTTPError as e:\n if e.response.status_code == 404:\n db.mark_as_deleted(type, id)\n return False\n else:\n raise","def test_resource_id(self):\n resource_id = '1234-1234-1234'\n\n # resource id does not exist\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 404)\n\n # create a resource ID\n resp = self.app.post(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 201)\n\n # resource id exists\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # cannot create twice\n resp = self.app.post(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 409)\n\n # delete resource id\n resp = self.app.delete(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # resource id does not exist\n resp = self.app.get(\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\n headers=admin_headers)\n self.assertEqual(resp.status_code, 404)","def ResourceExists(self, name):\n pass","def assert_has(self, type_id, message=''):\n if self.first_by_id(type_id):\n return\n raise AssertionError(message)","def does_resource_exist(resource):\n try:\n resource.load()\n return True\n except botocore.exceptions.ClientError as e:\n if e.response['Error']['Code'] == 'ValidationError':\n return False\n else:\n raise e","def check_action_type_exists(\n action_type_id: int\n) -> None:\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\n raise errors.ActionTypeDoesNotExistError()","def check_id_existence(self, id:str):\n\n oc_prefix = id[:(id.index(':')+1)]\n\n if oc_prefix == 'doi:':\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\n if oc_prefix == 'isbn:':\n vldt = isbn.ISBNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'issn:':\n vldt = issn.ISSNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'orcid:':\n vldt = orcid.ORCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmcid:':\n vldt = pmcid.PMCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmid:':\n vldt = pmid.PMIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'ror:':\n vldt = ror.RORManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'url:':\n vldt = url.URLManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'viaf:':\n vldt = viaf.ViafManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikidata:':\n vldt = wikidata.WikidataManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikipedia:':\n vldt = wikipedia.WikipediaManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))","def test_create_id_type(self):\n self.assertIsInstance(Rectangle.create().id, int)","def test_duplicate_flavorids_fail(self):\n flavorid = 'flavor1'\n instance_types.create('name one', 256, 1, 120, 200, flavorid)\n self.assertRaises(exception.InstanceTypeIdExists,\n instance_types.create,\n 'name two', 256, 1, 120, 200, flavorid)","def test_difference_id(self):\n self.assertFalse(\n self.factory.create_type('iphone') is self.factory.create_type(\n 'iphone'))","def validate_id(cls, id: str) -> ObjectId:\n return ObjectId(id)","def test_id_missing(self) -> None:\n with pytest.raises(NotFound):\n ObservationType.from_id(-1)","def check_unique_element_id(cls, instance, element_id):\n if not element_id:\n return\n try:\n element_ids = instance.placeholder.page.cascadepage.glossary['element_ids'][instance.language]\n except (AttributeError, KeyError, ObjectDoesNotExist):\n return\n else:\n for key, value in element_ids.items():\n if str(key) != str(instance.pk) and element_id == value:\n msg = _(\"The element ID '{}' is not unique for this page.\")\n raise ValidationError(msg.format(element_id))","def test_duplicate_id(self):\n with self.assertRaises(ValueError):\n REANATemplate(\n workflow_spec={},\n parameters=[\n pd.parameter_declaration('A', index=1),\n pd.parameter_declaration('B'),\n pd.parameter_declaration('C'),\n pd.parameter_declaration('A', index=2),\n pd.parameter_declaration('E', index=1)\n ],\n validate=True\n )","def test_create_resource(self):\n test_resource = ResourceTypeName.get() # the name of the resource type to create\n\n # the resource type should not exist yet\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 404)\n\n # create the resource type\n resp = self.app.post(f'/v1/resource/{test_resource}', data=json.dumps({'actions': ['tr:action1']}),\n headers=admin_headers)\n self.assertEqual(resp.status_code, 201)\n\n # the resource type exists\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # delete the resource type\n resp = self.app.delete(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 200)\n\n # the resource type should not exist\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\n self.assertEqual(resp.status_code, 404)","def _validate_create(context, db_api, create_data, model_name):\n ipaddrlist = utils.get_addresses(create_data['ip_address'])\n\n if not ipaddrlist:\n errors = (_(\"Failed to register (%s)\" +\n \". The (%s) IP Address (%s) could not \"\n \"be resolved.\")\n % (model_name, model_name, create_data['ip_address']))\n raise exception.AddressResolutionFailure(reason=errors)\n LOG.info(\"IP/FQDN for the \" + model_name + \" %s is %s\" % (\n create_data['ip_address'],\n ipaddrlist))\n try:\n get_all = getattr(db_api, \"get_all_%ss\" % model_name)\n res_data = get_all(context)\n if not res_data:\n # No registered resources\n LOG.info(\"No registered %s\" % model_name)\n return\n except Exception:\n errors = (_(\"Failed to retrieve data for (%s) %s\")\n % (model_name, create_data.get('ip_address')))\n raise exception.InternalFailure(reason=errors)\n name = create_data.get(\"name\")\n valid_name = _validate_duplicate_names(res_data, name)\n if not valid_name:\n msg = (_(\"Two different (%s) with same \"\n \"name cannot be registered\") % model_name)\n raise exception.ResourceExists(reason=msg)\n registered_data = []\n for data in res_data:\n registered_data.append(data['ip_address'])\n\n if set(ipaddrlist).intersection(set(registered_data)):\n errors = (_(\"(%s) by ip_address (%s) already exists.\")\n % (model_name, create_data['ip_address']))\n raise exception.ResourceExists(reason=errors)","def test_will_not_get_instance_type_with_bad_id(self):\n self.assertRaises(exception.InstanceTypeNotFound,\n instance_types.get_instance_type, 'asdf')","def test_check_resource(self):\n s1 = System()\n b1 = Books(\"1984\", \"George Orwell\", \"Harvill Secker\", \"1949\", \"0123456789123\")\n self.assertEqual(s1.check_resource(b1), False)\n s1.add_resource(b1)\n self.assertEqual(s1.check_resource(b1), True)","def resourceExists(node, name = None, resourceType = PROP_RESOURCE_TYPE_RESOURCE):\n \n exists = False\n if not node:\n return exists\n try:\n myResourceType = \"\"\n if name:\n # make sure it's unicode:\n if not isinstance(name, str):\n name = name.decode(sys.getfilesystemencoding())\n url = node.url\n if url.endswith(\"/\"):\n url = url + name\n else:\n url = url + \"/\" + name\n newNode = ResourceStorer(url, node.connection)\n element = newNode.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\n else: # name is \"None\":\n element = node.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\n \n if len(element.children) > 0:\n myResourceType = element.children[0].name\n if resourceType == myResourceType or resourceType == PROP_RESOURCE_TYPE_RESOURCE:\n exists = True\n else:\n exists = False\n except WebdavError as wderr:\n if wderr.code == CODE_NOT_FOUND:\n # node doesn't exist -> exists = False:\n exists = False\n else:\n # another exception occured -> \"re-raise\" it:\n raise\n return exists","def is_resource_id(schema_obj):\n\n if isinstance(schema_obj, schema.Field):\n return is_resource_id(schema_obj.metadata)\n elif isinstance(schema_obj, schema.Struct):\n return schema_obj.full_name == 'weave.common.ResourceId'\n return False","def is_existing_object(did):\n if not d1_gmn.app.did.is_existing_object(did):\n raise d1_common.types.exceptions.NotFound(\n 0,\n \"Identifier is {}. Expected a Persistent ID (PID) for an existing \"\n 'object. id=\"{}\"'.format(d1_gmn.app.did.classify_identifier(did), did),\n identifier=did,\n )","def test_will_not_get_instance_type_by_unknown_id(self):\n self.assertRaises(exception.InstanceTypeNotFound,\n instance_types.get_instance_type, 10000)","def validate_id(ctx, param, value):\r\n try:\r\n if value is None:\r\n return None\r\n obj = optiga.Object(int(value, base=16))\r\n obj = obj.meta\r\n return int(value, base=16)\r\n except (ValueError, TypeError, OSError) as no_object:\r\n raise click.BadParameter(\"Object ID doesn't exist. Please align with the Objects map\") from no_object","def taco_test_put_error_requires_id(self):\n body = '{ \"id\": 400, \"name\": \"item_new\", \"content\": \"after test update\" }'\n env = self.get_env('PUT', '/item', body=body)\n webapi_start(env, lambda status, response_headers: self.assertEqual(status, '501'))","def _create_resource(resource, **options):\n global _existing\n\n if _existing[resource]:\n print('{r} {k}:{v} already exists with id {i}.'.format(\n r=resource,\n k=args.tag,\n v=args.role,\n i=_existing[resource].id\n ))\n return True\n\n print('{v} a {r} with parameters: {p}...'.format(\n v='Would create' if dry else 'Creating',\n r=resource,\n p=str(options)\n ))\n\n if dry:\n return True\n\n # All easy cases out of the way, we now need to actually create something.\n r = None\n try:\n r = getattr(ec2, definitions[resource].create)(** options)\n # In some cases (instance) a list is returned instead of one item. Quack!\n try:\n r = r[0]\n except:\n pass\n _tag_resource(r)\n print('... {r} id {i} created.'.format(\n r=resource,\n i=r.id\n ))\n _existing[resource] = r\n return True\n except Exception as e:\n if r is None:\n print('Could not create resource {r}.'.format(\n r=resource\n ))\n traceback.print_exc()\n else:\n print('Could not tag resource {r}, id {i}.'.format(\n r=resource,\n i=r.id\n ))\n traceback.print_exc()\n _destroy_resource(resource)\n return False","def validate_identifier(self, identifier):\n pass","def needs_unique_instance(type_):\n return type_ in unique_instance_types","def _validate_call_id(self, call_id):\n\n self._validate_required_data(call_id, self.CALL_ID)\n\n query = CallRecord.objects.filter(call_id=call_id)\n\n if query.exists():\n raise NotAcceptable(\n detail='Call id is already in use. Please, choose another')","def identify_id(id: str) -> bool:\n return validate_handle(id)","def test_create_id_identity(self):\n self.assertIs(Rectangle.create(id=True).id, True)\n self.assertIs(Rectangle.create(id=type).id, type)\n self.assertIs(Rectangle.create(id=None).id, None)","def validate_user_id(self, value):\n if not User.objects.filter(id=value).exists():\n raise serializers.ValidationError('User with this id does not exist.')\n return value","def validate(self):\n # Validate all mandatory keys are present\n if not self.mandatory_keys.issubset(set(self.resource)):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] miss a \"\n \"mandatory key. Please check the model.\" % (\n self.__class__.MODEL_TYPE,\n self.id))\n\n # Validate the resource does not contains extra keys\n if not set(self.resource).issubset(self.keys):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] contains \"\n \"extra keys. Please check the model.\" % (\n self.__class__.MODEL_TYPE,\n self.id))\n\n # Validate the resource value type\n for key, value in self.resource.items():\n if not isinstance(value, self.__class__.MODEL[key][0]):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data type (expected: %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][0]))\n # For str type validate the content as according the regex\n if self.__class__.MODEL[key][0] is str:\n if not re.match(self.__class__.MODEL[key][1], value):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data content (expected match : %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][1]))\n # For list type validate the content as according the regex\n if self.__class__.MODEL[key][0] is list:\n if not all([re.match(self.__class__.MODEL[key][1], v)\n for v in value]):\n raise ResourceInvalidException(\n \"Resource [type: %s, ID: %s] has an invalid \"\n \"key (%s) data content (expected match : %s)\" % (\n self.__class__.MODEL_TYPE,\n self.id,\n key,\n self.__class__.MODEL[key][1]))","def test_check_input_id(self):\n r3 = Rectangle(10, 2, 0, 0, 12)\n self.assertEqual(r3.id, 12)","def resource(\n name: str,\n *,\n mime_type: str,\n parent_folder_id: drive_api.ResourceID,\n drive_service: Optional[discovery.Resource] = None,\n) -> drive_api.ResourceID:\n command = request(\n name,\n mime_type=mime_type,\n parent_folder_id=parent_folder_id,\n drive_service=drive_service,\n )\n result = command.execute()\n new_id: drive_api.ResourceID = result.get(\"id\")\n return new_id","def test_bad_id(self):\n r1 = Square(10, 2)\n self.assertEqual(r1.id, 1)\n\n r2 = Square(2, 10)\n self.assertEqual(r2.id, 2)","def validatePredefinedType(self, type: int) -> bool:\n ...","def validate_resources(self, folder, resources):\r\n self.validate_files_exist(folder, resources)\r\n self.validate_no_duplicate_paths(resources)","def __validateResourceStateEntry(self, resource: Dict[str, str]):\n if AZ_RESOURCE_ID not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (\n self.fullName, AZ_RESOURCE_ID))\n if SID not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (self.fullName, SID))\n if ARM_TYPE not in resource:\n raise ValueError(\n '[%s] %s is not present in the armMapping.' % (self.fullName, ARM_TYPE))","def validate_id(self, value):\n try:\n Tutor.objects.get(pk=value)\n except Tutor.DoesNotExist:\n raise serializers.ValidationError('Tutor object with id \\'{}\\' does not exist.'.format(value))\n return value","def test_readable_id_invalid(readable_id_value):\n program = ProgramFactory.build(readable_id=readable_id_value)\n with pytest.raises(ValidationError):\n program.save()\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\n with pytest.raises(ValidationError):\n course.save()","def test_api_update_book_with_id_does_not_exist(self):\n\n\t\tlogin_data = self.login_test_user()\n\t\ttoken = login_data['auth_token']\n\n\t\tbook = self.client.put(\n\t\t\tf'{URL_BOOKS}/1',\n\t\t\theaders=dict(Authorization=f'Bearer {token}'),\n\t\t\tcontent_type='application/json',\n\t\t\tdata=json.dumps(\n\t\t\t\tdict(\n\t\t\t\t\ttitle='updated book'\n\t\t\t\t)\n\t\t\t)\n\t\t)\n\n\t\tbook_res = json.loads(book.data.decode())\n\t\tself.assertTrue(book_res['message'] == 'book with id 1 does not exist')\n\t\tself.assertTrue(book_res['status'] == 'error')","def test_check_id(self):\n r1 = Rectangle(2, 10)\n r2 = Rectangle(2, 10)\n r3 = Rectangle(2, 10)\n self.assertGreater(r2.id, r1.id)\n self.assertGreater(r3.id, r2.id)","def create_resource(self, resource, resource_data, resource_type, **kwargs):\n if not isinstance(resource, Resource):\n raise KeyError(\"'resource' should be an instance of Resource\")\n if not isinstance(resource_data, ResourceData) or not resource_data.value:\n raise KeyError(\n \"'resource_data' should be ResourceData with 'value' attribute\")\n if not isinstance(resource_type, ResourceType):\n raise KeyError(\"'resource_type' should be an instance of ResourceType\")\n if not kwargs or 'feed_id' not in kwargs:\n raise KeyError('Variable \"feed_id\" id mandatory field!')\n\n resource_id = urlquote(resource.id, safe='')\n r = self._post('entity/f;{}/resource'.format(kwargs['feed_id']),\n data={\"name\": resource.name, \"id\": resource.id,\n \"resourceTypePath\": \"rt;{}\"\n .format(resource_type.path.resource_type_id)})\n if r:\n r = self._post('entity/f;{}/r;{}/data'\n .format(kwargs['feed_id'], resource_id),\n data={'role': 'configuration', \"value\": resource_data.value})\n else:\n # if resource or it's data was not created correctly, delete resource\n self._delete('entity/f;{}/r;{}'.format(kwargs['feed_id'], resource_id))\n return r","def checkValidId(self, id, prep_id = False):\n new_id = unquote(id)\n if prep_id: new_id = self.prepId(id)\n try:\n globalCheckValidId(self, new_id)\n return True\n except Exception:\n return str(sys.exc_info()[1])","def resource_exists(self, resource):\n products = Product.select(self.env, where={'name' : resource.id})\n return bool(products)","def test_cannot_add_existing_asset_code(self):\n self.assertEqual(self.all_assets.count(), 1)\n asset_code = \"IC002\"\n new_asset = Asset(asset_code, \"SN001\")\n with self.assertRaises(ValidationError):\n new_asset.save()\n self.assertEqual(self.all_assets.count(), 1)","def send_error_missing_id(message, obj_type):\n return make_response(jsonify({\"validation_error\": {\n \"error\": 'Missing id',\n \"object_type\": obj_type,\n \"description\": message\n }}), 400)","def test_init_id_identity(self):\n self.assertIs(Rectangle(1, 1, id=True).id, True)\n self.assertIs(Rectangle(1, 1, id=type).id, type)","def id_exists(host_id: int,\n database_connection: mysql.connector.connect) -> bool:\n return validate_id(host_id, database_connection)","def _validate_duplicate_names(res_data, name, _id=None):\n if _id:\n for data in res_data:\n if data.get(\"name\") == name and data.get(\"id\") != _id:\n return False\n return True\n else:\n for data in res_data:\n if data.get(\"name\") == name:\n return False\n return True","def validate(self):\n try:\n # update _resource to have default values from the schema\n self._resource = self.schema(self._resource)\n except MultipleInvalid as e:\n errors = [format_error(err, self.resource_type) for err in e.errors]\n raise exceptions.ValidationError({'errors': errors})\n\n yield self.check_unique()","def _uniqueness_check(self, cls, unique_in = None, **attr):\n # under the same datasource, only 1 subsystem, 1 neuropil, 1 tract of the name can exist\n # under the same neuropil, only 1 neuron of the name can exist\n # multiple (collections of) synapses can exist between two neurons\n if cls == 'Species':\n tmp = self.sql_query(\n \"\"\"select from Species where (name = \"{name}\" or \"{name}\" in synonyms) and stage = \"{stage}\" and sex = \"{sex}\" \"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex']))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"Species {name} at {stage} stage ({sex}) already exists with rid = {rid}\"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = objs[0]._id))\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"Species {name} (as its synonym) at {stage} stage ({sex}) already exists with rid = {rid}, use name {formalname} instead\"\"\".format(\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = obj._id, formalname = obj.name))\n elif cls == 'DataSource':\n objs = self.find_objs('DataSource', name=attr['name'], version=attr['version'])\n #if self.exists(cls, name = attr['name'], version = attr['version']):\n if len(objs):\n raise NodeAlreadyExistError(\"\"\"{} Node with attributes {} already exists with rid = {}\"\"\".format(\n cls, ', '.join([\"\"\"{} = {}\"\"\".format(key, value) \\\n for key, value in attr.items()]), objs[0]._id))\n elif cls == 'Neurotransmitter':\n tmp = self.sql_query(\n \"\"\"select from Neurotransmitter where name = \"{name}\" or \"{name}\" in synonyms\"\"\".format(\n name = attr['name']))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"Neurotransmitter {name} already exists with rid = {rid}\"\"\".format(\n name = attr['name'], rid = objs[0]._id))\n return objs\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"Neurotransmitter {name} (as its synonym) already exists with rid = {rid}, use name {formalname} instead\"\"\".format(\n name = attr['name'], rid = obj._id, formalname = obj.name))\n elif cls in ['Subsystem', 'Neuropil', 'Subregion', 'Tract']:\n # TODO: synonyms are not checked against existing names and synonyms\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where name = \"{name}\" or \"{name}\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'],\n ds = unique_in.name,\n version = unique_in.version, rid = objs[0]._id))\n else:\n for obj in objs:\n if attr['name'] in obj.synonyms:\n raise NodeAlreadyExistError(\n \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'], formalname = obj.name,\n ds = unique_in.name,\n version = unique_in.version, rid = obj._id))\n # Alternatively, try:\n # tmp = self.sql_query(\n # \"\"\"select from {cls} where name = \"{name}\" or \"{name}\" in synonyms\"\"\".format(\n # cls = cls, name = attr['name']))\n # ds = tmp.owned_by(cls = 'DataSource').has(rid = datasource)\n # if len(ds):\n # tmp1 = tmp.has(name = attr['name'])\n # if len(tmp1.owned_by(cls = 'DataSource').has(rid = datasource)):\n # raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}\"\"\".format(\n # cls = cls, name = attr['name'],\n # ds = datasource.name,\n # version = datasource.version))\n # else:\n # all_synonym_objs = (tmp - tmp1).node_objs\n # for obj in objs:\n # if len(QueryWrapper.from_rids(obj._id).has(cls = 'DataSource').has(rid = datasource)):\n # raise NodeAlreadyExistError(\n # \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}\"\"\".format(\n # cls = cls, name = attr['name'], formalname = obj.name,\n # ds = datasource.name,\n # version = datasource.version))\n\n # Alternatively 2, try: (will be slow when it has a lot of Owns edges)\n # tmp = sql_query(\n # \"\"\"\n # select from (select expand(out('Owns')[@class = \"{cls}\"]) from {rid}) where name = \"{name}\" or \"{name}\" in synonyms\n # \"\"\"\n # )\n # elif cls in ['Subregion']:\n # if not isinstance(unique_in, models.Neuropil):\n # raise TypeError('To check the uniqueness of a {} instance, unique_in must be a Neuropil object'.format(cls))\n # tmp = self.sql_query(\n # \"\"\"select from (select from {cls} where name = \"{name}\" or \"{name}\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='ucls' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n # rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n # if len(tmp):\n # objs = tmp.node_objs\n # if attr['name'] in [obj.name for obj in objs]:\n # raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under Neuropil {ds}\"\"\".format(\n # cls = cls, name = attr['name'],\n # ds = unique_in.name))\n # else:\n # for obj in objs:\n # if name in obj.synonyms:\n # raise NodeAlreadyExistError(\n # \"\"\"{cls} {name} already exists as a synonym of {cls} {formalname} under Neuropil {ds}\"\"\".format(\n # cls = cls, name = attr['name'], formalname = obj.name,\n # ds = unique_in.name))\n elif cls in ['Neuron', 'NeuronFragment']:\n # TODO: synonyms are not checked against existing names and synonyms\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where uname = \"{name}\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists with rid = {rid}, under DataSource {ds} version {version}\"\"\".format(\n cls = cls, name = attr['name'], rid = objs[0]._id,\n ds = unique_in.name,\n version = unique_in.version))\n elif cls == 'Circuit':\n if not isinstance(unique_in, models.DataSource):\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\n tmp = self.sql_query(\n \"\"\"select from (select from {cls} where name = \"{name}\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\"\"\".format(\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\n if len(tmp):\n objs = tmp.node_objs\n if attr['name'] in [obj.name for obj in objs]:\n raise NodeAlreadyExistError(\"\"\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\"\"\".format(\n cls = cls, name = attr['name'],\n ds = unique_in.name,\n version = unique_in.version, rid = objs[0]._id))\n elif cls == 'ArborizationData':\n if not isinstance(unique_in, (models.Neuron, models.Synapse)):\n raise TypeError('To check the uniqueness of a ArborizationData instance, unique_in must be a Neuron or a Synapse object')\n tmp = self.sql_query(\n \"\"\"select from (select expand(out(HasData)) from {rid}) where @class = 'ArborizationData' \"\"\".format(rid = unique_in._id))\n if len(tmp):\n raise NodeAlreadyExistError(\"\"\"ArborizationData already exists for {node} {uname} with rid = {rid}. Use NeuroArch.update_{node}_arborization to update the record\"\"\".format(\n node = unique_in.element_type.lower(), rid = tmp.node_objs[0]._id, uname = unique_in.uname))\n else:\n raise TypeError('Model type not understood.')\n return True","def is_resource(space, w_obj):\n return space.wrap(space.is_resource(w_obj))","def is_valid_pid_for_create(did):\n if not d1_gmn.app.did.is_valid_pid_for_create(did):\n raise d1_common.types.exceptions.IdentifierNotUnique(\n 0,\n 'Identifier is already in use as {}. did=\"{}\"'.format(\n d1_gmn.app.did.classify_identifier(did), did\n ),\n identifier=did,\n )","def test_validation_idaa_valid_and_exists(self):\n expected_discrepancies = 0\n\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][self.create_idaa_program_index]['fields'],\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\n )\n\n self.assertTrue(upload_program.is_valid())\n self.assertTrue(upload_program.tola_program_exists)\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)","def _check_for_preexisting_identifier(self, doi: Doi):\n # The database expects each field to be a list.\n query_criterias = {\"ids\": [doi.pds_identifier]}\n\n # Query database for rows with given id value.\n columns, rows = self._database_obj.select_latest_rows(query_criterias)\n\n for row in rows:\n existing_record = dict(zip(columns, row))\n\n if doi.doi != existing_record[\"doi\"]:\n raise IllegalDOIActionException(\n f\"There is already a DOI {existing_record['doi']} associated \"\n f\"with PDS identifier {doi.pds_identifier} \"\n f\"(status={existing_record['status']}).\\n\"\n f\"You cannot modify a DOI for an existing PDS identifier.\"\n )","def existence_validation(self, request, *args, **kwargs):\n lection_id = self.kwargs.get('lection_id')\n course_id = self.kwargs.get('course_id')\n lection = Lection.objects.filter(Q(course_id=course_id) & Q(id=lection_id)).first()\n error = {'error': f\"Either lection with ID{lection_id} doesn't belong to course with ID{course_id}, \"\n f\"or doesn't exist.\"}\n if lection:\n return method(self, request, *args, **kwargs)\n return Response(error, status=status.HTTP_403_FORBIDDEN)","def test_init_id_type(self):\n self.assertIsInstance(Rectangle(1, 1).id, int)\n self.assertIsInstance(Rectangle(1, 1, id=None).id, int)","def add_existing_key_fail(self, data):\n message = 'exists'\n rv = self.add_success(data)\n assert not in_response(rv, message)\n return self.add_fail(data, message)","def test_get_by_id_wrong_type(self):\n assert ExampleUserModel.get_by_id(\"xyz\") is None","def test_get_event_type_by_id_invalid_id(self):\n\t\trequest = self.client.get('/api/event_type/esper/0', follow=True)\n\t\tself.assertEqual(request.status_code, status.HTTP_400_BAD_REQUEST)","def test_resource_exists(self):\r\n\t\tself.assertTrue(self._configuration_.resources().has_key(\"AddWordTaskRepeat\") and self._configuration_.resources().has_key(\"RemoveWordTaskRepeat\"))","def test_register_subscription_existing_type(self):\n mock_type = Mock()\n bus = event_bus._event_bus\n bus._subscriptions[mock_type] = [\n EventSubscription(mock_type, lambda _: None)]\n new_subscription = EventSubscription(mock_type, lambda _: True)\n\n reg_id = event_bus.register_subscription(new_subscription)\n\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\n self.assertTrue(reg_id in bus._registration_id_map.keys())","def test_add_resource(self):\n s1 = System()\n b1 = Books(\"1984\", \"George Orwell\", \"Harvill Secker\", \"1949\", \"0123456789123\")\n self.assertNotIn(b1, s1.catalogue)\n s1.add_resource(b1)\n self.assertIn(b1, s1.catalogue)\n s1.add_resource(b1)\n self.assertEqual(len(s1.catalogue), 1)","def check_existed_did(self):\n for wallet in self.wallet_state_manager.wallets.values():\n if (\n wallet.type() == WalletType.DECENTRALIZED_ID\n and self.did_info.origin_coin.name() == wallet.did_info.origin_coin.name()\n ):\n self.log.warning(f\"DID {self.did_info.origin_coin} already existed, ignore the wallet creation.\")\n raise ValueError(\"Wallet already exists\")","def _resource_name_check(self, resource_name):\n return self._name_check(resource_name, 'resources')","def validate(self, entity_id):\n\n safe_entity = self.find_by_id(entity_id)\n if not safe_entity:\n raise EntityNotFound(\"The param_id = {} is not valid.\".format(entity_id))\n\n return safe_entity","def check_status(self, id):\n raise NotImplementedError()","def test_cannot_add_existing_serial_number(self):\n self.assertEqual(self.all_assets.count(), 1)\n serial_number = \"SN001\"\n new_asset = Asset(serial_number, \"SN001\")\n with self.assertRaises(ValidationError):\n new_asset.save()\n self.assertEqual(self.all_assets.count(), 1)","def delete_does_not_exist_fail(self, id_):\n assert is_404(self.get((id_, self.delete_url)))\n self.delete_fail(id_, 'does not exist')","def test_readable_id_valid(readable_id_value):\n program = ProgramFactory.build(readable_id=readable_id_value)\n program.save()\n assert program.id is not None\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\n course.save()\n assert course.id is not None","def validated_id(cls, name):\n if name:\n if name in cls._ids:\n return cls._ids[name]\n if cls.validated_name(name):\n if Accounts.exists(name):\n return cls.get_id(name)\n return None","def ResourceExists(resource_name, search_user_paths=True):\n try:\n ResourcePath(resource_name, search_user_paths)\n return True\n except ResourceNotFound:\n return False","def test_get_event_type_by_id_not_found(self):\n\t\tevent_type = EventType.objects.get(name=\"asd\")\n\t\trequest = self.client.get('/api/event_type/esper/' + str(event_type.id + 1), follow=True)\n\t\tself.assertEqual(request.status_code, status.HTTP_404_NOT_FOUND)","def test_create_with_bad_id(self):\n # Count the number of records before the save\n existing_records_count = Track.objects.all().count()\n post_data = {'source_type': 'spotify', 'source_id': 00}\n resp = self.api_client.post('/api/metadata/tracks/', data=post_data)\n data = json.loads(resp.content)\n new_records_count = Track.objects.all().count()\n\n # Ensure the request filed with a 404, and an error message is returned\n self.assertEqual(resp.status_code, 404)\n self.assertEqual(existing_records_count, new_records_count)\n self.assertEqual(data['detail'], u'The record could not be found.')","def is_resource(self, path):\n # type: (Text) -> bool\n raise FileNotFoundError","def validate_new_person(self, person_id):\n\n self.db_cursor.execute(\"\"\"SELECT COUNT(*) FROM Person WHERE id == %s\"\"\", (person_id,))\n ct = self.db_cursor.fetchone()\n ct = ct[0]\n if ct == 0:\n return False\n return True","async def test_create_invalid_field(self):\n data = {'id': 33, 'value': 'foo'}\n with self.assertRaises(InvalidResourceDetails) as cm:\n await self.resource.create(data)\n self.assertEqual(\n 'Error: \"id\": 33 is not a string: {\\'id\\': \\'\\'}',\n str(cm.exception))","def update_object_type(self, object_type=None):\n # Return Value\n # ------------\n # {success: true}\n #\n if not is_basic_identifier(object_type.name):\n raise BadRequest(\"Invalid object_type name: %s\" % object_type.name)\n if not is_yaml_string_valid(object_type.definition):\n raise BadRequest(\"Invalid YAML definition\")\n object_id, version = self.clients.resource_registry.update(object_type)\n return object_id","def find_by_id(cls, id):\n\t\tif id:\n\t\t\treturn cls.query.filter_by(id=id).first()\n\t\treturn {\n\t\t\t'message': 'id field is required',\n\t\t\t'status': 'Failed'\n\t\t\t}, 400","def validateID(id):\n\n if re.compile('[0-9]+').match(id) == None:\n output.completeOutputError(InvalidArgumentCount(descape =\"'%s' is not a valid Id. ID should be numeric with Length = '%s' \" \n\t\t\t% (id, lib.constants._ATTR_ID_LENGHT)))\n return -1\n else:\n # Check for the lenght \n counter = 0\n for char in id:\n counter += 1\n print counter , lib.constants._ATTR_ID_LENGHT\n if counter > lib.constants._ATTR_ID_LENGHT :\n output.completeOutputError(InvalidArgumentCount(descape =\"'%s' exceeded the given length i.e Max Length = '%s'\" % \n\t\t\t(id, lib.constants._ATTR_ID_LENGHT)))\n return -1\n else:\n return 0\n return 0","def test_id_uniqueness(self):\n user_2 = User()\n self.assertNotEqual(self.user_1.id, user_2.id)","def sanity_check(cls, data, ticket_id=None):\n if ticket_id is not None:\n ticket_id = int(ticket_id)\n ticket = DB_TICKET_TABLE.get(doc_id=ticket_id)\n if not ticket:\n flask_restful.abort(404, message=f\"ticket '{ticket_id}' not found!\")\n else:\n ticket = None\n\n # A custom validator to make sure the aportio ID remains unique\n def validate_aportio_id(aportio_id):\n if not isinstance(aportio_id, str):\n raise ValueError(\"expected string type for aportio ID\")\n TicketQuery = Query()\n ticket_with_aportio_id = DB_TICKET_TABLE.get(\n TicketQuery.aportio_id == aportio_id)\n if ticket_with_aportio_id and (ticket_with_aportio_id.doc_id != ticket_id):\n raise ValueError(f\"a ticket with aportio ID '{aportio_id}' \"\n f\"exists already\")\n return aportio_id\n\n # A custom validator for the short title\n def validate_short_title(text):\n return _str_len_check(text, cls.SHORT_TITLE_MIN_LEN, cls.SHORT_TITLE_MAX_LEN)\n\n # A custom validator for the long text\n def validate_long_text(text):\n return _str_len_check(text, cls.LONG_TEXT_MIN_LEN, cls.LONG_TEXT_MAX_LEN)\n\n # Perform some sanity checking of the provided attributes\n data = _dict_sanity_check(data,\n mandatory_keys = [\n (\"aportio_id\", validate_aportio_id),\n (\"customer_id\", Customer.exists),\n (\"short_title\", validate_short_title),\n (\"user_id\", User.exists),\n (\"status\", Ticket.valid_status),\n (\"classification\", Ticket.valid_classification),\n (\"long_text\", validate_long_text)\n ],\n optional_keys = [\n (\"custom_fields\", dict)\n ],\n obj=ticket)\n # Now check whether this user is even associated with that customer\n cust_id = data['customer_id']\n user_id = data['user_id']\n assoc_q = Query()\n assoc_data = DB_USER_CUSTOMER_RELS_TABLE.search((assoc_q.customer_id == cust_id) &\n (assoc_q.user_id == user_id))\n if not assoc_data:\n flask_restful.abort(400, message=f\"Bad Request - user '{user_id}' is not \"\n f\"associated with customer '{cust_id}'\")\n return data, ticket","def test_exists(self):\n with self.assertRaises(IncompetentQiitaDeveloperError):\n BaseSample.exists('SKM7.640188', SampleTemplate(1))","def test_validation_idaa_valid_and_does_not_exists(self):\n idaa_index = 1\n expected_discrepancies = 0\n\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][idaa_index]['fields'],\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\n )\n\n self.assertTrue(upload_program.is_valid())\n self.assertFalse(upload_program.tola_program_exists)\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)","def _check_id(self, keyword):\n if keyword not in self.request.data:\n return '{} parameter is missing'.format(keyword)\n \"\"\" Check if <keyword> parameter is not None \"\"\"\n if self.request.data[keyword] == '':\n return '{} ID cannot be None'.format(keyword)\n \"\"\" Check if <keyword> parameter is > 0 \"\"\"\n if int(self.request.data[keyword]) < 1:\n return '{} ID must be an integer > 0'.format(keyword)","def exists(self, obj):\n return False","def _check_subject_id(subject_id):\n if (subject_id and\n len(subject_id) > models.Subject.id.property.columns[\n 0].type.length):\n raise exception.SubjectNotFound()","def test_validate_post_existing_resource(client):\n response = client.post(\n '/user/',\n data=json.dumps({\n 'name': 'Jeff Knupp',\n 'email': 'jknupp@gmail.com',\n }),\n headers={'Content-Type': 'application/json'}\n )\n assert response.status_code == 400\n assert response.json['message'] == INVALID_ACTION_MESSAGE","def verify_object(self, data):\n rv = self.get(data[self.id_field])\n result = not is_404(rv)\n if result:\n for key, value in data:\n if not in_response(rv, value):\n return False\n return result","def validate_item_id(idx):\n item = ItemModel.query.get(idx)\n if item is None:\n raise NotFound(f'Item with id {idx} not found.')\n return item","def test_data_type_id(self):\n self.assertTrue(self.tester.data_type(ret_id=True), 2)","def check_person_existence(self, searched_person_id):\n self.__load_persons_from_file_into_memory()\n return super().check_person_existence(searched_person_id)","def check_instance(self, class_name, inst_id, stored_objects):\n '''get '<class_name>.id' to FileStorage.__objects key format'''\n instance = \"{}.{}\".format(class_name, inst_id)\n if instance not in stored_objects:\n \"\"\"given id does not exist\"\"\"\n print(\"** no instance found **\")\n instance = False\n return instance","def test_create_already_existing_campaign_fails(self):\n test_campaign = return_canned_campaign()\n self.test_org.campaign = [test_campaign]\n test_campaign.save()\n response = self.client.post(\n self.endpoint_url,\n json={\n \"logo\": test_campaign.logo,\n \"name\": test_campaign.name,\n \"organisations\": [self.test_org.id],\n \"url\": test_campaign.url,\n },\n headers={\"Authorization\": self.session_token},\n )\n response_body = response.get_json()\n self.assertEqual(response.status_code, 409)\n self.assertEqual(response_body[\"Error\"], \" Campaign name already exists\")\n self.assertEqual(response_body[\"SubCode\"], \"NameExists\")","def exists(self, Search_ID):\n if self.get_id(Search_ID) is None:\n return False\n else:\n return True","def validateID(self, id : int) -> int:\n # If ID is a string, ensure it can be casted to an int before casting and returning.\n if type(id) == str:\n if not lib.stringTyping.isInt(id):\n raise TypeError(\"user ID must be either int or string of digits\")\n return int(id)\n # If ID is not a string, nor an int, throw an error.\n elif type(id) != int:\n raise TypeError(\"user ID must be either int or string of digits\")\n # ID must be an int, so return it.\n return id","def id_exists(show_id: int,\n database_connection: mysql.connector.connect) -> bool:\n return validate_id(show_id, database_connection)"],"string":"[\n \"def test_id_already_exists(self) -> None:\\n with pytest.raises(IntegrityError):\\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\\n 'description': 'A new filter type.'})\",\n \"def check_id(self, id):\",\n \"def testValidateId(self):\\n #create a different person and try to use their id\\n self.directory.invokeFactory(type_name=\\\"FSDPerson\\\",id=\\\"def456\\\",firstName=\\\"Joe\\\",lastName=\\\"Blow\\\")\\n self.failUnless('def456' in self.person.validate_id('def456'))\\n #create a different content object and try to use its id\\n self.directory.invokeFactory(\\\"Document\\\", \\\"mydoc\\\")\\n self.failUnless('mydoc' in self.person.validate_id('mydoc'))\",\n \"def check_repost_exists(type, id):\\n \\n try:\\n soundcloud.get('/e1/me/{}_reposts/{}'.format(type, id))\\n return True\\n except HTTPError as e:\\n if e.response.status_code == 404:\\n db.mark_as_deleted(type, id)\\n return False\\n else:\\n raise\",\n \"def test_resource_id(self):\\n resource_id = '1234-1234-1234'\\n\\n # resource id does not exist\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\\n\\n # create a resource ID\\n resp = self.app.post(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 201)\\n\\n # resource id exists\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # cannot create twice\\n resp = self.app.post(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 409)\\n\\n # delete resource id\\n resp = self.app.delete(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # resource id does not exist\\n resp = self.app.get(\\n f'/v1/resource/{self.test_resource}/id/{resource_id}',\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\",\n \"def ResourceExists(self, name):\\n pass\",\n \"def assert_has(self, type_id, message=''):\\n if self.first_by_id(type_id):\\n return\\n raise AssertionError(message)\",\n \"def does_resource_exist(resource):\\n try:\\n resource.load()\\n return True\\n except botocore.exceptions.ClientError as e:\\n if e.response['Error']['Code'] == 'ValidationError':\\n return False\\n else:\\n raise e\",\n \"def check_action_type_exists(\\n action_type_id: int\\n) -> None:\\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\\n raise errors.ActionTypeDoesNotExistError()\",\n \"def check_id_existence(self, id:str):\\n\\n oc_prefix = id[:(id.index(':')+1)]\\n\\n if oc_prefix == 'doi:':\\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\\n if oc_prefix == 'isbn:':\\n vldt = isbn.ISBNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'issn:':\\n vldt = issn.ISSNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'orcid:':\\n vldt = orcid.ORCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmcid:':\\n vldt = pmcid.PMCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmid:':\\n vldt = pmid.PMIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'ror:':\\n vldt = ror.RORManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'url:':\\n vldt = url.URLManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'viaf:':\\n vldt = viaf.ViafManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikidata:':\\n vldt = wikidata.WikidataManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikipedia:':\\n vldt = wikipedia.WikipediaManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\",\n \"def test_create_id_type(self):\\n self.assertIsInstance(Rectangle.create().id, int)\",\n \"def test_duplicate_flavorids_fail(self):\\n flavorid = 'flavor1'\\n instance_types.create('name one', 256, 1, 120, 200, flavorid)\\n self.assertRaises(exception.InstanceTypeIdExists,\\n instance_types.create,\\n 'name two', 256, 1, 120, 200, flavorid)\",\n \"def test_difference_id(self):\\n self.assertFalse(\\n self.factory.create_type('iphone') is self.factory.create_type(\\n 'iphone'))\",\n \"def validate_id(cls, id: str) -> ObjectId:\\n return ObjectId(id)\",\n \"def test_id_missing(self) -> None:\\n with pytest.raises(NotFound):\\n ObservationType.from_id(-1)\",\n \"def check_unique_element_id(cls, instance, element_id):\\n if not element_id:\\n return\\n try:\\n element_ids = instance.placeholder.page.cascadepage.glossary['element_ids'][instance.language]\\n except (AttributeError, KeyError, ObjectDoesNotExist):\\n return\\n else:\\n for key, value in element_ids.items():\\n if str(key) != str(instance.pk) and element_id == value:\\n msg = _(\\\"The element ID '{}' is not unique for this page.\\\")\\n raise ValidationError(msg.format(element_id))\",\n \"def test_duplicate_id(self):\\n with self.assertRaises(ValueError):\\n REANATemplate(\\n workflow_spec={},\\n parameters=[\\n pd.parameter_declaration('A', index=1),\\n pd.parameter_declaration('B'),\\n pd.parameter_declaration('C'),\\n pd.parameter_declaration('A', index=2),\\n pd.parameter_declaration('E', index=1)\\n ],\\n validate=True\\n )\",\n \"def test_create_resource(self):\\n test_resource = ResourceTypeName.get() # the name of the resource type to create\\n\\n # the resource type should not exist yet\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\\n\\n # create the resource type\\n resp = self.app.post(f'/v1/resource/{test_resource}', data=json.dumps({'actions': ['tr:action1']}),\\n headers=admin_headers)\\n self.assertEqual(resp.status_code, 201)\\n\\n # the resource type exists\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # delete the resource type\\n resp = self.app.delete(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 200)\\n\\n # the resource type should not exist\\n resp = self.app.get(f'/v1/resource/{test_resource}', headers=admin_headers)\\n self.assertEqual(resp.status_code, 404)\",\n \"def _validate_create(context, db_api, create_data, model_name):\\n ipaddrlist = utils.get_addresses(create_data['ip_address'])\\n\\n if not ipaddrlist:\\n errors = (_(\\\"Failed to register (%s)\\\" +\\n \\\". The (%s) IP Address (%s) could not \\\"\\n \\\"be resolved.\\\")\\n % (model_name, model_name, create_data['ip_address']))\\n raise exception.AddressResolutionFailure(reason=errors)\\n LOG.info(\\\"IP/FQDN for the \\\" + model_name + \\\" %s is %s\\\" % (\\n create_data['ip_address'],\\n ipaddrlist))\\n try:\\n get_all = getattr(db_api, \\\"get_all_%ss\\\" % model_name)\\n res_data = get_all(context)\\n if not res_data:\\n # No registered resources\\n LOG.info(\\\"No registered %s\\\" % model_name)\\n return\\n except Exception:\\n errors = (_(\\\"Failed to retrieve data for (%s) %s\\\")\\n % (model_name, create_data.get('ip_address')))\\n raise exception.InternalFailure(reason=errors)\\n name = create_data.get(\\\"name\\\")\\n valid_name = _validate_duplicate_names(res_data, name)\\n if not valid_name:\\n msg = (_(\\\"Two different (%s) with same \\\"\\n \\\"name cannot be registered\\\") % model_name)\\n raise exception.ResourceExists(reason=msg)\\n registered_data = []\\n for data in res_data:\\n registered_data.append(data['ip_address'])\\n\\n if set(ipaddrlist).intersection(set(registered_data)):\\n errors = (_(\\\"(%s) by ip_address (%s) already exists.\\\")\\n % (model_name, create_data['ip_address']))\\n raise exception.ResourceExists(reason=errors)\",\n \"def test_will_not_get_instance_type_with_bad_id(self):\\n self.assertRaises(exception.InstanceTypeNotFound,\\n instance_types.get_instance_type, 'asdf')\",\n \"def test_check_resource(self):\\n s1 = System()\\n b1 = Books(\\\"1984\\\", \\\"George Orwell\\\", \\\"Harvill Secker\\\", \\\"1949\\\", \\\"0123456789123\\\")\\n self.assertEqual(s1.check_resource(b1), False)\\n s1.add_resource(b1)\\n self.assertEqual(s1.check_resource(b1), True)\",\n \"def resourceExists(node, name = None, resourceType = PROP_RESOURCE_TYPE_RESOURCE):\\n \\n exists = False\\n if not node:\\n return exists\\n try:\\n myResourceType = \\\"\\\"\\n if name:\\n # make sure it's unicode:\\n if not isinstance(name, str):\\n name = name.decode(sys.getfilesystemencoding())\\n url = node.url\\n if url.endswith(\\\"/\\\"):\\n url = url + name\\n else:\\n url = url + \\\"/\\\" + name\\n newNode = ResourceStorer(url, node.connection)\\n element = newNode.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\\n else: # name is \\\"None\\\":\\n element = node.readProperty(NS_DAV, PROP_RESOURCE_TYPE)\\n \\n if len(element.children) > 0:\\n myResourceType = element.children[0].name\\n if resourceType == myResourceType or resourceType == PROP_RESOURCE_TYPE_RESOURCE:\\n exists = True\\n else:\\n exists = False\\n except WebdavError as wderr:\\n if wderr.code == CODE_NOT_FOUND:\\n # node doesn't exist -> exists = False:\\n exists = False\\n else:\\n # another exception occured -> \\\"re-raise\\\" it:\\n raise\\n return exists\",\n \"def is_resource_id(schema_obj):\\n\\n if isinstance(schema_obj, schema.Field):\\n return is_resource_id(schema_obj.metadata)\\n elif isinstance(schema_obj, schema.Struct):\\n return schema_obj.full_name == 'weave.common.ResourceId'\\n return False\",\n \"def is_existing_object(did):\\n if not d1_gmn.app.did.is_existing_object(did):\\n raise d1_common.types.exceptions.NotFound(\\n 0,\\n \\\"Identifier is {}. Expected a Persistent ID (PID) for an existing \\\"\\n 'object. id=\\\"{}\\\"'.format(d1_gmn.app.did.classify_identifier(did), did),\\n identifier=did,\\n )\",\n \"def test_will_not_get_instance_type_by_unknown_id(self):\\n self.assertRaises(exception.InstanceTypeNotFound,\\n instance_types.get_instance_type, 10000)\",\n \"def validate_id(ctx, param, value):\\r\\n try:\\r\\n if value is None:\\r\\n return None\\r\\n obj = optiga.Object(int(value, base=16))\\r\\n obj = obj.meta\\r\\n return int(value, base=16)\\r\\n except (ValueError, TypeError, OSError) as no_object:\\r\\n raise click.BadParameter(\\\"Object ID doesn't exist. Please align with the Objects map\\\") from no_object\",\n \"def taco_test_put_error_requires_id(self):\\n body = '{ \\\"id\\\": 400, \\\"name\\\": \\\"item_new\\\", \\\"content\\\": \\\"after test update\\\" }'\\n env = self.get_env('PUT', '/item', body=body)\\n webapi_start(env, lambda status, response_headers: self.assertEqual(status, '501'))\",\n \"def _create_resource(resource, **options):\\n global _existing\\n\\n if _existing[resource]:\\n print('{r} {k}:{v} already exists with id {i}.'.format(\\n r=resource,\\n k=args.tag,\\n v=args.role,\\n i=_existing[resource].id\\n ))\\n return True\\n\\n print('{v} a {r} with parameters: {p}...'.format(\\n v='Would create' if dry else 'Creating',\\n r=resource,\\n p=str(options)\\n ))\\n\\n if dry:\\n return True\\n\\n # All easy cases out of the way, we now need to actually create something.\\n r = None\\n try:\\n r = getattr(ec2, definitions[resource].create)(** options)\\n # In some cases (instance) a list is returned instead of one item. Quack!\\n try:\\n r = r[0]\\n except:\\n pass\\n _tag_resource(r)\\n print('... {r} id {i} created.'.format(\\n r=resource,\\n i=r.id\\n ))\\n _existing[resource] = r\\n return True\\n except Exception as e:\\n if r is None:\\n print('Could not create resource {r}.'.format(\\n r=resource\\n ))\\n traceback.print_exc()\\n else:\\n print('Could not tag resource {r}, id {i}.'.format(\\n r=resource,\\n i=r.id\\n ))\\n traceback.print_exc()\\n _destroy_resource(resource)\\n return False\",\n \"def validate_identifier(self, identifier):\\n pass\",\n \"def needs_unique_instance(type_):\\n return type_ in unique_instance_types\",\n \"def _validate_call_id(self, call_id):\\n\\n self._validate_required_data(call_id, self.CALL_ID)\\n\\n query = CallRecord.objects.filter(call_id=call_id)\\n\\n if query.exists():\\n raise NotAcceptable(\\n detail='Call id is already in use. Please, choose another')\",\n \"def identify_id(id: str) -> bool:\\n return validate_handle(id)\",\n \"def test_create_id_identity(self):\\n self.assertIs(Rectangle.create(id=True).id, True)\\n self.assertIs(Rectangle.create(id=type).id, type)\\n self.assertIs(Rectangle.create(id=None).id, None)\",\n \"def validate_user_id(self, value):\\n if not User.objects.filter(id=value).exists():\\n raise serializers.ValidationError('User with this id does not exist.')\\n return value\",\n \"def validate(self):\\n # Validate all mandatory keys are present\\n if not self.mandatory_keys.issubset(set(self.resource)):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] miss a \\\"\\n \\\"mandatory key. Please check the model.\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id))\\n\\n # Validate the resource does not contains extra keys\\n if not set(self.resource).issubset(self.keys):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] contains \\\"\\n \\\"extra keys. Please check the model.\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id))\\n\\n # Validate the resource value type\\n for key, value in self.resource.items():\\n if not isinstance(value, self.__class__.MODEL[key][0]):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data type (expected: %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][0]))\\n # For str type validate the content as according the regex\\n if self.__class__.MODEL[key][0] is str:\\n if not re.match(self.__class__.MODEL[key][1], value):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data content (expected match : %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][1]))\\n # For list type validate the content as according the regex\\n if self.__class__.MODEL[key][0] is list:\\n if not all([re.match(self.__class__.MODEL[key][1], v)\\n for v in value]):\\n raise ResourceInvalidException(\\n \\\"Resource [type: %s, ID: %s] has an invalid \\\"\\n \\\"key (%s) data content (expected match : %s)\\\" % (\\n self.__class__.MODEL_TYPE,\\n self.id,\\n key,\\n self.__class__.MODEL[key][1]))\",\n \"def test_check_input_id(self):\\n r3 = Rectangle(10, 2, 0, 0, 12)\\n self.assertEqual(r3.id, 12)\",\n \"def resource(\\n name: str,\\n *,\\n mime_type: str,\\n parent_folder_id: drive_api.ResourceID,\\n drive_service: Optional[discovery.Resource] = None,\\n) -> drive_api.ResourceID:\\n command = request(\\n name,\\n mime_type=mime_type,\\n parent_folder_id=parent_folder_id,\\n drive_service=drive_service,\\n )\\n result = command.execute()\\n new_id: drive_api.ResourceID = result.get(\\\"id\\\")\\n return new_id\",\n \"def test_bad_id(self):\\n r1 = Square(10, 2)\\n self.assertEqual(r1.id, 1)\\n\\n r2 = Square(2, 10)\\n self.assertEqual(r2.id, 2)\",\n \"def validatePredefinedType(self, type: int) -> bool:\\n ...\",\n \"def validate_resources(self, folder, resources):\\r\\n self.validate_files_exist(folder, resources)\\r\\n self.validate_no_duplicate_paths(resources)\",\n \"def __validateResourceStateEntry(self, resource: Dict[str, str]):\\n if AZ_RESOURCE_ID not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (\\n self.fullName, AZ_RESOURCE_ID))\\n if SID not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (self.fullName, SID))\\n if ARM_TYPE not in resource:\\n raise ValueError(\\n '[%s] %s is not present in the armMapping.' % (self.fullName, ARM_TYPE))\",\n \"def validate_id(self, value):\\n try:\\n Tutor.objects.get(pk=value)\\n except Tutor.DoesNotExist:\\n raise serializers.ValidationError('Tutor object with id \\\\'{}\\\\' does not exist.'.format(value))\\n return value\",\n \"def test_readable_id_invalid(readable_id_value):\\n program = ProgramFactory.build(readable_id=readable_id_value)\\n with pytest.raises(ValidationError):\\n program.save()\\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\\n with pytest.raises(ValidationError):\\n course.save()\",\n \"def test_api_update_book_with_id_does_not_exist(self):\\n\\n\\t\\tlogin_data = self.login_test_user()\\n\\t\\ttoken = login_data['auth_token']\\n\\n\\t\\tbook = self.client.put(\\n\\t\\t\\tf'{URL_BOOKS}/1',\\n\\t\\t\\theaders=dict(Authorization=f'Bearer {token}'),\\n\\t\\t\\tcontent_type='application/json',\\n\\t\\t\\tdata=json.dumps(\\n\\t\\t\\t\\tdict(\\n\\t\\t\\t\\t\\ttitle='updated book'\\n\\t\\t\\t\\t)\\n\\t\\t\\t)\\n\\t\\t)\\n\\n\\t\\tbook_res = json.loads(book.data.decode())\\n\\t\\tself.assertTrue(book_res['message'] == 'book with id 1 does not exist')\\n\\t\\tself.assertTrue(book_res['status'] == 'error')\",\n \"def test_check_id(self):\\n r1 = Rectangle(2, 10)\\n r2 = Rectangle(2, 10)\\n r3 = Rectangle(2, 10)\\n self.assertGreater(r2.id, r1.id)\\n self.assertGreater(r3.id, r2.id)\",\n \"def create_resource(self, resource, resource_data, resource_type, **kwargs):\\n if not isinstance(resource, Resource):\\n raise KeyError(\\\"'resource' should be an instance of Resource\\\")\\n if not isinstance(resource_data, ResourceData) or not resource_data.value:\\n raise KeyError(\\n \\\"'resource_data' should be ResourceData with 'value' attribute\\\")\\n if not isinstance(resource_type, ResourceType):\\n raise KeyError(\\\"'resource_type' should be an instance of ResourceType\\\")\\n if not kwargs or 'feed_id' not in kwargs:\\n raise KeyError('Variable \\\"feed_id\\\" id mandatory field!')\\n\\n resource_id = urlquote(resource.id, safe='')\\n r = self._post('entity/f;{}/resource'.format(kwargs['feed_id']),\\n data={\\\"name\\\": resource.name, \\\"id\\\": resource.id,\\n \\\"resourceTypePath\\\": \\\"rt;{}\\\"\\n .format(resource_type.path.resource_type_id)})\\n if r:\\n r = self._post('entity/f;{}/r;{}/data'\\n .format(kwargs['feed_id'], resource_id),\\n data={'role': 'configuration', \\\"value\\\": resource_data.value})\\n else:\\n # if resource or it's data was not created correctly, delete resource\\n self._delete('entity/f;{}/r;{}'.format(kwargs['feed_id'], resource_id))\\n return r\",\n \"def checkValidId(self, id, prep_id = False):\\n new_id = unquote(id)\\n if prep_id: new_id = self.prepId(id)\\n try:\\n globalCheckValidId(self, new_id)\\n return True\\n except Exception:\\n return str(sys.exc_info()[1])\",\n \"def resource_exists(self, resource):\\n products = Product.select(self.env, where={'name' : resource.id})\\n return bool(products)\",\n \"def test_cannot_add_existing_asset_code(self):\\n self.assertEqual(self.all_assets.count(), 1)\\n asset_code = \\\"IC002\\\"\\n new_asset = Asset(asset_code, \\\"SN001\\\")\\n with self.assertRaises(ValidationError):\\n new_asset.save()\\n self.assertEqual(self.all_assets.count(), 1)\",\n \"def send_error_missing_id(message, obj_type):\\n return make_response(jsonify({\\\"validation_error\\\": {\\n \\\"error\\\": 'Missing id',\\n \\\"object_type\\\": obj_type,\\n \\\"description\\\": message\\n }}), 400)\",\n \"def test_init_id_identity(self):\\n self.assertIs(Rectangle(1, 1, id=True).id, True)\\n self.assertIs(Rectangle(1, 1, id=type).id, type)\",\n \"def id_exists(host_id: int,\\n database_connection: mysql.connector.connect) -> bool:\\n return validate_id(host_id, database_connection)\",\n \"def _validate_duplicate_names(res_data, name, _id=None):\\n if _id:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name and data.get(\\\"id\\\") != _id:\\n return False\\n return True\\n else:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name:\\n return False\\n return True\",\n \"def validate(self):\\n try:\\n # update _resource to have default values from the schema\\n self._resource = self.schema(self._resource)\\n except MultipleInvalid as e:\\n errors = [format_error(err, self.resource_type) for err in e.errors]\\n raise exceptions.ValidationError({'errors': errors})\\n\\n yield self.check_unique()\",\n \"def _uniqueness_check(self, cls, unique_in = None, **attr):\\n # under the same datasource, only 1 subsystem, 1 neuropil, 1 tract of the name can exist\\n # under the same neuropil, only 1 neuron of the name can exist\\n # multiple (collections of) synapses can exist between two neurons\\n if cls == 'Species':\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from Species where (name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) and stage = \\\"{stage}\\\" and sex = \\\"{sex}\\\" \\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex']))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"Species {name} at {stage} stage ({sex}) already exists with rid = {rid}\\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = objs[0]._id))\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"Species {name} (as its synonym) at {stage} stage ({sex}) already exists with rid = {rid}, use name {formalname} instead\\\"\\\"\\\".format(\\n name = attr['name'], stage = attr['stage'], sex = attr['sex'], rid = obj._id, formalname = obj.name))\\n elif cls == 'DataSource':\\n objs = self.find_objs('DataSource', name=attr['name'], version=attr['version'])\\n #if self.exists(cls, name = attr['name'], version = attr['version']):\\n if len(objs):\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{} Node with attributes {} already exists with rid = {}\\\"\\\"\\\".format(\\n cls, ', '.join([\\\"\\\"\\\"{} = {}\\\"\\\"\\\".format(key, value) \\\\\\n for key, value in attr.items()]), objs[0]._id))\\n elif cls == 'Neurotransmitter':\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from Neurotransmitter where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\\"\\\"\\\".format(\\n name = attr['name']))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"Neurotransmitter {name} already exists with rid = {rid}\\\"\\\"\\\".format(\\n name = attr['name'], rid = objs[0]._id))\\n return objs\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"Neurotransmitter {name} (as its synonym) already exists with rid = {rid}, use name {formalname} instead\\\"\\\"\\\".format(\\n name = attr['name'], rid = obj._id, formalname = obj.name))\\n elif cls in ['Subsystem', 'Neuropil', 'Subregion', 'Tract']:\\n # TODO: synonyms are not checked against existing names and synonyms\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'],\\n ds = unique_in.name,\\n version = unique_in.version, rid = objs[0]._id))\\n else:\\n for obj in objs:\\n if attr['name'] in obj.synonyms:\\n raise NodeAlreadyExistError(\\n \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'], formalname = obj.name,\\n ds = unique_in.name,\\n version = unique_in.version, rid = obj._id))\\n # Alternatively, try:\\n # tmp = self.sql_query(\\n # \\\"\\\"\\\"select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name']))\\n # ds = tmp.owned_by(cls = 'DataSource').has(rid = datasource)\\n # if len(ds):\\n # tmp1 = tmp.has(name = attr['name'])\\n # if len(tmp1.owned_by(cls = 'DataSource').has(rid = datasource)):\\n # raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'],\\n # ds = datasource.name,\\n # version = datasource.version))\\n # else:\\n # all_synonym_objs = (tmp - tmp1).node_objs\\n # for obj in objs:\\n # if len(QueryWrapper.from_rids(obj._id).has(cls = 'DataSource').has(rid = datasource)):\\n # raise NodeAlreadyExistError(\\n # \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'], formalname = obj.name,\\n # ds = datasource.name,\\n # version = datasource.version))\\n\\n # Alternatively 2, try: (will be slow when it has a lot of Owns edges)\\n # tmp = sql_query(\\n # \\\"\\\"\\\"\\n # select from (select expand(out('Owns')[@class = \\\"{cls}\\\"]) from {rid}) where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms\\n # \\\"\\\"\\\"\\n # )\\n # elif cls in ['Subregion']:\\n # if not isinstance(unique_in, models.Neuropil):\\n # raise TypeError('To check the uniqueness of a {} instance, unique_in must be a Neuropil object'.format(cls))\\n # tmp = self.sql_query(\\n # \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\" or \\\"{name}\\\" in synonyms) let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='ucls' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n # rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n # if len(tmp):\\n # objs = tmp.node_objs\\n # if attr['name'] in [obj.name for obj in objs]:\\n # raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under Neuropil {ds}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'],\\n # ds = unique_in.name))\\n # else:\\n # for obj in objs:\\n # if name in obj.synonyms:\\n # raise NodeAlreadyExistError(\\n # \\\"\\\"\\\"{cls} {name} already exists as a synonym of {cls} {formalname} under Neuropil {ds}\\\"\\\"\\\".format(\\n # cls = cls, name = attr['name'], formalname = obj.name,\\n # ds = unique_in.name))\\n elif cls in ['Neuron', 'NeuronFragment']:\\n # TODO: synonyms are not checked against existing names and synonyms\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where uname = \\\"{name}\\\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists with rid = {rid}, under DataSource {ds} version {version}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'], rid = objs[0]._id,\\n ds = unique_in.name,\\n version = unique_in.version))\\n elif cls == 'Circuit':\\n if not isinstance(unique_in, models.DataSource):\\n raise TypeError('To check the uniqueness of a {} instance, unique_in must be a DataSource object'.format(cls))\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select from {cls} where name = \\\"{name}\\\") let $q = (select from (select expand($parent.$parent.current.in('Owns'))) where @class='{ucls}' and @rid = {rid}) where $q.size() = 1\\\"\\\"\\\".format(\\n rid = unique_in._id, cls = cls, name = attr['name'], ucls = unique_in.element_type))\\n if len(tmp):\\n objs = tmp.node_objs\\n if attr['name'] in [obj.name for obj in objs]:\\n raise NodeAlreadyExistError(\\\"\\\"\\\"{cls} {name} already exists under DataSource {ds} version {version}, rid = {rid}\\\"\\\"\\\".format(\\n cls = cls, name = attr['name'],\\n ds = unique_in.name,\\n version = unique_in.version, rid = objs[0]._id))\\n elif cls == 'ArborizationData':\\n if not isinstance(unique_in, (models.Neuron, models.Synapse)):\\n raise TypeError('To check the uniqueness of a ArborizationData instance, unique_in must be a Neuron or a Synapse object')\\n tmp = self.sql_query(\\n \\\"\\\"\\\"select from (select expand(out(HasData)) from {rid}) where @class = 'ArborizationData' \\\"\\\"\\\".format(rid = unique_in._id))\\n if len(tmp):\\n raise NodeAlreadyExistError(\\\"\\\"\\\"ArborizationData already exists for {node} {uname} with rid = {rid}. Use NeuroArch.update_{node}_arborization to update the record\\\"\\\"\\\".format(\\n node = unique_in.element_type.lower(), rid = tmp.node_objs[0]._id, uname = unique_in.uname))\\n else:\\n raise TypeError('Model type not understood.')\\n return True\",\n \"def is_resource(space, w_obj):\\n return space.wrap(space.is_resource(w_obj))\",\n \"def is_valid_pid_for_create(did):\\n if not d1_gmn.app.did.is_valid_pid_for_create(did):\\n raise d1_common.types.exceptions.IdentifierNotUnique(\\n 0,\\n 'Identifier is already in use as {}. did=\\\"{}\\\"'.format(\\n d1_gmn.app.did.classify_identifier(did), did\\n ),\\n identifier=did,\\n )\",\n \"def test_validation_idaa_valid_and_exists(self):\\n expected_discrepancies = 0\\n\\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][self.create_idaa_program_index]['fields'],\\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\\n )\\n\\n self.assertTrue(upload_program.is_valid())\\n self.assertTrue(upload_program.tola_program_exists)\\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)\",\n \"def _check_for_preexisting_identifier(self, doi: Doi):\\n # The database expects each field to be a list.\\n query_criterias = {\\\"ids\\\": [doi.pds_identifier]}\\n\\n # Query database for rows with given id value.\\n columns, rows = self._database_obj.select_latest_rows(query_criterias)\\n\\n for row in rows:\\n existing_record = dict(zip(columns, row))\\n\\n if doi.doi != existing_record[\\\"doi\\\"]:\\n raise IllegalDOIActionException(\\n f\\\"There is already a DOI {existing_record['doi']} associated \\\"\\n f\\\"with PDS identifier {doi.pds_identifier} \\\"\\n f\\\"(status={existing_record['status']}).\\\\n\\\"\\n f\\\"You cannot modify a DOI for an existing PDS identifier.\\\"\\n )\",\n \"def existence_validation(self, request, *args, **kwargs):\\n lection_id = self.kwargs.get('lection_id')\\n course_id = self.kwargs.get('course_id')\\n lection = Lection.objects.filter(Q(course_id=course_id) & Q(id=lection_id)).first()\\n error = {'error': f\\\"Either lection with ID{lection_id} doesn't belong to course with ID{course_id}, \\\"\\n f\\\"or doesn't exist.\\\"}\\n if lection:\\n return method(self, request, *args, **kwargs)\\n return Response(error, status=status.HTTP_403_FORBIDDEN)\",\n \"def test_init_id_type(self):\\n self.assertIsInstance(Rectangle(1, 1).id, int)\\n self.assertIsInstance(Rectangle(1, 1, id=None).id, int)\",\n \"def add_existing_key_fail(self, data):\\n message = 'exists'\\n rv = self.add_success(data)\\n assert not in_response(rv, message)\\n return self.add_fail(data, message)\",\n \"def test_get_by_id_wrong_type(self):\\n assert ExampleUserModel.get_by_id(\\\"xyz\\\") is None\",\n \"def test_get_event_type_by_id_invalid_id(self):\\n\\t\\trequest = self.client.get('/api/event_type/esper/0', follow=True)\\n\\t\\tself.assertEqual(request.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def test_resource_exists(self):\\r\\n\\t\\tself.assertTrue(self._configuration_.resources().has_key(\\\"AddWordTaskRepeat\\\") and self._configuration_.resources().has_key(\\\"RemoveWordTaskRepeat\\\"))\",\n \"def test_register_subscription_existing_type(self):\\n mock_type = Mock()\\n bus = event_bus._event_bus\\n bus._subscriptions[mock_type] = [\\n EventSubscription(mock_type, lambda _: None)]\\n new_subscription = EventSubscription(mock_type, lambda _: True)\\n\\n reg_id = event_bus.register_subscription(new_subscription)\\n\\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\\n self.assertTrue(reg_id in bus._registration_id_map.keys())\",\n \"def test_add_resource(self):\\n s1 = System()\\n b1 = Books(\\\"1984\\\", \\\"George Orwell\\\", \\\"Harvill Secker\\\", \\\"1949\\\", \\\"0123456789123\\\")\\n self.assertNotIn(b1, s1.catalogue)\\n s1.add_resource(b1)\\n self.assertIn(b1, s1.catalogue)\\n s1.add_resource(b1)\\n self.assertEqual(len(s1.catalogue), 1)\",\n \"def check_existed_did(self):\\n for wallet in self.wallet_state_manager.wallets.values():\\n if (\\n wallet.type() == WalletType.DECENTRALIZED_ID\\n and self.did_info.origin_coin.name() == wallet.did_info.origin_coin.name()\\n ):\\n self.log.warning(f\\\"DID {self.did_info.origin_coin} already existed, ignore the wallet creation.\\\")\\n raise ValueError(\\\"Wallet already exists\\\")\",\n \"def _resource_name_check(self, resource_name):\\n return self._name_check(resource_name, 'resources')\",\n \"def validate(self, entity_id):\\n\\n safe_entity = self.find_by_id(entity_id)\\n if not safe_entity:\\n raise EntityNotFound(\\\"The param_id = {} is not valid.\\\".format(entity_id))\\n\\n return safe_entity\",\n \"def check_status(self, id):\\n raise NotImplementedError()\",\n \"def test_cannot_add_existing_serial_number(self):\\n self.assertEqual(self.all_assets.count(), 1)\\n serial_number = \\\"SN001\\\"\\n new_asset = Asset(serial_number, \\\"SN001\\\")\\n with self.assertRaises(ValidationError):\\n new_asset.save()\\n self.assertEqual(self.all_assets.count(), 1)\",\n \"def delete_does_not_exist_fail(self, id_):\\n assert is_404(self.get((id_, self.delete_url)))\\n self.delete_fail(id_, 'does not exist')\",\n \"def test_readable_id_valid(readable_id_value):\\n program = ProgramFactory.build(readable_id=readable_id_value)\\n program.save()\\n assert program.id is not None\\n course = CourseFactory.build(program=None, readable_id=readable_id_value)\\n course.save()\\n assert course.id is not None\",\n \"def validated_id(cls, name):\\n if name:\\n if name in cls._ids:\\n return cls._ids[name]\\n if cls.validated_name(name):\\n if Accounts.exists(name):\\n return cls.get_id(name)\\n return None\",\n \"def ResourceExists(resource_name, search_user_paths=True):\\n try:\\n ResourcePath(resource_name, search_user_paths)\\n return True\\n except ResourceNotFound:\\n return False\",\n \"def test_get_event_type_by_id_not_found(self):\\n\\t\\tevent_type = EventType.objects.get(name=\\\"asd\\\")\\n\\t\\trequest = self.client.get('/api/event_type/esper/' + str(event_type.id + 1), follow=True)\\n\\t\\tself.assertEqual(request.status_code, status.HTTP_404_NOT_FOUND)\",\n \"def test_create_with_bad_id(self):\\n # Count the number of records before the save\\n existing_records_count = Track.objects.all().count()\\n post_data = {'source_type': 'spotify', 'source_id': 00}\\n resp = self.api_client.post('/api/metadata/tracks/', data=post_data)\\n data = json.loads(resp.content)\\n new_records_count = Track.objects.all().count()\\n\\n # Ensure the request filed with a 404, and an error message is returned\\n self.assertEqual(resp.status_code, 404)\\n self.assertEqual(existing_records_count, new_records_count)\\n self.assertEqual(data['detail'], u'The record could not be found.')\",\n \"def is_resource(self, path):\\n # type: (Text) -> bool\\n raise FileNotFoundError\",\n \"def validate_new_person(self, person_id):\\n\\n self.db_cursor.execute(\\\"\\\"\\\"SELECT COUNT(*) FROM Person WHERE id == %s\\\"\\\"\\\", (person_id,))\\n ct = self.db_cursor.fetchone()\\n ct = ct[0]\\n if ct == 0:\\n return False\\n return True\",\n \"async def test_create_invalid_field(self):\\n data = {'id': 33, 'value': 'foo'}\\n with self.assertRaises(InvalidResourceDetails) as cm:\\n await self.resource.create(data)\\n self.assertEqual(\\n 'Error: \\\"id\\\": 33 is not a string: {\\\\'id\\\\': \\\\'\\\\'}',\\n str(cm.exception))\",\n \"def update_object_type(self, object_type=None):\\n # Return Value\\n # ------------\\n # {success: true}\\n #\\n if not is_basic_identifier(object_type.name):\\n raise BadRequest(\\\"Invalid object_type name: %s\\\" % object_type.name)\\n if not is_yaml_string_valid(object_type.definition):\\n raise BadRequest(\\\"Invalid YAML definition\\\")\\n object_id, version = self.clients.resource_registry.update(object_type)\\n return object_id\",\n \"def find_by_id(cls, id):\\n\\t\\tif id:\\n\\t\\t\\treturn cls.query.filter_by(id=id).first()\\n\\t\\treturn {\\n\\t\\t\\t'message': 'id field is required',\\n\\t\\t\\t'status': 'Failed'\\n\\t\\t\\t}, 400\",\n \"def validateID(id):\\n\\n if re.compile('[0-9]+').match(id) == None:\\n output.completeOutputError(InvalidArgumentCount(descape =\\\"'%s' is not a valid Id. ID should be numeric with Length = '%s' \\\" \\n\\t\\t\\t% (id, lib.constants._ATTR_ID_LENGHT)))\\n return -1\\n else:\\n # Check for the lenght \\n counter = 0\\n for char in id:\\n counter += 1\\n print counter , lib.constants._ATTR_ID_LENGHT\\n if counter > lib.constants._ATTR_ID_LENGHT :\\n output.completeOutputError(InvalidArgumentCount(descape =\\\"'%s' exceeded the given length i.e Max Length = '%s'\\\" % \\n\\t\\t\\t(id, lib.constants._ATTR_ID_LENGHT)))\\n return -1\\n else:\\n return 0\\n return 0\",\n \"def test_id_uniqueness(self):\\n user_2 = User()\\n self.assertNotEqual(self.user_1.id, user_2.id)\",\n \"def sanity_check(cls, data, ticket_id=None):\\n if ticket_id is not None:\\n ticket_id = int(ticket_id)\\n ticket = DB_TICKET_TABLE.get(doc_id=ticket_id)\\n if not ticket:\\n flask_restful.abort(404, message=f\\\"ticket '{ticket_id}' not found!\\\")\\n else:\\n ticket = None\\n\\n # A custom validator to make sure the aportio ID remains unique\\n def validate_aportio_id(aportio_id):\\n if not isinstance(aportio_id, str):\\n raise ValueError(\\\"expected string type for aportio ID\\\")\\n TicketQuery = Query()\\n ticket_with_aportio_id = DB_TICKET_TABLE.get(\\n TicketQuery.aportio_id == aportio_id)\\n if ticket_with_aportio_id and (ticket_with_aportio_id.doc_id != ticket_id):\\n raise ValueError(f\\\"a ticket with aportio ID '{aportio_id}' \\\"\\n f\\\"exists already\\\")\\n return aportio_id\\n\\n # A custom validator for the short title\\n def validate_short_title(text):\\n return _str_len_check(text, cls.SHORT_TITLE_MIN_LEN, cls.SHORT_TITLE_MAX_LEN)\\n\\n # A custom validator for the long text\\n def validate_long_text(text):\\n return _str_len_check(text, cls.LONG_TEXT_MIN_LEN, cls.LONG_TEXT_MAX_LEN)\\n\\n # Perform some sanity checking of the provided attributes\\n data = _dict_sanity_check(data,\\n mandatory_keys = [\\n (\\\"aportio_id\\\", validate_aportio_id),\\n (\\\"customer_id\\\", Customer.exists),\\n (\\\"short_title\\\", validate_short_title),\\n (\\\"user_id\\\", User.exists),\\n (\\\"status\\\", Ticket.valid_status),\\n (\\\"classification\\\", Ticket.valid_classification),\\n (\\\"long_text\\\", validate_long_text)\\n ],\\n optional_keys = [\\n (\\\"custom_fields\\\", dict)\\n ],\\n obj=ticket)\\n # Now check whether this user is even associated with that customer\\n cust_id = data['customer_id']\\n user_id = data['user_id']\\n assoc_q = Query()\\n assoc_data = DB_USER_CUSTOMER_RELS_TABLE.search((assoc_q.customer_id == cust_id) &\\n (assoc_q.user_id == user_id))\\n if not assoc_data:\\n flask_restful.abort(400, message=f\\\"Bad Request - user '{user_id}' is not \\\"\\n f\\\"associated with customer '{cust_id}'\\\")\\n return data, ticket\",\n \"def test_exists(self):\\n with self.assertRaises(IncompetentQiitaDeveloperError):\\n BaseSample.exists('SKM7.640188', SampleTemplate(1))\",\n \"def test_validation_idaa_valid_and_does_not_exists(self):\\n idaa_index = 1\\n expected_discrepancies = 0\\n\\n upload_program = program.ProgramUpload(idaa_program=self.idaa_json['value'][idaa_index]['fields'],\\n msr_country_codes_list=msr_country_codes_list, msr_gaitid_list=msr_gaitid_list, duplicated_gaitids=self.duplicated_gaitids\\n )\\n\\n self.assertTrue(upload_program.is_valid())\\n self.assertFalse(upload_program.tola_program_exists)\\n self.assertEquals(upload_program.discrepancy_count, expected_discrepancies)\",\n \"def _check_id(self, keyword):\\n if keyword not in self.request.data:\\n return '{} parameter is missing'.format(keyword)\\n \\\"\\\"\\\" Check if <keyword> parameter is not None \\\"\\\"\\\"\\n if self.request.data[keyword] == '':\\n return '{} ID cannot be None'.format(keyword)\\n \\\"\\\"\\\" Check if <keyword> parameter is > 0 \\\"\\\"\\\"\\n if int(self.request.data[keyword]) < 1:\\n return '{} ID must be an integer > 0'.format(keyword)\",\n \"def exists(self, obj):\\n return False\",\n \"def _check_subject_id(subject_id):\\n if (subject_id and\\n len(subject_id) > models.Subject.id.property.columns[\\n 0].type.length):\\n raise exception.SubjectNotFound()\",\n \"def test_validate_post_existing_resource(client):\\n response = client.post(\\n '/user/',\\n data=json.dumps({\\n 'name': 'Jeff Knupp',\\n 'email': 'jknupp@gmail.com',\\n }),\\n headers={'Content-Type': 'application/json'}\\n )\\n assert response.status_code == 400\\n assert response.json['message'] == INVALID_ACTION_MESSAGE\",\n \"def verify_object(self, data):\\n rv = self.get(data[self.id_field])\\n result = not is_404(rv)\\n if result:\\n for key, value in data:\\n if not in_response(rv, value):\\n return False\\n return result\",\n \"def validate_item_id(idx):\\n item = ItemModel.query.get(idx)\\n if item is None:\\n raise NotFound(f'Item with id {idx} not found.')\\n return item\",\n \"def test_data_type_id(self):\\n self.assertTrue(self.tester.data_type(ret_id=True), 2)\",\n \"def check_person_existence(self, searched_person_id):\\n self.__load_persons_from_file_into_memory()\\n return super().check_person_existence(searched_person_id)\",\n \"def check_instance(self, class_name, inst_id, stored_objects):\\n '''get '<class_name>.id' to FileStorage.__objects key format'''\\n instance = \\\"{}.{}\\\".format(class_name, inst_id)\\n if instance not in stored_objects:\\n \\\"\\\"\\\"given id does not exist\\\"\\\"\\\"\\n print(\\\"** no instance found **\\\")\\n instance = False\\n return instance\",\n \"def test_create_already_existing_campaign_fails(self):\\n test_campaign = return_canned_campaign()\\n self.test_org.campaign = [test_campaign]\\n test_campaign.save()\\n response = self.client.post(\\n self.endpoint_url,\\n json={\\n \\\"logo\\\": test_campaign.logo,\\n \\\"name\\\": test_campaign.name,\\n \\\"organisations\\\": [self.test_org.id],\\n \\\"url\\\": test_campaign.url,\\n },\\n headers={\\\"Authorization\\\": self.session_token},\\n )\\n response_body = response.get_json()\\n self.assertEqual(response.status_code, 409)\\n self.assertEqual(response_body[\\\"Error\\\"], \\\" Campaign name already exists\\\")\\n self.assertEqual(response_body[\\\"SubCode\\\"], \\\"NameExists\\\")\",\n \"def exists(self, Search_ID):\\n if self.get_id(Search_ID) is None:\\n return False\\n else:\\n return True\",\n \"def validateID(self, id : int) -> int:\\n # If ID is a string, ensure it can be casted to an int before casting and returning.\\n if type(id) == str:\\n if not lib.stringTyping.isInt(id):\\n raise TypeError(\\\"user ID must be either int or string of digits\\\")\\n return int(id)\\n # If ID is not a string, nor an int, throw an error.\\n elif type(id) != int:\\n raise TypeError(\\\"user ID must be either int or string of digits\\\")\\n # ID must be an int, so return it.\\n return id\",\n \"def id_exists(show_id: int,\\n database_connection: mysql.connector.connect) -> bool:\\n return validate_id(show_id, database_connection)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6422405","0.64173734","0.6142269","0.61312246","0.5939884","0.5908327","0.5880398","0.5806814","0.577634","0.5734848","0.5730072","0.56382006","0.55637","0.5501549","0.5488068","0.5485431","0.5476124","0.5466836","0.54339","0.5411698","0.5398409","0.5372584","0.53484315","0.53477323","0.5336371","0.5327411","0.5316241","0.5294655","0.5292505","0.52906764","0.5290138","0.52719474","0.52706325","0.52505064","0.5224689","0.5216522","0.5177424","0.5173158","0.5164601","0.51274157","0.51106805","0.5106305","0.50903237","0.5088144","0.50764173","0.5063056","0.5062557","0.50492555","0.50405514","0.5026922","0.5023985","0.5008982","0.50059426","0.5004298","0.5000435","0.49945658","0.49936256","0.49927726","0.4989894","0.49898884","0.49880224","0.49869823","0.49819273","0.49790868","0.49758255","0.49716154","0.49641553","0.49623126","0.49579415","0.49545392","0.49482954","0.49476528","0.49418265","0.49415585","0.4931851","0.49189654","0.49133888","0.4912833","0.49104878","0.49034798","0.4903424","0.4892134","0.48883384","0.4884316","0.48806715","0.48744503","0.48673403","0.48648918","0.48645955","0.48611632","0.48581317","0.4855877","0.48537856","0.48529413","0.48418126","0.48340088","0.482996","0.4826713","0.48135507","0.4812498","0.48092806"],"string":"[\n \"0.6422405\",\n \"0.64173734\",\n \"0.6142269\",\n \"0.61312246\",\n \"0.5939884\",\n \"0.5908327\",\n \"0.5880398\",\n \"0.5806814\",\n \"0.577634\",\n \"0.5734848\",\n \"0.5730072\",\n \"0.56382006\",\n \"0.55637\",\n \"0.5501549\",\n \"0.5488068\",\n \"0.5485431\",\n \"0.5476124\",\n \"0.5466836\",\n \"0.54339\",\n \"0.5411698\",\n \"0.5398409\",\n \"0.5372584\",\n \"0.53484315\",\n \"0.53477323\",\n \"0.5336371\",\n \"0.5327411\",\n \"0.5316241\",\n \"0.5294655\",\n \"0.5292505\",\n \"0.52906764\",\n \"0.5290138\",\n \"0.52719474\",\n \"0.52706325\",\n \"0.52505064\",\n \"0.5224689\",\n \"0.5216522\",\n \"0.5177424\",\n \"0.5173158\",\n \"0.5164601\",\n \"0.51274157\",\n \"0.51106805\",\n \"0.5106305\",\n \"0.50903237\",\n \"0.5088144\",\n \"0.50764173\",\n \"0.5063056\",\n \"0.5062557\",\n \"0.50492555\",\n \"0.50405514\",\n \"0.5026922\",\n \"0.5023985\",\n \"0.5008982\",\n \"0.50059426\",\n \"0.5004298\",\n \"0.5000435\",\n \"0.49945658\",\n \"0.49936256\",\n \"0.49927726\",\n \"0.4989894\",\n \"0.49898884\",\n \"0.49880224\",\n \"0.49869823\",\n \"0.49819273\",\n \"0.49790868\",\n \"0.49758255\",\n \"0.49716154\",\n \"0.49641553\",\n \"0.49623126\",\n \"0.49579415\",\n \"0.49545392\",\n \"0.49482954\",\n \"0.49476528\",\n \"0.49418265\",\n \"0.49415585\",\n \"0.4931851\",\n \"0.49189654\",\n \"0.49133888\",\n \"0.4912833\",\n \"0.49104878\",\n \"0.49034798\",\n \"0.4903424\",\n \"0.4892134\",\n \"0.48883384\",\n \"0.4884316\",\n \"0.48806715\",\n \"0.48744503\",\n \"0.48673403\",\n \"0.48648918\",\n \"0.48645955\",\n \"0.48611632\",\n \"0.48581317\",\n \"0.4855877\",\n \"0.48537856\",\n \"0.48529413\",\n \"0.48418126\",\n \"0.48340088\",\n \"0.482996\",\n \"0.4826713\",\n \"0.48135507\",\n \"0.4812498\",\n \"0.48092806\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":2294,"cells":{"query":{"kind":"string","value":"Try to delete a dataset, propagating error on failure."},"document":{"kind":"string","value":"def _TryDeleteDataset(dataset_id, project_id):\n client = GetApiClient()\n service = client.datasets\n delete_request_type = GetApiMessage('BigqueryDatasetsDeleteRequest')\n delete_request = delete_request_type(datasetId=dataset_id,\n projectId=project_id,\n deleteContents=True)\n service.Delete(delete_request)\n log.info('Deleted dataset [{}:{}]'.format(project_id, dataset_id))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_dataset(self, dataset):\n raise NotImplementedError('delete_dataset')","def _handle_creation_failure(session: Session, stub_dataset: Dataset, error: str):\n try:\n dataset.delete(session, stub_dataset)\n except requests.HTTPError:\n raise CreationFailure(\n f\"Created dataset did not delete after an earlier error: {error}\"\n )\n raise CreationFailure(error)","def _delete_dataset_netex(dataset_id):\n try:\n logging.info(\"Going to delete the netex file of the dataset %s\", dataset_id)\n community_resource = _find_community_resources(dataset_id)\n _delete_community_resources(dataset_id, community_resource)\n logging.info(\"deleted community resource for the dataset %s\", dataset_id)\n except requests.HTTPError as err:\n logging.warning(\n \"Unable to delete to the dataset %s. Http Error %s\", dataset_id, err\n )\n except Exception as err:\n logging.warning(\n \"Unable to delete to the dataset %s. Generic Error %s\", dataset_id, err\n )","def delete_dataset(self, dataset: DatasetDB):\n try:\n self._es.delete_index(dataset_records_index(dataset.id))\n finally:\n self._es.delete_document(index=DATASETS_INDEX_NAME, doc_id=dataset.id)","def test_dataset_deltitem(train_dataset):\n with pytest.raises(Exception):\n del train_dataset[0]","def delete(_id):\n dataset = ESDataset.get(id=_id, ignore=404)\n\n if not dataset:\n raise NoEntityError(f\"dataset {_id} does not exist.\")\n\n dataset.delete()\n\n return dataset.name","def delete(log, args):\n log('dataset id: {highlight}{id}{reset}',\n highlight=Fore.GREEN,\n id=args.id,\n reset=Style.RESET_ALL)\n log.warn('delete dataset command coming soon.')","def delete_dataset(self, identifier):\n # Delete the dataset directory if it exists. Otherwise return False\n dataset_dir = self.get_dataset_dir(identifier)\n if not os.path.isdir(dataset_dir):\n return False\n shutil.rmtree(dataset_dir)\n return True","def delete_dataset(dataset_path):\n force_rmtree(dataset_path)","def DeleteDataset(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details(\"Method not implemented!\")\n raise NotImplementedError(\"Method not implemented!\")","def delete_dataset(request):\n body = json.loads(request.body)\n dataset_id = body.get('dataset_id', '')\n organization_id = body.get('organization_id')\n # check if user has access to the dataset\n d = ImportRecord.objects.filter(\n super_organization_id=organization_id, pk=dataset_id\n )\n if not d.exists():\n return {\n 'status': 'error',\n 'message': 'user does not have permission to delete dataset',\n }\n d = d[0]\n d.delete()\n return {\n 'status': 'success',\n }","def delete(self, dataset_name=None, dataset_id=None, sure=False, really=False):\n if sure and really:\n dataset = self.get(dataset_name=dataset_name, dataset_id=dataset_id)\n success, response = self._client_api.gen_request(req_type='delete',\n path='/datasets/{}'.format(dataset.id))\n if not success:\n raise exceptions.PlatformException(response)\n logger.info('Dataset {} was deleted successfully'.format(dataset.name))\n return True\n else:\n raise exceptions.PlatformException(\n error='403',\n message='Cant delete dataset from SDK. Please login to platform to delete')","def delete(self, ds, del_raw_data=False, **kwargs):\n self.logger.warning('ds_id already exists: {}. Deleting'.format(ds.id))\n self._del_iso_images(ds)\n self._es.delete_ds(ds.id)\n self._db.alter('DELETE FROM dataset WHERE id=%s', ds.id)\n if del_raw_data:\n self.logger.warning('Deleting raw data: {}'.format(ds.input_path))\n wd_man = WorkDirManager(ds.id)\n wd_man.del_input_data(ds.input_path)\n if self.mode == 'queue':\n self._queue.publish({'ds_id': ds.id, 'status': DatasetStatus.DELETED}, SM_DS_STATUS)","def test_that_when_dataset_is_deleted_the_account_is_still_there(self):\n test_dataset = Dataset.objects.get(\n dataset_slug=\"google-geojson-example\")\n test_dataset.delete()\n with self.assertRaises(ObjectDoesNotExist):\n Dataset.objects.get(dataset_slug=\"google-geojson-example\")\n Account.objects.get(account_slug=\"test_user\")","def delete(self, name):\n assert name, \"Must input a valid dataset name.\"\n self.manager.delete_data(name)","def _try_delete_resource(self, delete_callable, *args, **kwargs):\n try:\n delete_callable(*args, **kwargs)\n # if resource is not found, this means it was deleted in the test\n except exceptions.NotFound:\n pass","def delete_datasetreplica(self, dataset_replica):\n raise NotImplementedError('delete_datasetreplica')","def delete(self, ds, del_raw_data=False):\n self._post_sm_msg(ds=ds, action=DatasetAction.DELETE, priority=DatasetActionPriority.HIGH)","def test_dataset_exists(client, to_delete):\n DATASET_ID = \"get_table_dataset_{}\".format(_millis())\n dataset_ref = client.dataset(DATASET_ID)\n dataset = bigquery.Dataset(dataset_ref)\n dataset = client.create_dataset(dataset)\n to_delete.append(dataset)\n\n assert dataset_exists(client, dataset_ref)\n assert not dataset_exists(client, client.dataset(\"dataset doesnot exist\"))","def delete_dataset_target_bigquery(self, dataset):\n return db.delete_dataset_bigquery(\n dataset, project=self.get_conn_env_var('TARGET_BIGQUERY', 'PROJECT')\n )","def purge_dataset(request):\n data = json.loads(request.body.decode('utf-8'))\n if not request.user.is_staff:\n return JsonResponse({'error': 'Only admin can purge dataset'}, status=403)\n try:\n dset = models.Dataset.objects.get(pk=data['item_id'])\n except models.Dataset.DoesNotExist:\n return JsonResponse({'error': 'Dataset does not exist'}, status=403)\n purgemsg = delete_dataset_from_cold(dset)\n if purgemsg['state'] == 'error':\n return JsonResponse(purgemsg, status=500)\n else:\n return JsonResponse(purgemsg)","def raise_exception_for_dataset(dataset_reference):\n if dataset_reference.dataset_id == non_existing_dataset_id:\n raise cloud.exceptions.NotFound('')","def delete_bigquery_dataset(self, shared_state: Dict[str, Any]):\n\n yield\n\n # Get the bigquery dataset id used for testing and wipe it\n bigquery_dataset = shared_state[\"bigquery_dataset\"]\n bigquery_client = shared_state[\"bigquery_client\"]\n bigquery_client.delete_dataset(\n bigquery_dataset.dataset_id, delete_contents=True, not_found_ok=True\n ) # Make an API request.","def test_delete_unexpected_error(self, requests_mock, capsys):\n requests_mock.delete(data_url, exc=ConnectionError)\n with pytest.raises(ConnectionError):\n r = operations.delete(data_url)\n assert 'Unexpected error when connecting to' in capsys.readouterr().out","def delete(dtype, name, rootdir=None):\n # type and the name\n # delete them\n num_deleted = 0\n for dataset in FreezableAPI.datasets(dtype,name,rootdir=rootdir,fullpath=True):\n # delete it\n shutil.rmtree(dataset)\n num_deleted += 1\n return num_deleted","def delete_temp_dataset():\n\n bq.delete_dataset(temp_dataset_ref, delete_contents=True, not_found_ok=True)","def delete(self, identifier, dataset):\n # Fix identifier because SQlAlchemy can't parse RDF Literals\n identifier = str(identifier)\n\n #self._load_config()\n self.log( 'Removing resource %s in dataset %s' % (identifier, dataset))\n\n # Remove it\n data = self.es_instance.delete_document(identifier, dataset)\n\n self.log( 'Registro %s removido com sucesso' % identifier)\n\n return data","def delete_task(dataset):\n Observation.delete_all(dataset)\n super(dataset.__class__, dataset).delete({DATASET_ID: dataset.dataset_id})","def do_delete(self, node_id):\n _error_code, _msg = RAMSTKDataModel.do_delete(self, node_id)\n\n # pylint: disable=attribute-defined-outside-init\n # It is defined in RAMSTKDataModel.__init__\n if _error_code != 0:\n _error_code = 1\n _msg = _msg + (\n '\\n RAMSTK ERROR: Attempted to delete non-existent '\n 'Allocation ID {0:d}.').format(node_id)\n else:\n self.last_id = max(self.tree.nodes.keys())\n\n return _error_code, _msg","def delete_ds(self, dt):\n\n for k in self.datasets_keys:\n for F in self.datasets[k]:\n if F not in data[k].keys():\n continue \n max_date = data[k][F]['max_date'] \n \"\"\" Deleting unecessary ds \"\"\"\n if dt > max_date : # check max date and check if data is still loaded\n print(blue + 'Memory used before deleting : ' , process.memory_info().rss/1000000000 , cend) \n del data[k][F] \n print(\"*** Erasing dataset: \" , k , ' ' , F ) \n print(blue + 'Memory used after deleting : ' , process.memory_info().rss/1000000000 , cend) \n \n else:\n continue","def dataset(bf):\n ds = bf.create_dataset(\"test_dataset_{}\".format(uuid4()))\n\n yield ds\n\n bf._api.datasets.delete(ds)","def destroyDataset(request):\n\n if request.method=='DELETE':\n json_data=json.loads(request.body)\n name=json_data['name']\n try:\n dataset=Dataset.nodes.get(name=name)\n dataset.delete()\n return JsonResponse({\"success\": \"Dataset deleted\"}, safe=False)\n except:\n return JsonResponse({\"error\":\"Error occurred\"}, safe=False)","def test_delete_voice_dataset(self):\n pass","def delete_data(self, name):\n assert name, \"Must input a valid dataset name.\"\n try:\n self.data[\"dataset\"].pop(name)\n self.update_categories()\n self.write_data_cache(self.data)\n except KeyError:\n raise KeyError(\"The dataset \\'{}\\' does not exist in the cache.\".format(name))","def test_deletion_fail(self):\n\n # Assert that a RelaxNoPipeError occurs when the data pipe does not exist.\n self.assertRaises(RelaxNoPipeError, pipes.delete, 'x')","def test_delete_http_error(self, requests_mock, capsys):\n requests_mock.delete(data_url, status_code=300)\n with pytest.raises(RuntimeError):\n r = operations.delete(data_url)\n assert 'HTTP error: 300' in capsys.readouterr().out","def test_delete_error(self):\n with self.assertRaises(QiitaDBExecutionError):\n PrepTemplate.delete(1)","def delete_datasets(self, base_url):\n response = requests.get(base_url + '/testdata')\n for index in range(len(response.json()['testdata'])):\n self.delete_dataset(base_url, response.json()['testdata'][index]['dataset'])","def test_delete(self):\n data_columns = ['id', 'column_string', 'column_float']\n data_values = [[1, 'string1', 456.956], [2, 'string2', 38.905]]\n data = pd.DataFrame(data_values, columns=data_columns)\n data.name = 'test_delete'\n my_conn = MySQL(*self.conn_params)\n my_conn.insert(data)\n table = my_conn.get_table(data.name)\n expected = 2\n current = my_conn.engine.scalar(\n select([func.count('*')]).select_from(table)\n )\n self.assertEqual(current, expected)\n\n # delete from operation\n # the None argument in delete DML is included to avoid pylint E1120\n table.delete(None).where(table.c.id == 2).execute()\n\n expected = 1\n current = my_conn.engine.scalar(\n select([func.count('*')]).select_from(table)\n )\n self.assertEqual(current, expected)\n my_conn.drop(data.name)","def delData(self, ide = None):\r\n try:\r\n if ide is not None:\r\n self.cursor.execute(\"DELETE FROM DATAS WHERE ID = %s;\" %(ide))\r\n return True\r\n else:\r\n return False\r\n except:\r\n return False","def delete():","def delete(self, data):\r\n pass","def delete_upload_data(self, id=None, name=None) -> None:\r\n # get the dataset\r\n dataset = self.get_upload_data(id=id, name=name)\r\n\r\n try:\r\n self.session.delete(dataset)\r\n self.session.commit()\r\n except Exception as e:\r\n self.session.rollback()\r\n raise e","def delete_run(self, run_id):\n ds = self.datastorage\n ds.get_metrics_dao().delete(run_id)\n # TODO: implement\n # ds.get_artifact_dao().delete(run_id)\n # ds.get_resource_dao().delete(run_id)\n ds.get_run_dao().delete(run_id)","def test_07_datastore_delete(self, Mock):\r\n html_request = FakeRequest(json.dumps({}), 200,\r\n {'content-type': 'application/json'})\r\n\r\n Mock.return_value = html_request\r\n with self.flask_app.test_request_context('/'):\r\n out = self.ckan.datastore_delete(name='task',\r\n resource_id=self.task_resource_id)\r\n err_msg = \"It should return True\"\r\n assert out is True, err_msg\r\n # Check the error\r\n Mock.return_value = self.server_error\r\n try:\r\n self.ckan.datastore_delete(name='task',\r\n resource_id=self.task_resource_id)\r\n except Exception as out:\r\n type, msg, status_code = out.args\r\n assert \"Server Error\" in msg, msg\r\n assert 500 == status_code, status_code\r\n assert \"CKAN: the remote site failed! datastore_delete failed\" == type, type","def delete_row(self, identifier, rowid, datastore):\n # Get dataset. Raise exception if dataset is unknown.\n dataset = datastore.get_dataset(identifier)\n if dataset is None:\n raise ValueError(\"unknown dataset '{}'\".format(identifier))\n # Delete the row at the given index position\n df = vizual.delete_rows(dataset.to_dataframe(), rowids=[rowid])\n # Store updated dataset to get new identifier.\n ds = datastore.update_dataset(\n origin=dataset,\n df=df,\n annotations=dataset.annotations.filter(rows=list(df.index))\n )\n return VizualApiResult(ds)","def dataset_delete(self, name, deep=False):\n\n # Checks inputs\n check_type(value=name, allowed_types=str, var_name=\"name\", raise_exception=True)\n check_is_valid_ds_name(value=name, raise_exception=True)\n check_type(value=deep, allowed_types=bool, var_name=\"deep\", raise_exception=True)\n\n template = 'dataset_remove'\n if deep:\n template = 'dataset_deep_remove'\n response = self.send(root_url=self.session.dm_url + self.root_url,\n verb=GenericClient.VERB.DELETE,\n template=TEMPLATES[template],\n uri_params={\n 'name': name\n })\n\n if response.status_code == 404:\n raise IkatsNotFoundError(\"Dataset %s not found in database\" % name)\n return response.text","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package(factory=DynamoPackage)\n self._save_pkgs(pkg)\n self.db.delete(pkg)\n count = self.engine.scan(DynamoPackage).count()\n self.assertEqual(count, 0)\n count = self.engine.scan(PackageSummary).count()\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def test_delete(self):\n SampleTemplate.create(self.metadata, self.new_study)\n SampleTemplate.delete(2)\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.required_sample_info WHERE study_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.study_sample_columns WHERE study_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n with self.assertRaises(QiitaDBExecutionError):\n self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.sample_2\")","def delete(self, identifier):\n self.get(identifier)\n conn = self.get_connector()\n cursor = conn.cursor()\n\n query = \"delete from {0} where {2}={1}\".format(\n self.ressource_config[\"table\"],\n identifier,\n self.model.pk_field.name)\n try:\n cursor.execute(query)\n except sqlite3.IntegrityError, e:\n message = \"\"\n if \"foreign\" in e.message:\n message = \"\"\"another ressource depends on this\n object. Cloud not delete before all ressources\n depending on it are also deleted\"\"\"\n\n raise BadRequest(message)\n\n conn.commit()\n conn.close()","def delete_dataset_without_original_url():\n logging.warning(\n \"*** deleting all netex files created by transport.data.gouv.fr ***\"\n )\n r = requests.get(\"https://transport.data.gouv.fr/api/datasets\")\n r.raise_for_status()\n datasets = r.json()\n\n print_resource = lambda r: f\"\\n\\t*[url = {r['url']} | extras = {r.get('extras')}]\"\n print_resources = lambda rs: [print_resource(r) for r in rs]\n\n for d in datasets:\n dataset_name = d[\"title\"]\n if d[\"type\"] != \"public-transit\":\n continue\n\n dataset_id = d[\"id\"]\n\n community_resources = _find_community_resources(dataset_id)\n logging.info(\"community ressources : %s\", print_resources(community_resources))\n old_community_resources = [\n r\n for r in community_resources\n if \"transport:original_resource_url\" not in r.get(\"extras\", {})\n ]\n if old_community_resources:\n logging.info(\n \"old community ressources : %s\",\n print_resources(old_community_resources),\n )\n _delete_community_resources(dataset_id, old_community_resources)\n logging.info(\"deleted community resource for the dataset %s\", dataset_id)","def test_do_delete_non_existent_id(test_dao):\r\n DUT = dtmFunction(test_dao, test=True)\r\n DUT.do_select_all(revision_id=1)\r\n\r\n _error_code, _msg = DUT.do_delete(300)\r\n\r\n assert _error_code == 2005\r\n assert _msg == (\"RAMSTK ERROR: Attempted to delete non-existent \"\r\n \"Function ID 300.\")","def test_delete_datasource(\n in_memory_runtime_context: EphemeralDataContext,\n) -> None:\n context = in_memory_runtime_context\n\n name = context.list_datasources()[0][\"name\"]\n context.delete_datasource(name)\n\n assert name not in context.datasources","def test_delete(self):\n\n self.metadata.create_or_update(data=self.create)\n\n # Find by name\n res_name = self.metadata.get_by_name(\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\n )\n # Then fetch by ID\n res_id = self.metadata.get_by_id(\n entity=Dashboard, entity_id=str(res_name.id.__root__)\n )\n\n # Delete\n self.metadata.delete(\n entity=Dashboard, entity_id=str(res_id.id.__root__), recursive=True\n )\n\n # Then we should not find it\n res = self.metadata.list_entities(entity=Dashboard)\n assert not next(\n iter(\n ent\n for ent in res.entities\n if ent.fullyQualifiedName == self.entity.fullyQualifiedName\n ),\n None,\n )","def _try_delete_and_return_permissions_error(component_url):\n try:\n delete_object_task.DeleteObjectTask(component_url, verbose=False).execute()\n except api_errors.CloudApiError as e:\n status = getattr(e, 'status_code', None)\n if status == 403:\n return e\n raise","async def test_delete_invalid(database,valid_data):\n test_valid_insert(database,valid_data)\n N = 10\n for idx in range(N+1,N*2):\n try:\n await database.delete(_id=idx,user_id=idx)\n assert False\n except:\n assert True\n await database.close_pool()","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package(factory=SQLPackage)\n self.sql.add(pkg)\n transaction.commit()\n self.sql.add(pkg)\n self.db.delete(pkg)\n count = self.sql.query(SQLPackage).count()\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def del_data(self, name):\n raise NotImplementedError('Do I want to delete data from a df?')","def delete_datasource_instance(connection, id, error_msg=None):\n url = f\"{connection.base_url}/api/datasources/{id}\"\n response = connection.session.delete(url=url)\n if not response.ok:\n if error_msg is None:\n error_msg = f\"Error deleting Datasource Instance with ID: {id}\"\n response_handler(response, error_msg)\n return response","def test_delete_run(self):\n pass","def delete(self, hostname):\n self.not_supported()","def do_delete(self, arg):\n \treturn False","def test_delete_data(self):\n data = Data.objects.create(\n name='Test data',\n contributor=self.user,\n process=self.proc,\n )\n\n data.output = {'json_field': {'foo': 'bar'}}\n data.status = Data.STATUS_DONE\n data.save()\n\n self.assertEqual(Storage.objects.count(), 1)\n\n data.delete()\n self.assertEqual(Storage.objects.count(), 0)","def test_wrong_delete_param(self):\n def close_conn():\n cli = LDAPClient(\"ldap://%s\" % self.ipaddr)\n LDAPConnection(cli).delete(\"cn=dummy\")\n self.assertRaises(ClosedConnection, close_conn)\n self.assertRaises(TypeError, lambda: self.conn.delete(0))","def testDeleteOpInvalidDN(self):\n self.assertRaises(AssertionError, delta.DeleteOp, 0)","def delete(self, ssubject: str, predicate: str, obj: str) -> None:\n raise NotImplementedError(\"The RDF graph is read-only: DELETE DATA queries are not allowed\")","def test_delete_failure(self):\r\n problem_url_name = 'H1P1'\r\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\r\n self.define_option_problem(problem_url_name)\r\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\r\n\r\n expected_message = \"bad things happened\"\r\n with patch('courseware.models.StudentModule.delete') as mock_delete:\r\n mock_delete.side_effect = ZeroDivisionError(expected_message)\r\n instructor_task = self.delete_problem_state('instructor', location)\r\n self._assert_task_failure(instructor_task.id, 'delete_problem_state', problem_url_name, expected_message)","def test_handle_delete_github_error(self):\n self.db.query.side_effect = GithubAPIException(\"error\")\n self.assertTupleEqual(self.testcommand.handle(\"team delete brs\", user),\n (\"Team delete was unsuccessful with \"\n \"the following error: \"\n \"error\", 200))\n self.db.delete.assert_not_called()\n self.gh.org_delete_team.assert_not_called()","def delete_datafile(self, save_instance=True):\n if self.datafile:\n logger.debug(\"Deleting datafile '%s'\", self.datafile.name)\n try:\n self.datafile.delete(save=save_instance)\n except OSError as exc:\n logger.error(\"Error deleting file '%s': %s\",\n self.datafile.name, exc)\n return False\n logger.info(\"Deleted datafile of '%s'\", self)","async def test_delete_batch_invalid(database,valid_data):\n test_valid_insert_batch(database,valid_data)\n N = 10\n batch_id = 1\n for idx in range(N+1,N*2):\n try:\n await database.delete_batch(batch_id=batch_id,user_id=idx)\n assert False\n except:\n assert True\n await database.close_pool()","def delete_rdataset(self, name, rdtype, covers=dns.rdatatype.NONE):\n\n name = self._validate_name(name)\n rdtype = dns.rdatatype.RdataType.make(rdtype)\n if covers is not None:\n covers = dns.rdatatype.RdataType.make(covers)\n node = self.get_node(name)\n if node is not None:\n node.delete_rdataset(self.rdclass, rdtype, covers)\n if len(node) == 0:\n self.delete_node(name)","def delete(self, context, id_):\n try:\n db_resource_data = self.db_api.get_resource(\n context, id_)\n\n if db_resource_data['type'] == (eon_const.\n EON_RESOURCE_TYPE_ESX_CLUSTER):\n msg = _(\"Delete operation not supported for type %s\"\n % db_resource_data['type'])\n raise exception.DeleteException(err=msg)\n\n _resource_data = _make_response(\n db_resource_data)\n _resource_data_log = deepcopy(_resource_data)\n _resource_data_log.pop(\"meta_data\", None)\n LOG.info(\"Details for the ID %s is: %s\" % (\n id_, logging.mask_password(_resource_data_log)))\n driver_obj = driver.load_resource_driver(\n db_resource_data['type'])\n driver_obj.validate_delete(db_resource_data)\n driver_obj.delete(context, id_)\n self.db_api.delete_resource(context, id_)\n # delete the data from hlm input model\n try:\n LOG.info(\"[%s] remove resource from input model\" % id_)\n hux_obj = HLMFacadeWrapper(context)\n resource_id = db_resource_data[eon_const.EON_RESOURCE_ID]\n hux_obj.delete_server(resource_id)\n hux_obj.commit_changes(resource_id, \"Delete compute resource\")\n except facade_excep.NotFound:\n # log and do nothing\n LOG.warn(\"[%s] resource not found in hlm input model\" % id_)\n LOG.info(\"[%s]: Deleted resource from eon\" % id_)\n # Notify the message to consumers\n try:\n message = {\"resource_id\": id_,\n \"resource_state\": eon_const.EON_RESOURCE_STATE_REMOVED,\n \"resource_details\": _resource_data,\n }\n message_notifier.notify(context,\n message_notifier.EVENT_PRIORITY_INFO,\n message_notifier.EVENT_TYPE[\n 'removed'],\n message)\n except Exception as ex:\n LOG.exception(\n \"Exception while notifying the message : %s\" % ex)\n except exception.NotFound as e:\n msg = (\"Failed to delete resource %s. Error: %s\") % (\n _resource_data['name'], e.message)\n LOG.exception(msg)\n raise e","def delete(self):\n self.logger.debug(\"In delete.\")\n\n if self._id is None:\n self.logger.warn(\"Attempt to delete a %s with no ID.\", __name__)\n raise Exception(\"{} does not have an ID.\".format(__name__))\n\n id = self._id\n\n session = iHMPSession.get_session()\n self.logger.info(\"Got iHMP session.\")\n\n # Assume failure\n success = False\n\n try:\n self.logger.info(\"Deleting %s with ID %s.\", __name__, id)\n session.get_osdf().delete_node(id)\n success = True\n except Exception as delete_exception:\n self.logger.exception(delete_exception)\n self.logger.error(\"An error occurred when deleting %s.\", self)\n\n return success","def test_sg_delete_non_associated(self):\n\n # Add a faked storage group to be tested and another one\n faked_storage_group = self.add_storage_group1()\n self.add_storage_group2()\n\n storage_group_mgr = self.console.storage_groups\n\n storage_group = storage_group_mgr.find(name=faked_storage_group.name)\n\n # Execute the code to be tested.\n storage_group.delete()\n\n # Check that the storage group no longer exists\n with pytest.raises(NotFound):\n storage_group_mgr.find(name=faked_storage_group.name)","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def test_delete_unkonwn_id_error(self):\n with self.assertRaises(QiitaDBUnknownIDError):\n PrepTemplate.delete(5)","def s3_delete_data(self):\n\n self.k.delete()","def delete(self, *args, **kwargs):\n raise NotImplementedError()","def delete(self, error_id):\n error = self.db.session.query(models.Error).get(error_id)\n if error:\n self.db.session.delete(error)\n self.db.session.commit()\n else:\n raise InvalidErrorReference(\"No error with id %s\" % str(error_id))","def delete_dataset(key=None) -> DeleteDatasetResponse:\n config = ThreatExchangeConfig.getx(str(key))\n hmaconfig.delete_config(config)\n return DeleteDatasetResponse(response=\"The privacy group is deleted\")","def clean(args):\n with_dataset(args, Dataset._clean)","def delete(self, predicate, successHandler=None, failHandler=None):\n queryDelete = \"DELETE FROM `article_article` \" \\\n \"WHERE `{}` {} %s LIMIT 1;\".format(\n predicate[0],\n predicate[1]\n )\n\n queryDeleteParams = []\n if isinstance(predicate[2], datetime):\n queryDeleteParams.append(predicate[2].strftime(\"%Y-%m-%d %H:%M:%S\"))\n else:\n queryDeleteParams.append(predicate[2])\n\n def failCallback(error):\n errorMessage = str(error)\n if isinstance(error, Failure):\n errorMessage = error.getErrorMessage()\n\n self.log.error(\n \"[Default.Article] delete() database error: {errorMessage}\",\n errorMessage=errorMessage\n )\n\n if failHandler is not None:\n reactor.callInThread(failHandler, [\"DatabaseError\"])\n\n def successCallback(results):\n if successHandler is not None:\n reactor.callInThread(successHandler)\n\n operation = self.dbService.runOperation(\n queryDelete,\n tuple(queryDeleteParams)\n )\n operation.addCallbacks(successCallback, failCallback)","def delete(self):\n raise NotImplementedError","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package()\n key = self.db.redis_key(pkg.filename)\n self.redis[key] = \"foobar\"\n self.db.delete(pkg)\n val = self.redis.get(key)\n self.assertIsNone(val)\n count = self.redis.scard(self.db.redis_set)\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def test_delete_unkonwn_id_error(self):\n with self.assertRaises(QiitaDBUnknownIDError):\n SampleTemplate.delete(5)","def remove_dataset(self, name):\n payload = {\"name\": name}\n r = self.request(\n \"delete\", url_path_join(USER_DATASET_RESOURCE_URL, self.owner), payload=payload\n )\n self.check_and_raise(r)","async def delete_dataset(\n self,\n request: Optional[\n Union[data_labeling_service.DeleteDatasetRequest, dict]\n ] = None,\n *,\n name: Optional[str] = None,\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\n timeout: Union[float, object] = gapic_v1.method.DEFAULT,\n metadata: Sequence[Tuple[str, str]] = (),\n ) -> None:\n # Create or coerce a protobuf request object.\n # Quick check: If we got a request object, we should *not* have\n # gotten any keyword arguments that map to the request.\n has_flattened_params = any([name])\n if request is not None and has_flattened_params:\n raise ValueError(\n \"If the `request` argument is set, then none of \"\n \"the individual field arguments should be set.\"\n )\n\n request = data_labeling_service.DeleteDatasetRequest(request)\n\n # If we have keyword arguments corresponding to fields on the\n # request, apply these.\n if name is not None:\n request.name = name\n\n # Wrap the RPC method; this adds retry and timeout information,\n # and friendly error handling.\n rpc = gapic_v1.method_async.wrap_method(\n self._client._transport.delete_dataset,\n default_retry=retries.Retry(\n initial=0.1,\n maximum=30.0,\n multiplier=1.3,\n predicate=retries.if_exception_type(\n core_exceptions.DeadlineExceeded,\n core_exceptions.ServiceUnavailable,\n ),\n deadline=30.0,\n ),\n default_timeout=30.0,\n client_info=DEFAULT_CLIENT_INFO,\n )\n\n # Certain fields should be provided within the metadata header;\n # add these here.\n metadata = tuple(metadata) + (\n gapic_v1.routing_header.to_grpc_metadata(((\"name\", request.name),)),\n )\n\n # Send the request.\n await rpc(\n request,\n retry=retry,\n timeout=timeout,\n metadata=metadata,\n )","def test_delete_edge_case_with_write_concern_0_return_None(self):\n p1 = self.Person(name=\"User Z\", age=20).save()\n del_result = p1.delete(w=0)\n assert del_result is None","def delete_table_data():\n try:\n print 'delete existing data'\n sql = 'delete from document'\n sql1 = 'delete from clean_keywords'\n sql2 = 'delete from keywords'\n util.executeSQL(conn, sql) # delete the existing data.\n util.executeSQL(conn, sql1)\n util.executeSQL(conn, sql2)\n except Exception as e:\n print e","def test_data_object_del(self):\n pass","def test_raise_when_no_id(self):\n model = self.Test({}, False)\n self.assertRaises(errors.PersistenceError, model.delete)","def delete(self, *args, **kwargs):\n return 0","def delete_file(self, filename=None):\n return self._service.delete_object(self._datasets_id, filename)","def test_delete(self, init_db, audit):\n audit.delete()\n assert Audit.get(audit.id) == None","def test_delete_category_does_not_exist(self):\n self.delete_does_not_exist_fail('hats')","def _TryDeleteTable(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')\n delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,\n projectId=project_id)\n service.Delete(delete_request)\n log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id))","def test_delete(self):\n pt = PrepTemplate.create(self.metadata, self.new_raw_data,\n self.test_study, self.data_type_id)\n PrepTemplate.delete(pt.id)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_template WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.common_prep_info WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_columns WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n with self.assertRaises(QiitaDBExecutionError):\n self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_2\")","def delete(self):\n raise NotImplementedError()","def delete(self):\n raise NotImplementedError()","def test_delete_without_partition_key(self):\r\n with self.assertRaises(query.QueryException):\r\n TestModel.objects(attempt_id=0).delete()"],"string":"[\n \"def delete_dataset(self, dataset):\\n raise NotImplementedError('delete_dataset')\",\n \"def _handle_creation_failure(session: Session, stub_dataset: Dataset, error: str):\\n try:\\n dataset.delete(session, stub_dataset)\\n except requests.HTTPError:\\n raise CreationFailure(\\n f\\\"Created dataset did not delete after an earlier error: {error}\\\"\\n )\\n raise CreationFailure(error)\",\n \"def _delete_dataset_netex(dataset_id):\\n try:\\n logging.info(\\\"Going to delete the netex file of the dataset %s\\\", dataset_id)\\n community_resource = _find_community_resources(dataset_id)\\n _delete_community_resources(dataset_id, community_resource)\\n logging.info(\\\"deleted community resource for the dataset %s\\\", dataset_id)\\n except requests.HTTPError as err:\\n logging.warning(\\n \\\"Unable to delete to the dataset %s. Http Error %s\\\", dataset_id, err\\n )\\n except Exception as err:\\n logging.warning(\\n \\\"Unable to delete to the dataset %s. Generic Error %s\\\", dataset_id, err\\n )\",\n \"def delete_dataset(self, dataset: DatasetDB):\\n try:\\n self._es.delete_index(dataset_records_index(dataset.id))\\n finally:\\n self._es.delete_document(index=DATASETS_INDEX_NAME, doc_id=dataset.id)\",\n \"def test_dataset_deltitem(train_dataset):\\n with pytest.raises(Exception):\\n del train_dataset[0]\",\n \"def delete(_id):\\n dataset = ESDataset.get(id=_id, ignore=404)\\n\\n if not dataset:\\n raise NoEntityError(f\\\"dataset {_id} does not exist.\\\")\\n\\n dataset.delete()\\n\\n return dataset.name\",\n \"def delete(log, args):\\n log('dataset id: {highlight}{id}{reset}',\\n highlight=Fore.GREEN,\\n id=args.id,\\n reset=Style.RESET_ALL)\\n log.warn('delete dataset command coming soon.')\",\n \"def delete_dataset(self, identifier):\\n # Delete the dataset directory if it exists. Otherwise return False\\n dataset_dir = self.get_dataset_dir(identifier)\\n if not os.path.isdir(dataset_dir):\\n return False\\n shutil.rmtree(dataset_dir)\\n return True\",\n \"def delete_dataset(dataset_path):\\n force_rmtree(dataset_path)\",\n \"def DeleteDataset(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details(\\\"Method not implemented!\\\")\\n raise NotImplementedError(\\\"Method not implemented!\\\")\",\n \"def delete_dataset(request):\\n body = json.loads(request.body)\\n dataset_id = body.get('dataset_id', '')\\n organization_id = body.get('organization_id')\\n # check if user has access to the dataset\\n d = ImportRecord.objects.filter(\\n super_organization_id=organization_id, pk=dataset_id\\n )\\n if not d.exists():\\n return {\\n 'status': 'error',\\n 'message': 'user does not have permission to delete dataset',\\n }\\n d = d[0]\\n d.delete()\\n return {\\n 'status': 'success',\\n }\",\n \"def delete(self, dataset_name=None, dataset_id=None, sure=False, really=False):\\n if sure and really:\\n dataset = self.get(dataset_name=dataset_name, dataset_id=dataset_id)\\n success, response = self._client_api.gen_request(req_type='delete',\\n path='/datasets/{}'.format(dataset.id))\\n if not success:\\n raise exceptions.PlatformException(response)\\n logger.info('Dataset {} was deleted successfully'.format(dataset.name))\\n return True\\n else:\\n raise exceptions.PlatformException(\\n error='403',\\n message='Cant delete dataset from SDK. Please login to platform to delete')\",\n \"def delete(self, ds, del_raw_data=False, **kwargs):\\n self.logger.warning('ds_id already exists: {}. Deleting'.format(ds.id))\\n self._del_iso_images(ds)\\n self._es.delete_ds(ds.id)\\n self._db.alter('DELETE FROM dataset WHERE id=%s', ds.id)\\n if del_raw_data:\\n self.logger.warning('Deleting raw data: {}'.format(ds.input_path))\\n wd_man = WorkDirManager(ds.id)\\n wd_man.del_input_data(ds.input_path)\\n if self.mode == 'queue':\\n self._queue.publish({'ds_id': ds.id, 'status': DatasetStatus.DELETED}, SM_DS_STATUS)\",\n \"def test_that_when_dataset_is_deleted_the_account_is_still_there(self):\\n test_dataset = Dataset.objects.get(\\n dataset_slug=\\\"google-geojson-example\\\")\\n test_dataset.delete()\\n with self.assertRaises(ObjectDoesNotExist):\\n Dataset.objects.get(dataset_slug=\\\"google-geojson-example\\\")\\n Account.objects.get(account_slug=\\\"test_user\\\")\",\n \"def delete(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n self.manager.delete_data(name)\",\n \"def _try_delete_resource(self, delete_callable, *args, **kwargs):\\n try:\\n delete_callable(*args, **kwargs)\\n # if resource is not found, this means it was deleted in the test\\n except exceptions.NotFound:\\n pass\",\n \"def delete_datasetreplica(self, dataset_replica):\\n raise NotImplementedError('delete_datasetreplica')\",\n \"def delete(self, ds, del_raw_data=False):\\n self._post_sm_msg(ds=ds, action=DatasetAction.DELETE, priority=DatasetActionPriority.HIGH)\",\n \"def test_dataset_exists(client, to_delete):\\n DATASET_ID = \\\"get_table_dataset_{}\\\".format(_millis())\\n dataset_ref = client.dataset(DATASET_ID)\\n dataset = bigquery.Dataset(dataset_ref)\\n dataset = client.create_dataset(dataset)\\n to_delete.append(dataset)\\n\\n assert dataset_exists(client, dataset_ref)\\n assert not dataset_exists(client, client.dataset(\\\"dataset doesnot exist\\\"))\",\n \"def delete_dataset_target_bigquery(self, dataset):\\n return db.delete_dataset_bigquery(\\n dataset, project=self.get_conn_env_var('TARGET_BIGQUERY', 'PROJECT')\\n )\",\n \"def purge_dataset(request):\\n data = json.loads(request.body.decode('utf-8'))\\n if not request.user.is_staff:\\n return JsonResponse({'error': 'Only admin can purge dataset'}, status=403)\\n try:\\n dset = models.Dataset.objects.get(pk=data['item_id'])\\n except models.Dataset.DoesNotExist:\\n return JsonResponse({'error': 'Dataset does not exist'}, status=403)\\n purgemsg = delete_dataset_from_cold(dset)\\n if purgemsg['state'] == 'error':\\n return JsonResponse(purgemsg, status=500)\\n else:\\n return JsonResponse(purgemsg)\",\n \"def raise_exception_for_dataset(dataset_reference):\\n if dataset_reference.dataset_id == non_existing_dataset_id:\\n raise cloud.exceptions.NotFound('')\",\n \"def delete_bigquery_dataset(self, shared_state: Dict[str, Any]):\\n\\n yield\\n\\n # Get the bigquery dataset id used for testing and wipe it\\n bigquery_dataset = shared_state[\\\"bigquery_dataset\\\"]\\n bigquery_client = shared_state[\\\"bigquery_client\\\"]\\n bigquery_client.delete_dataset(\\n bigquery_dataset.dataset_id, delete_contents=True, not_found_ok=True\\n ) # Make an API request.\",\n \"def test_delete_unexpected_error(self, requests_mock, capsys):\\n requests_mock.delete(data_url, exc=ConnectionError)\\n with pytest.raises(ConnectionError):\\n r = operations.delete(data_url)\\n assert 'Unexpected error when connecting to' in capsys.readouterr().out\",\n \"def delete(dtype, name, rootdir=None):\\n # type and the name\\n # delete them\\n num_deleted = 0\\n for dataset in FreezableAPI.datasets(dtype,name,rootdir=rootdir,fullpath=True):\\n # delete it\\n shutil.rmtree(dataset)\\n num_deleted += 1\\n return num_deleted\",\n \"def delete_temp_dataset():\\n\\n bq.delete_dataset(temp_dataset_ref, delete_contents=True, not_found_ok=True)\",\n \"def delete(self, identifier, dataset):\\n # Fix identifier because SQlAlchemy can't parse RDF Literals\\n identifier = str(identifier)\\n\\n #self._load_config()\\n self.log( 'Removing resource %s in dataset %s' % (identifier, dataset))\\n\\n # Remove it\\n data = self.es_instance.delete_document(identifier, dataset)\\n\\n self.log( 'Registro %s removido com sucesso' % identifier)\\n\\n return data\",\n \"def delete_task(dataset):\\n Observation.delete_all(dataset)\\n super(dataset.__class__, dataset).delete({DATASET_ID: dataset.dataset_id})\",\n \"def do_delete(self, node_id):\\n _error_code, _msg = RAMSTKDataModel.do_delete(self, node_id)\\n\\n # pylint: disable=attribute-defined-outside-init\\n # It is defined in RAMSTKDataModel.__init__\\n if _error_code != 0:\\n _error_code = 1\\n _msg = _msg + (\\n '\\\\n RAMSTK ERROR: Attempted to delete non-existent '\\n 'Allocation ID {0:d}.').format(node_id)\\n else:\\n self.last_id = max(self.tree.nodes.keys())\\n\\n return _error_code, _msg\",\n \"def delete_ds(self, dt):\\n\\n for k in self.datasets_keys:\\n for F in self.datasets[k]:\\n if F not in data[k].keys():\\n continue \\n max_date = data[k][F]['max_date'] \\n \\\"\\\"\\\" Deleting unecessary ds \\\"\\\"\\\"\\n if dt > max_date : # check max date and check if data is still loaded\\n print(blue + 'Memory used before deleting : ' , process.memory_info().rss/1000000000 , cend) \\n del data[k][F] \\n print(\\\"*** Erasing dataset: \\\" , k , ' ' , F ) \\n print(blue + 'Memory used after deleting : ' , process.memory_info().rss/1000000000 , cend) \\n \\n else:\\n continue\",\n \"def dataset(bf):\\n ds = bf.create_dataset(\\\"test_dataset_{}\\\".format(uuid4()))\\n\\n yield ds\\n\\n bf._api.datasets.delete(ds)\",\n \"def destroyDataset(request):\\n\\n if request.method=='DELETE':\\n json_data=json.loads(request.body)\\n name=json_data['name']\\n try:\\n dataset=Dataset.nodes.get(name=name)\\n dataset.delete()\\n return JsonResponse({\\\"success\\\": \\\"Dataset deleted\\\"}, safe=False)\\n except:\\n return JsonResponse({\\\"error\\\":\\\"Error occurred\\\"}, safe=False)\",\n \"def test_delete_voice_dataset(self):\\n pass\",\n \"def delete_data(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n try:\\n self.data[\\\"dataset\\\"].pop(name)\\n self.update_categories()\\n self.write_data_cache(self.data)\\n except KeyError:\\n raise KeyError(\\\"The dataset \\\\'{}\\\\' does not exist in the cache.\\\".format(name))\",\n \"def test_deletion_fail(self):\\n\\n # Assert that a RelaxNoPipeError occurs when the data pipe does not exist.\\n self.assertRaises(RelaxNoPipeError, pipes.delete, 'x')\",\n \"def test_delete_http_error(self, requests_mock, capsys):\\n requests_mock.delete(data_url, status_code=300)\\n with pytest.raises(RuntimeError):\\n r = operations.delete(data_url)\\n assert 'HTTP error: 300' in capsys.readouterr().out\",\n \"def test_delete_error(self):\\n with self.assertRaises(QiitaDBExecutionError):\\n PrepTemplate.delete(1)\",\n \"def delete_datasets(self, base_url):\\n response = requests.get(base_url + '/testdata')\\n for index in range(len(response.json()['testdata'])):\\n self.delete_dataset(base_url, response.json()['testdata'][index]['dataset'])\",\n \"def test_delete(self):\\n data_columns = ['id', 'column_string', 'column_float']\\n data_values = [[1, 'string1', 456.956], [2, 'string2', 38.905]]\\n data = pd.DataFrame(data_values, columns=data_columns)\\n data.name = 'test_delete'\\n my_conn = MySQL(*self.conn_params)\\n my_conn.insert(data)\\n table = my_conn.get_table(data.name)\\n expected = 2\\n current = my_conn.engine.scalar(\\n select([func.count('*')]).select_from(table)\\n )\\n self.assertEqual(current, expected)\\n\\n # delete from operation\\n # the None argument in delete DML is included to avoid pylint E1120\\n table.delete(None).where(table.c.id == 2).execute()\\n\\n expected = 1\\n current = my_conn.engine.scalar(\\n select([func.count('*')]).select_from(table)\\n )\\n self.assertEqual(current, expected)\\n my_conn.drop(data.name)\",\n \"def delData(self, ide = None):\\r\\n try:\\r\\n if ide is not None:\\r\\n self.cursor.execute(\\\"DELETE FROM DATAS WHERE ID = %s;\\\" %(ide))\\r\\n return True\\r\\n else:\\r\\n return False\\r\\n except:\\r\\n return False\",\n \"def delete():\",\n \"def delete(self, data):\\r\\n pass\",\n \"def delete_upload_data(self, id=None, name=None) -> None:\\r\\n # get the dataset\\r\\n dataset = self.get_upload_data(id=id, name=name)\\r\\n\\r\\n try:\\r\\n self.session.delete(dataset)\\r\\n self.session.commit()\\r\\n except Exception as e:\\r\\n self.session.rollback()\\r\\n raise e\",\n \"def delete_run(self, run_id):\\n ds = self.datastorage\\n ds.get_metrics_dao().delete(run_id)\\n # TODO: implement\\n # ds.get_artifact_dao().delete(run_id)\\n # ds.get_resource_dao().delete(run_id)\\n ds.get_run_dao().delete(run_id)\",\n \"def test_07_datastore_delete(self, Mock):\\r\\n html_request = FakeRequest(json.dumps({}), 200,\\r\\n {'content-type': 'application/json'})\\r\\n\\r\\n Mock.return_value = html_request\\r\\n with self.flask_app.test_request_context('/'):\\r\\n out = self.ckan.datastore_delete(name='task',\\r\\n resource_id=self.task_resource_id)\\r\\n err_msg = \\\"It should return True\\\"\\r\\n assert out is True, err_msg\\r\\n # Check the error\\r\\n Mock.return_value = self.server_error\\r\\n try:\\r\\n self.ckan.datastore_delete(name='task',\\r\\n resource_id=self.task_resource_id)\\r\\n except Exception as out:\\r\\n type, msg, status_code = out.args\\r\\n assert \\\"Server Error\\\" in msg, msg\\r\\n assert 500 == status_code, status_code\\r\\n assert \\\"CKAN: the remote site failed! datastore_delete failed\\\" == type, type\",\n \"def delete_row(self, identifier, rowid, datastore):\\n # Get dataset. Raise exception if dataset is unknown.\\n dataset = datastore.get_dataset(identifier)\\n if dataset is None:\\n raise ValueError(\\\"unknown dataset '{}'\\\".format(identifier))\\n # Delete the row at the given index position\\n df = vizual.delete_rows(dataset.to_dataframe(), rowids=[rowid])\\n # Store updated dataset to get new identifier.\\n ds = datastore.update_dataset(\\n origin=dataset,\\n df=df,\\n annotations=dataset.annotations.filter(rows=list(df.index))\\n )\\n return VizualApiResult(ds)\",\n \"def dataset_delete(self, name, deep=False):\\n\\n # Checks inputs\\n check_type(value=name, allowed_types=str, var_name=\\\"name\\\", raise_exception=True)\\n check_is_valid_ds_name(value=name, raise_exception=True)\\n check_type(value=deep, allowed_types=bool, var_name=\\\"deep\\\", raise_exception=True)\\n\\n template = 'dataset_remove'\\n if deep:\\n template = 'dataset_deep_remove'\\n response = self.send(root_url=self.session.dm_url + self.root_url,\\n verb=GenericClient.VERB.DELETE,\\n template=TEMPLATES[template],\\n uri_params={\\n 'name': name\\n })\\n\\n if response.status_code == 404:\\n raise IkatsNotFoundError(\\\"Dataset %s not found in database\\\" % name)\\n return response.text\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package(factory=DynamoPackage)\\n self._save_pkgs(pkg)\\n self.db.delete(pkg)\\n count = self.engine.scan(DynamoPackage).count()\\n self.assertEqual(count, 0)\\n count = self.engine.scan(PackageSummary).count()\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def test_delete(self):\\n SampleTemplate.create(self.metadata, self.new_study)\\n SampleTemplate.delete(2)\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.required_sample_info WHERE study_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.study_sample_columns WHERE study_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n with self.assertRaises(QiitaDBExecutionError):\\n self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.sample_2\\\")\",\n \"def delete(self, identifier):\\n self.get(identifier)\\n conn = self.get_connector()\\n cursor = conn.cursor()\\n\\n query = \\\"delete from {0} where {2}={1}\\\".format(\\n self.ressource_config[\\\"table\\\"],\\n identifier,\\n self.model.pk_field.name)\\n try:\\n cursor.execute(query)\\n except sqlite3.IntegrityError, e:\\n message = \\\"\\\"\\n if \\\"foreign\\\" in e.message:\\n message = \\\"\\\"\\\"another ressource depends on this\\n object. Cloud not delete before all ressources\\n depending on it are also deleted\\\"\\\"\\\"\\n\\n raise BadRequest(message)\\n\\n conn.commit()\\n conn.close()\",\n \"def delete_dataset_without_original_url():\\n logging.warning(\\n \\\"*** deleting all netex files created by transport.data.gouv.fr ***\\\"\\n )\\n r = requests.get(\\\"https://transport.data.gouv.fr/api/datasets\\\")\\n r.raise_for_status()\\n datasets = r.json()\\n\\n print_resource = lambda r: f\\\"\\\\n\\\\t*[url = {r['url']} | extras = {r.get('extras')}]\\\"\\n print_resources = lambda rs: [print_resource(r) for r in rs]\\n\\n for d in datasets:\\n dataset_name = d[\\\"title\\\"]\\n if d[\\\"type\\\"] != \\\"public-transit\\\":\\n continue\\n\\n dataset_id = d[\\\"id\\\"]\\n\\n community_resources = _find_community_resources(dataset_id)\\n logging.info(\\\"community ressources : %s\\\", print_resources(community_resources))\\n old_community_resources = [\\n r\\n for r in community_resources\\n if \\\"transport:original_resource_url\\\" not in r.get(\\\"extras\\\", {})\\n ]\\n if old_community_resources:\\n logging.info(\\n \\\"old community ressources : %s\\\",\\n print_resources(old_community_resources),\\n )\\n _delete_community_resources(dataset_id, old_community_resources)\\n logging.info(\\\"deleted community resource for the dataset %s\\\", dataset_id)\",\n \"def test_do_delete_non_existent_id(test_dao):\\r\\n DUT = dtmFunction(test_dao, test=True)\\r\\n DUT.do_select_all(revision_id=1)\\r\\n\\r\\n _error_code, _msg = DUT.do_delete(300)\\r\\n\\r\\n assert _error_code == 2005\\r\\n assert _msg == (\\\"RAMSTK ERROR: Attempted to delete non-existent \\\"\\r\\n \\\"Function ID 300.\\\")\",\n \"def test_delete_datasource(\\n in_memory_runtime_context: EphemeralDataContext,\\n) -> None:\\n context = in_memory_runtime_context\\n\\n name = context.list_datasources()[0][\\\"name\\\"]\\n context.delete_datasource(name)\\n\\n assert name not in context.datasources\",\n \"def test_delete(self):\\n\\n self.metadata.create_or_update(data=self.create)\\n\\n # Find by name\\n res_name = self.metadata.get_by_name(\\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\\n )\\n # Then fetch by ID\\n res_id = self.metadata.get_by_id(\\n entity=Dashboard, entity_id=str(res_name.id.__root__)\\n )\\n\\n # Delete\\n self.metadata.delete(\\n entity=Dashboard, entity_id=str(res_id.id.__root__), recursive=True\\n )\\n\\n # Then we should not find it\\n res = self.metadata.list_entities(entity=Dashboard)\\n assert not next(\\n iter(\\n ent\\n for ent in res.entities\\n if ent.fullyQualifiedName == self.entity.fullyQualifiedName\\n ),\\n None,\\n )\",\n \"def _try_delete_and_return_permissions_error(component_url):\\n try:\\n delete_object_task.DeleteObjectTask(component_url, verbose=False).execute()\\n except api_errors.CloudApiError as e:\\n status = getattr(e, 'status_code', None)\\n if status == 403:\\n return e\\n raise\",\n \"async def test_delete_invalid(database,valid_data):\\n test_valid_insert(database,valid_data)\\n N = 10\\n for idx in range(N+1,N*2):\\n try:\\n await database.delete(_id=idx,user_id=idx)\\n assert False\\n except:\\n assert True\\n await database.close_pool()\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package(factory=SQLPackage)\\n self.sql.add(pkg)\\n transaction.commit()\\n self.sql.add(pkg)\\n self.db.delete(pkg)\\n count = self.sql.query(SQLPackage).count()\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def del_data(self, name):\\n raise NotImplementedError('Do I want to delete data from a df?')\",\n \"def delete_datasource_instance(connection, id, error_msg=None):\\n url = f\\\"{connection.base_url}/api/datasources/{id}\\\"\\n response = connection.session.delete(url=url)\\n if not response.ok:\\n if error_msg is None:\\n error_msg = f\\\"Error deleting Datasource Instance with ID: {id}\\\"\\n response_handler(response, error_msg)\\n return response\",\n \"def test_delete_run(self):\\n pass\",\n \"def delete(self, hostname):\\n self.not_supported()\",\n \"def do_delete(self, arg):\\n \\treturn False\",\n \"def test_delete_data(self):\\n data = Data.objects.create(\\n name='Test data',\\n contributor=self.user,\\n process=self.proc,\\n )\\n\\n data.output = {'json_field': {'foo': 'bar'}}\\n data.status = Data.STATUS_DONE\\n data.save()\\n\\n self.assertEqual(Storage.objects.count(), 1)\\n\\n data.delete()\\n self.assertEqual(Storage.objects.count(), 0)\",\n \"def test_wrong_delete_param(self):\\n def close_conn():\\n cli = LDAPClient(\\\"ldap://%s\\\" % self.ipaddr)\\n LDAPConnection(cli).delete(\\\"cn=dummy\\\")\\n self.assertRaises(ClosedConnection, close_conn)\\n self.assertRaises(TypeError, lambda: self.conn.delete(0))\",\n \"def testDeleteOpInvalidDN(self):\\n self.assertRaises(AssertionError, delta.DeleteOp, 0)\",\n \"def delete(self, ssubject: str, predicate: str, obj: str) -> None:\\n raise NotImplementedError(\\\"The RDF graph is read-only: DELETE DATA queries are not allowed\\\")\",\n \"def test_delete_failure(self):\\r\\n problem_url_name = 'H1P1'\\r\\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\\r\\n self.define_option_problem(problem_url_name)\\r\\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\\r\\n\\r\\n expected_message = \\\"bad things happened\\\"\\r\\n with patch('courseware.models.StudentModule.delete') as mock_delete:\\r\\n mock_delete.side_effect = ZeroDivisionError(expected_message)\\r\\n instructor_task = self.delete_problem_state('instructor', location)\\r\\n self._assert_task_failure(instructor_task.id, 'delete_problem_state', problem_url_name, expected_message)\",\n \"def test_handle_delete_github_error(self):\\n self.db.query.side_effect = GithubAPIException(\\\"error\\\")\\n self.assertTupleEqual(self.testcommand.handle(\\\"team delete brs\\\", user),\\n (\\\"Team delete was unsuccessful with \\\"\\n \\\"the following error: \\\"\\n \\\"error\\\", 200))\\n self.db.delete.assert_not_called()\\n self.gh.org_delete_team.assert_not_called()\",\n \"def delete_datafile(self, save_instance=True):\\n if self.datafile:\\n logger.debug(\\\"Deleting datafile '%s'\\\", self.datafile.name)\\n try:\\n self.datafile.delete(save=save_instance)\\n except OSError as exc:\\n logger.error(\\\"Error deleting file '%s': %s\\\",\\n self.datafile.name, exc)\\n return False\\n logger.info(\\\"Deleted datafile of '%s'\\\", self)\",\n \"async def test_delete_batch_invalid(database,valid_data):\\n test_valid_insert_batch(database,valid_data)\\n N = 10\\n batch_id = 1\\n for idx in range(N+1,N*2):\\n try:\\n await database.delete_batch(batch_id=batch_id,user_id=idx)\\n assert False\\n except:\\n assert True\\n await database.close_pool()\",\n \"def delete_rdataset(self, name, rdtype, covers=dns.rdatatype.NONE):\\n\\n name = self._validate_name(name)\\n rdtype = dns.rdatatype.RdataType.make(rdtype)\\n if covers is not None:\\n covers = dns.rdatatype.RdataType.make(covers)\\n node = self.get_node(name)\\n if node is not None:\\n node.delete_rdataset(self.rdclass, rdtype, covers)\\n if len(node) == 0:\\n self.delete_node(name)\",\n \"def delete(self, context, id_):\\n try:\\n db_resource_data = self.db_api.get_resource(\\n context, id_)\\n\\n if db_resource_data['type'] == (eon_const.\\n EON_RESOURCE_TYPE_ESX_CLUSTER):\\n msg = _(\\\"Delete operation not supported for type %s\\\"\\n % db_resource_data['type'])\\n raise exception.DeleteException(err=msg)\\n\\n _resource_data = _make_response(\\n db_resource_data)\\n _resource_data_log = deepcopy(_resource_data)\\n _resource_data_log.pop(\\\"meta_data\\\", None)\\n LOG.info(\\\"Details for the ID %s is: %s\\\" % (\\n id_, logging.mask_password(_resource_data_log)))\\n driver_obj = driver.load_resource_driver(\\n db_resource_data['type'])\\n driver_obj.validate_delete(db_resource_data)\\n driver_obj.delete(context, id_)\\n self.db_api.delete_resource(context, id_)\\n # delete the data from hlm input model\\n try:\\n LOG.info(\\\"[%s] remove resource from input model\\\" % id_)\\n hux_obj = HLMFacadeWrapper(context)\\n resource_id = db_resource_data[eon_const.EON_RESOURCE_ID]\\n hux_obj.delete_server(resource_id)\\n hux_obj.commit_changes(resource_id, \\\"Delete compute resource\\\")\\n except facade_excep.NotFound:\\n # log and do nothing\\n LOG.warn(\\\"[%s] resource not found in hlm input model\\\" % id_)\\n LOG.info(\\\"[%s]: Deleted resource from eon\\\" % id_)\\n # Notify the message to consumers\\n try:\\n message = {\\\"resource_id\\\": id_,\\n \\\"resource_state\\\": eon_const.EON_RESOURCE_STATE_REMOVED,\\n \\\"resource_details\\\": _resource_data,\\n }\\n message_notifier.notify(context,\\n message_notifier.EVENT_PRIORITY_INFO,\\n message_notifier.EVENT_TYPE[\\n 'removed'],\\n message)\\n except Exception as ex:\\n LOG.exception(\\n \\\"Exception while notifying the message : %s\\\" % ex)\\n except exception.NotFound as e:\\n msg = (\\\"Failed to delete resource %s. Error: %s\\\") % (\\n _resource_data['name'], e.message)\\n LOG.exception(msg)\\n raise e\",\n \"def delete(self):\\n self.logger.debug(\\\"In delete.\\\")\\n\\n if self._id is None:\\n self.logger.warn(\\\"Attempt to delete a %s with no ID.\\\", __name__)\\n raise Exception(\\\"{} does not have an ID.\\\".format(__name__))\\n\\n id = self._id\\n\\n session = iHMPSession.get_session()\\n self.logger.info(\\\"Got iHMP session.\\\")\\n\\n # Assume failure\\n success = False\\n\\n try:\\n self.logger.info(\\\"Deleting %s with ID %s.\\\", __name__, id)\\n session.get_osdf().delete_node(id)\\n success = True\\n except Exception as delete_exception:\\n self.logger.exception(delete_exception)\\n self.logger.error(\\\"An error occurred when deleting %s.\\\", self)\\n\\n return success\",\n \"def test_sg_delete_non_associated(self):\\n\\n # Add a faked storage group to be tested and another one\\n faked_storage_group = self.add_storage_group1()\\n self.add_storage_group2()\\n\\n storage_group_mgr = self.console.storage_groups\\n\\n storage_group = storage_group_mgr.find(name=faked_storage_group.name)\\n\\n # Execute the code to be tested.\\n storage_group.delete()\\n\\n # Check that the storage group no longer exists\\n with pytest.raises(NotFound):\\n storage_group_mgr.find(name=faked_storage_group.name)\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def test_delete_unkonwn_id_error(self):\\n with self.assertRaises(QiitaDBUnknownIDError):\\n PrepTemplate.delete(5)\",\n \"def s3_delete_data(self):\\n\\n self.k.delete()\",\n \"def delete(self, *args, **kwargs):\\n raise NotImplementedError()\",\n \"def delete(self, error_id):\\n error = self.db.session.query(models.Error).get(error_id)\\n if error:\\n self.db.session.delete(error)\\n self.db.session.commit()\\n else:\\n raise InvalidErrorReference(\\\"No error with id %s\\\" % str(error_id))\",\n \"def delete_dataset(key=None) -> DeleteDatasetResponse:\\n config = ThreatExchangeConfig.getx(str(key))\\n hmaconfig.delete_config(config)\\n return DeleteDatasetResponse(response=\\\"The privacy group is deleted\\\")\",\n \"def clean(args):\\n with_dataset(args, Dataset._clean)\",\n \"def delete(self, predicate, successHandler=None, failHandler=None):\\n queryDelete = \\\"DELETE FROM `article_article` \\\" \\\\\\n \\\"WHERE `{}` {} %s LIMIT 1;\\\".format(\\n predicate[0],\\n predicate[1]\\n )\\n\\n queryDeleteParams = []\\n if isinstance(predicate[2], datetime):\\n queryDeleteParams.append(predicate[2].strftime(\\\"%Y-%m-%d %H:%M:%S\\\"))\\n else:\\n queryDeleteParams.append(predicate[2])\\n\\n def failCallback(error):\\n errorMessage = str(error)\\n if isinstance(error, Failure):\\n errorMessage = error.getErrorMessage()\\n\\n self.log.error(\\n \\\"[Default.Article] delete() database error: {errorMessage}\\\",\\n errorMessage=errorMessage\\n )\\n\\n if failHandler is not None:\\n reactor.callInThread(failHandler, [\\\"DatabaseError\\\"])\\n\\n def successCallback(results):\\n if successHandler is not None:\\n reactor.callInThread(successHandler)\\n\\n operation = self.dbService.runOperation(\\n queryDelete,\\n tuple(queryDeleteParams)\\n )\\n operation.addCallbacks(successCallback, failCallback)\",\n \"def delete(self):\\n raise NotImplementedError\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package()\\n key = self.db.redis_key(pkg.filename)\\n self.redis[key] = \\\"foobar\\\"\\n self.db.delete(pkg)\\n val = self.redis.get(key)\\n self.assertIsNone(val)\\n count = self.redis.scard(self.db.redis_set)\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def test_delete_unkonwn_id_error(self):\\n with self.assertRaises(QiitaDBUnknownIDError):\\n SampleTemplate.delete(5)\",\n \"def remove_dataset(self, name):\\n payload = {\\\"name\\\": name}\\n r = self.request(\\n \\\"delete\\\", url_path_join(USER_DATASET_RESOURCE_URL, self.owner), payload=payload\\n )\\n self.check_and_raise(r)\",\n \"async def delete_dataset(\\n self,\\n request: Optional[\\n Union[data_labeling_service.DeleteDatasetRequest, dict]\\n ] = None,\\n *,\\n name: Optional[str] = None,\\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\\n timeout: Union[float, object] = gapic_v1.method.DEFAULT,\\n metadata: Sequence[Tuple[str, str]] = (),\\n ) -> None:\\n # Create or coerce a protobuf request object.\\n # Quick check: If we got a request object, we should *not* have\\n # gotten any keyword arguments that map to the request.\\n has_flattened_params = any([name])\\n if request is not None and has_flattened_params:\\n raise ValueError(\\n \\\"If the `request` argument is set, then none of \\\"\\n \\\"the individual field arguments should be set.\\\"\\n )\\n\\n request = data_labeling_service.DeleteDatasetRequest(request)\\n\\n # If we have keyword arguments corresponding to fields on the\\n # request, apply these.\\n if name is not None:\\n request.name = name\\n\\n # Wrap the RPC method; this adds retry and timeout information,\\n # and friendly error handling.\\n rpc = gapic_v1.method_async.wrap_method(\\n self._client._transport.delete_dataset,\\n default_retry=retries.Retry(\\n initial=0.1,\\n maximum=30.0,\\n multiplier=1.3,\\n predicate=retries.if_exception_type(\\n core_exceptions.DeadlineExceeded,\\n core_exceptions.ServiceUnavailable,\\n ),\\n deadline=30.0,\\n ),\\n default_timeout=30.0,\\n client_info=DEFAULT_CLIENT_INFO,\\n )\\n\\n # Certain fields should be provided within the metadata header;\\n # add these here.\\n metadata = tuple(metadata) + (\\n gapic_v1.routing_header.to_grpc_metadata(((\\\"name\\\", request.name),)),\\n )\\n\\n # Send the request.\\n await rpc(\\n request,\\n retry=retry,\\n timeout=timeout,\\n metadata=metadata,\\n )\",\n \"def test_delete_edge_case_with_write_concern_0_return_None(self):\\n p1 = self.Person(name=\\\"User Z\\\", age=20).save()\\n del_result = p1.delete(w=0)\\n assert del_result is None\",\n \"def delete_table_data():\\n try:\\n print 'delete existing data'\\n sql = 'delete from document'\\n sql1 = 'delete from clean_keywords'\\n sql2 = 'delete from keywords'\\n util.executeSQL(conn, sql) # delete the existing data.\\n util.executeSQL(conn, sql1)\\n util.executeSQL(conn, sql2)\\n except Exception as e:\\n print e\",\n \"def test_data_object_del(self):\\n pass\",\n \"def test_raise_when_no_id(self):\\n model = self.Test({}, False)\\n self.assertRaises(errors.PersistenceError, model.delete)\",\n \"def delete(self, *args, **kwargs):\\n return 0\",\n \"def delete_file(self, filename=None):\\n return self._service.delete_object(self._datasets_id, filename)\",\n \"def test_delete(self, init_db, audit):\\n audit.delete()\\n assert Audit.get(audit.id) == None\",\n \"def test_delete_category_does_not_exist(self):\\n self.delete_does_not_exist_fail('hats')\",\n \"def _TryDeleteTable(dataset_id, table_id, project_id):\\n client = GetApiClient()\\n service = client.tables\\n delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')\\n delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,\\n projectId=project_id)\\n service.Delete(delete_request)\\n log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id))\",\n \"def test_delete(self):\\n pt = PrepTemplate.create(self.metadata, self.new_raw_data,\\n self.test_study, self.data_type_id)\\n PrepTemplate.delete(pt.id)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_template WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.common_prep_info WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_columns WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n with self.assertRaises(QiitaDBExecutionError):\\n self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_2\\\")\",\n \"def delete(self):\\n raise NotImplementedError()\",\n \"def delete(self):\\n raise NotImplementedError()\",\n \"def test_delete_without_partition_key(self):\\r\\n with self.assertRaises(query.QueryException):\\r\\n TestModel.objects(attempt_id=0).delete()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7605005","0.7107175","0.70523417","0.69809973","0.6883148","0.6740322","0.6667521","0.65653944","0.6536053","0.65328515","0.65034896","0.6410687","0.6386324","0.6328574","0.63253295","0.62904114","0.6277353","0.62735856","0.6252367","0.61857146","0.6168082","0.6162157","0.613244","0.6089961","0.60710067","0.60618997","0.6054307","0.60175395","0.59812534","0.59728926","0.5945504","0.5898049","0.58455795","0.5814105","0.58104396","0.5775425","0.5733373","0.5725115","0.570578","0.5701192","0.5630272","0.56293786","0.56126684","0.56120926","0.5611404","0.56092745","0.5607267","0.5595084","0.5575618","0.5560845","0.55180013","0.55004615","0.54946786","0.5494068","0.5493824","0.54772246","0.5475572","0.54748356","0.54659593","0.54646385","0.546054","0.545929","0.5447527","0.5440744","0.54403776","0.5428439","0.5425052","0.5412754","0.53937244","0.53930616","0.5389392","0.53804857","0.537615","0.53478956","0.5340608","0.533264","0.53314257","0.5328683","0.53236055","0.5322863","0.5313439","0.53118443","0.5311221","0.5309877","0.530916","0.53082687","0.52888113","0.5282388","0.52746874","0.52719414","0.5265507","0.5262418","0.5255371","0.52480537","0.52463824","0.52461874","0.5243807","0.5236309","0.5236309","0.52332956"],"string":"[\n \"0.7605005\",\n \"0.7107175\",\n \"0.70523417\",\n \"0.69809973\",\n \"0.6883148\",\n \"0.6740322\",\n \"0.6667521\",\n \"0.65653944\",\n \"0.6536053\",\n \"0.65328515\",\n \"0.65034896\",\n \"0.6410687\",\n \"0.6386324\",\n \"0.6328574\",\n \"0.63253295\",\n \"0.62904114\",\n \"0.6277353\",\n \"0.62735856\",\n \"0.6252367\",\n \"0.61857146\",\n \"0.6168082\",\n \"0.6162157\",\n \"0.613244\",\n \"0.6089961\",\n \"0.60710067\",\n \"0.60618997\",\n \"0.6054307\",\n \"0.60175395\",\n \"0.59812534\",\n \"0.59728926\",\n \"0.5945504\",\n \"0.5898049\",\n \"0.58455795\",\n \"0.5814105\",\n \"0.58104396\",\n \"0.5775425\",\n \"0.5733373\",\n \"0.5725115\",\n \"0.570578\",\n \"0.5701192\",\n \"0.5630272\",\n \"0.56293786\",\n \"0.56126684\",\n \"0.56120926\",\n \"0.5611404\",\n \"0.56092745\",\n \"0.5607267\",\n \"0.5595084\",\n \"0.5575618\",\n \"0.5560845\",\n \"0.55180013\",\n \"0.55004615\",\n \"0.54946786\",\n \"0.5494068\",\n \"0.5493824\",\n \"0.54772246\",\n \"0.5475572\",\n \"0.54748356\",\n \"0.54659593\",\n \"0.54646385\",\n \"0.546054\",\n \"0.545929\",\n \"0.5447527\",\n \"0.5440744\",\n \"0.54403776\",\n \"0.5428439\",\n \"0.5425052\",\n \"0.5412754\",\n \"0.53937244\",\n \"0.53930616\",\n \"0.5389392\",\n \"0.53804857\",\n \"0.537615\",\n \"0.53478956\",\n \"0.5340608\",\n \"0.533264\",\n \"0.53314257\",\n \"0.5328683\",\n \"0.53236055\",\n \"0.5322863\",\n \"0.5313439\",\n \"0.53118443\",\n \"0.5311221\",\n \"0.5309877\",\n \"0.530916\",\n \"0.53082687\",\n \"0.52888113\",\n \"0.5282388\",\n \"0.52746874\",\n \"0.52719414\",\n \"0.5265507\",\n \"0.5262418\",\n \"0.5255371\",\n \"0.52480537\",\n \"0.52463824\",\n \"0.52461874\",\n \"0.5243807\",\n \"0.5236309\",\n \"0.5236309\",\n \"0.52332956\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.74737805"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":2295,"cells":{"query":{"kind":"string","value":"Try to delete a dataset, propagating error on failure."},"document":{"kind":"string","value":"def _TryDeleteTable(dataset_id, table_id, project_id):\n client = GetApiClient()\n service = client.tables\n delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')\n delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,\n projectId=project_id)\n service.Delete(delete_request)\n log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_dataset(self, dataset):\n raise NotImplementedError('delete_dataset')","def _TryDeleteDataset(dataset_id, project_id):\n client = GetApiClient()\n service = client.datasets\n delete_request_type = GetApiMessage('BigqueryDatasetsDeleteRequest')\n delete_request = delete_request_type(datasetId=dataset_id,\n projectId=project_id,\n deleteContents=True)\n service.Delete(delete_request)\n log.info('Deleted dataset [{}:{}]'.format(project_id, dataset_id))","def _handle_creation_failure(session: Session, stub_dataset: Dataset, error: str):\n try:\n dataset.delete(session, stub_dataset)\n except requests.HTTPError:\n raise CreationFailure(\n f\"Created dataset did not delete after an earlier error: {error}\"\n )\n raise CreationFailure(error)","def _delete_dataset_netex(dataset_id):\n try:\n logging.info(\"Going to delete the netex file of the dataset %s\", dataset_id)\n community_resource = _find_community_resources(dataset_id)\n _delete_community_resources(dataset_id, community_resource)\n logging.info(\"deleted community resource for the dataset %s\", dataset_id)\n except requests.HTTPError as err:\n logging.warning(\n \"Unable to delete to the dataset %s. Http Error %s\", dataset_id, err\n )\n except Exception as err:\n logging.warning(\n \"Unable to delete to the dataset %s. Generic Error %s\", dataset_id, err\n )","def delete_dataset(self, dataset: DatasetDB):\n try:\n self._es.delete_index(dataset_records_index(dataset.id))\n finally:\n self._es.delete_document(index=DATASETS_INDEX_NAME, doc_id=dataset.id)","def test_dataset_deltitem(train_dataset):\n with pytest.raises(Exception):\n del train_dataset[0]","def delete(_id):\n dataset = ESDataset.get(id=_id, ignore=404)\n\n if not dataset:\n raise NoEntityError(f\"dataset {_id} does not exist.\")\n\n dataset.delete()\n\n return dataset.name","def delete(log, args):\n log('dataset id: {highlight}{id}{reset}',\n highlight=Fore.GREEN,\n id=args.id,\n reset=Style.RESET_ALL)\n log.warn('delete dataset command coming soon.')","def delete_dataset(self, identifier):\n # Delete the dataset directory if it exists. Otherwise return False\n dataset_dir = self.get_dataset_dir(identifier)\n if not os.path.isdir(dataset_dir):\n return False\n shutil.rmtree(dataset_dir)\n return True","def delete_dataset(dataset_path):\n force_rmtree(dataset_path)","def DeleteDataset(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details(\"Method not implemented!\")\n raise NotImplementedError(\"Method not implemented!\")","def delete_dataset(request):\n body = json.loads(request.body)\n dataset_id = body.get('dataset_id', '')\n organization_id = body.get('organization_id')\n # check if user has access to the dataset\n d = ImportRecord.objects.filter(\n super_organization_id=organization_id, pk=dataset_id\n )\n if not d.exists():\n return {\n 'status': 'error',\n 'message': 'user does not have permission to delete dataset',\n }\n d = d[0]\n d.delete()\n return {\n 'status': 'success',\n }","def delete(self, dataset_name=None, dataset_id=None, sure=False, really=False):\n if sure and really:\n dataset = self.get(dataset_name=dataset_name, dataset_id=dataset_id)\n success, response = self._client_api.gen_request(req_type='delete',\n path='/datasets/{}'.format(dataset.id))\n if not success:\n raise exceptions.PlatformException(response)\n logger.info('Dataset {} was deleted successfully'.format(dataset.name))\n return True\n else:\n raise exceptions.PlatformException(\n error='403',\n message='Cant delete dataset from SDK. Please login to platform to delete')","def delete(self, ds, del_raw_data=False, **kwargs):\n self.logger.warning('ds_id already exists: {}. Deleting'.format(ds.id))\n self._del_iso_images(ds)\n self._es.delete_ds(ds.id)\n self._db.alter('DELETE FROM dataset WHERE id=%s', ds.id)\n if del_raw_data:\n self.logger.warning('Deleting raw data: {}'.format(ds.input_path))\n wd_man = WorkDirManager(ds.id)\n wd_man.del_input_data(ds.input_path)\n if self.mode == 'queue':\n self._queue.publish({'ds_id': ds.id, 'status': DatasetStatus.DELETED}, SM_DS_STATUS)","def test_that_when_dataset_is_deleted_the_account_is_still_there(self):\n test_dataset = Dataset.objects.get(\n dataset_slug=\"google-geojson-example\")\n test_dataset.delete()\n with self.assertRaises(ObjectDoesNotExist):\n Dataset.objects.get(dataset_slug=\"google-geojson-example\")\n Account.objects.get(account_slug=\"test_user\")","def delete(self, name):\n assert name, \"Must input a valid dataset name.\"\n self.manager.delete_data(name)","def _try_delete_resource(self, delete_callable, *args, **kwargs):\n try:\n delete_callable(*args, **kwargs)\n # if resource is not found, this means it was deleted in the test\n except exceptions.NotFound:\n pass","def delete_datasetreplica(self, dataset_replica):\n raise NotImplementedError('delete_datasetreplica')","def delete(self, ds, del_raw_data=False):\n self._post_sm_msg(ds=ds, action=DatasetAction.DELETE, priority=DatasetActionPriority.HIGH)","def test_dataset_exists(client, to_delete):\n DATASET_ID = \"get_table_dataset_{}\".format(_millis())\n dataset_ref = client.dataset(DATASET_ID)\n dataset = bigquery.Dataset(dataset_ref)\n dataset = client.create_dataset(dataset)\n to_delete.append(dataset)\n\n assert dataset_exists(client, dataset_ref)\n assert not dataset_exists(client, client.dataset(\"dataset doesnot exist\"))","def delete_dataset_target_bigquery(self, dataset):\n return db.delete_dataset_bigquery(\n dataset, project=self.get_conn_env_var('TARGET_BIGQUERY', 'PROJECT')\n )","def purge_dataset(request):\n data = json.loads(request.body.decode('utf-8'))\n if not request.user.is_staff:\n return JsonResponse({'error': 'Only admin can purge dataset'}, status=403)\n try:\n dset = models.Dataset.objects.get(pk=data['item_id'])\n except models.Dataset.DoesNotExist:\n return JsonResponse({'error': 'Dataset does not exist'}, status=403)\n purgemsg = delete_dataset_from_cold(dset)\n if purgemsg['state'] == 'error':\n return JsonResponse(purgemsg, status=500)\n else:\n return JsonResponse(purgemsg)","def raise_exception_for_dataset(dataset_reference):\n if dataset_reference.dataset_id == non_existing_dataset_id:\n raise cloud.exceptions.NotFound('')","def delete_bigquery_dataset(self, shared_state: Dict[str, Any]):\n\n yield\n\n # Get the bigquery dataset id used for testing and wipe it\n bigquery_dataset = shared_state[\"bigquery_dataset\"]\n bigquery_client = shared_state[\"bigquery_client\"]\n bigquery_client.delete_dataset(\n bigquery_dataset.dataset_id, delete_contents=True, not_found_ok=True\n ) # Make an API request.","def test_delete_unexpected_error(self, requests_mock, capsys):\n requests_mock.delete(data_url, exc=ConnectionError)\n with pytest.raises(ConnectionError):\n r = operations.delete(data_url)\n assert 'Unexpected error when connecting to' in capsys.readouterr().out","def delete(dtype, name, rootdir=None):\n # type and the name\n # delete them\n num_deleted = 0\n for dataset in FreezableAPI.datasets(dtype,name,rootdir=rootdir,fullpath=True):\n # delete it\n shutil.rmtree(dataset)\n num_deleted += 1\n return num_deleted","def delete_temp_dataset():\n\n bq.delete_dataset(temp_dataset_ref, delete_contents=True, not_found_ok=True)","def delete(self, identifier, dataset):\n # Fix identifier because SQlAlchemy can't parse RDF Literals\n identifier = str(identifier)\n\n #self._load_config()\n self.log( 'Removing resource %s in dataset %s' % (identifier, dataset))\n\n # Remove it\n data = self.es_instance.delete_document(identifier, dataset)\n\n self.log( 'Registro %s removido com sucesso' % identifier)\n\n return data","def delete_task(dataset):\n Observation.delete_all(dataset)\n super(dataset.__class__, dataset).delete({DATASET_ID: dataset.dataset_id})","def do_delete(self, node_id):\n _error_code, _msg = RAMSTKDataModel.do_delete(self, node_id)\n\n # pylint: disable=attribute-defined-outside-init\n # It is defined in RAMSTKDataModel.__init__\n if _error_code != 0:\n _error_code = 1\n _msg = _msg + (\n '\\n RAMSTK ERROR: Attempted to delete non-existent '\n 'Allocation ID {0:d}.').format(node_id)\n else:\n self.last_id = max(self.tree.nodes.keys())\n\n return _error_code, _msg","def delete_ds(self, dt):\n\n for k in self.datasets_keys:\n for F in self.datasets[k]:\n if F not in data[k].keys():\n continue \n max_date = data[k][F]['max_date'] \n \"\"\" Deleting unecessary ds \"\"\"\n if dt > max_date : # check max date and check if data is still loaded\n print(blue + 'Memory used before deleting : ' , process.memory_info().rss/1000000000 , cend) \n del data[k][F] \n print(\"*** Erasing dataset: \" , k , ' ' , F ) \n print(blue + 'Memory used after deleting : ' , process.memory_info().rss/1000000000 , cend) \n \n else:\n continue","def dataset(bf):\n ds = bf.create_dataset(\"test_dataset_{}\".format(uuid4()))\n\n yield ds\n\n bf._api.datasets.delete(ds)","def destroyDataset(request):\n\n if request.method=='DELETE':\n json_data=json.loads(request.body)\n name=json_data['name']\n try:\n dataset=Dataset.nodes.get(name=name)\n dataset.delete()\n return JsonResponse({\"success\": \"Dataset deleted\"}, safe=False)\n except:\n return JsonResponse({\"error\":\"Error occurred\"}, safe=False)","def test_delete_voice_dataset(self):\n pass","def delete_data(self, name):\n assert name, \"Must input a valid dataset name.\"\n try:\n self.data[\"dataset\"].pop(name)\n self.update_categories()\n self.write_data_cache(self.data)\n except KeyError:\n raise KeyError(\"The dataset \\'{}\\' does not exist in the cache.\".format(name))","def test_deletion_fail(self):\n\n # Assert that a RelaxNoPipeError occurs when the data pipe does not exist.\n self.assertRaises(RelaxNoPipeError, pipes.delete, 'x')","def test_delete_http_error(self, requests_mock, capsys):\n requests_mock.delete(data_url, status_code=300)\n with pytest.raises(RuntimeError):\n r = operations.delete(data_url)\n assert 'HTTP error: 300' in capsys.readouterr().out","def test_delete_error(self):\n with self.assertRaises(QiitaDBExecutionError):\n PrepTemplate.delete(1)","def delete_datasets(self, base_url):\n response = requests.get(base_url + '/testdata')\n for index in range(len(response.json()['testdata'])):\n self.delete_dataset(base_url, response.json()['testdata'][index]['dataset'])","def test_delete(self):\n data_columns = ['id', 'column_string', 'column_float']\n data_values = [[1, 'string1', 456.956], [2, 'string2', 38.905]]\n data = pd.DataFrame(data_values, columns=data_columns)\n data.name = 'test_delete'\n my_conn = MySQL(*self.conn_params)\n my_conn.insert(data)\n table = my_conn.get_table(data.name)\n expected = 2\n current = my_conn.engine.scalar(\n select([func.count('*')]).select_from(table)\n )\n self.assertEqual(current, expected)\n\n # delete from operation\n # the None argument in delete DML is included to avoid pylint E1120\n table.delete(None).where(table.c.id == 2).execute()\n\n expected = 1\n current = my_conn.engine.scalar(\n select([func.count('*')]).select_from(table)\n )\n self.assertEqual(current, expected)\n my_conn.drop(data.name)","def delData(self, ide = None):\r\n try:\r\n if ide is not None:\r\n self.cursor.execute(\"DELETE FROM DATAS WHERE ID = %s;\" %(ide))\r\n return True\r\n else:\r\n return False\r\n except:\r\n return False","def delete():","def delete(self, data):\r\n pass","def delete_upload_data(self, id=None, name=None) -> None:\r\n # get the dataset\r\n dataset = self.get_upload_data(id=id, name=name)\r\n\r\n try:\r\n self.session.delete(dataset)\r\n self.session.commit()\r\n except Exception as e:\r\n self.session.rollback()\r\n raise e","def delete_run(self, run_id):\n ds = self.datastorage\n ds.get_metrics_dao().delete(run_id)\n # TODO: implement\n # ds.get_artifact_dao().delete(run_id)\n # ds.get_resource_dao().delete(run_id)\n ds.get_run_dao().delete(run_id)","def test_07_datastore_delete(self, Mock):\r\n html_request = FakeRequest(json.dumps({}), 200,\r\n {'content-type': 'application/json'})\r\n\r\n Mock.return_value = html_request\r\n with self.flask_app.test_request_context('/'):\r\n out = self.ckan.datastore_delete(name='task',\r\n resource_id=self.task_resource_id)\r\n err_msg = \"It should return True\"\r\n assert out is True, err_msg\r\n # Check the error\r\n Mock.return_value = self.server_error\r\n try:\r\n self.ckan.datastore_delete(name='task',\r\n resource_id=self.task_resource_id)\r\n except Exception as out:\r\n type, msg, status_code = out.args\r\n assert \"Server Error\" in msg, msg\r\n assert 500 == status_code, status_code\r\n assert \"CKAN: the remote site failed! datastore_delete failed\" == type, type","def delete_row(self, identifier, rowid, datastore):\n # Get dataset. Raise exception if dataset is unknown.\n dataset = datastore.get_dataset(identifier)\n if dataset is None:\n raise ValueError(\"unknown dataset '{}'\".format(identifier))\n # Delete the row at the given index position\n df = vizual.delete_rows(dataset.to_dataframe(), rowids=[rowid])\n # Store updated dataset to get new identifier.\n ds = datastore.update_dataset(\n origin=dataset,\n df=df,\n annotations=dataset.annotations.filter(rows=list(df.index))\n )\n return VizualApiResult(ds)","def dataset_delete(self, name, deep=False):\n\n # Checks inputs\n check_type(value=name, allowed_types=str, var_name=\"name\", raise_exception=True)\n check_is_valid_ds_name(value=name, raise_exception=True)\n check_type(value=deep, allowed_types=bool, var_name=\"deep\", raise_exception=True)\n\n template = 'dataset_remove'\n if deep:\n template = 'dataset_deep_remove'\n response = self.send(root_url=self.session.dm_url + self.root_url,\n verb=GenericClient.VERB.DELETE,\n template=TEMPLATES[template],\n uri_params={\n 'name': name\n })\n\n if response.status_code == 404:\n raise IkatsNotFoundError(\"Dataset %s not found in database\" % name)\n return response.text","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package(factory=DynamoPackage)\n self._save_pkgs(pkg)\n self.db.delete(pkg)\n count = self.engine.scan(DynamoPackage).count()\n self.assertEqual(count, 0)\n count = self.engine.scan(PackageSummary).count()\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def test_delete(self):\n SampleTemplate.create(self.metadata, self.new_study)\n SampleTemplate.delete(2)\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.required_sample_info WHERE study_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.study_sample_columns WHERE study_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n with self.assertRaises(QiitaDBExecutionError):\n self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.sample_2\")","def delete(self, identifier):\n self.get(identifier)\n conn = self.get_connector()\n cursor = conn.cursor()\n\n query = \"delete from {0} where {2}={1}\".format(\n self.ressource_config[\"table\"],\n identifier,\n self.model.pk_field.name)\n try:\n cursor.execute(query)\n except sqlite3.IntegrityError, e:\n message = \"\"\n if \"foreign\" in e.message:\n message = \"\"\"another ressource depends on this\n object. Cloud not delete before all ressources\n depending on it are also deleted\"\"\"\n\n raise BadRequest(message)\n\n conn.commit()\n conn.close()","def delete_dataset_without_original_url():\n logging.warning(\n \"*** deleting all netex files created by transport.data.gouv.fr ***\"\n )\n r = requests.get(\"https://transport.data.gouv.fr/api/datasets\")\n r.raise_for_status()\n datasets = r.json()\n\n print_resource = lambda r: f\"\\n\\t*[url = {r['url']} | extras = {r.get('extras')}]\"\n print_resources = lambda rs: [print_resource(r) for r in rs]\n\n for d in datasets:\n dataset_name = d[\"title\"]\n if d[\"type\"] != \"public-transit\":\n continue\n\n dataset_id = d[\"id\"]\n\n community_resources = _find_community_resources(dataset_id)\n logging.info(\"community ressources : %s\", print_resources(community_resources))\n old_community_resources = [\n r\n for r in community_resources\n if \"transport:original_resource_url\" not in r.get(\"extras\", {})\n ]\n if old_community_resources:\n logging.info(\n \"old community ressources : %s\",\n print_resources(old_community_resources),\n )\n _delete_community_resources(dataset_id, old_community_resources)\n logging.info(\"deleted community resource for the dataset %s\", dataset_id)","def test_do_delete_non_existent_id(test_dao):\r\n DUT = dtmFunction(test_dao, test=True)\r\n DUT.do_select_all(revision_id=1)\r\n\r\n _error_code, _msg = DUT.do_delete(300)\r\n\r\n assert _error_code == 2005\r\n assert _msg == (\"RAMSTK ERROR: Attempted to delete non-existent \"\r\n \"Function ID 300.\")","def test_delete_datasource(\n in_memory_runtime_context: EphemeralDataContext,\n) -> None:\n context = in_memory_runtime_context\n\n name = context.list_datasources()[0][\"name\"]\n context.delete_datasource(name)\n\n assert name not in context.datasources","def test_delete(self):\n\n self.metadata.create_or_update(data=self.create)\n\n # Find by name\n res_name = self.metadata.get_by_name(\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\n )\n # Then fetch by ID\n res_id = self.metadata.get_by_id(\n entity=Dashboard, entity_id=str(res_name.id.__root__)\n )\n\n # Delete\n self.metadata.delete(\n entity=Dashboard, entity_id=str(res_id.id.__root__), recursive=True\n )\n\n # Then we should not find it\n res = self.metadata.list_entities(entity=Dashboard)\n assert not next(\n iter(\n ent\n for ent in res.entities\n if ent.fullyQualifiedName == self.entity.fullyQualifiedName\n ),\n None,\n )","def _try_delete_and_return_permissions_error(component_url):\n try:\n delete_object_task.DeleteObjectTask(component_url, verbose=False).execute()\n except api_errors.CloudApiError as e:\n status = getattr(e, 'status_code', None)\n if status == 403:\n return e\n raise","async def test_delete_invalid(database,valid_data):\n test_valid_insert(database,valid_data)\n N = 10\n for idx in range(N+1,N*2):\n try:\n await database.delete(_id=idx,user_id=idx)\n assert False\n except:\n assert True\n await database.close_pool()","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package(factory=SQLPackage)\n self.sql.add(pkg)\n transaction.commit()\n self.sql.add(pkg)\n self.db.delete(pkg)\n count = self.sql.query(SQLPackage).count()\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def del_data(self, name):\n raise NotImplementedError('Do I want to delete data from a df?')","def delete_datasource_instance(connection, id, error_msg=None):\n url = f\"{connection.base_url}/api/datasources/{id}\"\n response = connection.session.delete(url=url)\n if not response.ok:\n if error_msg is None:\n error_msg = f\"Error deleting Datasource Instance with ID: {id}\"\n response_handler(response, error_msg)\n return response","def test_delete_run(self):\n pass","def delete(self, hostname):\n self.not_supported()","def do_delete(self, arg):\n \treturn False","def test_delete_data(self):\n data = Data.objects.create(\n name='Test data',\n contributor=self.user,\n process=self.proc,\n )\n\n data.output = {'json_field': {'foo': 'bar'}}\n data.status = Data.STATUS_DONE\n data.save()\n\n self.assertEqual(Storage.objects.count(), 1)\n\n data.delete()\n self.assertEqual(Storage.objects.count(), 0)","def test_wrong_delete_param(self):\n def close_conn():\n cli = LDAPClient(\"ldap://%s\" % self.ipaddr)\n LDAPConnection(cli).delete(\"cn=dummy\")\n self.assertRaises(ClosedConnection, close_conn)\n self.assertRaises(TypeError, lambda: self.conn.delete(0))","def testDeleteOpInvalidDN(self):\n self.assertRaises(AssertionError, delta.DeleteOp, 0)","def delete(self, ssubject: str, predicate: str, obj: str) -> None:\n raise NotImplementedError(\"The RDF graph is read-only: DELETE DATA queries are not allowed\")","def test_delete_failure(self):\r\n problem_url_name = 'H1P1'\r\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\r\n self.define_option_problem(problem_url_name)\r\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\r\n\r\n expected_message = \"bad things happened\"\r\n with patch('courseware.models.StudentModule.delete') as mock_delete:\r\n mock_delete.side_effect = ZeroDivisionError(expected_message)\r\n instructor_task = self.delete_problem_state('instructor', location)\r\n self._assert_task_failure(instructor_task.id, 'delete_problem_state', problem_url_name, expected_message)","def test_handle_delete_github_error(self):\n self.db.query.side_effect = GithubAPIException(\"error\")\n self.assertTupleEqual(self.testcommand.handle(\"team delete brs\", user),\n (\"Team delete was unsuccessful with \"\n \"the following error: \"\n \"error\", 200))\n self.db.delete.assert_not_called()\n self.gh.org_delete_team.assert_not_called()","def delete_datafile(self, save_instance=True):\n if self.datafile:\n logger.debug(\"Deleting datafile '%s'\", self.datafile.name)\n try:\n self.datafile.delete(save=save_instance)\n except OSError as exc:\n logger.error(\"Error deleting file '%s': %s\",\n self.datafile.name, exc)\n return False\n logger.info(\"Deleted datafile of '%s'\", self)","async def test_delete_batch_invalid(database,valid_data):\n test_valid_insert_batch(database,valid_data)\n N = 10\n batch_id = 1\n for idx in range(N+1,N*2):\n try:\n await database.delete_batch(batch_id=batch_id,user_id=idx)\n assert False\n except:\n assert True\n await database.close_pool()","def delete_rdataset(self, name, rdtype, covers=dns.rdatatype.NONE):\n\n name = self._validate_name(name)\n rdtype = dns.rdatatype.RdataType.make(rdtype)\n if covers is not None:\n covers = dns.rdatatype.RdataType.make(covers)\n node = self.get_node(name)\n if node is not None:\n node.delete_rdataset(self.rdclass, rdtype, covers)\n if len(node) == 0:\n self.delete_node(name)","def delete(self, context, id_):\n try:\n db_resource_data = self.db_api.get_resource(\n context, id_)\n\n if db_resource_data['type'] == (eon_const.\n EON_RESOURCE_TYPE_ESX_CLUSTER):\n msg = _(\"Delete operation not supported for type %s\"\n % db_resource_data['type'])\n raise exception.DeleteException(err=msg)\n\n _resource_data = _make_response(\n db_resource_data)\n _resource_data_log = deepcopy(_resource_data)\n _resource_data_log.pop(\"meta_data\", None)\n LOG.info(\"Details for the ID %s is: %s\" % (\n id_, logging.mask_password(_resource_data_log)))\n driver_obj = driver.load_resource_driver(\n db_resource_data['type'])\n driver_obj.validate_delete(db_resource_data)\n driver_obj.delete(context, id_)\n self.db_api.delete_resource(context, id_)\n # delete the data from hlm input model\n try:\n LOG.info(\"[%s] remove resource from input model\" % id_)\n hux_obj = HLMFacadeWrapper(context)\n resource_id = db_resource_data[eon_const.EON_RESOURCE_ID]\n hux_obj.delete_server(resource_id)\n hux_obj.commit_changes(resource_id, \"Delete compute resource\")\n except facade_excep.NotFound:\n # log and do nothing\n LOG.warn(\"[%s] resource not found in hlm input model\" % id_)\n LOG.info(\"[%s]: Deleted resource from eon\" % id_)\n # Notify the message to consumers\n try:\n message = {\"resource_id\": id_,\n \"resource_state\": eon_const.EON_RESOURCE_STATE_REMOVED,\n \"resource_details\": _resource_data,\n }\n message_notifier.notify(context,\n message_notifier.EVENT_PRIORITY_INFO,\n message_notifier.EVENT_TYPE[\n 'removed'],\n message)\n except Exception as ex:\n LOG.exception(\n \"Exception while notifying the message : %s\" % ex)\n except exception.NotFound as e:\n msg = (\"Failed to delete resource %s. Error: %s\") % (\n _resource_data['name'], e.message)\n LOG.exception(msg)\n raise e","def delete(self):\n self.logger.debug(\"In delete.\")\n\n if self._id is None:\n self.logger.warn(\"Attempt to delete a %s with no ID.\", __name__)\n raise Exception(\"{} does not have an ID.\".format(__name__))\n\n id = self._id\n\n session = iHMPSession.get_session()\n self.logger.info(\"Got iHMP session.\")\n\n # Assume failure\n success = False\n\n try:\n self.logger.info(\"Deleting %s with ID %s.\", __name__, id)\n session.get_osdf().delete_node(id)\n success = True\n except Exception as delete_exception:\n self.logger.exception(delete_exception)\n self.logger.error(\"An error occurred when deleting %s.\", self)\n\n return success","def test_sg_delete_non_associated(self):\n\n # Add a faked storage group to be tested and another one\n faked_storage_group = self.add_storage_group1()\n self.add_storage_group2()\n\n storage_group_mgr = self.console.storage_groups\n\n storage_group = storage_group_mgr.find(name=faked_storage_group.name)\n\n # Execute the code to be tested.\n storage_group.delete()\n\n # Check that the storage group no longer exists\n with pytest.raises(NotFound):\n storage_group_mgr.find(name=faked_storage_group.name)","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def test_delete_unkonwn_id_error(self):\n with self.assertRaises(QiitaDBUnknownIDError):\n PrepTemplate.delete(5)","def s3_delete_data(self):\n\n self.k.delete()","def delete(self, *args, **kwargs):\n raise NotImplementedError()","def delete(self, error_id):\n error = self.db.session.query(models.Error).get(error_id)\n if error:\n self.db.session.delete(error)\n self.db.session.commit()\n else:\n raise InvalidErrorReference(\"No error with id %s\" % str(error_id))","def delete_dataset(key=None) -> DeleteDatasetResponse:\n config = ThreatExchangeConfig.getx(str(key))\n hmaconfig.delete_config(config)\n return DeleteDatasetResponse(response=\"The privacy group is deleted\")","def clean(args):\n with_dataset(args, Dataset._clean)","def delete(self, predicate, successHandler=None, failHandler=None):\n queryDelete = \"DELETE FROM `article_article` \" \\\n \"WHERE `{}` {} %s LIMIT 1;\".format(\n predicate[0],\n predicate[1]\n )\n\n queryDeleteParams = []\n if isinstance(predicate[2], datetime):\n queryDeleteParams.append(predicate[2].strftime(\"%Y-%m-%d %H:%M:%S\"))\n else:\n queryDeleteParams.append(predicate[2])\n\n def failCallback(error):\n errorMessage = str(error)\n if isinstance(error, Failure):\n errorMessage = error.getErrorMessage()\n\n self.log.error(\n \"[Default.Article] delete() database error: {errorMessage}\",\n errorMessage=errorMessage\n )\n\n if failHandler is not None:\n reactor.callInThread(failHandler, [\"DatabaseError\"])\n\n def successCallback(results):\n if successHandler is not None:\n reactor.callInThread(successHandler)\n\n operation = self.dbService.runOperation(\n queryDelete,\n tuple(queryDeleteParams)\n )\n operation.addCallbacks(successCallback, failCallback)","def delete(self):\n raise NotImplementedError","def test_delete(self):\n self.request.access.allow_delete = [\"everyone\"]\n pkg = make_package()\n key = self.db.redis_key(pkg.filename)\n self.redis[key] = \"foobar\"\n self.db.delete(pkg)\n val = self.redis.get(key)\n self.assertIsNone(val)\n count = self.redis.scard(self.db.redis_set)\n self.assertEqual(count, 0)\n self.storage.delete.assert_called_with(pkg)","def test_delete_unkonwn_id_error(self):\n with self.assertRaises(QiitaDBUnknownIDError):\n SampleTemplate.delete(5)","def remove_dataset(self, name):\n payload = {\"name\": name}\n r = self.request(\n \"delete\", url_path_join(USER_DATASET_RESOURCE_URL, self.owner), payload=payload\n )\n self.check_and_raise(r)","async def delete_dataset(\n self,\n request: Optional[\n Union[data_labeling_service.DeleteDatasetRequest, dict]\n ] = None,\n *,\n name: Optional[str] = None,\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\n timeout: Union[float, object] = gapic_v1.method.DEFAULT,\n metadata: Sequence[Tuple[str, str]] = (),\n ) -> None:\n # Create or coerce a protobuf request object.\n # Quick check: If we got a request object, we should *not* have\n # gotten any keyword arguments that map to the request.\n has_flattened_params = any([name])\n if request is not None and has_flattened_params:\n raise ValueError(\n \"If the `request` argument is set, then none of \"\n \"the individual field arguments should be set.\"\n )\n\n request = data_labeling_service.DeleteDatasetRequest(request)\n\n # If we have keyword arguments corresponding to fields on the\n # request, apply these.\n if name is not None:\n request.name = name\n\n # Wrap the RPC method; this adds retry and timeout information,\n # and friendly error handling.\n rpc = gapic_v1.method_async.wrap_method(\n self._client._transport.delete_dataset,\n default_retry=retries.Retry(\n initial=0.1,\n maximum=30.0,\n multiplier=1.3,\n predicate=retries.if_exception_type(\n core_exceptions.DeadlineExceeded,\n core_exceptions.ServiceUnavailable,\n ),\n deadline=30.0,\n ),\n default_timeout=30.0,\n client_info=DEFAULT_CLIENT_INFO,\n )\n\n # Certain fields should be provided within the metadata header;\n # add these here.\n metadata = tuple(metadata) + (\n gapic_v1.routing_header.to_grpc_metadata(((\"name\", request.name),)),\n )\n\n # Send the request.\n await rpc(\n request,\n retry=retry,\n timeout=timeout,\n metadata=metadata,\n )","def test_delete_edge_case_with_write_concern_0_return_None(self):\n p1 = self.Person(name=\"User Z\", age=20).save()\n del_result = p1.delete(w=0)\n assert del_result is None","def delete_table_data():\n try:\n print 'delete existing data'\n sql = 'delete from document'\n sql1 = 'delete from clean_keywords'\n sql2 = 'delete from keywords'\n util.executeSQL(conn, sql) # delete the existing data.\n util.executeSQL(conn, sql1)\n util.executeSQL(conn, sql2)\n except Exception as e:\n print e","def test_data_object_del(self):\n pass","def test_raise_when_no_id(self):\n model = self.Test({}, False)\n self.assertRaises(errors.PersistenceError, model.delete)","def delete(self, *args, **kwargs):\n return 0","def delete_file(self, filename=None):\n return self._service.delete_object(self._datasets_id, filename)","def test_delete(self, init_db, audit):\n audit.delete()\n assert Audit.get(audit.id) == None","def test_delete_category_does_not_exist(self):\n self.delete_does_not_exist_fail('hats')","def test_delete(self):\n pt = PrepTemplate.create(self.metadata, self.new_raw_data,\n self.test_study, self.data_type_id)\n PrepTemplate.delete(pt.id)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_template WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.common_prep_info WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n obs = self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_columns WHERE prep_template_id=2\")\n exp = []\n self.assertEqual(obs, exp)\n\n with self.assertRaises(QiitaDBExecutionError):\n self.conn_handler.execute_fetchall(\n \"SELECT * FROM qiita.prep_2\")","def delete(self):\n raise NotImplementedError()","def delete(self):\n raise NotImplementedError()","def test_delete_without_partition_key(self):\r\n with self.assertRaises(query.QueryException):\r\n TestModel.objects(attempt_id=0).delete()"],"string":"[\n \"def delete_dataset(self, dataset):\\n raise NotImplementedError('delete_dataset')\",\n \"def _TryDeleteDataset(dataset_id, project_id):\\n client = GetApiClient()\\n service = client.datasets\\n delete_request_type = GetApiMessage('BigqueryDatasetsDeleteRequest')\\n delete_request = delete_request_type(datasetId=dataset_id,\\n projectId=project_id,\\n deleteContents=True)\\n service.Delete(delete_request)\\n log.info('Deleted dataset [{}:{}]'.format(project_id, dataset_id))\",\n \"def _handle_creation_failure(session: Session, stub_dataset: Dataset, error: str):\\n try:\\n dataset.delete(session, stub_dataset)\\n except requests.HTTPError:\\n raise CreationFailure(\\n f\\\"Created dataset did not delete after an earlier error: {error}\\\"\\n )\\n raise CreationFailure(error)\",\n \"def _delete_dataset_netex(dataset_id):\\n try:\\n logging.info(\\\"Going to delete the netex file of the dataset %s\\\", dataset_id)\\n community_resource = _find_community_resources(dataset_id)\\n _delete_community_resources(dataset_id, community_resource)\\n logging.info(\\\"deleted community resource for the dataset %s\\\", dataset_id)\\n except requests.HTTPError as err:\\n logging.warning(\\n \\\"Unable to delete to the dataset %s. Http Error %s\\\", dataset_id, err\\n )\\n except Exception as err:\\n logging.warning(\\n \\\"Unable to delete to the dataset %s. Generic Error %s\\\", dataset_id, err\\n )\",\n \"def delete_dataset(self, dataset: DatasetDB):\\n try:\\n self._es.delete_index(dataset_records_index(dataset.id))\\n finally:\\n self._es.delete_document(index=DATASETS_INDEX_NAME, doc_id=dataset.id)\",\n \"def test_dataset_deltitem(train_dataset):\\n with pytest.raises(Exception):\\n del train_dataset[0]\",\n \"def delete(_id):\\n dataset = ESDataset.get(id=_id, ignore=404)\\n\\n if not dataset:\\n raise NoEntityError(f\\\"dataset {_id} does not exist.\\\")\\n\\n dataset.delete()\\n\\n return dataset.name\",\n \"def delete(log, args):\\n log('dataset id: {highlight}{id}{reset}',\\n highlight=Fore.GREEN,\\n id=args.id,\\n reset=Style.RESET_ALL)\\n log.warn('delete dataset command coming soon.')\",\n \"def delete_dataset(self, identifier):\\n # Delete the dataset directory if it exists. Otherwise return False\\n dataset_dir = self.get_dataset_dir(identifier)\\n if not os.path.isdir(dataset_dir):\\n return False\\n shutil.rmtree(dataset_dir)\\n return True\",\n \"def delete_dataset(dataset_path):\\n force_rmtree(dataset_path)\",\n \"def DeleteDataset(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details(\\\"Method not implemented!\\\")\\n raise NotImplementedError(\\\"Method not implemented!\\\")\",\n \"def delete_dataset(request):\\n body = json.loads(request.body)\\n dataset_id = body.get('dataset_id', '')\\n organization_id = body.get('organization_id')\\n # check if user has access to the dataset\\n d = ImportRecord.objects.filter(\\n super_organization_id=organization_id, pk=dataset_id\\n )\\n if not d.exists():\\n return {\\n 'status': 'error',\\n 'message': 'user does not have permission to delete dataset',\\n }\\n d = d[0]\\n d.delete()\\n return {\\n 'status': 'success',\\n }\",\n \"def delete(self, dataset_name=None, dataset_id=None, sure=False, really=False):\\n if sure and really:\\n dataset = self.get(dataset_name=dataset_name, dataset_id=dataset_id)\\n success, response = self._client_api.gen_request(req_type='delete',\\n path='/datasets/{}'.format(dataset.id))\\n if not success:\\n raise exceptions.PlatformException(response)\\n logger.info('Dataset {} was deleted successfully'.format(dataset.name))\\n return True\\n else:\\n raise exceptions.PlatformException(\\n error='403',\\n message='Cant delete dataset from SDK. Please login to platform to delete')\",\n \"def delete(self, ds, del_raw_data=False, **kwargs):\\n self.logger.warning('ds_id already exists: {}. Deleting'.format(ds.id))\\n self._del_iso_images(ds)\\n self._es.delete_ds(ds.id)\\n self._db.alter('DELETE FROM dataset WHERE id=%s', ds.id)\\n if del_raw_data:\\n self.logger.warning('Deleting raw data: {}'.format(ds.input_path))\\n wd_man = WorkDirManager(ds.id)\\n wd_man.del_input_data(ds.input_path)\\n if self.mode == 'queue':\\n self._queue.publish({'ds_id': ds.id, 'status': DatasetStatus.DELETED}, SM_DS_STATUS)\",\n \"def test_that_when_dataset_is_deleted_the_account_is_still_there(self):\\n test_dataset = Dataset.objects.get(\\n dataset_slug=\\\"google-geojson-example\\\")\\n test_dataset.delete()\\n with self.assertRaises(ObjectDoesNotExist):\\n Dataset.objects.get(dataset_slug=\\\"google-geojson-example\\\")\\n Account.objects.get(account_slug=\\\"test_user\\\")\",\n \"def delete(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n self.manager.delete_data(name)\",\n \"def _try_delete_resource(self, delete_callable, *args, **kwargs):\\n try:\\n delete_callable(*args, **kwargs)\\n # if resource is not found, this means it was deleted in the test\\n except exceptions.NotFound:\\n pass\",\n \"def delete_datasetreplica(self, dataset_replica):\\n raise NotImplementedError('delete_datasetreplica')\",\n \"def delete(self, ds, del_raw_data=False):\\n self._post_sm_msg(ds=ds, action=DatasetAction.DELETE, priority=DatasetActionPriority.HIGH)\",\n \"def test_dataset_exists(client, to_delete):\\n DATASET_ID = \\\"get_table_dataset_{}\\\".format(_millis())\\n dataset_ref = client.dataset(DATASET_ID)\\n dataset = bigquery.Dataset(dataset_ref)\\n dataset = client.create_dataset(dataset)\\n to_delete.append(dataset)\\n\\n assert dataset_exists(client, dataset_ref)\\n assert not dataset_exists(client, client.dataset(\\\"dataset doesnot exist\\\"))\",\n \"def delete_dataset_target_bigquery(self, dataset):\\n return db.delete_dataset_bigquery(\\n dataset, project=self.get_conn_env_var('TARGET_BIGQUERY', 'PROJECT')\\n )\",\n \"def purge_dataset(request):\\n data = json.loads(request.body.decode('utf-8'))\\n if not request.user.is_staff:\\n return JsonResponse({'error': 'Only admin can purge dataset'}, status=403)\\n try:\\n dset = models.Dataset.objects.get(pk=data['item_id'])\\n except models.Dataset.DoesNotExist:\\n return JsonResponse({'error': 'Dataset does not exist'}, status=403)\\n purgemsg = delete_dataset_from_cold(dset)\\n if purgemsg['state'] == 'error':\\n return JsonResponse(purgemsg, status=500)\\n else:\\n return JsonResponse(purgemsg)\",\n \"def raise_exception_for_dataset(dataset_reference):\\n if dataset_reference.dataset_id == non_existing_dataset_id:\\n raise cloud.exceptions.NotFound('')\",\n \"def delete_bigquery_dataset(self, shared_state: Dict[str, Any]):\\n\\n yield\\n\\n # Get the bigquery dataset id used for testing and wipe it\\n bigquery_dataset = shared_state[\\\"bigquery_dataset\\\"]\\n bigquery_client = shared_state[\\\"bigquery_client\\\"]\\n bigquery_client.delete_dataset(\\n bigquery_dataset.dataset_id, delete_contents=True, not_found_ok=True\\n ) # Make an API request.\",\n \"def test_delete_unexpected_error(self, requests_mock, capsys):\\n requests_mock.delete(data_url, exc=ConnectionError)\\n with pytest.raises(ConnectionError):\\n r = operations.delete(data_url)\\n assert 'Unexpected error when connecting to' in capsys.readouterr().out\",\n \"def delete(dtype, name, rootdir=None):\\n # type and the name\\n # delete them\\n num_deleted = 0\\n for dataset in FreezableAPI.datasets(dtype,name,rootdir=rootdir,fullpath=True):\\n # delete it\\n shutil.rmtree(dataset)\\n num_deleted += 1\\n return num_deleted\",\n \"def delete_temp_dataset():\\n\\n bq.delete_dataset(temp_dataset_ref, delete_contents=True, not_found_ok=True)\",\n \"def delete(self, identifier, dataset):\\n # Fix identifier because SQlAlchemy can't parse RDF Literals\\n identifier = str(identifier)\\n\\n #self._load_config()\\n self.log( 'Removing resource %s in dataset %s' % (identifier, dataset))\\n\\n # Remove it\\n data = self.es_instance.delete_document(identifier, dataset)\\n\\n self.log( 'Registro %s removido com sucesso' % identifier)\\n\\n return data\",\n \"def delete_task(dataset):\\n Observation.delete_all(dataset)\\n super(dataset.__class__, dataset).delete({DATASET_ID: dataset.dataset_id})\",\n \"def do_delete(self, node_id):\\n _error_code, _msg = RAMSTKDataModel.do_delete(self, node_id)\\n\\n # pylint: disable=attribute-defined-outside-init\\n # It is defined in RAMSTKDataModel.__init__\\n if _error_code != 0:\\n _error_code = 1\\n _msg = _msg + (\\n '\\\\n RAMSTK ERROR: Attempted to delete non-existent '\\n 'Allocation ID {0:d}.').format(node_id)\\n else:\\n self.last_id = max(self.tree.nodes.keys())\\n\\n return _error_code, _msg\",\n \"def delete_ds(self, dt):\\n\\n for k in self.datasets_keys:\\n for F in self.datasets[k]:\\n if F not in data[k].keys():\\n continue \\n max_date = data[k][F]['max_date'] \\n \\\"\\\"\\\" Deleting unecessary ds \\\"\\\"\\\"\\n if dt > max_date : # check max date and check if data is still loaded\\n print(blue + 'Memory used before deleting : ' , process.memory_info().rss/1000000000 , cend) \\n del data[k][F] \\n print(\\\"*** Erasing dataset: \\\" , k , ' ' , F ) \\n print(blue + 'Memory used after deleting : ' , process.memory_info().rss/1000000000 , cend) \\n \\n else:\\n continue\",\n \"def dataset(bf):\\n ds = bf.create_dataset(\\\"test_dataset_{}\\\".format(uuid4()))\\n\\n yield ds\\n\\n bf._api.datasets.delete(ds)\",\n \"def destroyDataset(request):\\n\\n if request.method=='DELETE':\\n json_data=json.loads(request.body)\\n name=json_data['name']\\n try:\\n dataset=Dataset.nodes.get(name=name)\\n dataset.delete()\\n return JsonResponse({\\\"success\\\": \\\"Dataset deleted\\\"}, safe=False)\\n except:\\n return JsonResponse({\\\"error\\\":\\\"Error occurred\\\"}, safe=False)\",\n \"def test_delete_voice_dataset(self):\\n pass\",\n \"def delete_data(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n try:\\n self.data[\\\"dataset\\\"].pop(name)\\n self.update_categories()\\n self.write_data_cache(self.data)\\n except KeyError:\\n raise KeyError(\\\"The dataset \\\\'{}\\\\' does not exist in the cache.\\\".format(name))\",\n \"def test_deletion_fail(self):\\n\\n # Assert that a RelaxNoPipeError occurs when the data pipe does not exist.\\n self.assertRaises(RelaxNoPipeError, pipes.delete, 'x')\",\n \"def test_delete_http_error(self, requests_mock, capsys):\\n requests_mock.delete(data_url, status_code=300)\\n with pytest.raises(RuntimeError):\\n r = operations.delete(data_url)\\n assert 'HTTP error: 300' in capsys.readouterr().out\",\n \"def test_delete_error(self):\\n with self.assertRaises(QiitaDBExecutionError):\\n PrepTemplate.delete(1)\",\n \"def delete_datasets(self, base_url):\\n response = requests.get(base_url + '/testdata')\\n for index in range(len(response.json()['testdata'])):\\n self.delete_dataset(base_url, response.json()['testdata'][index]['dataset'])\",\n \"def test_delete(self):\\n data_columns = ['id', 'column_string', 'column_float']\\n data_values = [[1, 'string1', 456.956], [2, 'string2', 38.905]]\\n data = pd.DataFrame(data_values, columns=data_columns)\\n data.name = 'test_delete'\\n my_conn = MySQL(*self.conn_params)\\n my_conn.insert(data)\\n table = my_conn.get_table(data.name)\\n expected = 2\\n current = my_conn.engine.scalar(\\n select([func.count('*')]).select_from(table)\\n )\\n self.assertEqual(current, expected)\\n\\n # delete from operation\\n # the None argument in delete DML is included to avoid pylint E1120\\n table.delete(None).where(table.c.id == 2).execute()\\n\\n expected = 1\\n current = my_conn.engine.scalar(\\n select([func.count('*')]).select_from(table)\\n )\\n self.assertEqual(current, expected)\\n my_conn.drop(data.name)\",\n \"def delData(self, ide = None):\\r\\n try:\\r\\n if ide is not None:\\r\\n self.cursor.execute(\\\"DELETE FROM DATAS WHERE ID = %s;\\\" %(ide))\\r\\n return True\\r\\n else:\\r\\n return False\\r\\n except:\\r\\n return False\",\n \"def delete():\",\n \"def delete(self, data):\\r\\n pass\",\n \"def delete_upload_data(self, id=None, name=None) -> None:\\r\\n # get the dataset\\r\\n dataset = self.get_upload_data(id=id, name=name)\\r\\n\\r\\n try:\\r\\n self.session.delete(dataset)\\r\\n self.session.commit()\\r\\n except Exception as e:\\r\\n self.session.rollback()\\r\\n raise e\",\n \"def delete_run(self, run_id):\\n ds = self.datastorage\\n ds.get_metrics_dao().delete(run_id)\\n # TODO: implement\\n # ds.get_artifact_dao().delete(run_id)\\n # ds.get_resource_dao().delete(run_id)\\n ds.get_run_dao().delete(run_id)\",\n \"def test_07_datastore_delete(self, Mock):\\r\\n html_request = FakeRequest(json.dumps({}), 200,\\r\\n {'content-type': 'application/json'})\\r\\n\\r\\n Mock.return_value = html_request\\r\\n with self.flask_app.test_request_context('/'):\\r\\n out = self.ckan.datastore_delete(name='task',\\r\\n resource_id=self.task_resource_id)\\r\\n err_msg = \\\"It should return True\\\"\\r\\n assert out is True, err_msg\\r\\n # Check the error\\r\\n Mock.return_value = self.server_error\\r\\n try:\\r\\n self.ckan.datastore_delete(name='task',\\r\\n resource_id=self.task_resource_id)\\r\\n except Exception as out:\\r\\n type, msg, status_code = out.args\\r\\n assert \\\"Server Error\\\" in msg, msg\\r\\n assert 500 == status_code, status_code\\r\\n assert \\\"CKAN: the remote site failed! datastore_delete failed\\\" == type, type\",\n \"def delete_row(self, identifier, rowid, datastore):\\n # Get dataset. Raise exception if dataset is unknown.\\n dataset = datastore.get_dataset(identifier)\\n if dataset is None:\\n raise ValueError(\\\"unknown dataset '{}'\\\".format(identifier))\\n # Delete the row at the given index position\\n df = vizual.delete_rows(dataset.to_dataframe(), rowids=[rowid])\\n # Store updated dataset to get new identifier.\\n ds = datastore.update_dataset(\\n origin=dataset,\\n df=df,\\n annotations=dataset.annotations.filter(rows=list(df.index))\\n )\\n return VizualApiResult(ds)\",\n \"def dataset_delete(self, name, deep=False):\\n\\n # Checks inputs\\n check_type(value=name, allowed_types=str, var_name=\\\"name\\\", raise_exception=True)\\n check_is_valid_ds_name(value=name, raise_exception=True)\\n check_type(value=deep, allowed_types=bool, var_name=\\\"deep\\\", raise_exception=True)\\n\\n template = 'dataset_remove'\\n if deep:\\n template = 'dataset_deep_remove'\\n response = self.send(root_url=self.session.dm_url + self.root_url,\\n verb=GenericClient.VERB.DELETE,\\n template=TEMPLATES[template],\\n uri_params={\\n 'name': name\\n })\\n\\n if response.status_code == 404:\\n raise IkatsNotFoundError(\\\"Dataset %s not found in database\\\" % name)\\n return response.text\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package(factory=DynamoPackage)\\n self._save_pkgs(pkg)\\n self.db.delete(pkg)\\n count = self.engine.scan(DynamoPackage).count()\\n self.assertEqual(count, 0)\\n count = self.engine.scan(PackageSummary).count()\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def test_delete(self):\\n SampleTemplate.create(self.metadata, self.new_study)\\n SampleTemplate.delete(2)\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.required_sample_info WHERE study_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.study_sample_columns WHERE study_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n with self.assertRaises(QiitaDBExecutionError):\\n self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.sample_2\\\")\",\n \"def delete(self, identifier):\\n self.get(identifier)\\n conn = self.get_connector()\\n cursor = conn.cursor()\\n\\n query = \\\"delete from {0} where {2}={1}\\\".format(\\n self.ressource_config[\\\"table\\\"],\\n identifier,\\n self.model.pk_field.name)\\n try:\\n cursor.execute(query)\\n except sqlite3.IntegrityError, e:\\n message = \\\"\\\"\\n if \\\"foreign\\\" in e.message:\\n message = \\\"\\\"\\\"another ressource depends on this\\n object. Cloud not delete before all ressources\\n depending on it are also deleted\\\"\\\"\\\"\\n\\n raise BadRequest(message)\\n\\n conn.commit()\\n conn.close()\",\n \"def delete_dataset_without_original_url():\\n logging.warning(\\n \\\"*** deleting all netex files created by transport.data.gouv.fr ***\\\"\\n )\\n r = requests.get(\\\"https://transport.data.gouv.fr/api/datasets\\\")\\n r.raise_for_status()\\n datasets = r.json()\\n\\n print_resource = lambda r: f\\\"\\\\n\\\\t*[url = {r['url']} | extras = {r.get('extras')}]\\\"\\n print_resources = lambda rs: [print_resource(r) for r in rs]\\n\\n for d in datasets:\\n dataset_name = d[\\\"title\\\"]\\n if d[\\\"type\\\"] != \\\"public-transit\\\":\\n continue\\n\\n dataset_id = d[\\\"id\\\"]\\n\\n community_resources = _find_community_resources(dataset_id)\\n logging.info(\\\"community ressources : %s\\\", print_resources(community_resources))\\n old_community_resources = [\\n r\\n for r in community_resources\\n if \\\"transport:original_resource_url\\\" not in r.get(\\\"extras\\\", {})\\n ]\\n if old_community_resources:\\n logging.info(\\n \\\"old community ressources : %s\\\",\\n print_resources(old_community_resources),\\n )\\n _delete_community_resources(dataset_id, old_community_resources)\\n logging.info(\\\"deleted community resource for the dataset %s\\\", dataset_id)\",\n \"def test_do_delete_non_existent_id(test_dao):\\r\\n DUT = dtmFunction(test_dao, test=True)\\r\\n DUT.do_select_all(revision_id=1)\\r\\n\\r\\n _error_code, _msg = DUT.do_delete(300)\\r\\n\\r\\n assert _error_code == 2005\\r\\n assert _msg == (\\\"RAMSTK ERROR: Attempted to delete non-existent \\\"\\r\\n \\\"Function ID 300.\\\")\",\n \"def test_delete_datasource(\\n in_memory_runtime_context: EphemeralDataContext,\\n) -> None:\\n context = in_memory_runtime_context\\n\\n name = context.list_datasources()[0][\\\"name\\\"]\\n context.delete_datasource(name)\\n\\n assert name not in context.datasources\",\n \"def test_delete(self):\\n\\n self.metadata.create_or_update(data=self.create)\\n\\n # Find by name\\n res_name = self.metadata.get_by_name(\\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\\n )\\n # Then fetch by ID\\n res_id = self.metadata.get_by_id(\\n entity=Dashboard, entity_id=str(res_name.id.__root__)\\n )\\n\\n # Delete\\n self.metadata.delete(\\n entity=Dashboard, entity_id=str(res_id.id.__root__), recursive=True\\n )\\n\\n # Then we should not find it\\n res = self.metadata.list_entities(entity=Dashboard)\\n assert not next(\\n iter(\\n ent\\n for ent in res.entities\\n if ent.fullyQualifiedName == self.entity.fullyQualifiedName\\n ),\\n None,\\n )\",\n \"def _try_delete_and_return_permissions_error(component_url):\\n try:\\n delete_object_task.DeleteObjectTask(component_url, verbose=False).execute()\\n except api_errors.CloudApiError as e:\\n status = getattr(e, 'status_code', None)\\n if status == 403:\\n return e\\n raise\",\n \"async def test_delete_invalid(database,valid_data):\\n test_valid_insert(database,valid_data)\\n N = 10\\n for idx in range(N+1,N*2):\\n try:\\n await database.delete(_id=idx,user_id=idx)\\n assert False\\n except:\\n assert True\\n await database.close_pool()\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package(factory=SQLPackage)\\n self.sql.add(pkg)\\n transaction.commit()\\n self.sql.add(pkg)\\n self.db.delete(pkg)\\n count = self.sql.query(SQLPackage).count()\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def del_data(self, name):\\n raise NotImplementedError('Do I want to delete data from a df?')\",\n \"def delete_datasource_instance(connection, id, error_msg=None):\\n url = f\\\"{connection.base_url}/api/datasources/{id}\\\"\\n response = connection.session.delete(url=url)\\n if not response.ok:\\n if error_msg is None:\\n error_msg = f\\\"Error deleting Datasource Instance with ID: {id}\\\"\\n response_handler(response, error_msg)\\n return response\",\n \"def test_delete_run(self):\\n pass\",\n \"def delete(self, hostname):\\n self.not_supported()\",\n \"def do_delete(self, arg):\\n \\treturn False\",\n \"def test_delete_data(self):\\n data = Data.objects.create(\\n name='Test data',\\n contributor=self.user,\\n process=self.proc,\\n )\\n\\n data.output = {'json_field': {'foo': 'bar'}}\\n data.status = Data.STATUS_DONE\\n data.save()\\n\\n self.assertEqual(Storage.objects.count(), 1)\\n\\n data.delete()\\n self.assertEqual(Storage.objects.count(), 0)\",\n \"def test_wrong_delete_param(self):\\n def close_conn():\\n cli = LDAPClient(\\\"ldap://%s\\\" % self.ipaddr)\\n LDAPConnection(cli).delete(\\\"cn=dummy\\\")\\n self.assertRaises(ClosedConnection, close_conn)\\n self.assertRaises(TypeError, lambda: self.conn.delete(0))\",\n \"def testDeleteOpInvalidDN(self):\\n self.assertRaises(AssertionError, delta.DeleteOp, 0)\",\n \"def delete(self, ssubject: str, predicate: str, obj: str) -> None:\\n raise NotImplementedError(\\\"The RDF graph is read-only: DELETE DATA queries are not allowed\\\")\",\n \"def test_delete_failure(self):\\r\\n problem_url_name = 'H1P1'\\r\\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\\r\\n self.define_option_problem(problem_url_name)\\r\\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\\r\\n\\r\\n expected_message = \\\"bad things happened\\\"\\r\\n with patch('courseware.models.StudentModule.delete') as mock_delete:\\r\\n mock_delete.side_effect = ZeroDivisionError(expected_message)\\r\\n instructor_task = self.delete_problem_state('instructor', location)\\r\\n self._assert_task_failure(instructor_task.id, 'delete_problem_state', problem_url_name, expected_message)\",\n \"def test_handle_delete_github_error(self):\\n self.db.query.side_effect = GithubAPIException(\\\"error\\\")\\n self.assertTupleEqual(self.testcommand.handle(\\\"team delete brs\\\", user),\\n (\\\"Team delete was unsuccessful with \\\"\\n \\\"the following error: \\\"\\n \\\"error\\\", 200))\\n self.db.delete.assert_not_called()\\n self.gh.org_delete_team.assert_not_called()\",\n \"def delete_datafile(self, save_instance=True):\\n if self.datafile:\\n logger.debug(\\\"Deleting datafile '%s'\\\", self.datafile.name)\\n try:\\n self.datafile.delete(save=save_instance)\\n except OSError as exc:\\n logger.error(\\\"Error deleting file '%s': %s\\\",\\n self.datafile.name, exc)\\n return False\\n logger.info(\\\"Deleted datafile of '%s'\\\", self)\",\n \"async def test_delete_batch_invalid(database,valid_data):\\n test_valid_insert_batch(database,valid_data)\\n N = 10\\n batch_id = 1\\n for idx in range(N+1,N*2):\\n try:\\n await database.delete_batch(batch_id=batch_id,user_id=idx)\\n assert False\\n except:\\n assert True\\n await database.close_pool()\",\n \"def delete_rdataset(self, name, rdtype, covers=dns.rdatatype.NONE):\\n\\n name = self._validate_name(name)\\n rdtype = dns.rdatatype.RdataType.make(rdtype)\\n if covers is not None:\\n covers = dns.rdatatype.RdataType.make(covers)\\n node = self.get_node(name)\\n if node is not None:\\n node.delete_rdataset(self.rdclass, rdtype, covers)\\n if len(node) == 0:\\n self.delete_node(name)\",\n \"def delete(self, context, id_):\\n try:\\n db_resource_data = self.db_api.get_resource(\\n context, id_)\\n\\n if db_resource_data['type'] == (eon_const.\\n EON_RESOURCE_TYPE_ESX_CLUSTER):\\n msg = _(\\\"Delete operation not supported for type %s\\\"\\n % db_resource_data['type'])\\n raise exception.DeleteException(err=msg)\\n\\n _resource_data = _make_response(\\n db_resource_data)\\n _resource_data_log = deepcopy(_resource_data)\\n _resource_data_log.pop(\\\"meta_data\\\", None)\\n LOG.info(\\\"Details for the ID %s is: %s\\\" % (\\n id_, logging.mask_password(_resource_data_log)))\\n driver_obj = driver.load_resource_driver(\\n db_resource_data['type'])\\n driver_obj.validate_delete(db_resource_data)\\n driver_obj.delete(context, id_)\\n self.db_api.delete_resource(context, id_)\\n # delete the data from hlm input model\\n try:\\n LOG.info(\\\"[%s] remove resource from input model\\\" % id_)\\n hux_obj = HLMFacadeWrapper(context)\\n resource_id = db_resource_data[eon_const.EON_RESOURCE_ID]\\n hux_obj.delete_server(resource_id)\\n hux_obj.commit_changes(resource_id, \\\"Delete compute resource\\\")\\n except facade_excep.NotFound:\\n # log and do nothing\\n LOG.warn(\\\"[%s] resource not found in hlm input model\\\" % id_)\\n LOG.info(\\\"[%s]: Deleted resource from eon\\\" % id_)\\n # Notify the message to consumers\\n try:\\n message = {\\\"resource_id\\\": id_,\\n \\\"resource_state\\\": eon_const.EON_RESOURCE_STATE_REMOVED,\\n \\\"resource_details\\\": _resource_data,\\n }\\n message_notifier.notify(context,\\n message_notifier.EVENT_PRIORITY_INFO,\\n message_notifier.EVENT_TYPE[\\n 'removed'],\\n message)\\n except Exception as ex:\\n LOG.exception(\\n \\\"Exception while notifying the message : %s\\\" % ex)\\n except exception.NotFound as e:\\n msg = (\\\"Failed to delete resource %s. Error: %s\\\") % (\\n _resource_data['name'], e.message)\\n LOG.exception(msg)\\n raise e\",\n \"def delete(self):\\n self.logger.debug(\\\"In delete.\\\")\\n\\n if self._id is None:\\n self.logger.warn(\\\"Attempt to delete a %s with no ID.\\\", __name__)\\n raise Exception(\\\"{} does not have an ID.\\\".format(__name__))\\n\\n id = self._id\\n\\n session = iHMPSession.get_session()\\n self.logger.info(\\\"Got iHMP session.\\\")\\n\\n # Assume failure\\n success = False\\n\\n try:\\n self.logger.info(\\\"Deleting %s with ID %s.\\\", __name__, id)\\n session.get_osdf().delete_node(id)\\n success = True\\n except Exception as delete_exception:\\n self.logger.exception(delete_exception)\\n self.logger.error(\\\"An error occurred when deleting %s.\\\", self)\\n\\n return success\",\n \"def test_sg_delete_non_associated(self):\\n\\n # Add a faked storage group to be tested and another one\\n faked_storage_group = self.add_storage_group1()\\n self.add_storage_group2()\\n\\n storage_group_mgr = self.console.storage_groups\\n\\n storage_group = storage_group_mgr.find(name=faked_storage_group.name)\\n\\n # Execute the code to be tested.\\n storage_group.delete()\\n\\n # Check that the storage group no longer exists\\n with pytest.raises(NotFound):\\n storage_group_mgr.find(name=faked_storage_group.name)\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def test_delete_unkonwn_id_error(self):\\n with self.assertRaises(QiitaDBUnknownIDError):\\n PrepTemplate.delete(5)\",\n \"def s3_delete_data(self):\\n\\n self.k.delete()\",\n \"def delete(self, *args, **kwargs):\\n raise NotImplementedError()\",\n \"def delete(self, error_id):\\n error = self.db.session.query(models.Error).get(error_id)\\n if error:\\n self.db.session.delete(error)\\n self.db.session.commit()\\n else:\\n raise InvalidErrorReference(\\\"No error with id %s\\\" % str(error_id))\",\n \"def delete_dataset(key=None) -> DeleteDatasetResponse:\\n config = ThreatExchangeConfig.getx(str(key))\\n hmaconfig.delete_config(config)\\n return DeleteDatasetResponse(response=\\\"The privacy group is deleted\\\")\",\n \"def clean(args):\\n with_dataset(args, Dataset._clean)\",\n \"def delete(self, predicate, successHandler=None, failHandler=None):\\n queryDelete = \\\"DELETE FROM `article_article` \\\" \\\\\\n \\\"WHERE `{}` {} %s LIMIT 1;\\\".format(\\n predicate[0],\\n predicate[1]\\n )\\n\\n queryDeleteParams = []\\n if isinstance(predicate[2], datetime):\\n queryDeleteParams.append(predicate[2].strftime(\\\"%Y-%m-%d %H:%M:%S\\\"))\\n else:\\n queryDeleteParams.append(predicate[2])\\n\\n def failCallback(error):\\n errorMessage = str(error)\\n if isinstance(error, Failure):\\n errorMessage = error.getErrorMessage()\\n\\n self.log.error(\\n \\\"[Default.Article] delete() database error: {errorMessage}\\\",\\n errorMessage=errorMessage\\n )\\n\\n if failHandler is not None:\\n reactor.callInThread(failHandler, [\\\"DatabaseError\\\"])\\n\\n def successCallback(results):\\n if successHandler is not None:\\n reactor.callInThread(successHandler)\\n\\n operation = self.dbService.runOperation(\\n queryDelete,\\n tuple(queryDeleteParams)\\n )\\n operation.addCallbacks(successCallback, failCallback)\",\n \"def delete(self):\\n raise NotImplementedError\",\n \"def test_delete(self):\\n self.request.access.allow_delete = [\\\"everyone\\\"]\\n pkg = make_package()\\n key = self.db.redis_key(pkg.filename)\\n self.redis[key] = \\\"foobar\\\"\\n self.db.delete(pkg)\\n val = self.redis.get(key)\\n self.assertIsNone(val)\\n count = self.redis.scard(self.db.redis_set)\\n self.assertEqual(count, 0)\\n self.storage.delete.assert_called_with(pkg)\",\n \"def test_delete_unkonwn_id_error(self):\\n with self.assertRaises(QiitaDBUnknownIDError):\\n SampleTemplate.delete(5)\",\n \"def remove_dataset(self, name):\\n payload = {\\\"name\\\": name}\\n r = self.request(\\n \\\"delete\\\", url_path_join(USER_DATASET_RESOURCE_URL, self.owner), payload=payload\\n )\\n self.check_and_raise(r)\",\n \"async def delete_dataset(\\n self,\\n request: Optional[\\n Union[data_labeling_service.DeleteDatasetRequest, dict]\\n ] = None,\\n *,\\n name: Optional[str] = None,\\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\\n timeout: Union[float, object] = gapic_v1.method.DEFAULT,\\n metadata: Sequence[Tuple[str, str]] = (),\\n ) -> None:\\n # Create or coerce a protobuf request object.\\n # Quick check: If we got a request object, we should *not* have\\n # gotten any keyword arguments that map to the request.\\n has_flattened_params = any([name])\\n if request is not None and has_flattened_params:\\n raise ValueError(\\n \\\"If the `request` argument is set, then none of \\\"\\n \\\"the individual field arguments should be set.\\\"\\n )\\n\\n request = data_labeling_service.DeleteDatasetRequest(request)\\n\\n # If we have keyword arguments corresponding to fields on the\\n # request, apply these.\\n if name is not None:\\n request.name = name\\n\\n # Wrap the RPC method; this adds retry and timeout information,\\n # and friendly error handling.\\n rpc = gapic_v1.method_async.wrap_method(\\n self._client._transport.delete_dataset,\\n default_retry=retries.Retry(\\n initial=0.1,\\n maximum=30.0,\\n multiplier=1.3,\\n predicate=retries.if_exception_type(\\n core_exceptions.DeadlineExceeded,\\n core_exceptions.ServiceUnavailable,\\n ),\\n deadline=30.0,\\n ),\\n default_timeout=30.0,\\n client_info=DEFAULT_CLIENT_INFO,\\n )\\n\\n # Certain fields should be provided within the metadata header;\\n # add these here.\\n metadata = tuple(metadata) + (\\n gapic_v1.routing_header.to_grpc_metadata(((\\\"name\\\", request.name),)),\\n )\\n\\n # Send the request.\\n await rpc(\\n request,\\n retry=retry,\\n timeout=timeout,\\n metadata=metadata,\\n )\",\n \"def test_delete_edge_case_with_write_concern_0_return_None(self):\\n p1 = self.Person(name=\\\"User Z\\\", age=20).save()\\n del_result = p1.delete(w=0)\\n assert del_result is None\",\n \"def delete_table_data():\\n try:\\n print 'delete existing data'\\n sql = 'delete from document'\\n sql1 = 'delete from clean_keywords'\\n sql2 = 'delete from keywords'\\n util.executeSQL(conn, sql) # delete the existing data.\\n util.executeSQL(conn, sql1)\\n util.executeSQL(conn, sql2)\\n except Exception as e:\\n print e\",\n \"def test_data_object_del(self):\\n pass\",\n \"def test_raise_when_no_id(self):\\n model = self.Test({}, False)\\n self.assertRaises(errors.PersistenceError, model.delete)\",\n \"def delete(self, *args, **kwargs):\\n return 0\",\n \"def delete_file(self, filename=None):\\n return self._service.delete_object(self._datasets_id, filename)\",\n \"def test_delete(self, init_db, audit):\\n audit.delete()\\n assert Audit.get(audit.id) == None\",\n \"def test_delete_category_does_not_exist(self):\\n self.delete_does_not_exist_fail('hats')\",\n \"def test_delete(self):\\n pt = PrepTemplate.create(self.metadata, self.new_raw_data,\\n self.test_study, self.data_type_id)\\n PrepTemplate.delete(pt.id)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_template WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.common_prep_info WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n obs = self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_columns WHERE prep_template_id=2\\\")\\n exp = []\\n self.assertEqual(obs, exp)\\n\\n with self.assertRaises(QiitaDBExecutionError):\\n self.conn_handler.execute_fetchall(\\n \\\"SELECT * FROM qiita.prep_2\\\")\",\n \"def delete(self):\\n raise NotImplementedError()\",\n \"def delete(self):\\n raise NotImplementedError()\",\n \"def test_delete_without_partition_key(self):\\r\\n with self.assertRaises(query.QueryException):\\r\\n TestModel.objects(attempt_id=0).delete()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7605005","0.74737805","0.7107175","0.70523417","0.69809973","0.6883148","0.6740322","0.6667521","0.65653944","0.6536053","0.65328515","0.65034896","0.6410687","0.6386324","0.6328574","0.63253295","0.62904114","0.6277353","0.62735856","0.6252367","0.61857146","0.6168082","0.6162157","0.613244","0.6089961","0.60710067","0.60618997","0.6054307","0.60175395","0.59812534","0.59728926","0.5945504","0.5898049","0.58455795","0.5814105","0.58104396","0.5775425","0.5733373","0.5725115","0.570578","0.5701192","0.5630272","0.56293786","0.56126684","0.56120926","0.5611404","0.56092745","0.5607267","0.5595084","0.5575618","0.5560845","0.55180013","0.55004615","0.54946786","0.5494068","0.5493824","0.54772246","0.5475572","0.54748356","0.54659593","0.54646385","0.546054","0.545929","0.5447527","0.5440744","0.54403776","0.5428439","0.5425052","0.5412754","0.53937244","0.53930616","0.5389392","0.53804857","0.537615","0.53478956","0.5340608","0.533264","0.53314257","0.5328683","0.53236055","0.5322863","0.5313439","0.53118443","0.5311221","0.5309877","0.530916","0.53082687","0.52888113","0.5282388","0.52746874","0.52719414","0.5265507","0.5262418","0.5255371","0.52480537","0.52463824","0.5243807","0.5236309","0.5236309","0.52332956"],"string":"[\n \"0.7605005\",\n \"0.74737805\",\n \"0.7107175\",\n \"0.70523417\",\n \"0.69809973\",\n \"0.6883148\",\n \"0.6740322\",\n \"0.6667521\",\n \"0.65653944\",\n \"0.6536053\",\n \"0.65328515\",\n \"0.65034896\",\n \"0.6410687\",\n \"0.6386324\",\n \"0.6328574\",\n \"0.63253295\",\n \"0.62904114\",\n \"0.6277353\",\n \"0.62735856\",\n \"0.6252367\",\n \"0.61857146\",\n \"0.6168082\",\n \"0.6162157\",\n \"0.613244\",\n \"0.6089961\",\n \"0.60710067\",\n \"0.60618997\",\n \"0.6054307\",\n \"0.60175395\",\n \"0.59812534\",\n \"0.59728926\",\n \"0.5945504\",\n \"0.5898049\",\n \"0.58455795\",\n \"0.5814105\",\n \"0.58104396\",\n \"0.5775425\",\n \"0.5733373\",\n \"0.5725115\",\n \"0.570578\",\n \"0.5701192\",\n \"0.5630272\",\n \"0.56293786\",\n \"0.56126684\",\n \"0.56120926\",\n \"0.5611404\",\n \"0.56092745\",\n \"0.5607267\",\n \"0.5595084\",\n \"0.5575618\",\n \"0.5560845\",\n \"0.55180013\",\n \"0.55004615\",\n \"0.54946786\",\n \"0.5494068\",\n \"0.5493824\",\n \"0.54772246\",\n \"0.5475572\",\n \"0.54748356\",\n \"0.54659593\",\n \"0.54646385\",\n \"0.546054\",\n \"0.545929\",\n \"0.5447527\",\n \"0.5440744\",\n \"0.54403776\",\n \"0.5428439\",\n \"0.5425052\",\n \"0.5412754\",\n \"0.53937244\",\n \"0.53930616\",\n \"0.5389392\",\n \"0.53804857\",\n \"0.537615\",\n \"0.53478956\",\n \"0.5340608\",\n \"0.533264\",\n \"0.53314257\",\n \"0.5328683\",\n \"0.53236055\",\n \"0.5322863\",\n \"0.5313439\",\n \"0.53118443\",\n \"0.5311221\",\n \"0.5309877\",\n \"0.530916\",\n \"0.53082687\",\n \"0.52888113\",\n \"0.5282388\",\n \"0.52746874\",\n \"0.52719414\",\n \"0.5265507\",\n \"0.5262418\",\n \"0.5255371\",\n \"0.52480537\",\n \"0.52463824\",\n \"0.5243807\",\n \"0.5236309\",\n \"0.5236309\",\n \"0.52332956\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.52461874"},"document_rank":{"kind":"string","value":"96"}}},{"rowIdx":2296,"cells":{"query":{"kind":"string","value":"Get Table resource args (source, destination) for copy command."},"document":{"kind":"string","value":"def GetTableCopyResourceArgs():\n table_spec_data = yaml_data.ResourceYAMLData.FromPath('bq.table')\n arg_specs = [\n resource_args.GetResourcePresentationSpec(\n verb='to copy from', name='source', required=True, prefixes=True,\n attribute_overrides={'table': 'source'}, positional=False,\n resource_data=table_spec_data.GetData()),\n resource_args.GetResourcePresentationSpec(\n verb='to copy to', name='destination',\n required=True, prefixes=True,\n attribute_overrides={'table': 'destination'}, positional=False,\n resource_data=table_spec_data.GetData())]\n fallthroughs = {\n '--source.dataset': ['--destination.dataset'],\n '--destination.dataset': ['--source.dataset']\n }\n return [concept_parsers.ConceptParser(arg_specs, fallthroughs)]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ProcessTableCopyConfiguration(ref, args, request):\n del ref # Unused\n source_ref = args.CONCEPTS.source.Parse()\n destination_ref = args.CONCEPTS.destination.Parse()\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.datasetId',\n destination_ref.Parent().Name())\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.projectId',\n destination_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.destinationTable.tableId',\n destination_ref.Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.datasetId',\n source_ref.Parent().Name())\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.projectId',\n source_ref.projectId)\n arg_utils.SetFieldInMessage(request,\n 'job.configuration.copy.sourceTable.tableId',\n source_ref.Name())\n return request","def visit_copy_command(element, compiler, **kw):\n qs = \"\"\"COPY {table}{columns} FROM :data_location\n WITH CREDENTIALS AS :credentials\n {format}\n {parameters}\"\"\"\n parameters = []\n bindparams = [\n sa.bindparam(\n 'data_location',\n value=element.data_location,\n type_=sa.String,\n ),\n sa.bindparam(\n 'credentials',\n value=element.credentials,\n type_=sa.String,\n ),\n ]\n\n if element.format == Format.csv:\n format_ = 'FORMAT AS CSV'\n if element.quote is not None:\n format_ += ' QUOTE AS :quote_character'\n bindparams.append(sa.bindparam(\n 'quote_character',\n value=element.quote,\n type_=sa.String,\n ))\n elif element.format == Format.json:\n format_ = 'FORMAT AS JSON AS :json_option'\n bindparams.append(sa.bindparam(\n 'json_option',\n value=element.path_file,\n type_=sa.String,\n ))\n elif element.format == Format.avro:\n format_ = 'FORMAT AS AVRO AS :avro_option'\n bindparams.append(sa.bindparam(\n 'avro_option',\n value=element.path_file,\n type_=sa.String,\n ))\n elif element.format == Format.orc:\n format_ = 'FORMAT AS ORC'\n elif element.format == Format.parquet:\n format_ = 'FORMAT AS PARQUET'\n elif element.format == Format.fixed_width and element.fixed_width is None:\n raise sa_exc.CompileError(\n \"'fixed_width' argument required for format 'FIXEDWIDTH'.\")\n else:\n format_ = ''\n\n if element.delimiter is not None:\n parameters.append('DELIMITER AS :delimiter_char')\n bindparams.append(sa.bindparam(\n 'delimiter_char',\n value=element.delimiter,\n type_=sa.String,\n ))\n\n if element.fixed_width is not None:\n parameters.append('FIXEDWIDTH AS :fixedwidth_spec')\n bindparams.append(sa.bindparam(\n 'fixedwidth_spec',\n value=_process_fixed_width(element.fixed_width),\n type_=sa.String,\n ))\n\n if element.compression is not None:\n parameters.append(Compression(element.compression).value)\n\n if element.manifest:\n parameters.append('MANIFEST')\n\n if element.accept_any_date:\n parameters.append('ACCEPTANYDATE')\n\n if element.accept_inv_chars is not None:\n parameters.append('ACCEPTINVCHARS AS :replacement_char')\n bindparams.append(sa.bindparam(\n 'replacement_char',\n value=element.accept_inv_chars,\n type_=sa.String\n ))\n\n if element.blanks_as_null:\n parameters.append('BLANKSASNULL')\n\n if element.date_format is not None:\n parameters.append('DATEFORMAT AS :dateformat_string')\n bindparams.append(sa.bindparam(\n 'dateformat_string',\n value=element.date_format,\n type_=sa.String,\n ))\n\n if element.empty_as_null:\n parameters.append('EMPTYASNULL')\n\n if element.encoding is not None:\n parameters.append('ENCODING AS ' + Encoding(element.encoding).value)\n\n if element.escape:\n parameters.append('ESCAPE')\n\n if element.explicit_ids:\n parameters.append('EXPLICIT_IDS')\n\n if element.fill_record:\n parameters.append('FILLRECORD')\n\n if element.ignore_blank_lines:\n parameters.append('IGNOREBLANKLINES')\n\n if element.ignore_header is not None:\n parameters.append('IGNOREHEADER AS :number_rows')\n bindparams.append(sa.bindparam(\n 'number_rows',\n value=element.ignore_header,\n type_=sa.Integer,\n ))\n\n if element.dangerous_null_delimiter is not None:\n parameters.append(\"NULL AS '%s'\" % element.dangerous_null_delimiter)\n\n if element.remove_quotes:\n parameters.append('REMOVEQUOTES')\n\n if element.roundec:\n parameters.append('ROUNDEC')\n\n if element.time_format is not None:\n parameters.append('TIMEFORMAT AS :timeformat_string')\n bindparams.append(sa.bindparam(\n 'timeformat_string',\n value=element.time_format,\n type_=sa.String,\n ))\n\n if element.trim_blanks:\n parameters.append('TRIMBLANKS')\n\n if element.truncate_columns:\n parameters.append('TRUNCATECOLUMNS')\n\n if element.comp_rows:\n parameters.append('COMPROWS :numrows')\n bindparams.append(sa.bindparam(\n 'numrows',\n value=element.comp_rows,\n type_=sa.Integer,\n ))\n\n if element.comp_update:\n parameters.append('COMPUPDATE ON')\n elif element.comp_update is not None:\n parameters.append('COMPUPDATE OFF')\n\n if element.max_error is not None:\n parameters.append('MAXERROR AS :error_count')\n bindparams.append(sa.bindparam(\n 'error_count',\n value=element.max_error,\n type_=sa.Integer,\n ))\n\n if element.no_load:\n parameters.append('NOLOAD')\n\n if element.stat_update:\n parameters.append('STATUPDATE ON')\n elif element.stat_update is not None:\n parameters.append('STATUPDATE OFF')\n\n if element.region is not None:\n parameters.append('REGION :region')\n bindparams.append(sa.bindparam(\n 'region',\n value=element.region,\n type_=sa.String\n ))\n\n columns = ' (%s)' % ', '.join(\n compiler.preparer.format_column(column) for column in element.columns\n ) if element.columns else ''\n\n qs = qs.format(\n table=compiler.preparer.format_table(element.table),\n columns=columns,\n format=format_,\n parameters='\\n'.join(parameters)\n )\n\n return compiler.process(sa.text(qs).bindparams(*bindparams), **kw)","def CopyFile(self, *args, **kwargs):\n # type: (*Any, **Any) -> None\n payload = {}\n for i in range(len(args)):\n payload[\"Arg%s\" % (i + 1)] = args[i]\n for item in kwargs.items():\n payload[item[0]] = item[1]\n return self._execute(\"copyFile\", payload=payload, response_object=None)","def getCloneArgs(self):\n\n values = {\n \"dest\": self.subnode_dest.makeClone()\n if self.subnode_dest is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def test_args_copy():\n args = cli.parse_args(['-c'])\n assert args.copy\n args = cli.parse_args(['--copy'])\n assert args.copy","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def command_copy(args):\n sources = args.sources\n destpath = args.destpath\n source_files = []\n for file_ in sources:\n if \"*\" in file_:\n selected = glob(file_)\n source_files.extend(selected)\n elif os.path.isfile(file_):\n source_files.append(file_)\n\n if destpath.endswith(\"/\") or os.path.isdir(destpath) or len(sources) > 1:\n # -- DESTDIR-MODE: Last argument is a directory.\n destdir = destpath\n else:\n # -- DESTFILE-MODE: Copy (and rename) one file.\n assert len(source_files) == 1\n destdir = os.path.dirname(destpath)\n\n # -- WORK-HORSE: Copy one or more files to destpath.\n if not os.path.isdir(destdir):\n sys.stdout.write(\"copy: Create dir %s\\n\" % destdir)\n os.makedirs(destdir)\n for source in source_files:\n destname = os.path.join(destdir, os.path.basename(source))\n sys.stdout.write(\"copy: %s => %s\\n\" % (source, destname))\n shutil.copy(source, destname)\n return 0","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n \"subscribed\": self.subnode_subscribed.makeClone(),\n \"subscript\": self.subnode_subscript.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def CopyObjsCommand(self, args, sub_opts=None, headers=None, debug=0,\n command='cp'):\n # Expand wildcards and containers in source StorageUris.\n src_uri_expansion = self.ExpandWildcardsAndContainers(\n args[0:len(args)-1], sub_opts, headers, debug)\n\n # Check for various problems and determine base_dst_uri based for request.\n (base_dst_uri, multi_src_request) = self.ErrorCheckCopyRequest(\n src_uri_expansion, args[-1], headers, debug, command)\n # Rewrite base_dst_uri and create dest dir as needed for multi-source copy.\n if multi_src_request:\n base_dst_uri = self.HandleMultiSrcCopyRequst(src_uri_expansion,\n base_dst_uri)\n\n # Now iterate over expanded src URIs, and perform copy operations.\n total_elapsed_time = total_bytes_transferred = 0\n for src_uri in iter(src_uri_expansion):\n for exp_src_uri in src_uri_expansion[src_uri]:\n print 'Copying %s...' % exp_src_uri\n dst_uri = self.ConstructDstUri(src_uri, exp_src_uri, base_dst_uri)\n (elapsed_time, bytes_transferred) = self.PerformCopy(\n exp_src_uri, dst_uri, sub_opts, headers, debug)\n total_elapsed_time += elapsed_time\n total_bytes_transferred += bytes_transferred\n if debug == 3:\n # Note that this only counts the actual GET and PUT bytes for the copy\n # - not any transfers for doing wildcard expansion, the initial HEAD\n # request boto performs when doing a bucket.get_key() operation, etc.\n if total_bytes_transferred != 0:\n print 'Total bytes copied=%d, total elapsed time=%5.3f secs (%sps)' % (\n total_bytes_transferred, total_elapsed_time,\n MakeHumanReadable(float(total_bytes_transferred) /\n float(total_elapsed_time)))","def doTheCopy(argpath,argdest):\n print(\"To copy:\"+argpath)\n shutil.copy(argpath,argdest)","def supported_table_args(self) -> t.Tuple[str, ...]:","def cp(self, copy_from, copy_to, **kwargs):\n return self.exec_command('cp %s %s' % (copy_from, copy_to), **kwargs)","def getCloneArgs(self):\n\n values = {\n \"dest\": self.subnode_dest.makeClone()\n if self.subnode_dest is not None\n else None,\n \"value\": self.subnode_value.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def args():\n\n useDB = docopt(__doc__)['--from-db']\n snapFile = docopt(__doc__)['-i']\n # csvFile = docopt(__doc__)['-o']\n # utils.askErase(csvFile)\n\n return [snapFile, useDB]","def copyData(self, src_schema, src_table, src_columns, dest_schema, dest_table, dest_columns):\r\n sql = 'INSERT INTO {} ( {} ) SELECT {} FROM {}'.format(self.encodeTableName(dest_schema, dest_table), ','.join(dest_columns),\r\n ','.join(src_columns), self.encodeTableName(src_schema, src_table))\r\n return self.runSql(sql)","def copy(CopySource=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, SourceClient=None, Config=None):\n pass","def svn_client_copy_source_t_path_get(svn_client_copy_source_t_self): # real signature unknown; restored from __doc__\n return \"\"","def get_source_system_profile_params(argv):\n with get_audit_db(argv) as audit_db:\n if audit_db is None:\n if not argv.tablelist:\n return []\n\n if len(argv.tablelist) == 1:\n # A file containing table names\n if os.path.isfile(argv.tablelist[0]):\n with open(argv.tablelist[0]) as f:\n return [(argv.sourceschema,\n t.strip(),\n argv.targetschema,\n None) for t in f]\n\n return [(argv.sourceschema, table, argv.targetschema, None)\n for table in argv.tablelist]\n\n sql = \"\"\"\n SELECT source_region, object_name, target_region, query_condition\n FROM {audit_schema}.source_system_profile\n WHERE profile_name = %s\n AND version = %s\n AND active_ind = 'Y'\n ORDER BY object_seq\"\"\".format(audit_schema=argv.auditschema)\n\n bind_values = [argv.profilename, argv.profileversion]\n result = audit_db.execute_query(sql, argv.arraysize, bind_values)\n\n return [(row[0], row[1], row[2], row[3]) for row in result]","def infocalypse_copy(ui_, repo, **opts):\n params, stored_cfg = get_config_info(ui_, opts)\n\n insert_uri = opts['inserturi']\n if insert_uri == '':\n # REDFLAG: fix parameter definition so that it is required?\n ui_.warn(\"Please set the insert URI with --inserturi.\\n\")\n return\n\n request_uri = opts['requesturi']\n if request_uri == '':\n request_uri = stored_cfg.get_request_uri(repo.root)\n if not request_uri:\n ui_.warn(\"There is no stored request URI for this repo.\\n\"\n \"Please set one with the --requesturi option.\\n\")\n return\n\n params['INSERT_URI'] = insert_uri\n params['REQUEST_URI'] = request_uri\n execute_copy(ui_, repo, params, stored_cfg)","def svn_fs_copy(*args):\r\n return _fs.svn_fs_copy(*args)","def destination(self) -> str:\n for a in self.args:\n if a[0] != '-':\n return a\n try:\n return self.kwargs['dest']\n except KeyError:\n for a in self.args:\n if a.startswith('--'):\n dest = a.lstrip('-').replace('-', '_')\n if dest.isidentifier():\n return dest\n raise AttributeError(F'The argument with these values has no destination: {self!r}')","def _copy_to_head_args(args: Namespace) -> Namespace:\n\n _head_args = copy.deepcopy(args)\n _head_args.polling = args.polling\n _head_args.port = args.port\n _head_args.host = args.host[0]\n _head_args.uses = args.uses\n _head_args.pod_role = PodRoleType.HEAD\n _head_args.runtime_cls = 'HeadRuntime'\n _head_args.replicas = 1\n\n if args.name:\n _head_args.name = f'{args.name}/head'\n else:\n _head_args.name = f'head'\n\n return _head_args","def copyCommand(self):\n\n selection = self.selectedIndexes()\n\n if selection:\n rows = [index.row() for index in selection]\n columns = [index.column() for index in selection]\n if len(rows) == 4:\n model = self.proxyModel.sourceModel()\n row = rows[3]\n column = columns[3]\n command = model.dataset.data[row][column].cell\n QApplication.clipboard().setText(command)","def destination(self) -> pulumi.Input['DestinationArgs']:\n return pulumi.get(self, \"destination\")","def test_args_combination():\n args = cli.parse_args(['-cp'])\n assert args.copy\n assert args.paste\n args = cli.parse_args(['-c', '-p'])\n assert args.copy\n assert args.paste","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n \"expression\": self.subnode_expression.makeClone(),\n \"lower\": self.subnode_lower.makeClone()\n if self.subnode_lower is not None\n else None,\n \"upper\": self.subnode_upper.makeClone()\n if self.subnode_upper is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"source\": self.subnode_source.makeClone(),\n \"expression\": self.subnode_expression.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def _copy_file ( self, source, dest ):\n return","def print_dry_run_copy_info(source, dest):\n\n def shorten_home(path):\n expanded_home = os.path.expanduser(\"~\")\n path = str(path)\n if path.startswith(expanded_home):\n return path.replace(expanded_home, \"~\")\n return path\n\n def truncate_middle(path: str, acceptable_len: int):\n \"\"\"Middle truncate a string\n https://www.xormedia.com/string-truncate-middle-with-ellipsis/\n \"\"\"\n if len(path) <= acceptable_len:\n return path\n # half of the size, minus the 3 .'s\n n_2 = int(acceptable_len / 2 - 3)\n # whatever's left\n n_1 = int(acceptable_len - n_2 - 3)\n return f\"{path[:n_1]}...{path[-n_2:]}\"\n\n trimmed_source = shorten_home(source)\n trimmed_dest = shorten_home(dest)\n longest_allowed_path_len = 87\n if len(trimmed_source) + len(trimmed_dest) > longest_allowed_path_len:\n trimmed_source = truncate_middle(trimmed_source, longest_allowed_path_len)\n trimmed_dest = truncate_middle(trimmed_dest, longest_allowed_path_len)\n print(\n Fore.YELLOW + Style.BRIGHT + trimmed_source + Style.NORMAL,\n \"->\",\n Style.BRIGHT + trimmed_dest + Style.RESET_ALL,\n )","def getCloneArgs(self):\n\n values = {\n \"subscribed\": self.subnode_subscribed.makeClone(),\n \"subscript\": self.subnode_subscript.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def CopyTapSettings(self, *args, **kwargs):\n # type: (*Any, **Any) -> None\n payload = { \"Arg1\": self.href }\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\n for item in kwargs.items(): payload[item[0]] = item[1]\n return self._execute('copyTapSettings', payload=payload, response_object=None)","def get_args():\n parser = argparse.ArgumentParser(description='Rsync like thingy')\n parser.add_argument('--dry-run', required=False,\n action='store_true', default=False, dest='dry_run',\n help='Does not do anything on the destination filesystem')\n\n parser.add_argument('-v', '--verbose', required=False,\n action='count', default=0, dest='vlevel',\n help='Log level')\n\n parser.add_argument('--dump-delta', required=False,\n default=None, metavar='DELTA_PATH', dest='delta_path',\n help='If a filename is specified, the delta is dumped into the file as JSON')\n\n parser.add_argument('--max-depth', required=False,\n type=int, default=10, dest='max_depth',\n help='Max depth for both local and remote')\n\n parser.add_argument('--adb-batch-size', required=False,\n type=int, default=5, dest='adb_batch_size',\n help='Maximum number of adb push to run in parallel')\n\n parser.add_argument('--command-batch-size', required=False,\n type=int, default=100, dest='command_batch_size',\n help='Maximum number of arguments / chained commands to run at once')\n\n parser.add_argument('--delete', required=False,\n action='store_true', default=False, dest='delete_files',\n help='Creates a \"perfect mirror\" of local at remote')\n \n parser.add_argument('source', help='The source')\n parser.add_argument('destination', help='The destination')\n return parser.parse_args()","def svn_client_copy(svn_client_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def __get_datatables_args():\n\n table_args = dict()\n\n #\n # Common Arguments\n #\n\n table_args['column-count'] = 0\n table_args['sort-col-count'] = 0\n\n if request.args.get('draw'):\n table_args['sequence'] = request.args.get('draw')\n\n if request.args.get('start'):\n table_args['offset'] = int(request.args.get('start'))\n\n if request.args.get('length'):\n table_args['limit'] = int(request.args.get('length'))\n\n if request.args.get('search[value]'):\n table_args['filter'] = request.args.get('search[value]')\n\n if request.args.get('search[regex]'):\n table_args['filter-regex'] = request.args.get('search[regex]')\n\n #\n # Custom Arguments\n #\n\n if request.args.get('time_filter'):\n table_args['time_filter'] = request.args.get('time_filter')\n\n i = 0\n while True:\n if request.args.get('columns[%d][data]' % i):\n table_args['column-count'] += 1\n table_args['mDataProp_%d' % i] = request.args.get('columns[%d][data]' % i)\n else:\n break\n\n #\n # Column Search\n #\n\n if request.args.get('columns[%d][searchable]' % i):\n table_args['bSearchable_%d' % i] = request.args.get('columns[%d][searchable]' % i)\n\n if request.args.get('columns[%d][search][value]' % i):\n table_args['sSearch_%d' % i] = request.args.get('columns[%d][search][value]' % i)\n\n if request.args.get('columns[%d][search][regex]' % i):\n table_args['bRegex_%d' % i] = request.args.get('columns[%d][search][regex]' % i)\n\n #\n # Column Sort\n #\n\n if request.args.get('columns[%d][orderable]' % i):\n table_args['bSortable_%d' % i] = request.args.get('columns[%d][orderable]' % i)\n\n if request.args.get('order[%d][column]' % i):\n table_args['sort-col-count'] += 1\n table_args['iSortCol_%d' % i] = int(request.args.get('order[%d][column]' % i))\n\n if request.args.get('order[%d][dir]' % i):\n table_args['sSortDir_%d' % i] = request.args.get('order[%d][dir]' % i)\n\n i += 1\n\n return table_args","def copyFlexor(*args, **kwargs)->AnyStr:\n pass","def copy_db(src=FRESHDB, dst=[APPDB]):\n for dest in dst:\n try:\n x = shutil.copy2(src, dest)\n print('File copied to {}'.format(x))\n except shutil.SameFileError:\n print('Both source and destination are identical.')","def ProcessTableCopyOverwrite(ref, args, request):\n del ref # Unused\n if args.overwrite:\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\n return request","def _copyTexture(self, src, dest):\n self.copyTextureNode.setShaderInput(\"src\", src)\n self.copyTextureNode.setShaderInput(\"dest\", dest)\n self._executeShader(\n self.copyTextureNode,\n (src.getXSize() + 15) / 16,\n (src.getYSize() + 15) / 16)","def copy_source_arn(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"copy_source_arn\")","def getCloneArgs(self):\n\n values = {}\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"dict_arg\": self.subnode_dict_arg.makeClone(),\n \"key\": self.subnode_key.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def copy(self, src_path: str, tgt_path: str) -> None:","async def copy(self, _id: str, dst_id: str, *,\n rev: Optional[str] = None,\n dst_rev: Optional[str] = None,\n batch: Optional[bool] = None) -> dict:\n\n headers = dict(\n Destination=f'{dst_id}?rev={dst_rev}' if dst_rev else dst_id\n )\n\n params = dict(\n rev=rev,\n batch=\"ok\" if batch else None,\n )\n\n return await self.__connection.query('COPY', self._get_path(_id), params=params, headers=headers)","def getCloneArgs(self):\n\n values = {\n \"source_code\": self.subnode_source_code.makeClone(),\n \"globals_arg\": self.subnode_globals_arg.makeClone()\n if self.subnode_globals_arg is not None\n else None,\n \"locals_arg\": self.subnode_locals_arg.makeClone()\n if self.subnode_locals_arg is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"condition\": self.subnode_condition.makeClone(),\n \"yes_branch\": self.subnode_yes_branch.makeClone()\n if self.subnode_yes_branch is not None\n else None,\n \"no_branch\": self.subnode_no_branch.makeClone()\n if self.subnode_no_branch is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def parse_args():\n\n copy_help = 'Copy files back to original target directory? Default False'\n\n parser = argparse.ArgumentParser()\n parser.add_argument('-c', help=copy_help, action='store_true',\n required=False)\n arguments = parser.parse_args()\n return arguments","def run_copy(self, src, dst):\n pass","def get(self):\n copies = db.session.query(models.Copy)\n args = copy_query_parser.parse_args()\n copy_id = args['copy_id']\n if copy_id is not None:\n copies = copies.filter_by(id=copy_id)\n book_id = args['book_id']\n if book_id is not None:\n copies = copies.filter_by(book=book_id)\n\n username = args['user']\n if username is not None:\n copies = copies.filter_by(user=username)\n status = args[\"status\"]\n if status is not None:\n copies = copies.filter_by(status=status)\n if copy_id is None and book_id is None and username is None and status is None:\n return 'Please proved searching parameter', 400\n return [copy.serialize() for copy in copies], 200","def getCloneArgs(self):\n\n values = {\n \"value\": self.subnode_value.makeClone(),\n \"dict_arg\": self.subnode_dict_arg.makeClone(),\n \"key\": self.subnode_key.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def svn_client_copy_source_t_revision_get(svn_client_copy_source_t_self): # real signature unknown; restored from __doc__\n pass","def parse_args(args):\n parser = argparse.ArgumentParser(description='Parse Mysql Copy account you want',add_help=False)\n connect_setting = parser.add_argument_group('connect setting')\n connect_setting.add_argument('-h','--host',dest='host',type=str,help='Host the MySQL database server located',default='127.0.0.1')\n connect_setting.add_argument('-u','--user',dest='user',type=str,help='MySQL Username to log in as',default='root')\n connect_setting.add_argument('-p','--password',dest='password',type=str,help='MySQL Password to use', default='')\n connect_setting.add_argument('-P', '--port', dest='port', type=int,help='MySQL port to use', default=3306)\n copy_user = parser.add_argument_group('copy user')\n copy_user.add_argument('--src-user',dest='srcuser',type=str,help='copy from the user',nargs='*',default='*')\n copy_user.add_argument('--src-host',dest='srchost',type=str,help='copy from the host',nargs='*',default='*')\n copy_user.add_argument('--dest-user',dest='destuser',type=str,help='copy to the user',nargs='*',default='')\n copy_user.add_argument('--dest-host',dest='desthost',type=str,help='copy to the host',nargs='*',default='')\n\n parser.add_argument('--help', dest='help', action='store_true', help='help infomation', default=False)\n\n return parser","def svn_client_copy2(svn_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def copy_table(self, source_table_name, dest_table_name):\n logger.info(f\"Creating {dest_table_name} from {source_table_name}\")\n try:\n self._submit_single_q(COPY_TABLE_DDL.format(new_table_name=dest_table_name, old_table_name=source_table_name))\n except connector.errors.ProgrammingError as e:\n logger.error(f\"Table {dest_table_name} already exists. Exiting.\")\n return\n except Exception as e:\n logger.error(\"Failed creating table\")\n raise\n\n try:\n q = COPY_TABLE_DATA_DML.format(new_table_name=dest_table_name, old_table_name=source_table_name)\n self._submit_single_q(COPY_TABLE_DATA_DML.format(new_table_name=dest_table_name, old_table_name=source_table_name))\n except Exception as e:\n logger.error(\"Failed inserting data\")\n raise e\n\n # print(self._submit_single_q(\"checksum table xfrm_product, staging_product\")","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def copy(self, *args, **kwargs): # real signature unknown\n pass","def CopyTo(self, *args, **kwargs):\n pass","def copyPetscArguments(jobdir, argsfile):\n shutil.copyfile(argsfile, os.path.join(jobdir, \"petsc_commandline_arg\"))","def get_args():\n parser = argparse.ArgumentParser(\n description=\"Extract a sample of the data.\")\n\n parser.add_argument(\"userid\", help=\"User ID\")\n parser.add_argument(\"start\", help=\"Start\")\n parser.add_argument(\"end\", help=\"End\")\n parser.add_argument(\"source\", help=\"Source data file\")\n parser.add_argument(\"dest\", help=\"Destination file\")\n\n return parser.parse_args()","def copy(ctx, source, dest, force=False):\n # print \"COPY:\", locals()\n # print \"COPY:\", ctx.force, ctx.verbose\n if source == dest:\n return dest\n\n source = os.path.normcase(os.path.normpath(str(source)))\n dest = os.path.normcase(os.path.normpath(str(dest)))\n flags = \"\"\n if sys.platform == 'win32':\n if force:\n flags += \" /Y\"\n # print 'copy {flags} {source} {dest}'.format(**locals())\n ctx.run('copy {flags} {source} {dest}'.format(**locals()))\n else: # pragma: nocover\n if force:\n flags += \" --force\"\n ctx.run('cp {flags} {source} {dest}'.format(**locals()))\n return dest","def getCloneArgs(self):\n\n values = {\n \"iterator\": self.subnode_iterator.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def copyAttr(*args, attribute: Union[AnyStr, List[AnyStr]]=\"\", containerParentChild: bool=True,\n inConnections: bool=True, keepSourceConnections: bool=True, outConnections:\n bool=True, renameTargetContainer: bool=True, values: bool=True, q=True, query=True,\n e=True, edit=True, **kwargs)->Union[None, Any]:\n pass","def get_arguments():\n\tparser.add_argument('-i', '--interface', help='interface to affect')\n\tparser.add_argument('-m','--mac', help='mac to allocate')\n\n\targs = parser.parse_args()\n\tinterface = args.interface\n\tmac = args.mac\n\treturn (interface, mac)","def args(self) -> typing.Tuple[str, typing.List[str]]:\n func = inspect.stack()[1][3]\n command = func[len(self.CMD_PREFIX):]\n return ('{} {}'.format(sys.argv[0], command),\n sys.argv[2:])","def copy_continuous_backups_properties(events: dict, context: dict) -> List:\n if 'SourceTableName' not in events:\n raise KeyError('Requires SourceTableName')\n if 'TargetTableName' not in events:\n raise KeyError('Requires TargetTableName')\n\n source_table_name: str = events['SourceTableName']\n target_table_name: str = events['TargetTableName']\n continuous_backups_settings = _describe_continuous_backups(table_name=source_table_name)\n continuous_backups_status = continuous_backups_settings\\\n .get('ContinuousBackupsDescription', {})\\\n .get('PointInTimeRecoveryDescription', {})\\\n .get('PointInTimeRecoveryStatus', '')\n\n if continuous_backups_status in ['ENABLED', 'ENABLING']:\n _enable_continuous_backups(table_name=target_table_name)\n\n return continuous_backups_status","def get_clipboard(*args, **kwargs):\n return G.DEVICE.get_clipboard(*args, **kwargs)","def copy_resource_tags(events: dict, context: dict) -> dict:\n if 'SourceTableName' not in events:\n raise KeyError('Requires SourceTableName')\n if 'TargetTableName' not in events:\n raise KeyError('Requires TargetTableName')\n if 'Region' not in events:\n raise KeyError('Requires Region')\n if 'Account' not in events:\n raise KeyError('Requires Account')\n\n source_table_name = events['SourceTableName']\n region = events['Region']\n account = events['Account']\n resource_arn = f'arn:aws:dynamodb:{region}:{account}:table/{source_table_name}'\n tags = list(_list_tags(resource_arn=resource_arn))\n if tags:\n target_table_name = events['TargetTableName']\n resource_arn = f'arn:aws:dynamodb:{region}:{account}:table/{target_table_name}'\n _update_tags(resource_arn=resource_arn, tags=tags)\n\n return {\n \"Tags\": tags\n }","def _FormSCPCommandLine(self, src, dst, extra_scp_args=None):\n assert not self.local, \"Cannot use SCP on local target.\"\n\n args = ['scp', '-P', str(self._ssh_port)] + self._ssh_args\n if self._ssh_identity:\n args.extend(['-i', self._ssh_identity])\n if extra_scp_args:\n args.extend(extra_scp_args)\n args += [src, dst]\n return args","def destination_table(self) -> str:\n return pulumi.get(self, \"destination_table\")","def getCloneArgs(self):\n\n values = {\n \"statements\": tuple(v.makeClone() for v in self.subnode_statements),\n }\n\n values.update(self.getDetails())\n\n return values","def getCloneArgs(self):\n\n values = {\n \"dict_arg\": self.subnode_dict_arg.makeClone(),\n \"value\": self.subnode_value.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def test_source_copy_round_trip(self):\n self.prepare()\n self.session.execute(\"\"\"\n CREATE TABLE testcopyto (\n a int,\n b text,\n c float,\n d uuid,\n PRIMARY KEY (a, b)\n )\"\"\")\n\n insert_statement = self.session.prepare(\"INSERT INTO testcopyto (a, b, c, d) VALUES (?, ?, ?, ?)\")\n args = [(i, str(i), float(i) + 0.5, uuid4()) for i in range(1000)]\n execute_concurrent_with_args(self.session, insert_statement, args)\n\n results = list(self.session.execute(\"SELECT * FROM testcopyto\"))\n\n tempfile = self.get_temp_file()\n logger.debug('Exporting to csv file: {name}'.format(name=tempfile.name))\n\n commandfile = self.get_temp_file()\n with open(commandfile.name, 'w') as f:\n f.write('USE ks;\\n')\n f.write(\"COPY ks.testcopyto TO '{name}' WITH HEADER=false;\".format(name=tempfile.name))\n\n self.run_cqlsh(cmds=\"SOURCE '{name}'\".format(name=commandfile.name))\n\n # import the CSV file with COPY FROM\n self.session.execute(\"TRUNCATE ks.testcopyto\")\n logger.debug('Importing from csv file: {name}'.format(name=tempfile.name))\n\n commandfile = self.get_temp_file()\n with open(commandfile.name, 'w') as f:\n f.write('USE ks;\\n')\n f.write(\"COPY ks.testcopyto FROM '{name}' WITH HEADER=false;\".format(name=tempfile.name))\n\n self.run_cqlsh(cmds=\"SOURCE '{name}'\".format(name=commandfile.name))\n new_results = list(self.session.execute(\"SELECT * FROM testcopyto\"))\n assert sorted(results) == sorted(new_results)","def command_args(self):\n return self._command_args","def clone(source, destination):\n\t\treturn \"CREATE DATABASE {0} WITH TEMPLATE {1};\".format(destination, source)","def get_args_from_console(args):\n return {\n \"cleaning_policy\": args.cleaning_policy,\n \"clear\": args.clear,\n \"content\": args.content,\n \"dry_run\": args.dry_run,\n \"force\": args.force,\n \"in_lines\": args.in_lines,\n \"max_size\": args.max_size,\n \"regex\": args.regex,\n \"restore\": args.restore,\n \"rmdir\": args.rmdir,\n \"short\": args.short,\n \"silent\": args.silent,\n \"storage_time\": args.storage_time,\n \"wastebasket_path\": args.wastebasket_path\n }","def copy_file_to_table(self, schema, table, filepath):\n fields = \", \".join(self.schemas[schema][table][0])\n sql = f'set role {self.write_role}; ' \\\n f'COPY {schema}.{table}( {fields} ) FROM stdin WITH DELIMITER \\',\\' CSV header;'\n return sql, open(filepath, 'r')","def getCopyDestinations(self, hiveDB, hiveTable):\n\n\t\tsession = self.configDBSession()\n\t\tcopyTables = aliased(configSchema.copyTables)\n\n\t\tself.copyDestinations = []\n\n\t\tcopyTablesResult = pd.DataFrame(session.query(copyTables.copy_id, copyTables.hive_filter, copyTables.destination, copyTables.data_transfer).all()).fillna('')\n\t\tfor index, row in copyTablesResult.iterrows():\n\t\t\tif ';' in row['destination']:\n\t\t\t\tlogging.error(\"';' not supported in the Copy Destination name\")\n\t\t\t\tself.remove_temporary_files()\n\t\t\t\tsys.exit(1)\n\n\t\t\tfor hiveFilterSplit in row['hive_filter'].split(';'):\n\n\t\t\t\tif '.' not in hiveFilterSplit:\n\t\t\t\t\tlogging.warning(\"The filter in table 'copy_tables' with copy_id = %s contains an invalid filter. Missing a . in the database.table format\"%(row['copy_id']))\n\t\t\t\telse:\n\t\t\t\t\tfilterDB = hiveFilterSplit.split('.')[0]\n\t\t\t\t\tfilterTable = hiveFilterSplit.split('.')[1]\n\n\t\t\t\t\tif fnmatch.fnmatch(hiveDB, filterDB) and fnmatch.fnmatch(hiveTable, filterTable):\n\t\t\t\t\t\tdestString = \"%s;%s\"%(row['destination'], row['data_transfer'])\n\t\t\t\t\t\tdestStringASync = \"%s;Asynchronous\"%(row['destination'])\n\t\t\t\t\t\tdestStringSync = \"%s;Synchronous\"%(row['destination'])\n\t\t\t\t\t\tif destStringSync in self.copyDestinations and destString == destStringASync:\n\t\t\t\t\t\t\t# ASync have priority. So if sync is already in there, we remove it and add async\n\t\t\t\t\t\t\tself.copyDestinations.remove(destStringSync)\n\t\t\t\t\t\tif destStringASync not in self.copyDestinations and destStringSync not in self.copyDestinations:\n\t\t\t\t\t\t\tself.copyDestinations.append(destString)\n\t\n\t\tif self.copyDestinations == []:\n\t\t\tself.copyDestinations = None\n\t\treturn self.copyDestinations","def svn_client_copy4(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def cp(self, src, dest):\r\n return self._call(\"-cp\", src, dest, suppress_output=True)","def _FormSCPCommandLine(self, src, dst, extra_scp_args=None):\n assert not self.local, \"Cannot use SCP on local target.\"\n\n # -C enables compression.\n args = ['scp', '-C', '-P', str(self._ssh_port)] + self._ssh_args\n if self._ssh_identity:\n args.extend(['-i', self._ssh_identity])\n if extra_scp_args:\n args.extend(extra_scp_args)\n args += [src, dst]\n return args","def getCloneArgs(self):\n\n values = {\n \"iterated_length\": self.subnode_iterated_length.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def test_copy_sources(self):\n metric_copy = copy_metric(self.metric, self.DATA_MODEL)\n self.assertEqual(\"Source\", first(metric_copy[\"sources\"].values())[\"name\"])","def getPlainCopyPrefices():\n\n oldPrefix = \"\"\n newPrefix = \"\"\n\n # get the copyprefices\n copyprefix = readpar('copyprefixin')\n if copyprefix == \"\":\n copyprefix = readpar('copyprefix')\n\n if \"^\" in copyprefix:\n prefices = copyprefix.split(\"^\")\n oldPrefix = prefices[0]\n newPrefix = prefices[1]\n else:\n tolog(\"!!WARNING!!4444!! Unexpected copyprefix[in] format: %s\" % (copyprefix))\n\n return oldPrefix, newPrefix","def args(self):\n return self._args.copy()","def create_copyfile_dict(child):\n\n attrs = ['src', 'dest']\n values = [child.get(attr) for attr in attrs]\n\n if None in values:\n raise InvalidManifest(\n 'Missing required attribute in copyfile element'\n )\n\n return dict(zip(attrs, values))","def getCloneArgs(self):\n\n values = {\n \"set_arg\": self.subnode_set_arg.makeClone(),\n \"value\": self.subnode_value.makeClone(),\n }\n\n values.update(self.getDetails())\n\n return values","def getCopyRef(self):\n return self.base.get(\"copy_ref\", [])","def getCloneArgs(self):\n\n values = {\n \"tried\": self.subnode_tried.makeClone(),\n \"except_handler\": self.subnode_except_handler.makeClone()\n if self.subnode_except_handler is not None\n else None,\n \"break_handler\": self.subnode_break_handler.makeClone()\n if self.subnode_break_handler is not None\n else None,\n \"continue_handler\": self.subnode_continue_handler.makeClone()\n if self.subnode_continue_handler is not None\n else None,\n \"return_handler\": self.subnode_return_handler.makeClone()\n if self.subnode_return_handler is not None\n else None,\n }\n\n values.update(self.getDetails())\n\n return values","def copy_table(source_table, destination_table, db='default'):\n try:\n with connections[db].cursor() as cursor:\n cursor.execute('CREATE TABLE IF NOT EXISTS %s LIKE %s;' % (destination_table, source_table))\n except:\n pass","def get_args(self):\n req_argv = self._ptr.contents.argv\n args = []\n if bool(req_argv):\n i = 0\n while 1:\n s = bytestostr(req_argv[i])\n i += 1\n if s == None:\n break\n args.append(s)\n return args","def svn_client_commit_item2_t_copyfrom_url_get(svn_client_commit_item2_t_self): # real signature unknown; restored from __doc__\n return \"\"","def drag_dest_info(self):\n return DdTargets.URI_LIST","def svn_fs_copied_from(*args):\r\n return _fs.svn_fs_copied_from(*args)","def dest_columns(self):\n return self.intersection + self.dest_renames"],"string":"[\n \"def ProcessTableCopyConfiguration(ref, args, request):\\n del ref # Unused\\n source_ref = args.CONCEPTS.source.Parse()\\n destination_ref = args.CONCEPTS.destination.Parse()\\n arg_utils.SetFieldInMessage(\\n request, 'job.configuration.copy.destinationTable.datasetId',\\n destination_ref.Parent().Name())\\n arg_utils.SetFieldInMessage(\\n request, 'job.configuration.copy.destinationTable.projectId',\\n destination_ref.projectId)\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.destinationTable.tableId',\\n destination_ref.Name())\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.datasetId',\\n source_ref.Parent().Name())\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.projectId',\\n source_ref.projectId)\\n arg_utils.SetFieldInMessage(request,\\n 'job.configuration.copy.sourceTable.tableId',\\n source_ref.Name())\\n return request\",\n \"def visit_copy_command(element, compiler, **kw):\\n qs = \\\"\\\"\\\"COPY {table}{columns} FROM :data_location\\n WITH CREDENTIALS AS :credentials\\n {format}\\n {parameters}\\\"\\\"\\\"\\n parameters = []\\n bindparams = [\\n sa.bindparam(\\n 'data_location',\\n value=element.data_location,\\n type_=sa.String,\\n ),\\n sa.bindparam(\\n 'credentials',\\n value=element.credentials,\\n type_=sa.String,\\n ),\\n ]\\n\\n if element.format == Format.csv:\\n format_ = 'FORMAT AS CSV'\\n if element.quote is not None:\\n format_ += ' QUOTE AS :quote_character'\\n bindparams.append(sa.bindparam(\\n 'quote_character',\\n value=element.quote,\\n type_=sa.String,\\n ))\\n elif element.format == Format.json:\\n format_ = 'FORMAT AS JSON AS :json_option'\\n bindparams.append(sa.bindparam(\\n 'json_option',\\n value=element.path_file,\\n type_=sa.String,\\n ))\\n elif element.format == Format.avro:\\n format_ = 'FORMAT AS AVRO AS :avro_option'\\n bindparams.append(sa.bindparam(\\n 'avro_option',\\n value=element.path_file,\\n type_=sa.String,\\n ))\\n elif element.format == Format.orc:\\n format_ = 'FORMAT AS ORC'\\n elif element.format == Format.parquet:\\n format_ = 'FORMAT AS PARQUET'\\n elif element.format == Format.fixed_width and element.fixed_width is None:\\n raise sa_exc.CompileError(\\n \\\"'fixed_width' argument required for format 'FIXEDWIDTH'.\\\")\\n else:\\n format_ = ''\\n\\n if element.delimiter is not None:\\n parameters.append('DELIMITER AS :delimiter_char')\\n bindparams.append(sa.bindparam(\\n 'delimiter_char',\\n value=element.delimiter,\\n type_=sa.String,\\n ))\\n\\n if element.fixed_width is not None:\\n parameters.append('FIXEDWIDTH AS :fixedwidth_spec')\\n bindparams.append(sa.bindparam(\\n 'fixedwidth_spec',\\n value=_process_fixed_width(element.fixed_width),\\n type_=sa.String,\\n ))\\n\\n if element.compression is not None:\\n parameters.append(Compression(element.compression).value)\\n\\n if element.manifest:\\n parameters.append('MANIFEST')\\n\\n if element.accept_any_date:\\n parameters.append('ACCEPTANYDATE')\\n\\n if element.accept_inv_chars is not None:\\n parameters.append('ACCEPTINVCHARS AS :replacement_char')\\n bindparams.append(sa.bindparam(\\n 'replacement_char',\\n value=element.accept_inv_chars,\\n type_=sa.String\\n ))\\n\\n if element.blanks_as_null:\\n parameters.append('BLANKSASNULL')\\n\\n if element.date_format is not None:\\n parameters.append('DATEFORMAT AS :dateformat_string')\\n bindparams.append(sa.bindparam(\\n 'dateformat_string',\\n value=element.date_format,\\n type_=sa.String,\\n ))\\n\\n if element.empty_as_null:\\n parameters.append('EMPTYASNULL')\\n\\n if element.encoding is not None:\\n parameters.append('ENCODING AS ' + Encoding(element.encoding).value)\\n\\n if element.escape:\\n parameters.append('ESCAPE')\\n\\n if element.explicit_ids:\\n parameters.append('EXPLICIT_IDS')\\n\\n if element.fill_record:\\n parameters.append('FILLRECORD')\\n\\n if element.ignore_blank_lines:\\n parameters.append('IGNOREBLANKLINES')\\n\\n if element.ignore_header is not None:\\n parameters.append('IGNOREHEADER AS :number_rows')\\n bindparams.append(sa.bindparam(\\n 'number_rows',\\n value=element.ignore_header,\\n type_=sa.Integer,\\n ))\\n\\n if element.dangerous_null_delimiter is not None:\\n parameters.append(\\\"NULL AS '%s'\\\" % element.dangerous_null_delimiter)\\n\\n if element.remove_quotes:\\n parameters.append('REMOVEQUOTES')\\n\\n if element.roundec:\\n parameters.append('ROUNDEC')\\n\\n if element.time_format is not None:\\n parameters.append('TIMEFORMAT AS :timeformat_string')\\n bindparams.append(sa.bindparam(\\n 'timeformat_string',\\n value=element.time_format,\\n type_=sa.String,\\n ))\\n\\n if element.trim_blanks:\\n parameters.append('TRIMBLANKS')\\n\\n if element.truncate_columns:\\n parameters.append('TRUNCATECOLUMNS')\\n\\n if element.comp_rows:\\n parameters.append('COMPROWS :numrows')\\n bindparams.append(sa.bindparam(\\n 'numrows',\\n value=element.comp_rows,\\n type_=sa.Integer,\\n ))\\n\\n if element.comp_update:\\n parameters.append('COMPUPDATE ON')\\n elif element.comp_update is not None:\\n parameters.append('COMPUPDATE OFF')\\n\\n if element.max_error is not None:\\n parameters.append('MAXERROR AS :error_count')\\n bindparams.append(sa.bindparam(\\n 'error_count',\\n value=element.max_error,\\n type_=sa.Integer,\\n ))\\n\\n if element.no_load:\\n parameters.append('NOLOAD')\\n\\n if element.stat_update:\\n parameters.append('STATUPDATE ON')\\n elif element.stat_update is not None:\\n parameters.append('STATUPDATE OFF')\\n\\n if element.region is not None:\\n parameters.append('REGION :region')\\n bindparams.append(sa.bindparam(\\n 'region',\\n value=element.region,\\n type_=sa.String\\n ))\\n\\n columns = ' (%s)' % ', '.join(\\n compiler.preparer.format_column(column) for column in element.columns\\n ) if element.columns else ''\\n\\n qs = qs.format(\\n table=compiler.preparer.format_table(element.table),\\n columns=columns,\\n format=format_,\\n parameters='\\\\n'.join(parameters)\\n )\\n\\n return compiler.process(sa.text(qs).bindparams(*bindparams), **kw)\",\n \"def CopyFile(self, *args, **kwargs):\\n # type: (*Any, **Any) -> None\\n payload = {}\\n for i in range(len(args)):\\n payload[\\\"Arg%s\\\" % (i + 1)] = args[i]\\n for item in kwargs.items():\\n payload[item[0]] = item[1]\\n return self._execute(\\\"copyFile\\\", payload=payload, response_object=None)\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"dest\\\": self.subnode_dest.makeClone()\\n if self.subnode_dest is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def test_args_copy():\\n args = cli.parse_args(['-c'])\\n assert args.copy\\n args = cli.parse_args(['--copy'])\\n assert args.copy\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def command_copy(args):\\n sources = args.sources\\n destpath = args.destpath\\n source_files = []\\n for file_ in sources:\\n if \\\"*\\\" in file_:\\n selected = glob(file_)\\n source_files.extend(selected)\\n elif os.path.isfile(file_):\\n source_files.append(file_)\\n\\n if destpath.endswith(\\\"/\\\") or os.path.isdir(destpath) or len(sources) > 1:\\n # -- DESTDIR-MODE: Last argument is a directory.\\n destdir = destpath\\n else:\\n # -- DESTFILE-MODE: Copy (and rename) one file.\\n assert len(source_files) == 1\\n destdir = os.path.dirname(destpath)\\n\\n # -- WORK-HORSE: Copy one or more files to destpath.\\n if not os.path.isdir(destdir):\\n sys.stdout.write(\\\"copy: Create dir %s\\\\n\\\" % destdir)\\n os.makedirs(destdir)\\n for source in source_files:\\n destname = os.path.join(destdir, os.path.basename(source))\\n sys.stdout.write(\\\"copy: %s => %s\\\\n\\\" % (source, destname))\\n shutil.copy(source, destname)\\n return 0\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n \\\"subscribed\\\": self.subnode_subscribed.makeClone(),\\n \\\"subscript\\\": self.subnode_subscript.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def CopyObjsCommand(self, args, sub_opts=None, headers=None, debug=0,\\n command='cp'):\\n # Expand wildcards and containers in source StorageUris.\\n src_uri_expansion = self.ExpandWildcardsAndContainers(\\n args[0:len(args)-1], sub_opts, headers, debug)\\n\\n # Check for various problems and determine base_dst_uri based for request.\\n (base_dst_uri, multi_src_request) = self.ErrorCheckCopyRequest(\\n src_uri_expansion, args[-1], headers, debug, command)\\n # Rewrite base_dst_uri and create dest dir as needed for multi-source copy.\\n if multi_src_request:\\n base_dst_uri = self.HandleMultiSrcCopyRequst(src_uri_expansion,\\n base_dst_uri)\\n\\n # Now iterate over expanded src URIs, and perform copy operations.\\n total_elapsed_time = total_bytes_transferred = 0\\n for src_uri in iter(src_uri_expansion):\\n for exp_src_uri in src_uri_expansion[src_uri]:\\n print 'Copying %s...' % exp_src_uri\\n dst_uri = self.ConstructDstUri(src_uri, exp_src_uri, base_dst_uri)\\n (elapsed_time, bytes_transferred) = self.PerformCopy(\\n exp_src_uri, dst_uri, sub_opts, headers, debug)\\n total_elapsed_time += elapsed_time\\n total_bytes_transferred += bytes_transferred\\n if debug == 3:\\n # Note that this only counts the actual GET and PUT bytes for the copy\\n # - not any transfers for doing wildcard expansion, the initial HEAD\\n # request boto performs when doing a bucket.get_key() operation, etc.\\n if total_bytes_transferred != 0:\\n print 'Total bytes copied=%d, total elapsed time=%5.3f secs (%sps)' % (\\n total_bytes_transferred, total_elapsed_time,\\n MakeHumanReadable(float(total_bytes_transferred) /\\n float(total_elapsed_time)))\",\n \"def doTheCopy(argpath,argdest):\\n print(\\\"To copy:\\\"+argpath)\\n shutil.copy(argpath,argdest)\",\n \"def supported_table_args(self) -> t.Tuple[str, ...]:\",\n \"def cp(self, copy_from, copy_to, **kwargs):\\n return self.exec_command('cp %s %s' % (copy_from, copy_to), **kwargs)\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"dest\\\": self.subnode_dest.makeClone()\\n if self.subnode_dest is not None\\n else None,\\n \\\"value\\\": self.subnode_value.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def args():\\n\\n useDB = docopt(__doc__)['--from-db']\\n snapFile = docopt(__doc__)['-i']\\n # csvFile = docopt(__doc__)['-o']\\n # utils.askErase(csvFile)\\n\\n return [snapFile, useDB]\",\n \"def copyData(self, src_schema, src_table, src_columns, dest_schema, dest_table, dest_columns):\\r\\n sql = 'INSERT INTO {} ( {} ) SELECT {} FROM {}'.format(self.encodeTableName(dest_schema, dest_table), ','.join(dest_columns),\\r\\n ','.join(src_columns), self.encodeTableName(src_schema, src_table))\\r\\n return self.runSql(sql)\",\n \"def copy(CopySource=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, SourceClient=None, Config=None):\\n pass\",\n \"def svn_client_copy_source_t_path_get(svn_client_copy_source_t_self): # real signature unknown; restored from __doc__\\n return \\\"\\\"\",\n \"def get_source_system_profile_params(argv):\\n with get_audit_db(argv) as audit_db:\\n if audit_db is None:\\n if not argv.tablelist:\\n return []\\n\\n if len(argv.tablelist) == 1:\\n # A file containing table names\\n if os.path.isfile(argv.tablelist[0]):\\n with open(argv.tablelist[0]) as f:\\n return [(argv.sourceschema,\\n t.strip(),\\n argv.targetschema,\\n None) for t in f]\\n\\n return [(argv.sourceschema, table, argv.targetschema, None)\\n for table in argv.tablelist]\\n\\n sql = \\\"\\\"\\\"\\n SELECT source_region, object_name, target_region, query_condition\\n FROM {audit_schema}.source_system_profile\\n WHERE profile_name = %s\\n AND version = %s\\n AND active_ind = 'Y'\\n ORDER BY object_seq\\\"\\\"\\\".format(audit_schema=argv.auditschema)\\n\\n bind_values = [argv.profilename, argv.profileversion]\\n result = audit_db.execute_query(sql, argv.arraysize, bind_values)\\n\\n return [(row[0], row[1], row[2], row[3]) for row in result]\",\n \"def infocalypse_copy(ui_, repo, **opts):\\n params, stored_cfg = get_config_info(ui_, opts)\\n\\n insert_uri = opts['inserturi']\\n if insert_uri == '':\\n # REDFLAG: fix parameter definition so that it is required?\\n ui_.warn(\\\"Please set the insert URI with --inserturi.\\\\n\\\")\\n return\\n\\n request_uri = opts['requesturi']\\n if request_uri == '':\\n request_uri = stored_cfg.get_request_uri(repo.root)\\n if not request_uri:\\n ui_.warn(\\\"There is no stored request URI for this repo.\\\\n\\\"\\n \\\"Please set one with the --requesturi option.\\\\n\\\")\\n return\\n\\n params['INSERT_URI'] = insert_uri\\n params['REQUEST_URI'] = request_uri\\n execute_copy(ui_, repo, params, stored_cfg)\",\n \"def svn_fs_copy(*args):\\r\\n return _fs.svn_fs_copy(*args)\",\n \"def destination(self) -> str:\\n for a in self.args:\\n if a[0] != '-':\\n return a\\n try:\\n return self.kwargs['dest']\\n except KeyError:\\n for a in self.args:\\n if a.startswith('--'):\\n dest = a.lstrip('-').replace('-', '_')\\n if dest.isidentifier():\\n return dest\\n raise AttributeError(F'The argument with these values has no destination: {self!r}')\",\n \"def _copy_to_head_args(args: Namespace) -> Namespace:\\n\\n _head_args = copy.deepcopy(args)\\n _head_args.polling = args.polling\\n _head_args.port = args.port\\n _head_args.host = args.host[0]\\n _head_args.uses = args.uses\\n _head_args.pod_role = PodRoleType.HEAD\\n _head_args.runtime_cls = 'HeadRuntime'\\n _head_args.replicas = 1\\n\\n if args.name:\\n _head_args.name = f'{args.name}/head'\\n else:\\n _head_args.name = f'head'\\n\\n return _head_args\",\n \"def copyCommand(self):\\n\\n selection = self.selectedIndexes()\\n\\n if selection:\\n rows = [index.row() for index in selection]\\n columns = [index.column() for index in selection]\\n if len(rows) == 4:\\n model = self.proxyModel.sourceModel()\\n row = rows[3]\\n column = columns[3]\\n command = model.dataset.data[row][column].cell\\n QApplication.clipboard().setText(command)\",\n \"def destination(self) -> pulumi.Input['DestinationArgs']:\\n return pulumi.get(self, \\\"destination\\\")\",\n \"def test_args_combination():\\n args = cli.parse_args(['-cp'])\\n assert args.copy\\n assert args.paste\\n args = cli.parse_args(['-c', '-p'])\\n assert args.copy\\n assert args.paste\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n \\\"expression\\\": self.subnode_expression.makeClone(),\\n \\\"lower\\\": self.subnode_lower.makeClone()\\n if self.subnode_lower is not None\\n else None,\\n \\\"upper\\\": self.subnode_upper.makeClone()\\n if self.subnode_upper is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source\\\": self.subnode_source.makeClone(),\\n \\\"expression\\\": self.subnode_expression.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def _copy_file ( self, source, dest ):\\n return\",\n \"def print_dry_run_copy_info(source, dest):\\n\\n def shorten_home(path):\\n expanded_home = os.path.expanduser(\\\"~\\\")\\n path = str(path)\\n if path.startswith(expanded_home):\\n return path.replace(expanded_home, \\\"~\\\")\\n return path\\n\\n def truncate_middle(path: str, acceptable_len: int):\\n \\\"\\\"\\\"Middle truncate a string\\n https://www.xormedia.com/string-truncate-middle-with-ellipsis/\\n \\\"\\\"\\\"\\n if len(path) <= acceptable_len:\\n return path\\n # half of the size, minus the 3 .'s\\n n_2 = int(acceptable_len / 2 - 3)\\n # whatever's left\\n n_1 = int(acceptable_len - n_2 - 3)\\n return f\\\"{path[:n_1]}...{path[-n_2:]}\\\"\\n\\n trimmed_source = shorten_home(source)\\n trimmed_dest = shorten_home(dest)\\n longest_allowed_path_len = 87\\n if len(trimmed_source) + len(trimmed_dest) > longest_allowed_path_len:\\n trimmed_source = truncate_middle(trimmed_source, longest_allowed_path_len)\\n trimmed_dest = truncate_middle(trimmed_dest, longest_allowed_path_len)\\n print(\\n Fore.YELLOW + Style.BRIGHT + trimmed_source + Style.NORMAL,\\n \\\"->\\\",\\n Style.BRIGHT + trimmed_dest + Style.RESET_ALL,\\n )\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"subscribed\\\": self.subnode_subscribed.makeClone(),\\n \\\"subscript\\\": self.subnode_subscript.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def CopyTapSettings(self, *args, **kwargs):\\n # type: (*Any, **Any) -> None\\n payload = { \\\"Arg1\\\": self.href }\\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\\n for item in kwargs.items(): payload[item[0]] = item[1]\\n return self._execute('copyTapSettings', payload=payload, response_object=None)\",\n \"def get_args():\\n parser = argparse.ArgumentParser(description='Rsync like thingy')\\n parser.add_argument('--dry-run', required=False,\\n action='store_true', default=False, dest='dry_run',\\n help='Does not do anything on the destination filesystem')\\n\\n parser.add_argument('-v', '--verbose', required=False,\\n action='count', default=0, dest='vlevel',\\n help='Log level')\\n\\n parser.add_argument('--dump-delta', required=False,\\n default=None, metavar='DELTA_PATH', dest='delta_path',\\n help='If a filename is specified, the delta is dumped into the file as JSON')\\n\\n parser.add_argument('--max-depth', required=False,\\n type=int, default=10, dest='max_depth',\\n help='Max depth for both local and remote')\\n\\n parser.add_argument('--adb-batch-size', required=False,\\n type=int, default=5, dest='adb_batch_size',\\n help='Maximum number of adb push to run in parallel')\\n\\n parser.add_argument('--command-batch-size', required=False,\\n type=int, default=100, dest='command_batch_size',\\n help='Maximum number of arguments / chained commands to run at once')\\n\\n parser.add_argument('--delete', required=False,\\n action='store_true', default=False, dest='delete_files',\\n help='Creates a \\\"perfect mirror\\\" of local at remote')\\n \\n parser.add_argument('source', help='The source')\\n parser.add_argument('destination', help='The destination')\\n return parser.parse_args()\",\n \"def svn_client_copy(svn_client_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def __get_datatables_args():\\n\\n table_args = dict()\\n\\n #\\n # Common Arguments\\n #\\n\\n table_args['column-count'] = 0\\n table_args['sort-col-count'] = 0\\n\\n if request.args.get('draw'):\\n table_args['sequence'] = request.args.get('draw')\\n\\n if request.args.get('start'):\\n table_args['offset'] = int(request.args.get('start'))\\n\\n if request.args.get('length'):\\n table_args['limit'] = int(request.args.get('length'))\\n\\n if request.args.get('search[value]'):\\n table_args['filter'] = request.args.get('search[value]')\\n\\n if request.args.get('search[regex]'):\\n table_args['filter-regex'] = request.args.get('search[regex]')\\n\\n #\\n # Custom Arguments\\n #\\n\\n if request.args.get('time_filter'):\\n table_args['time_filter'] = request.args.get('time_filter')\\n\\n i = 0\\n while True:\\n if request.args.get('columns[%d][data]' % i):\\n table_args['column-count'] += 1\\n table_args['mDataProp_%d' % i] = request.args.get('columns[%d][data]' % i)\\n else:\\n break\\n\\n #\\n # Column Search\\n #\\n\\n if request.args.get('columns[%d][searchable]' % i):\\n table_args['bSearchable_%d' % i] = request.args.get('columns[%d][searchable]' % i)\\n\\n if request.args.get('columns[%d][search][value]' % i):\\n table_args['sSearch_%d' % i] = request.args.get('columns[%d][search][value]' % i)\\n\\n if request.args.get('columns[%d][search][regex]' % i):\\n table_args['bRegex_%d' % i] = request.args.get('columns[%d][search][regex]' % i)\\n\\n #\\n # Column Sort\\n #\\n\\n if request.args.get('columns[%d][orderable]' % i):\\n table_args['bSortable_%d' % i] = request.args.get('columns[%d][orderable]' % i)\\n\\n if request.args.get('order[%d][column]' % i):\\n table_args['sort-col-count'] += 1\\n table_args['iSortCol_%d' % i] = int(request.args.get('order[%d][column]' % i))\\n\\n if request.args.get('order[%d][dir]' % i):\\n table_args['sSortDir_%d' % i] = request.args.get('order[%d][dir]' % i)\\n\\n i += 1\\n\\n return table_args\",\n \"def copyFlexor(*args, **kwargs)->AnyStr:\\n pass\",\n \"def copy_db(src=FRESHDB, dst=[APPDB]):\\n for dest in dst:\\n try:\\n x = shutil.copy2(src, dest)\\n print('File copied to {}'.format(x))\\n except shutil.SameFileError:\\n print('Both source and destination are identical.')\",\n \"def ProcessTableCopyOverwrite(ref, args, request):\\n del ref # Unused\\n if args.overwrite:\\n request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'\\n return request\",\n \"def _copyTexture(self, src, dest):\\n self.copyTextureNode.setShaderInput(\\\"src\\\", src)\\n self.copyTextureNode.setShaderInput(\\\"dest\\\", dest)\\n self._executeShader(\\n self.copyTextureNode,\\n (src.getXSize() + 15) / 16,\\n (src.getYSize() + 15) / 16)\",\n \"def copy_source_arn(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"copy_source_arn\\\")\",\n \"def getCloneArgs(self):\\n\\n values = {}\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"dict_arg\\\": self.subnode_dict_arg.makeClone(),\\n \\\"key\\\": self.subnode_key.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def copy(self, src_path: str, tgt_path: str) -> None:\",\n \"async def copy(self, _id: str, dst_id: str, *,\\n rev: Optional[str] = None,\\n dst_rev: Optional[str] = None,\\n batch: Optional[bool] = None) -> dict:\\n\\n headers = dict(\\n Destination=f'{dst_id}?rev={dst_rev}' if dst_rev else dst_id\\n )\\n\\n params = dict(\\n rev=rev,\\n batch=\\\"ok\\\" if batch else None,\\n )\\n\\n return await self.__connection.query('COPY', self._get_path(_id), params=params, headers=headers)\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"source_code\\\": self.subnode_source_code.makeClone(),\\n \\\"globals_arg\\\": self.subnode_globals_arg.makeClone()\\n if self.subnode_globals_arg is not None\\n else None,\\n \\\"locals_arg\\\": self.subnode_locals_arg.makeClone()\\n if self.subnode_locals_arg is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"condition\\\": self.subnode_condition.makeClone(),\\n \\\"yes_branch\\\": self.subnode_yes_branch.makeClone()\\n if self.subnode_yes_branch is not None\\n else None,\\n \\\"no_branch\\\": self.subnode_no_branch.makeClone()\\n if self.subnode_no_branch is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def parse_args():\\n\\n copy_help = 'Copy files back to original target directory? Default False'\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-c', help=copy_help, action='store_true',\\n required=False)\\n arguments = parser.parse_args()\\n return arguments\",\n \"def run_copy(self, src, dst):\\n pass\",\n \"def get(self):\\n copies = db.session.query(models.Copy)\\n args = copy_query_parser.parse_args()\\n copy_id = args['copy_id']\\n if copy_id is not None:\\n copies = copies.filter_by(id=copy_id)\\n book_id = args['book_id']\\n if book_id is not None:\\n copies = copies.filter_by(book=book_id)\\n\\n username = args['user']\\n if username is not None:\\n copies = copies.filter_by(user=username)\\n status = args[\\\"status\\\"]\\n if status is not None:\\n copies = copies.filter_by(status=status)\\n if copy_id is None and book_id is None and username is None and status is None:\\n return 'Please proved searching parameter', 400\\n return [copy.serialize() for copy in copies], 200\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"value\\\": self.subnode_value.makeClone(),\\n \\\"dict_arg\\\": self.subnode_dict_arg.makeClone(),\\n \\\"key\\\": self.subnode_key.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def svn_client_copy_source_t_revision_get(svn_client_copy_source_t_self): # real signature unknown; restored from __doc__\\n pass\",\n \"def parse_args(args):\\n parser = argparse.ArgumentParser(description='Parse Mysql Copy account you want',add_help=False)\\n connect_setting = parser.add_argument_group('connect setting')\\n connect_setting.add_argument('-h','--host',dest='host',type=str,help='Host the MySQL database server located',default='127.0.0.1')\\n connect_setting.add_argument('-u','--user',dest='user',type=str,help='MySQL Username to log in as',default='root')\\n connect_setting.add_argument('-p','--password',dest='password',type=str,help='MySQL Password to use', default='')\\n connect_setting.add_argument('-P', '--port', dest='port', type=int,help='MySQL port to use', default=3306)\\n copy_user = parser.add_argument_group('copy user')\\n copy_user.add_argument('--src-user',dest='srcuser',type=str,help='copy from the user',nargs='*',default='*')\\n copy_user.add_argument('--src-host',dest='srchost',type=str,help='copy from the host',nargs='*',default='*')\\n copy_user.add_argument('--dest-user',dest='destuser',type=str,help='copy to the user',nargs='*',default='')\\n copy_user.add_argument('--dest-host',dest='desthost',type=str,help='copy to the host',nargs='*',default='')\\n\\n parser.add_argument('--help', dest='help', action='store_true', help='help infomation', default=False)\\n\\n return parser\",\n \"def svn_client_copy2(svn_commit_info_t_commit_info_p, char_src_path, svn_opt_revision_t_src_revision, char_dst_path, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def copy_table(self, source_table_name, dest_table_name):\\n logger.info(f\\\"Creating {dest_table_name} from {source_table_name}\\\")\\n try:\\n self._submit_single_q(COPY_TABLE_DDL.format(new_table_name=dest_table_name, old_table_name=source_table_name))\\n except connector.errors.ProgrammingError as e:\\n logger.error(f\\\"Table {dest_table_name} already exists. Exiting.\\\")\\n return\\n except Exception as e:\\n logger.error(\\\"Failed creating table\\\")\\n raise\\n\\n try:\\n q = COPY_TABLE_DATA_DML.format(new_table_name=dest_table_name, old_table_name=source_table_name)\\n self._submit_single_q(COPY_TABLE_DATA_DML.format(new_table_name=dest_table_name, old_table_name=source_table_name))\\n except Exception as e:\\n logger.error(\\\"Failed inserting data\\\")\\n raise e\\n\\n # print(self._submit_single_q(\\\"checksum table xfrm_product, staging_product\\\")\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def copy(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def CopyTo(self, *args, **kwargs):\\n pass\",\n \"def copyPetscArguments(jobdir, argsfile):\\n shutil.copyfile(argsfile, os.path.join(jobdir, \\\"petsc_commandline_arg\\\"))\",\n \"def get_args():\\n parser = argparse.ArgumentParser(\\n description=\\\"Extract a sample of the data.\\\")\\n\\n parser.add_argument(\\\"userid\\\", help=\\\"User ID\\\")\\n parser.add_argument(\\\"start\\\", help=\\\"Start\\\")\\n parser.add_argument(\\\"end\\\", help=\\\"End\\\")\\n parser.add_argument(\\\"source\\\", help=\\\"Source data file\\\")\\n parser.add_argument(\\\"dest\\\", help=\\\"Destination file\\\")\\n\\n return parser.parse_args()\",\n \"def copy(ctx, source, dest, force=False):\\n # print \\\"COPY:\\\", locals()\\n # print \\\"COPY:\\\", ctx.force, ctx.verbose\\n if source == dest:\\n return dest\\n\\n source = os.path.normcase(os.path.normpath(str(source)))\\n dest = os.path.normcase(os.path.normpath(str(dest)))\\n flags = \\\"\\\"\\n if sys.platform == 'win32':\\n if force:\\n flags += \\\" /Y\\\"\\n # print 'copy {flags} {source} {dest}'.format(**locals())\\n ctx.run('copy {flags} {source} {dest}'.format(**locals()))\\n else: # pragma: nocover\\n if force:\\n flags += \\\" --force\\\"\\n ctx.run('cp {flags} {source} {dest}'.format(**locals()))\\n return dest\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"iterator\\\": self.subnode_iterator.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def copyAttr(*args, attribute: Union[AnyStr, List[AnyStr]]=\\\"\\\", containerParentChild: bool=True,\\n inConnections: bool=True, keepSourceConnections: bool=True, outConnections:\\n bool=True, renameTargetContainer: bool=True, values: bool=True, q=True, query=True,\\n e=True, edit=True, **kwargs)->Union[None, Any]:\\n pass\",\n \"def get_arguments():\\n\\tparser.add_argument('-i', '--interface', help='interface to affect')\\n\\tparser.add_argument('-m','--mac', help='mac to allocate')\\n\\n\\targs = parser.parse_args()\\n\\tinterface = args.interface\\n\\tmac = args.mac\\n\\treturn (interface, mac)\",\n \"def args(self) -> typing.Tuple[str, typing.List[str]]:\\n func = inspect.stack()[1][3]\\n command = func[len(self.CMD_PREFIX):]\\n return ('{} {}'.format(sys.argv[0], command),\\n sys.argv[2:])\",\n \"def copy_continuous_backups_properties(events: dict, context: dict) -> List:\\n if 'SourceTableName' not in events:\\n raise KeyError('Requires SourceTableName')\\n if 'TargetTableName' not in events:\\n raise KeyError('Requires TargetTableName')\\n\\n source_table_name: str = events['SourceTableName']\\n target_table_name: str = events['TargetTableName']\\n continuous_backups_settings = _describe_continuous_backups(table_name=source_table_name)\\n continuous_backups_status = continuous_backups_settings\\\\\\n .get('ContinuousBackupsDescription', {})\\\\\\n .get('PointInTimeRecoveryDescription', {})\\\\\\n .get('PointInTimeRecoveryStatus', '')\\n\\n if continuous_backups_status in ['ENABLED', 'ENABLING']:\\n _enable_continuous_backups(table_name=target_table_name)\\n\\n return continuous_backups_status\",\n \"def get_clipboard(*args, **kwargs):\\n return G.DEVICE.get_clipboard(*args, **kwargs)\",\n \"def copy_resource_tags(events: dict, context: dict) -> dict:\\n if 'SourceTableName' not in events:\\n raise KeyError('Requires SourceTableName')\\n if 'TargetTableName' not in events:\\n raise KeyError('Requires TargetTableName')\\n if 'Region' not in events:\\n raise KeyError('Requires Region')\\n if 'Account' not in events:\\n raise KeyError('Requires Account')\\n\\n source_table_name = events['SourceTableName']\\n region = events['Region']\\n account = events['Account']\\n resource_arn = f'arn:aws:dynamodb:{region}:{account}:table/{source_table_name}'\\n tags = list(_list_tags(resource_arn=resource_arn))\\n if tags:\\n target_table_name = events['TargetTableName']\\n resource_arn = f'arn:aws:dynamodb:{region}:{account}:table/{target_table_name}'\\n _update_tags(resource_arn=resource_arn, tags=tags)\\n\\n return {\\n \\\"Tags\\\": tags\\n }\",\n \"def _FormSCPCommandLine(self, src, dst, extra_scp_args=None):\\n assert not self.local, \\\"Cannot use SCP on local target.\\\"\\n\\n args = ['scp', '-P', str(self._ssh_port)] + self._ssh_args\\n if self._ssh_identity:\\n args.extend(['-i', self._ssh_identity])\\n if extra_scp_args:\\n args.extend(extra_scp_args)\\n args += [src, dst]\\n return args\",\n \"def destination_table(self) -> str:\\n return pulumi.get(self, \\\"destination_table\\\")\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"statements\\\": tuple(v.makeClone() for v in self.subnode_statements),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"dict_arg\\\": self.subnode_dict_arg.makeClone(),\\n \\\"value\\\": self.subnode_value.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def test_source_copy_round_trip(self):\\n self.prepare()\\n self.session.execute(\\\"\\\"\\\"\\n CREATE TABLE testcopyto (\\n a int,\\n b text,\\n c float,\\n d uuid,\\n PRIMARY KEY (a, b)\\n )\\\"\\\"\\\")\\n\\n insert_statement = self.session.prepare(\\\"INSERT INTO testcopyto (a, b, c, d) VALUES (?, ?, ?, ?)\\\")\\n args = [(i, str(i), float(i) + 0.5, uuid4()) for i in range(1000)]\\n execute_concurrent_with_args(self.session, insert_statement, args)\\n\\n results = list(self.session.execute(\\\"SELECT * FROM testcopyto\\\"))\\n\\n tempfile = self.get_temp_file()\\n logger.debug('Exporting to csv file: {name}'.format(name=tempfile.name))\\n\\n commandfile = self.get_temp_file()\\n with open(commandfile.name, 'w') as f:\\n f.write('USE ks;\\\\n')\\n f.write(\\\"COPY ks.testcopyto TO '{name}' WITH HEADER=false;\\\".format(name=tempfile.name))\\n\\n self.run_cqlsh(cmds=\\\"SOURCE '{name}'\\\".format(name=commandfile.name))\\n\\n # import the CSV file with COPY FROM\\n self.session.execute(\\\"TRUNCATE ks.testcopyto\\\")\\n logger.debug('Importing from csv file: {name}'.format(name=tempfile.name))\\n\\n commandfile = self.get_temp_file()\\n with open(commandfile.name, 'w') as f:\\n f.write('USE ks;\\\\n')\\n f.write(\\\"COPY ks.testcopyto FROM '{name}' WITH HEADER=false;\\\".format(name=tempfile.name))\\n\\n self.run_cqlsh(cmds=\\\"SOURCE '{name}'\\\".format(name=commandfile.name))\\n new_results = list(self.session.execute(\\\"SELECT * FROM testcopyto\\\"))\\n assert sorted(results) == sorted(new_results)\",\n \"def command_args(self):\\n return self._command_args\",\n \"def clone(source, destination):\\n\\t\\treturn \\\"CREATE DATABASE {0} WITH TEMPLATE {1};\\\".format(destination, source)\",\n \"def get_args_from_console(args):\\n return {\\n \\\"cleaning_policy\\\": args.cleaning_policy,\\n \\\"clear\\\": args.clear,\\n \\\"content\\\": args.content,\\n \\\"dry_run\\\": args.dry_run,\\n \\\"force\\\": args.force,\\n \\\"in_lines\\\": args.in_lines,\\n \\\"max_size\\\": args.max_size,\\n \\\"regex\\\": args.regex,\\n \\\"restore\\\": args.restore,\\n \\\"rmdir\\\": args.rmdir,\\n \\\"short\\\": args.short,\\n \\\"silent\\\": args.silent,\\n \\\"storage_time\\\": args.storage_time,\\n \\\"wastebasket_path\\\": args.wastebasket_path\\n }\",\n \"def copy_file_to_table(self, schema, table, filepath):\\n fields = \\\", \\\".join(self.schemas[schema][table][0])\\n sql = f'set role {self.write_role}; ' \\\\\\n f'COPY {schema}.{table}( {fields} ) FROM stdin WITH DELIMITER \\\\',\\\\' CSV header;'\\n return sql, open(filepath, 'r')\",\n \"def getCopyDestinations(self, hiveDB, hiveTable):\\n\\n\\t\\tsession = self.configDBSession()\\n\\t\\tcopyTables = aliased(configSchema.copyTables)\\n\\n\\t\\tself.copyDestinations = []\\n\\n\\t\\tcopyTablesResult = pd.DataFrame(session.query(copyTables.copy_id, copyTables.hive_filter, copyTables.destination, copyTables.data_transfer).all()).fillna('')\\n\\t\\tfor index, row in copyTablesResult.iterrows():\\n\\t\\t\\tif ';' in row['destination']:\\n\\t\\t\\t\\tlogging.error(\\\"';' not supported in the Copy Destination name\\\")\\n\\t\\t\\t\\tself.remove_temporary_files()\\n\\t\\t\\t\\tsys.exit(1)\\n\\n\\t\\t\\tfor hiveFilterSplit in row['hive_filter'].split(';'):\\n\\n\\t\\t\\t\\tif '.' not in hiveFilterSplit:\\n\\t\\t\\t\\t\\tlogging.warning(\\\"The filter in table 'copy_tables' with copy_id = %s contains an invalid filter. Missing a . in the database.table format\\\"%(row['copy_id']))\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tfilterDB = hiveFilterSplit.split('.')[0]\\n\\t\\t\\t\\t\\tfilterTable = hiveFilterSplit.split('.')[1]\\n\\n\\t\\t\\t\\t\\tif fnmatch.fnmatch(hiveDB, filterDB) and fnmatch.fnmatch(hiveTable, filterTable):\\n\\t\\t\\t\\t\\t\\tdestString = \\\"%s;%s\\\"%(row['destination'], row['data_transfer'])\\n\\t\\t\\t\\t\\t\\tdestStringASync = \\\"%s;Asynchronous\\\"%(row['destination'])\\n\\t\\t\\t\\t\\t\\tdestStringSync = \\\"%s;Synchronous\\\"%(row['destination'])\\n\\t\\t\\t\\t\\t\\tif destStringSync in self.copyDestinations and destString == destStringASync:\\n\\t\\t\\t\\t\\t\\t\\t# ASync have priority. So if sync is already in there, we remove it and add async\\n\\t\\t\\t\\t\\t\\t\\tself.copyDestinations.remove(destStringSync)\\n\\t\\t\\t\\t\\t\\tif destStringASync not in self.copyDestinations and destStringSync not in self.copyDestinations:\\n\\t\\t\\t\\t\\t\\t\\tself.copyDestinations.append(destString)\\n\\t\\n\\t\\tif self.copyDestinations == []:\\n\\t\\t\\tself.copyDestinations = None\\n\\t\\treturn self.copyDestinations\",\n \"def svn_client_copy4(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def cp(self, src, dest):\\r\\n return self._call(\\\"-cp\\\", src, dest, suppress_output=True)\",\n \"def _FormSCPCommandLine(self, src, dst, extra_scp_args=None):\\n assert not self.local, \\\"Cannot use SCP on local target.\\\"\\n\\n # -C enables compression.\\n args = ['scp', '-C', '-P', str(self._ssh_port)] + self._ssh_args\\n if self._ssh_identity:\\n args.extend(['-i', self._ssh_identity])\\n if extra_scp_args:\\n args.extend(extra_scp_args)\\n args += [src, dst]\\n return args\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"iterated_length\\\": self.subnode_iterated_length.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def test_copy_sources(self):\\n metric_copy = copy_metric(self.metric, self.DATA_MODEL)\\n self.assertEqual(\\\"Source\\\", first(metric_copy[\\\"sources\\\"].values())[\\\"name\\\"])\",\n \"def getPlainCopyPrefices():\\n\\n oldPrefix = \\\"\\\"\\n newPrefix = \\\"\\\"\\n\\n # get the copyprefices\\n copyprefix = readpar('copyprefixin')\\n if copyprefix == \\\"\\\":\\n copyprefix = readpar('copyprefix')\\n\\n if \\\"^\\\" in copyprefix:\\n prefices = copyprefix.split(\\\"^\\\")\\n oldPrefix = prefices[0]\\n newPrefix = prefices[1]\\n else:\\n tolog(\\\"!!WARNING!!4444!! Unexpected copyprefix[in] format: %s\\\" % (copyprefix))\\n\\n return oldPrefix, newPrefix\",\n \"def args(self):\\n return self._args.copy()\",\n \"def create_copyfile_dict(child):\\n\\n attrs = ['src', 'dest']\\n values = [child.get(attr) for attr in attrs]\\n\\n if None in values:\\n raise InvalidManifest(\\n 'Missing required attribute in copyfile element'\\n )\\n\\n return dict(zip(attrs, values))\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"set_arg\\\": self.subnode_set_arg.makeClone(),\\n \\\"value\\\": self.subnode_value.makeClone(),\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def getCopyRef(self):\\n return self.base.get(\\\"copy_ref\\\", [])\",\n \"def getCloneArgs(self):\\n\\n values = {\\n \\\"tried\\\": self.subnode_tried.makeClone(),\\n \\\"except_handler\\\": self.subnode_except_handler.makeClone()\\n if self.subnode_except_handler is not None\\n else None,\\n \\\"break_handler\\\": self.subnode_break_handler.makeClone()\\n if self.subnode_break_handler is not None\\n else None,\\n \\\"continue_handler\\\": self.subnode_continue_handler.makeClone()\\n if self.subnode_continue_handler is not None\\n else None,\\n \\\"return_handler\\\": self.subnode_return_handler.makeClone()\\n if self.subnode_return_handler is not None\\n else None,\\n }\\n\\n values.update(self.getDetails())\\n\\n return values\",\n \"def copy_table(source_table, destination_table, db='default'):\\n try:\\n with connections[db].cursor() as cursor:\\n cursor.execute('CREATE TABLE IF NOT EXISTS %s LIKE %s;' % (destination_table, source_table))\\n except:\\n pass\",\n \"def get_args(self):\\n req_argv = self._ptr.contents.argv\\n args = []\\n if bool(req_argv):\\n i = 0\\n while 1:\\n s = bytestostr(req_argv[i])\\n i += 1\\n if s == None:\\n break\\n args.append(s)\\n return args\",\n \"def svn_client_commit_item2_t_copyfrom_url_get(svn_client_commit_item2_t_self): # real signature unknown; restored from __doc__\\n return \\\"\\\"\",\n \"def drag_dest_info(self):\\n return DdTargets.URI_LIST\",\n \"def svn_fs_copied_from(*args):\\r\\n return _fs.svn_fs_copied_from(*args)\",\n \"def dest_columns(self):\\n return self.intersection + self.dest_renames\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.62132674","0.56889355","0.55710876","0.55588037","0.5540921","0.54608697","0.54608697","0.54608697","0.53417224","0.5325953","0.52964944","0.52829","0.5282849","0.52788526","0.52047265","0.52009565","0.51657414","0.51652837","0.516145","0.5143834","0.5141003","0.5089321","0.5060838","0.5059258","0.5040755","0.50163513","0.4990004","0.49761227","0.4948509","0.4938476","0.49368966","0.49062234","0.48965007","0.4858598","0.48385695","0.4830435","0.48218018","0.48083597","0.48037088","0.4801186","0.48010105","0.4800827","0.47903466","0.478679","0.47862244","0.4776404","0.476859","0.47649565","0.47568598","0.474825","0.4725044","0.47191182","0.47161132","0.47158703","0.47028","0.46928236","0.46928236","0.46928236","0.46928236","0.46928236","0.46928236","0.46928236","0.4689384","0.4687183","0.46865472","0.46853408","0.46819425","0.46801308","0.46769735","0.46666905","0.4666626","0.4666013","0.4645687","0.46397057","0.46252763","0.46245512","0.46213064","0.4617944","0.4614827","0.46081105","0.46067435","0.4602058","0.4600361","0.45927164","0.45917934","0.4591577","0.4589844","0.45893788","0.45889303","0.45842716","0.45831826","0.45789352","0.45689532","0.4568338","0.4566945","0.4565554","0.45598337","0.45584893","0.4558324","0.45500827"],"string":"[\n \"0.62132674\",\n \"0.56889355\",\n \"0.55710876\",\n \"0.55588037\",\n \"0.5540921\",\n \"0.54608697\",\n \"0.54608697\",\n \"0.54608697\",\n \"0.53417224\",\n \"0.5325953\",\n \"0.52964944\",\n \"0.52829\",\n \"0.5282849\",\n \"0.52788526\",\n \"0.52047265\",\n \"0.52009565\",\n \"0.51657414\",\n \"0.51652837\",\n \"0.516145\",\n \"0.5143834\",\n \"0.5141003\",\n \"0.5089321\",\n \"0.5060838\",\n \"0.5059258\",\n \"0.5040755\",\n \"0.50163513\",\n \"0.4990004\",\n \"0.49761227\",\n \"0.4948509\",\n \"0.4938476\",\n \"0.49368966\",\n \"0.49062234\",\n \"0.48965007\",\n \"0.4858598\",\n \"0.48385695\",\n \"0.4830435\",\n \"0.48218018\",\n \"0.48083597\",\n \"0.48037088\",\n \"0.4801186\",\n \"0.48010105\",\n \"0.4800827\",\n \"0.47903466\",\n \"0.478679\",\n \"0.47862244\",\n \"0.4776404\",\n \"0.476859\",\n \"0.47649565\",\n \"0.47568598\",\n \"0.474825\",\n \"0.4725044\",\n \"0.47191182\",\n \"0.47161132\",\n \"0.47158703\",\n \"0.47028\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.46928236\",\n \"0.4689384\",\n \"0.4687183\",\n \"0.46865472\",\n \"0.46853408\",\n \"0.46819425\",\n \"0.46801308\",\n \"0.46769735\",\n \"0.46666905\",\n \"0.4666626\",\n \"0.4666013\",\n \"0.4645687\",\n \"0.46397057\",\n \"0.46252763\",\n \"0.46245512\",\n \"0.46213064\",\n \"0.4617944\",\n \"0.4614827\",\n \"0.46081105\",\n \"0.46067435\",\n \"0.4602058\",\n \"0.4600361\",\n \"0.45927164\",\n \"0.45917934\",\n \"0.4591577\",\n \"0.4589844\",\n \"0.45893788\",\n \"0.45889303\",\n \"0.45842716\",\n \"0.45831826\",\n \"0.45789352\",\n \"0.45689532\",\n \"0.4568338\",\n \"0.4566945\",\n \"0.4565554\",\n \"0.45598337\",\n \"0.45584893\",\n \"0.4558324\",\n \"0.45500827\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8508633"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":2297,"cells":{"query":{"kind":"string","value":"Print a simple greeting to each user in the list."},"document":{"kind":"string","value":"def greet_users(names):\n for name in names:\n msg = \"Hello, \" + name.title() + \"!\"\n print(msg)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def greet_users(names):\n for name in names:\n print(f\"Hello, {name.title()}!\")","def greeting(list_of_guests):\r\n for i in list_of_guests: \r\n print('Witaj ' + i)","def greet_users(names):\n for name in names:\n msg = f\"Hello, {name.title()}\"\n print(msg)","def greet_users(names):\n for name in names:\n msg = f\"Hello, {name.title()}!\"\n print(msg)","def greet_users(names):\n for name in names:\n msg = f\"Hello, {name.title()}!\"\n print(msg)","def greet_user(names):\n\n for name in names:\n msg = f\"Hello, {name.title()} !\"\n print(msg)","def print_users(self):\n for i, item in enumerate(self.users):\n print(\"{}. {}\".format(i, item.name))","def greet_user(self):\n print(\"Hello, \" + self.first_name.title() + \" \" + self.last_name.title() + \"!\")","def greet_user(self):\n print(\"Hello \" + self.first_name.title() + \" \" +\n self.last_name.title() + \", welcome back!\")","def greet_user(self):\n print(\"Welcome, \" + self.first_name.title() + \"!\")","def greet_user(self):\r\n\r\n print(\"Hello \" + self.first_name.title() + \" \" + self.last_name.title() + \".\")","def greet_user(self):\n greeting = f\"Hi {self.first_name.title()}, welcome back!\\n\"\n print(greeting)","def greet_user(self):\n print(\"\\nWelcome, \" + self.username + \"!\")","def greet_user(self):\n print(\"\\nWelcome, \" + self.username + \"!\")","def greet_user(self):\r\n\t\tprint(f\"\\nHello {self.first_name}!\\n\")","def greet_user(self):\n print(\"Hello \" + self.f_name.title() + \"!, hope you're well today!\")","def greet_user(username):\r\n print(f\"Hello, {username.title()}!\")","def greet_user(self):\n\t\tprint(f\"How are you doing {self.first_name.title()}?\")","def greet_user():\r\n print('Hi,' + FirstName + ' ' + LastName + ' thanks for joining us inside the beer app!')","async def _welcome(self, ctx, *, users: discord.User = None):\n if not users:\n await ctx.send(f\"Welcome {ctx.author.mention} to {ctx.guild.name}!\")\n else:\n if len(users) > 1:\n users = humanize_list(users)\n else:\n users = users[0].mention\n await ctx.send(f\"Welcome {users} to {ctx.guild.name}!\")","def print_users(self):\n for user in self.users.values():\n print(user)","def greet_user(self):\n print(f\"Hiya {self.username}!\")","def greet_user(username):\n print(\"Hello, \" + username.title() + \"!\")","def greet_user(username):\n print(\"Hello, \" + username.title() + \"!\")","def greet_user(username):\r\n print(\"Hello, \" + username + \"!\")","def greeter_user(username):\n print(f\"Hello {username}\")","def greet_user(username):\n print(\"Hello, \" + username + \"!\")","def greet_user(self):\n print(\"Greatings \"+ self.first_name + \" \" + self.last_name +\", welcome to the matrix.\")","def greet_user():\n print(\"Hello\")","def greeting(players_name):\n print \"\\nGreat! Welcome, \" + players_name + \". The purpose of this game is to fill in the blanks for all the sentences provided.\"","def greet_user():\n username = get_user()\n\n if username:\n print(f\"Välkommen tillbaks {username.title()}!!\")\n else:\n username = create_new_user()\n print(f\"Vi kommer ihåg dig när du återvänder {username}\")","def greet_username(username):\n print(\"Hello, \" + username.title() + \"!\")","async def greeting(self, ctx):\n await self.bot.say('hello {0.name}'.format(ctx.message.author))","def greet_user():\n print(\"Hello!\")","def greet_user():\n print(\"Hello!\")","def greet_user():\n print(\"Hello!\")","def greet(*names):\n print(names)\n for name in names:\n print(' Hello {0}!'.format(name))","def list_users(item):\n users = User.load_all_users(item)\n for user in users:\n print(user.username)","def show_greeting(self):\n self.output(' ------------------------ ')\n self.output('You are now playing ' + self.name)\n self.output(self.greeting)\n self.output(' ------------------------ ')","def welcome_user():\n welcome_string = 'Welcome to the brain Brain Games!\\n'\n print(welcome_string)\n name = prompt.string('May I have your name? ')\n print('{0}, {1}!'.format('Hello', name))","def greet_user():\r\n print(\"hello!\")","def greet_user():\n username = get_stored_username()\n if username:\n print(\"Welcome back, \" + username['Name'] + \"!\")\n else:\n username = get_new_username()\n print(\"We'll remember you when you come back, \" + username + \"!\")","def __list_all_users(self):\n\n usernames_dict = get_data.get_usernames_dict()\n if len(usernames_dict) > 0:\n first_str = 'user'\n second_str = 'posts scraped'\n descriptor = '{:<40} {}'\n print('')\n print(descriptor.format(first_str, second_str))\n print(descriptor.format(len(first_str) * '-', len(second_str) * '-'))\n for number, username in usernames_dict.items():\n space_str = ' ' if len(str(number)) > 1 else ' '\n first = '[' + space_str + str(number) + '] ' + username\n second = str(get_data.get_user_post_count(username))\n print(descriptor.format(first, second))\n else:\n print('no users found in the database')","def greeting(self):\n print(\"Hello! My name is {name}.\".format(name=self.name))","def greeting(self):\n print(\"Hello! My name is {name}.\".format(name=self.name))","def greet_user():\n username = load_user_data()\n if username != None:\n print(\"Welcome back, \" + username)\n else:\n register_user()","def greeting(name, message):\n print(f'Hello {name}!')\n print(message)","def user_list(server_object, client, address, command_args):\n\n\tmsg = \"\"\n\n\t#: Create a formatted string of all the users.\n\tfor usr in server_object.usrs.values():\n\t\tmsg += usr + '\\n'\n\n\tclient.send(msg.encode())","def list_users():\n\n users = User.query.order_by(\"last_name\").all()\n return render_template(\"users/user_list.html\", users=users)","def list_users():\n users = User.query.order_by(User.last_name, User.first_name).all()\n return render_template('index.html', users=users)","def show_users():\n return 'hehe'","def home_list():\n\tui.lst1()\n\tui.lst2()\n\tx = db.get_users()\n\tfor i in x:\n\t\tz = len(i[1])\n\t\tf = 16-z\n\t\tl = \" \"*f\n\t\tprint i[1], l, i[4],l,i[5]\n\traw_input(\"Press [enter] to goto homescreen\")\n\thome()","def greet_user(name = 'Menoetius'):\n print(\"Hello, my name is \" + name.title() + \"!\")","def welcome():\n name = prompt.string('May I have your name? ')\n print(f'Hello, {name}!') # noqa: WPS421","def greeting(name):\n print(\"\")\n print(\n \"Welcome to Mister Sweet's Mad Lib Story Telling Journey \" + name +\n \" :)\")\n print(\"\")","def show():\n return render_template(\n 'listUsers.html',\n title='List Users',\n message='These are the users in our system'\n )","def greet_user():\n\tusername = get_stored_username()\n\tif username:\n\t\tprint(\"Welcome back, \" + username + \"!\")\n\telse:\n\t\tusername = get_new_username()\n\t\tprint(\"We'll remember you when you come back, \" + username + \"!\")","def do_list_users(self, line):\n users = self.protocol.cmd_list_users(exp=line, return_list=True)\n t = PrettyTable(users[0])\n for u in users[1:]:\n t.add_row(u)\n print(t)","def greet_guest():\n print('Welcome')","def greeting():\n print('\\n',\n '=' * 45,\n \"\\n Welcome to this Module-Creation-Test-Program!!!\",\n '\\n',\n '=' * 45)","def _list_users(self):\n users = fileIO.load_json(\"users.json\")\n print(\"The list of users is as follows:\")\n for i in users:\n print(users[i][\"name\"])\n self._list_user_settings(users)","def user_list():\n\n users = User.query.all()\n\n return render_template(\"user_list.html\", users=users)","def display_list(the_list):\n print(\"\\n===================================\")\n for person in the_list:\n print(\"{name:12s}\\t\\t{phone}\".format(name=person.name, phone=person.phone))\n if the_list == []:\n print(\"\\nNo entries found!\\n\")\n print(\"===================================\\n\")","def printusers(self, irc, msg, args):\n irc.reply(self.user_report(), prefixNick=False)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list():\n\n users = User.query.all()\n return render_template(\"user_list.html\", users=users)","def user_list_all(message=''):\n return Response(render_template('employee/user/list.html',\n users=User.query.all(),\n message=message),\n mimetype='text/html')","def list_users(self, user=None):\n from expfactory.database.models import Participant\n\n participants = Participant.query.all()\n users = []\n for user in participants:\n users.append(self.print_user(user))\n return users","def user_list(ctx):\n data = ctx.obj.get_all_users()\n output_json_data(data)","def guestlist_handler(userdata, *args):\n\t\tfor guest in userdata[\"guestlist\"]:\n\t\t\tprint(shlex.quote(guest), end=\" \")\n\t\t\n\t\tprint()","def user_list():\n\n users = User.query.all()\n \n return render_template(\"user_list.html\", users=users)","async def tod_list(self, ctx, *args):\n message = \"__Currently Playing__\\n\"\n if len(self.players) == 0:\n message = \"There are currently no users playing.\"\n for player in self.players:\n message += f\"> {str(player)[:-5]}\\n\"\n await ctx.send(message)","def do_user_list(cs, args):\n _, users = cs.users.list()\n fields = ['user_id', 'username', 'email', 'realname', 'comment']\n utils.print_list(users, fields, sortby=args.sortby)","def print_user_host(host_list, user, ul):\n \n print('\\nHost-group info pertaining to {0}:'.format(user))\n print('-'.center(80, '-'))\n if len(ul) == 0:\n print('User is not a member of any user-lists.')\n else:\n print('User belongs to the following user-lists:')\n for u in ul:\n print(u)\n print()\n print('User has access to the following host-groups:')\n for hg in host_list:\n print(hg)\n print('-'.center(80, '-') + '\\n')\n return","def user_list():\n\n users = User.query.all()\n return render_template(\"/user_list.html\", users=users)","async def list_users(self, ctx):\n \n path = \"Users\"\n headers = {\n 'accept': 'application/json'\n }\n response = send_request(method=\"get\", path=path, headers=headers)\n users = []\n for page in response:\n users.append(f\"**{page['Name']}**: ``{page['Id']}``\")\n log.debug(users)\n\n embed = embeds.make_embed(ctx=ctx, title=\"List Users\", image_url=\"https://emby.media/resources/logowhite_1881.png\")\n\n await LinePaginator.paginate([line for line in users], ctx, embed, restrict_to_user=ctx.author)","def describe_user(self):\n\t\tprint(f\"\\n{self.first_name.title()} {self.last_name.title()} \"\n\t\t\tf\"is from {self.location.title()}.\")","def greet_user():\n\tusername = get_stored_username()\n\tif username:\n\t\tprint(f\"WElcome back {username}!\")\n\telse:\n\t\tusername = get_new_username()\n\t\tprint(f\"We'll remember you when you come back again {username}! \")","def list( self, mess, args):\n user = self.get_sender_username(mess)\n args = args.replace(' ', '_')\n if user in self.users:\n user_list = 'All these users are subscribed - \\n'\n user_list += '\\n'.join(['%s :: %s' %(u, self.users[u]) for u in sorted(self.users)])\n if self.invited.keys():\n user_list += '\\n The following users are invited - \\n'\n user_list += '\\n'.join(self.invited.keys())\n self.log.info( '%s checks list of users.' % user)\n return user_list","def user_list(message=''):\n target_users = User.query.filter_by(name=request.form['name']).all()\n\n if not any(target_users):\n return search_user(\"Unknown user.\")\n\n return Response(render_template('employee/user/list.html',\n users=target_users,\n message=message),\n mimetype='text/html')","def do_list(self, arg):\n print('The roster includes the following members:\\n')\n lines = formatTable(\n map(self.memberToList, self.roster),\n [\n ColumnFormat('id', 4),\n ColumnFormat('name', 30),\n ColumnFormat('introduced', 12)\n ]) \n for line in lines: \n print(line)","def listusers():\n\n try:\n users = User.query.order_by(User.email).all()\n click.echo(\n tabulate(\n [\n [u.username, u.email, \"admin\" if u.is_admin else None]\n for u in users\n ]\n )\n )\n except OperationalError:\n click.echo(\"Tabela de usuários inexistente...\")","def welcome_user():\n print('Welcome to the Brain Games!')\n name = prompt.string('May I have your name? ')\n print('Hello, {0}!'.format(name)) # noqa: WPS421\n return name","def list_users():\n\n db_users = User.query.all()\n\n return render_template(\"list_users.html\", headline=\"Blogly Users\", users=db_users)","def greeting_message(name):\n print('My name is ' + name)","def user_list(message=''):\n return Response(render_template('admin/user/list.html',\n users=User.query.all(),\n message=message),\n mimetype='text/html')","def welcome(self):\n print(\"\\t\\t\\t\\t\\t============================\")\n print(\"\\t\\t\\tWelcome to Shakespeare's Phrase Hunter!\"\n \"\\n\\t\\t\\tYou will be tested on your Shakespeare knowledge with various \"\n \"\\n\\t\\t\\tphrases from his writings.\")\n print(\"\\t\\t\\t\\t\\t============================\")","def say_hi(self):\n print(\"Hi there, everyone!\")","def __ui_list_all_persons(self):\n persons_list = self.__person_service.service_get_persons_list()\n\n if len(persons_list) == 0:\n print(\"The list of persons is empty!\")\n else:\n print(\"The list of persons in your agenda:\")\n for person in persons_list:\n print(\" \" + str(person))\n print(\"\")","def view_users(stdscr):\n stdscr.clear()\n safe_put(stdscr, \"* marks a user online at last update. Hit any key to return to menu.\", (2, 1))\n row = 4\n for user in taunet.users.all():\n if user.is_on:\n safe_put(stdscr, \"*\", (row, 1))\n safe_put(stdscr, user.name, (row, 3))\n row += 1\n stdscr.refresh()\n\n # Wait for any key, then clear and return to menu.\n stdscr.getch()\n stdscr.clear()\n stdscr.refresh()","def main():\n data = get_db()\n myCursor = data.cursor()\n myCursor.execute(\"SELECT * FROM users\")\n description = [desc[0] for desc in myCursor.description]\n\n logger = get_logger()\n\n for user in myCursor:\n userInfo = \"\".join(\n f'{des}={str(usr)}; ' for usr, des in zip(user, description)\n )\n logger.info(userInfo)\n\n myCursor.close()\n data.close()","def describe_user(self):\r\n print('\\nFirst Name: ' + self.first_name.title(), end='\\n',)\r\n print('Last Name: ' + self.last_name.title(), end='\\n')\r\n print('Address: ' + self.address.title(), end='\\n',)\r\n print('State: ' + self.state.title(), end='\\n',)\r\n print('Country: ' + self.country.title())","def show_users():\r\n users = User.query.order_by(User.last_name,User.first_name).all()\r\n return render_template('list.html', users=users)","def greet_player(name):\n\t\n\tprint \"How are are you doing %s?\" % name","def greet(*args):\n print(greet.__doc__)\n # names is a tuple with arguments\n for name in args:\n print(\"Hello\", name)"],"string":"[\n \"def greet_users(names):\\n for name in names:\\n print(f\\\"Hello, {name.title()}!\\\")\",\n \"def greeting(list_of_guests):\\r\\n for i in list_of_guests: \\r\\n print('Witaj ' + i)\",\n \"def greet_users(names):\\n for name in names:\\n msg = f\\\"Hello, {name.title()}\\\"\\n print(msg)\",\n \"def greet_users(names):\\n for name in names:\\n msg = f\\\"Hello, {name.title()}!\\\"\\n print(msg)\",\n \"def greet_users(names):\\n for name in names:\\n msg = f\\\"Hello, {name.title()}!\\\"\\n print(msg)\",\n \"def greet_user(names):\\n\\n for name in names:\\n msg = f\\\"Hello, {name.title()} !\\\"\\n print(msg)\",\n \"def print_users(self):\\n for i, item in enumerate(self.users):\\n print(\\\"{}. {}\\\".format(i, item.name))\",\n \"def greet_user(self):\\n print(\\\"Hello, \\\" + self.first_name.title() + \\\" \\\" + self.last_name.title() + \\\"!\\\")\",\n \"def greet_user(self):\\n print(\\\"Hello \\\" + self.first_name.title() + \\\" \\\" +\\n self.last_name.title() + \\\", welcome back!\\\")\",\n \"def greet_user(self):\\n print(\\\"Welcome, \\\" + self.first_name.title() + \\\"!\\\")\",\n \"def greet_user(self):\\r\\n\\r\\n print(\\\"Hello \\\" + self.first_name.title() + \\\" \\\" + self.last_name.title() + \\\".\\\")\",\n \"def greet_user(self):\\n greeting = f\\\"Hi {self.first_name.title()}, welcome back!\\\\n\\\"\\n print(greeting)\",\n \"def greet_user(self):\\n print(\\\"\\\\nWelcome, \\\" + self.username + \\\"!\\\")\",\n \"def greet_user(self):\\n print(\\\"\\\\nWelcome, \\\" + self.username + \\\"!\\\")\",\n \"def greet_user(self):\\r\\n\\t\\tprint(f\\\"\\\\nHello {self.first_name}!\\\\n\\\")\",\n \"def greet_user(self):\\n print(\\\"Hello \\\" + self.f_name.title() + \\\"!, hope you're well today!\\\")\",\n \"def greet_user(username):\\r\\n print(f\\\"Hello, {username.title()}!\\\")\",\n \"def greet_user(self):\\n\\t\\tprint(f\\\"How are you doing {self.first_name.title()}?\\\")\",\n \"def greet_user():\\r\\n print('Hi,' + FirstName + ' ' + LastName + ' thanks for joining us inside the beer app!')\",\n \"async def _welcome(self, ctx, *, users: discord.User = None):\\n if not users:\\n await ctx.send(f\\\"Welcome {ctx.author.mention} to {ctx.guild.name}!\\\")\\n else:\\n if len(users) > 1:\\n users = humanize_list(users)\\n else:\\n users = users[0].mention\\n await ctx.send(f\\\"Welcome {users} to {ctx.guild.name}!\\\")\",\n \"def print_users(self):\\n for user in self.users.values():\\n print(user)\",\n \"def greet_user(self):\\n print(f\\\"Hiya {self.username}!\\\")\",\n \"def greet_user(username):\\n print(\\\"Hello, \\\" + username.title() + \\\"!\\\")\",\n \"def greet_user(username):\\n print(\\\"Hello, \\\" + username.title() + \\\"!\\\")\",\n \"def greet_user(username):\\r\\n print(\\\"Hello, \\\" + username + \\\"!\\\")\",\n \"def greeter_user(username):\\n print(f\\\"Hello {username}\\\")\",\n \"def greet_user(username):\\n print(\\\"Hello, \\\" + username + \\\"!\\\")\",\n \"def greet_user(self):\\n print(\\\"Greatings \\\"+ self.first_name + \\\" \\\" + self.last_name +\\\", welcome to the matrix.\\\")\",\n \"def greet_user():\\n print(\\\"Hello\\\")\",\n \"def greeting(players_name):\\n print \\\"\\\\nGreat! Welcome, \\\" + players_name + \\\". The purpose of this game is to fill in the blanks for all the sentences provided.\\\"\",\n \"def greet_user():\\n username = get_user()\\n\\n if username:\\n print(f\\\"Välkommen tillbaks {username.title()}!!\\\")\\n else:\\n username = create_new_user()\\n print(f\\\"Vi kommer ihåg dig när du återvänder {username}\\\")\",\n \"def greet_username(username):\\n print(\\\"Hello, \\\" + username.title() + \\\"!\\\")\",\n \"async def greeting(self, ctx):\\n await self.bot.say('hello {0.name}'.format(ctx.message.author))\",\n \"def greet_user():\\n print(\\\"Hello!\\\")\",\n \"def greet_user():\\n print(\\\"Hello!\\\")\",\n \"def greet_user():\\n print(\\\"Hello!\\\")\",\n \"def greet(*names):\\n print(names)\\n for name in names:\\n print(' Hello {0}!'.format(name))\",\n \"def list_users(item):\\n users = User.load_all_users(item)\\n for user in users:\\n print(user.username)\",\n \"def show_greeting(self):\\n self.output(' ------------------------ ')\\n self.output('You are now playing ' + self.name)\\n self.output(self.greeting)\\n self.output(' ------------------------ ')\",\n \"def welcome_user():\\n welcome_string = 'Welcome to the brain Brain Games!\\\\n'\\n print(welcome_string)\\n name = prompt.string('May I have your name? ')\\n print('{0}, {1}!'.format('Hello', name))\",\n \"def greet_user():\\r\\n print(\\\"hello!\\\")\",\n \"def greet_user():\\n username = get_stored_username()\\n if username:\\n print(\\\"Welcome back, \\\" + username['Name'] + \\\"!\\\")\\n else:\\n username = get_new_username()\\n print(\\\"We'll remember you when you come back, \\\" + username + \\\"!\\\")\",\n \"def __list_all_users(self):\\n\\n usernames_dict = get_data.get_usernames_dict()\\n if len(usernames_dict) > 0:\\n first_str = 'user'\\n second_str = 'posts scraped'\\n descriptor = '{:<40} {}'\\n print('')\\n print(descriptor.format(first_str, second_str))\\n print(descriptor.format(len(first_str) * '-', len(second_str) * '-'))\\n for number, username in usernames_dict.items():\\n space_str = ' ' if len(str(number)) > 1 else ' '\\n first = '[' + space_str + str(number) + '] ' + username\\n second = str(get_data.get_user_post_count(username))\\n print(descriptor.format(first, second))\\n else:\\n print('no users found in the database')\",\n \"def greeting(self):\\n print(\\\"Hello! My name is {name}.\\\".format(name=self.name))\",\n \"def greeting(self):\\n print(\\\"Hello! My name is {name}.\\\".format(name=self.name))\",\n \"def greet_user():\\n username = load_user_data()\\n if username != None:\\n print(\\\"Welcome back, \\\" + username)\\n else:\\n register_user()\",\n \"def greeting(name, message):\\n print(f'Hello {name}!')\\n print(message)\",\n \"def user_list(server_object, client, address, command_args):\\n\\n\\tmsg = \\\"\\\"\\n\\n\\t#: Create a formatted string of all the users.\\n\\tfor usr in server_object.usrs.values():\\n\\t\\tmsg += usr + '\\\\n'\\n\\n\\tclient.send(msg.encode())\",\n \"def list_users():\\n\\n users = User.query.order_by(\\\"last_name\\\").all()\\n return render_template(\\\"users/user_list.html\\\", users=users)\",\n \"def list_users():\\n users = User.query.order_by(User.last_name, User.first_name).all()\\n return render_template('index.html', users=users)\",\n \"def show_users():\\n return 'hehe'\",\n \"def home_list():\\n\\tui.lst1()\\n\\tui.lst2()\\n\\tx = db.get_users()\\n\\tfor i in x:\\n\\t\\tz = len(i[1])\\n\\t\\tf = 16-z\\n\\t\\tl = \\\" \\\"*f\\n\\t\\tprint i[1], l, i[4],l,i[5]\\n\\traw_input(\\\"Press [enter] to goto homescreen\\\")\\n\\thome()\",\n \"def greet_user(name = 'Menoetius'):\\n print(\\\"Hello, my name is \\\" + name.title() + \\\"!\\\")\",\n \"def welcome():\\n name = prompt.string('May I have your name? ')\\n print(f'Hello, {name}!') # noqa: WPS421\",\n \"def greeting(name):\\n print(\\\"\\\")\\n print(\\n \\\"Welcome to Mister Sweet's Mad Lib Story Telling Journey \\\" + name +\\n \\\" :)\\\")\\n print(\\\"\\\")\",\n \"def show():\\n return render_template(\\n 'listUsers.html',\\n title='List Users',\\n message='These are the users in our system'\\n )\",\n \"def greet_user():\\n\\tusername = get_stored_username()\\n\\tif username:\\n\\t\\tprint(\\\"Welcome back, \\\" + username + \\\"!\\\")\\n\\telse:\\n\\t\\tusername = get_new_username()\\n\\t\\tprint(\\\"We'll remember you when you come back, \\\" + username + \\\"!\\\")\",\n \"def do_list_users(self, line):\\n users = self.protocol.cmd_list_users(exp=line, return_list=True)\\n t = PrettyTable(users[0])\\n for u in users[1:]:\\n t.add_row(u)\\n print(t)\",\n \"def greet_guest():\\n print('Welcome')\",\n \"def greeting():\\n print('\\\\n',\\n '=' * 45,\\n \\\"\\\\n Welcome to this Module-Creation-Test-Program!!!\\\",\\n '\\\\n',\\n '=' * 45)\",\n \"def _list_users(self):\\n users = fileIO.load_json(\\\"users.json\\\")\\n print(\\\"The list of users is as follows:\\\")\\n for i in users:\\n print(users[i][\\\"name\\\"])\\n self._list_user_settings(users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def display_list(the_list):\\n print(\\\"\\\\n===================================\\\")\\n for person in the_list:\\n print(\\\"{name:12s}\\\\t\\\\t{phone}\\\".format(name=person.name, phone=person.phone))\\n if the_list == []:\\n print(\\\"\\\\nNo entries found!\\\\n\\\")\\n print(\\\"===================================\\\\n\\\")\",\n \"def printusers(self, irc, msg, args):\\n irc.reply(self.user_report(), prefixNick=False)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"def user_list_all(message=''):\\n return Response(render_template('employee/user/list.html',\\n users=User.query.all(),\\n message=message),\\n mimetype='text/html')\",\n \"def list_users(self, user=None):\\n from expfactory.database.models import Participant\\n\\n participants = Participant.query.all()\\n users = []\\n for user in participants:\\n users.append(self.print_user(user))\\n return users\",\n \"def user_list(ctx):\\n data = ctx.obj.get_all_users()\\n output_json_data(data)\",\n \"def guestlist_handler(userdata, *args):\\n\\t\\tfor guest in userdata[\\\"guestlist\\\"]:\\n\\t\\t\\tprint(shlex.quote(guest), end=\\\" \\\")\\n\\t\\t\\n\\t\\tprint()\",\n \"def user_list():\\n\\n users = User.query.all()\\n \\n return render_template(\\\"user_list.html\\\", users=users)\",\n \"async def tod_list(self, ctx, *args):\\n message = \\\"__Currently Playing__\\\\n\\\"\\n if len(self.players) == 0:\\n message = \\\"There are currently no users playing.\\\"\\n for player in self.players:\\n message += f\\\"> {str(player)[:-5]}\\\\n\\\"\\n await ctx.send(message)\",\n \"def do_user_list(cs, args):\\n _, users = cs.users.list()\\n fields = ['user_id', 'username', 'email', 'realname', 'comment']\\n utils.print_list(users, fields, sortby=args.sortby)\",\n \"def print_user_host(host_list, user, ul):\\n \\n print('\\\\nHost-group info pertaining to {0}:'.format(user))\\n print('-'.center(80, '-'))\\n if len(ul) == 0:\\n print('User is not a member of any user-lists.')\\n else:\\n print('User belongs to the following user-lists:')\\n for u in ul:\\n print(u)\\n print()\\n print('User has access to the following host-groups:')\\n for hg in host_list:\\n print(hg)\\n print('-'.center(80, '-') + '\\\\n')\\n return\",\n \"def user_list():\\n\\n users = User.query.all()\\n return render_template(\\\"/user_list.html\\\", users=users)\",\n \"async def list_users(self, ctx):\\n \\n path = \\\"Users\\\"\\n headers = {\\n 'accept': 'application/json'\\n }\\n response = send_request(method=\\\"get\\\", path=path, headers=headers)\\n users = []\\n for page in response:\\n users.append(f\\\"**{page['Name']}**: ``{page['Id']}``\\\")\\n log.debug(users)\\n\\n embed = embeds.make_embed(ctx=ctx, title=\\\"List Users\\\", image_url=\\\"https://emby.media/resources/logowhite_1881.png\\\")\\n\\n await LinePaginator.paginate([line for line in users], ctx, embed, restrict_to_user=ctx.author)\",\n \"def describe_user(self):\\n\\t\\tprint(f\\\"\\\\n{self.first_name.title()} {self.last_name.title()} \\\"\\n\\t\\t\\tf\\\"is from {self.location.title()}.\\\")\",\n \"def greet_user():\\n\\tusername = get_stored_username()\\n\\tif username:\\n\\t\\tprint(f\\\"WElcome back {username}!\\\")\\n\\telse:\\n\\t\\tusername = get_new_username()\\n\\t\\tprint(f\\\"We'll remember you when you come back again {username}! \\\")\",\n \"def list( self, mess, args):\\n user = self.get_sender_username(mess)\\n args = args.replace(' ', '_')\\n if user in self.users:\\n user_list = 'All these users are subscribed - \\\\n'\\n user_list += '\\\\n'.join(['%s :: %s' %(u, self.users[u]) for u in sorted(self.users)])\\n if self.invited.keys():\\n user_list += '\\\\n The following users are invited - \\\\n'\\n user_list += '\\\\n'.join(self.invited.keys())\\n self.log.info( '%s checks list of users.' % user)\\n return user_list\",\n \"def user_list(message=''):\\n target_users = User.query.filter_by(name=request.form['name']).all()\\n\\n if not any(target_users):\\n return search_user(\\\"Unknown user.\\\")\\n\\n return Response(render_template('employee/user/list.html',\\n users=target_users,\\n message=message),\\n mimetype='text/html')\",\n \"def do_list(self, arg):\\n print('The roster includes the following members:\\\\n')\\n lines = formatTable(\\n map(self.memberToList, self.roster),\\n [\\n ColumnFormat('id', 4),\\n ColumnFormat('name', 30),\\n ColumnFormat('introduced', 12)\\n ]) \\n for line in lines: \\n print(line)\",\n \"def listusers():\\n\\n try:\\n users = User.query.order_by(User.email).all()\\n click.echo(\\n tabulate(\\n [\\n [u.username, u.email, \\\"admin\\\" if u.is_admin else None]\\n for u in users\\n ]\\n )\\n )\\n except OperationalError:\\n click.echo(\\\"Tabela de usuários inexistente...\\\")\",\n \"def welcome_user():\\n print('Welcome to the Brain Games!')\\n name = prompt.string('May I have your name? ')\\n print('Hello, {0}!'.format(name)) # noqa: WPS421\\n return name\",\n \"def list_users():\\n\\n db_users = User.query.all()\\n\\n return render_template(\\\"list_users.html\\\", headline=\\\"Blogly Users\\\", users=db_users)\",\n \"def greeting_message(name):\\n print('My name is ' + name)\",\n \"def user_list(message=''):\\n return Response(render_template('admin/user/list.html',\\n users=User.query.all(),\\n message=message),\\n mimetype='text/html')\",\n \"def welcome(self):\\n print(\\\"\\\\t\\\\t\\\\t\\\\t\\\\t============================\\\")\\n print(\\\"\\\\t\\\\t\\\\tWelcome to Shakespeare's Phrase Hunter!\\\"\\n \\\"\\\\n\\\\t\\\\t\\\\tYou will be tested on your Shakespeare knowledge with various \\\"\\n \\\"\\\\n\\\\t\\\\t\\\\tphrases from his writings.\\\")\\n print(\\\"\\\\t\\\\t\\\\t\\\\t\\\\t============================\\\")\",\n \"def say_hi(self):\\n print(\\\"Hi there, everyone!\\\")\",\n \"def __ui_list_all_persons(self):\\n persons_list = self.__person_service.service_get_persons_list()\\n\\n if len(persons_list) == 0:\\n print(\\\"The list of persons is empty!\\\")\\n else:\\n print(\\\"The list of persons in your agenda:\\\")\\n for person in persons_list:\\n print(\\\" \\\" + str(person))\\n print(\\\"\\\")\",\n \"def view_users(stdscr):\\n stdscr.clear()\\n safe_put(stdscr, \\\"* marks a user online at last update. Hit any key to return to menu.\\\", (2, 1))\\n row = 4\\n for user in taunet.users.all():\\n if user.is_on:\\n safe_put(stdscr, \\\"*\\\", (row, 1))\\n safe_put(stdscr, user.name, (row, 3))\\n row += 1\\n stdscr.refresh()\\n\\n # Wait for any key, then clear and return to menu.\\n stdscr.getch()\\n stdscr.clear()\\n stdscr.refresh()\",\n \"def main():\\n data = get_db()\\n myCursor = data.cursor()\\n myCursor.execute(\\\"SELECT * FROM users\\\")\\n description = [desc[0] for desc in myCursor.description]\\n\\n logger = get_logger()\\n\\n for user in myCursor:\\n userInfo = \\\"\\\".join(\\n f'{des}={str(usr)}; ' for usr, des in zip(user, description)\\n )\\n logger.info(userInfo)\\n\\n myCursor.close()\\n data.close()\",\n \"def describe_user(self):\\r\\n print('\\\\nFirst Name: ' + self.first_name.title(), end='\\\\n',)\\r\\n print('Last Name: ' + self.last_name.title(), end='\\\\n')\\r\\n print('Address: ' + self.address.title(), end='\\\\n',)\\r\\n print('State: ' + self.state.title(), end='\\\\n',)\\r\\n print('Country: ' + self.country.title())\",\n \"def show_users():\\r\\n users = User.query.order_by(User.last_name,User.first_name).all()\\r\\n return render_template('list.html', users=users)\",\n \"def greet_player(name):\\n\\t\\n\\tprint \\\"How are are you doing %s?\\\" % name\",\n \"def greet(*args):\\n print(greet.__doc__)\\n # names is a tuple with arguments\\n for name in args:\\n print(\\\"Hello\\\", name)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7734112","0.77260417","0.77145106","0.76987046","0.76987046","0.7657923","0.7309932","0.7257354","0.72450185","0.71396","0.7127663","0.71238464","0.70934796","0.70934796","0.7048947","0.70248073","0.69579583","0.69458425","0.6898827","0.6775238","0.67534596","0.6752124","0.67099774","0.67099774","0.6647687","0.6625254","0.66171527","0.66072917","0.6599232","0.6530941","0.6511075","0.6386513","0.63414574","0.6332193","0.6332193","0.6332193","0.63153094","0.6304812","0.62947744","0.62882507","0.6280475","0.6264375","0.6261962","0.6204842","0.6204842","0.61728466","0.6123615","0.61222816","0.6119334","0.6117244","0.61068803","0.61064","0.6101039","0.60837436","0.6071284","0.60652494","0.6060082","0.6052348","0.6016096","0.6013506","0.60024095","0.6000968","0.600021","0.5997099","0.59944695","0.59944695","0.59944695","0.59944695","0.59944695","0.59944695","0.5994234","0.59913105","0.59907746","0.5987951","0.59814095","0.5979029","0.59762615","0.59697515","0.59508884","0.59490275","0.59419936","0.59373695","0.5933945","0.5927176","0.59161186","0.59079194","0.59035516","0.59019226","0.5887828","0.58837277","0.585537","0.5853326","0.5848565","0.5838953","0.58369875","0.58303624","0.581508","0.58148783","0.58062875"],"string":"[\n \"0.7734112\",\n \"0.77260417\",\n \"0.77145106\",\n \"0.76987046\",\n \"0.76987046\",\n \"0.7657923\",\n \"0.7309932\",\n \"0.7257354\",\n \"0.72450185\",\n \"0.71396\",\n \"0.7127663\",\n \"0.71238464\",\n \"0.70934796\",\n \"0.70934796\",\n \"0.7048947\",\n \"0.70248073\",\n \"0.69579583\",\n \"0.69458425\",\n \"0.6898827\",\n \"0.6775238\",\n \"0.67534596\",\n \"0.6752124\",\n \"0.67099774\",\n \"0.67099774\",\n \"0.6647687\",\n \"0.6625254\",\n \"0.66171527\",\n \"0.66072917\",\n \"0.6599232\",\n \"0.6530941\",\n \"0.6511075\",\n \"0.6386513\",\n \"0.63414574\",\n \"0.6332193\",\n \"0.6332193\",\n \"0.6332193\",\n \"0.63153094\",\n \"0.6304812\",\n \"0.62947744\",\n \"0.62882507\",\n \"0.6280475\",\n \"0.6264375\",\n \"0.6261962\",\n \"0.6204842\",\n \"0.6204842\",\n \"0.61728466\",\n \"0.6123615\",\n \"0.61222816\",\n \"0.6119334\",\n \"0.6117244\",\n \"0.61068803\",\n \"0.61064\",\n \"0.6101039\",\n \"0.60837436\",\n \"0.6071284\",\n \"0.60652494\",\n \"0.6060082\",\n \"0.6052348\",\n \"0.6016096\",\n \"0.6013506\",\n \"0.60024095\",\n \"0.6000968\",\n \"0.600021\",\n \"0.5997099\",\n \"0.59944695\",\n \"0.59944695\",\n \"0.59944695\",\n \"0.59944695\",\n \"0.59944695\",\n \"0.59944695\",\n \"0.5994234\",\n \"0.59913105\",\n \"0.59907746\",\n \"0.5987951\",\n \"0.59814095\",\n \"0.5979029\",\n \"0.59762615\",\n \"0.59697515\",\n \"0.59508884\",\n \"0.59490275\",\n \"0.59419936\",\n \"0.59373695\",\n \"0.5933945\",\n \"0.5927176\",\n \"0.59161186\",\n \"0.59079194\",\n \"0.59035516\",\n \"0.59019226\",\n \"0.5887828\",\n \"0.58837277\",\n \"0.585537\",\n \"0.5853326\",\n \"0.5848565\",\n \"0.5838953\",\n \"0.58369875\",\n \"0.58303624\",\n \"0.581508\",\n \"0.58148783\",\n \"0.58062875\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7734813"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":2298,"cells":{"query":{"kind":"string","value":"Return a full name, neatly formatted."},"document":{"kind":"string","value":"def get_formatted_name(first_name, last_name, middle_name=''):\n if middle_name:\n full_name = first_name + ' ' + middle_name + ' ' + last_name\n else:\n full_name = first_name + ' ' + last_name\n return full_name.title()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_full_name(self):\n full_name = '{0} {1} {2}'.format(self.last_name, self.first_name, self.patronymic)\n return full_name.strip()","def get_full_name(self):\n\t\tfull_name = '%s %s' % (self.first_name, self.last_name)\n\t\treturn full_name.strip()","def get_full_name(self):\r\n full_name = '%s %s' % (self.first_name, self.last_name)\r\n return full_name.strip()","def get_full_name(self):\r\n full_name = '%s %s' % (self.first_name, self.last_name)\r\n return full_name.strip()","def full_name(self) -> str:\r\n\t\tname = f'{self.last_name} {self.first_name}'\r\n\t\tif self.middle_name:\r\n\t\t\tname += ' ' + self.middle_name\r\n\t\treturn name","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\r\n full_name = '%s' % (self.name)\r\n return full_name.strip()","def get_formatted_name(first, last):\n\tfull_name = first + ' ' + last\n\treturn full_name.title()","def get_full_name(self):\n\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_full_name(self):\n\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def format_name(self):\n\t\tself.full_name = self.first + \" \" + self.last","def get_full_name(self):\n return \"%s %s\" % (self._first_name, self._last_name)","def get_full_name(self):\n full_name = u'%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def get_formatted_name(first_name, last_name): \r\n full_name = f\"{first_name} {last_name}\"\r\n return full_name.title()","def get_full_name(self):\n full_name = '%s %s' % (self.first_name, self.last_name)\n return full_name.strip()","def full_name(self):\n \tif self.first_name and self.last_name:\n \t\treturn \"{} {}\".format(self.first_name, self.last_name)","def get_formatted_name(first, last):\n full_name = first + ' ' + last\n return full_name.title()","def get_full_name(self):\n full_name = \"%s %s\" % (self.firstname, self.lastname)\n return full_name.strip()","def get_full_name(self):\n full_name = '{} {}'.format(self.first_name, self.last_name)\n return full_name.strip()","def get_formatted_name(first_name, last_name):\n full_name = first_name + ' ' + last_name\n return full_name.title()","def get_formatted_name(first_name, last_name):\n full_name = first_name + ' ' + last_name\n return full_name.title()","def get_formatted_name(first_name, last_name):\n full_name = first_name + ' ' + last_name\n return full_name.title()","def get_formatted_name(first_name,last_name):\n full_name = f\"{first_name} {last_name}\"\n return full_name.title()","def get_full_name(self):\n return u'%s %s' % (self.first_name, self.last_name)","def get_formatted_name(first_name,last_name):\n\tfull_name=first_name+ ' ' +last_name\n\treturn full_name.title()","def get_formatted_name(first, last):\n full_name = f\"{first} {last}\"\n return full_name.title()","def get_full_name(self):\n if self.patronymic_name:\n return '{} {} {}'.format(\n self.first_name,\n self.patronymic_name,\n self.last_name,\n )\n\n return '{} {}'.format(\n self.first_name,\n self.last_name,\n )","def get_full_name(self):\n return \"{} {}\".format(self.first_name, self.last_name)","def get_formatted_name(first_name, last_name):\n full_name = f\"{first_name} {last_name}\"\n return full_name.title()","def get_formatted_name(first_name, last_name):\n full_name = f\"{first_name} {last_name}\"\n return full_name.title()","def get_formatted_name(first_name, last_name):\n full_name = f\"{first_name} {last_name}\"\n return full_name.title()","def get_formatted_name(first, last):\n full_name = f'{first} {last}'\n return full_name.title()","def _get_full_name(self):\n if self.middle_name:\n return u'%s %s %s' % (self.first_name, self.middle_name,\n self.last_name)\n else:\n return u'%s %s' % (self.first_name, self.last_name)","def get_formatted_name(first_name,last_name):\n full_name= first_name + \" \"+last_name\n return full_name.title()","def full_name(self):\n return f\"{self.first_name} {self.last_name}\"","def full_name(self):\n return f\"{self.first_name} {self.last_name}\"","def full_name(self):\n return f\"{self.first_name} {self.last_name}\"","def get_full_name(self):\n return f'{self.first_name} {self.last_name}'","def get_formatted_name(first_name, middle_name, last_name):\n full_name = f\"{first_name} {middle_name} {last_name}\"\n return full_name.title()","def get_full_name(self):\n return self.name+self.last_name","def full_name(self):\n return self.first_name + \" \" + self.last_name","def get_full_name(self):\n return \"{0} {1}\".format(self.first_name, self.last_surname)","def get_full_name(self) -> str:\n return f\"{self.first_name} {self.last_name}\"","def get_full_name(self):\n return f\"{self.first_name} {self.last_name}\"","def get_full_name(self):\n return f\"{self.first_name} {self.last_name}\"","def get_formatted_name(self):\n\n return '%s %s' % (self.last_name, self.first_initial)","def full_name(first_name, last_name):\n\t\n\treturn first_name + \" \" + last_name","def get_full_name(self):\n return self.first_name + ' ' + self.last_name","def full_name(self):\n return u\"{} {}\".format(self.pref_first_name(), self.last_name)","def get_name(self):\n return \"%s %s\" % (\n self.first_name,\n self.last_name\n )","def get_formatted_name(first_name, last_name, middle_name=''):\r\n if middle_name:\r\n full_name = f\"{first_name} {middle_name} {last_name}\"\r\n else:\r\n full_name = f\"{first_name} {last_name}\"\r\n return full_name.title()","def get_full_name(self):\n return self.last_name + self.first_name","def get_formatted_name(first_name, last_name, middle_name = ''):\n if middle_name:\n full_name = f\"{first_name} {middle_name} {last_name}\"\n else:\n full_name = f\"{first_name} {last_name}\"\n return full_name.title()","def full_name_short(self):\n return \"{}. {}\".format(str(self.user.first_name)[:1], self.user.last_name)","def full_name(first_name, last_name):\n return first_name + \" \" + last_name","def full_name(self):\n return \"{} {}\".format(self.user.first_name, self.user.last_name)","def get_full_name(self):\n full_name = f'{self.first_name} {self.last_name}' if self.first_name and self.last_name else self.username\n return full_name.strip()","def get_formated_name(first_name,last_name):\n\tfull_name = first_name + '' + last_name\n\treturn full_name.title()","def get_formatted_name(first_name, last_name, middle_name = ''):\n if middle_name:\n full_name = first_name + ' ' + middle_name + ' ' + last_name\n else:\n full_name = first_name + ' ' + last_name\n return full_name.title()","def get_full_name(self):\n return self.name + \" \" + self.email","def formatted_name(first_name, last_name, middle_name = ''):\n full_name = first_name + ' ' + middle_name + ' ' + last_name\n return full_name.title()","def get_formatted_name(first_name, last_name):\n # Describe the function\n # The names are joined into full name\n formatted_name = first_name + ' ' + last_name\n # return the value, don't do anything with it yet\n return formatted_name.title()","def short_name(self) -> str:\r\n\t\treturn f'{self.last_name} {self.first_name}'","def name(self):\n return \"%s %s\" % (self.first_name, self.last_name)","def get_full_name(self):\n full_name = '%s %s' % (self.user.first_name.strip(), self.user.last_name.strip())\n if len(full_name.strip()) == 0:\n full_name = self.user.username\n return full_name.strip()","def get_name(self):\r\n return ('%s %s' % ( self.first_name, self.last_name ))","def get_full_name(self):\n return self.first_name+\" \"+self.last_name","def get_formatted_name(first,last,middle = ''):\n if middle:\n full_name = first + ' ' + middle + ' ' + last\n else:\n full_name = first + ' ' + last\n return full_name.title()","def fullname(self):\n return '{} {}'.format(self.fname,self.lname)","def get_short_name(self):\n return f\"{self.first_name} {self.last_name[:1]}\" if self.first_name else self.username","def get_full_name(self):\n return '{}, {}'.format(self.last_name, self.first_name)","def fullname(self):\n return self.fname() + ' ' + self.lname()","def get_full_name(self):\n return self.name"],"string":"[\n \"def get_full_name(self):\\n full_name = '{0} {1} {2}'.format(self.last_name, self.first_name, self.patronymic)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n\\t\\tfull_name = '%s %s' % (self.first_name, self.last_name)\\n\\t\\treturn full_name.strip()\",\n \"def get_full_name(self):\\r\\n full_name = '%s %s' % (self.first_name, self.last_name)\\r\\n return full_name.strip()\",\n \"def get_full_name(self):\\r\\n full_name = '%s %s' % (self.first_name, self.last_name)\\r\\n return full_name.strip()\",\n \"def full_name(self) -> str:\\r\\n\\t\\tname = f'{self.last_name} {self.first_name}'\\r\\n\\t\\tif self.middle_name:\\r\\n\\t\\t\\tname += ' ' + self.middle_name\\r\\n\\t\\treturn name\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\r\\n full_name = '%s' % (self.name)\\r\\n return full_name.strip()\",\n \"def get_formatted_name(first, last):\\n\\tfull_name = first + ' ' + last\\n\\treturn full_name.title()\",\n \"def get_full_name(self):\\n\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def format_name(self):\\n\\t\\tself.full_name = self.first + \\\" \\\" + self.last\",\n \"def get_full_name(self):\\n return \\\"%s %s\\\" % (self._first_name, self._last_name)\",\n \"def get_full_name(self):\\n full_name = u'%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_formatted_name(first_name, last_name): \\r\\n full_name = f\\\"{first_name} {last_name}\\\"\\r\\n return full_name.title()\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def full_name(self):\\n \\tif self.first_name and self.last_name:\\n \\t\\treturn \\\"{} {}\\\".format(self.first_name, self.last_name)\",\n \"def get_formatted_name(first, last):\\n full_name = first + ' ' + last\\n return full_name.title()\",\n \"def get_full_name(self):\\n full_name = \\\"%s %s\\\" % (self.firstname, self.lastname)\\n return full_name.strip()\",\n \"def get_full_name(self):\\n full_name = '{} {}'.format(self.first_name, self.last_name)\\n return full_name.strip()\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = first_name + ' ' + last_name\\n return full_name.title()\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = first_name + ' ' + last_name\\n return full_name.title()\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = first_name + ' ' + last_name\\n return full_name.title()\",\n \"def get_formatted_name(first_name,last_name):\\n full_name = f\\\"{first_name} {last_name}\\\"\\n return full_name.title()\",\n \"def get_full_name(self):\\n return u'%s %s' % (self.first_name, self.last_name)\",\n \"def get_formatted_name(first_name,last_name):\\n\\tfull_name=first_name+ ' ' +last_name\\n\\treturn full_name.title()\",\n \"def get_formatted_name(first, last):\\n full_name = f\\\"{first} {last}\\\"\\n return full_name.title()\",\n \"def get_full_name(self):\\n if self.patronymic_name:\\n return '{} {} {}'.format(\\n self.first_name,\\n self.patronymic_name,\\n self.last_name,\\n )\\n\\n return '{} {}'.format(\\n self.first_name,\\n self.last_name,\\n )\",\n \"def get_full_name(self):\\n return \\\"{} {}\\\".format(self.first_name, self.last_name)\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = f\\\"{first_name} {last_name}\\\"\\n return full_name.title()\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = f\\\"{first_name} {last_name}\\\"\\n return full_name.title()\",\n \"def get_formatted_name(first_name, last_name):\\n full_name = f\\\"{first_name} {last_name}\\\"\\n return full_name.title()\",\n \"def get_formatted_name(first, last):\\n full_name = f'{first} {last}'\\n return full_name.title()\",\n \"def _get_full_name(self):\\n if self.middle_name:\\n return u'%s %s %s' % (self.first_name, self.middle_name,\\n self.last_name)\\n else:\\n return u'%s %s' % (self.first_name, self.last_name)\",\n \"def get_formatted_name(first_name,last_name):\\n full_name= first_name + \\\" \\\"+last_name\\n return full_name.title()\",\n \"def full_name(self):\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def full_name(self):\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def full_name(self):\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def get_full_name(self):\\n return f'{self.first_name} {self.last_name}'\",\n \"def get_formatted_name(first_name, middle_name, last_name):\\n full_name = f\\\"{first_name} {middle_name} {last_name}\\\"\\n return full_name.title()\",\n \"def get_full_name(self):\\n return self.name+self.last_name\",\n \"def full_name(self):\\n return self.first_name + \\\" \\\" + self.last_name\",\n \"def get_full_name(self):\\n return \\\"{0} {1}\\\".format(self.first_name, self.last_surname)\",\n \"def get_full_name(self) -> str:\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def get_full_name(self):\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def get_full_name(self):\\n return f\\\"{self.first_name} {self.last_name}\\\"\",\n \"def get_formatted_name(self):\\n\\n return '%s %s' % (self.last_name, self.first_initial)\",\n \"def full_name(first_name, last_name):\\n\\t\\n\\treturn first_name + \\\" \\\" + last_name\",\n \"def get_full_name(self):\\n return self.first_name + ' ' + self.last_name\",\n \"def full_name(self):\\n return u\\\"{} {}\\\".format(self.pref_first_name(), self.last_name)\",\n \"def get_name(self):\\n return \\\"%s %s\\\" % (\\n self.first_name,\\n self.last_name\\n )\",\n \"def get_formatted_name(first_name, last_name, middle_name=''):\\r\\n if middle_name:\\r\\n full_name = f\\\"{first_name} {middle_name} {last_name}\\\"\\r\\n else:\\r\\n full_name = f\\\"{first_name} {last_name}\\\"\\r\\n return full_name.title()\",\n \"def get_full_name(self):\\n return self.last_name + self.first_name\",\n \"def get_formatted_name(first_name, last_name, middle_name = ''):\\n if middle_name:\\n full_name = f\\\"{first_name} {middle_name} {last_name}\\\"\\n else:\\n full_name = f\\\"{first_name} {last_name}\\\"\\n return full_name.title()\",\n \"def full_name_short(self):\\n return \\\"{}. {}\\\".format(str(self.user.first_name)[:1], self.user.last_name)\",\n \"def full_name(first_name, last_name):\\n return first_name + \\\" \\\" + last_name\",\n \"def full_name(self):\\n return \\\"{} {}\\\".format(self.user.first_name, self.user.last_name)\",\n \"def get_full_name(self):\\n full_name = f'{self.first_name} {self.last_name}' if self.first_name and self.last_name else self.username\\n return full_name.strip()\",\n \"def get_formated_name(first_name,last_name):\\n\\tfull_name = first_name + '' + last_name\\n\\treturn full_name.title()\",\n \"def get_formatted_name(first_name, last_name, middle_name = ''):\\n if middle_name:\\n full_name = first_name + ' ' + middle_name + ' ' + last_name\\n else:\\n full_name = first_name + ' ' + last_name\\n return full_name.title()\",\n \"def get_full_name(self):\\n return self.name + \\\" \\\" + self.email\",\n \"def formatted_name(first_name, last_name, middle_name = ''):\\n full_name = first_name + ' ' + middle_name + ' ' + last_name\\n return full_name.title()\",\n \"def get_formatted_name(first_name, last_name):\\n # Describe the function\\n # The names are joined into full name\\n formatted_name = first_name + ' ' + last_name\\n # return the value, don't do anything with it yet\\n return formatted_name.title()\",\n \"def short_name(self) -> str:\\r\\n\\t\\treturn f'{self.last_name} {self.first_name}'\",\n \"def name(self):\\n return \\\"%s %s\\\" % (self.first_name, self.last_name)\",\n \"def get_full_name(self):\\n full_name = '%s %s' % (self.user.first_name.strip(), self.user.last_name.strip())\\n if len(full_name.strip()) == 0:\\n full_name = self.user.username\\n return full_name.strip()\",\n \"def get_name(self):\\r\\n return ('%s %s' % ( self.first_name, self.last_name ))\",\n \"def get_full_name(self):\\n return self.first_name+\\\" \\\"+self.last_name\",\n \"def get_formatted_name(first,last,middle = ''):\\n if middle:\\n full_name = first + ' ' + middle + ' ' + last\\n else:\\n full_name = first + ' ' + last\\n return full_name.title()\",\n \"def fullname(self):\\n return '{} {}'.format(self.fname,self.lname)\",\n \"def get_short_name(self):\\n return f\\\"{self.first_name} {self.last_name[:1]}\\\" if self.first_name else self.username\",\n \"def get_full_name(self):\\n return '{}, {}'.format(self.last_name, self.first_name)\",\n \"def fullname(self):\\n return self.fname() + ' ' + self.lname()\",\n \"def get_full_name(self):\\n return self.name\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.87166595","0.86399925","0.860218","0.860218","0.8595642","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.8579464","0.85681736","0.8555431","0.85347563","0.85347563","0.85340965","0.8530991","0.85229343","0.85161304","0.85101086","0.8504636","0.848572","0.8475814","0.84587014","0.84312713","0.84312713","0.84312713","0.8427818","0.8427174","0.8419169","0.84167993","0.84123874","0.8409802","0.84084505","0.84084505","0.84084505","0.8394749","0.83689845","0.8364981","0.83552843","0.83552843","0.83552843","0.834448","0.83326125","0.8326628","0.83254","0.83004296","0.8295617","0.8280516","0.8280516","0.8263089","0.8261442","0.8251206","0.82287455","0.82184637","0.82184035","0.820879","0.819135","0.8184172","0.8176628","0.8160043","0.81207067","0.81086946","0.80960333","0.8095","0.80775666","0.8075149","0.8074684","0.806589","0.80025256","0.7995147","0.79878163","0.79397106","0.792853","0.78728807","0.7862347","0.7800958","0.77908313"],"string":"[\n \"0.87166595\",\n \"0.86399925\",\n \"0.860218\",\n \"0.860218\",\n \"0.8595642\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.8579464\",\n \"0.85681736\",\n \"0.8555431\",\n \"0.85347563\",\n \"0.85347563\",\n \"0.85340965\",\n \"0.8530991\",\n \"0.85229343\",\n \"0.85161304\",\n \"0.85101086\",\n \"0.8504636\",\n \"0.848572\",\n \"0.8475814\",\n \"0.84587014\",\n \"0.84312713\",\n \"0.84312713\",\n \"0.84312713\",\n \"0.8427818\",\n \"0.8427174\",\n \"0.8419169\",\n \"0.84167993\",\n \"0.84123874\",\n \"0.8409802\",\n \"0.84084505\",\n \"0.84084505\",\n \"0.84084505\",\n \"0.8394749\",\n \"0.83689845\",\n \"0.8364981\",\n \"0.83552843\",\n \"0.83552843\",\n \"0.83552843\",\n \"0.834448\",\n \"0.83326125\",\n \"0.8326628\",\n \"0.83254\",\n \"0.83004296\",\n \"0.8295617\",\n \"0.8280516\",\n \"0.8280516\",\n \"0.8263089\",\n \"0.8261442\",\n \"0.8251206\",\n \"0.82287455\",\n \"0.82184637\",\n \"0.82184035\",\n \"0.820879\",\n \"0.819135\",\n \"0.8184172\",\n \"0.8176628\",\n \"0.8160043\",\n \"0.81207067\",\n \"0.81086946\",\n \"0.80960333\",\n \"0.8095\",\n \"0.80775666\",\n \"0.8075149\",\n \"0.8074684\",\n \"0.806589\",\n \"0.80025256\",\n \"0.7995147\",\n \"0.79878163\",\n \"0.79397106\",\n \"0.792853\",\n \"0.78728807\",\n \"0.7862347\",\n \"0.7800958\",\n \"0.77908313\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8130383"},"document_rank":{"kind":"string","value":"83"}}},{"rowIdx":2299,"cells":{"query":{"kind":"string","value":"Return a dictionary of information about a person."},"document":{"kind":"string","value":"def build_person(first_name, last_name, age=''):\n person = {'first': first_name, 'last': last_name}\n if age:\n person['age'] = age\n return person"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_person(self):\n person_dict = {\n 'firstname': self.__firstname,\n 'lastname': self.__lastname,\n 'height': self.__height,\n 'weight': self.__weight,\n 'age': self.__age\n }\n return person_dict","def who_am_i():\n return {'name': 'Jonathan Martinez', 'id': '201095569', 'email': 'martijon@post.bgu.ac.il'}","def get_person(self, url: str) -> dict:\n person = self.read_html(url)\n\n return {\n # TODO: There's a better way of doing this.\n self._columns[0]: person.select_one(\"h1\").text.strip(),\n self._columns[1]: person.select_one(\".party-membership--party\").text,\n self._columns[2]: \"; \".join(\n [a.text for a in person.select('[href^=\"tel:\"]')]\n ),\n self._columns[3]: \"; \".join(\n [a.text for a in person.select(\".email-address a\")]\n ),\n self._columns[4]: \"; \".join(\n [a.text.strip() for a in person.select(\".contact-actions__twitter\")]\n ),\n }","def parse_person(person):\n person_name = person['name']\n person_id = person['id']\n\n pages = get_pages_from_wiki_search(person_name)\n page = select_page_like_person(pages, person)\n\n wiki_person = {\n 'id': person_id, 'fullname': person_name,\n 'url': page.get('fullurl', None), \n 'declarator_profile': page.get('declarator_profile', None),\n 'words_intersection': page.get('words_intersection', None),\n }\n\n # if page with image\n if 'pageimage' in page:\n try:\n image = page['pageimage']\n url = page['original']['source']\n license = get_license_from_wiki(image, is_file=True)\n\n photo = {'title': image, 'url': url, 'license': license}\n wiki_person['photo'] = photo\n except KeyError as e:\n message = \"person_id: %i, Not found key: %s\" % (person_id, e)\n Querylog.error(message)\n return wiki_person","def get_person(self, id):\n try:\n person = Person.get(Person.id == id)\n data = model_to_dict(person)\n except DoesNotExist:\n response.status = 404\n data = \"Not found\"\n return dict(name='Person', data=data)","def get_person_like_json(self):\n return json.dumps(self.get_person())","def display_person(person):\n name = person['name']\n followers = person['follower_count']\n description = person['description']\n country = person['country']\n print(f'{name}, a(n) {description}, from {country}.')\n return followers","def showInfo(p,personDict):\n info1 = personDict['EnterpriseID'][p[0]]\n info2 = personDict['EnterpriseID'][p[1]]\n print (\"Person A:\",info1)\n print (\"Person B:\",info2)","def getData(self):\r\n return personData(\r\n self.title.getVal(),\r\n self.first.getVal(),\r\n self.middle.getVal(),\r\n self.last.getVal(),\r\n self.suffix.getVal(),\r\n self.phone.getVal(),\r\n self.ext.getVal(),\r\n self.email.getVal(),\r\n self.affiliation.getVal())","def get_user_info_by_name(self, username: str) -> dict:","def info() -> Dict[str, Any]:","def get_persons(self):\n response = self.do_request('/misc/user/export/json')\n if response:\n return response.json()","def current_person(self):\n d = self.people_table_data[self.row_i]\n\n # \"fullname\", \"lunaid\", \"age\", \"dob\", \"sex\", \"lastvisit\", \"maxdrop\", \"studies\",\n info = dict(zip(self.person_columns, d))\n info[\"pid\"] = d[8] # pid not shown\n\n # dont get fname and lname from table\n # could word split, but need to be accurate at least for edit module\n if self.sql:\n res = self.sql.query.get_name(pid=info[\"pid\"])\n info[\"fname\"] = res[0][0]\n info[\"lname\"] = res[0][1]\n return info\n # # main model\n # self.checkin_button.setEnabled(False)\n # print('people table: subject selected: %s' % d[8])\n # self.render_person(pid=d[8], fullname=d[0], age=d[2],\n # sex=d[4], lunaid=d[1])\n # self.render_schedule(ScheduleFrom.PERSON)","def get_dictionary(self):\n data = {\n \"user_first_name\": self.user.first_name,\n \"user_last_name\": self.user.last_name,\n }\n dct = provider.Provider.get_dictionary(self)\n dct.update(data)\n return dct","def _build_person_data(request):\n if hasattr(request, 'rollbar_person'):\n rollbar_person_prop = request.rollbar_person\n person = rollbar_person_prop() if callable(rollbar_person_prop) else rollbar_person_prop\n if person and isinstance(person, dict):\n return person\n else:\n return None\n\n if StarletteRequest:\n from rollbar.contrib.starlette.requests import hasuser\n else:\n def hasuser(request): return True\n\n if hasuser(request) and hasattr(request, 'user'):\n user_prop = request.user\n user = user_prop() if callable(user_prop) else user_prop\n if not user:\n return None\n elif isinstance(user, dict):\n return user\n else:\n retval = {}\n if getattr(user, 'id', None):\n retval['id'] = str(user.id)\n elif getattr(user, 'user_id', None):\n retval['id'] = str(user.user_id)\n\n # id is required, so only include username/email if we have an id\n if retval.get('id'):\n username = getattr(user, 'username', None)\n email = getattr(user, 'email', None)\n retval.update({\n 'username': username,\n 'email': email\n })\n return retval\n\n if hasattr(request, 'user_id'):\n user_id_prop = request.user_id\n user_id = user_id_prop() if callable(user_id_prop) else user_id_prop\n if not user_id:\n return None\n return {'id': str(user_id)}","def get_info(self) -> Optional[Dict[str, Any]]:","def find(self, person):\n page = self.find_page(person)\n try:\n entity_id = self.get_entity_id(page.title)\n entity = self.get_entity(entity_id)\n person.dob = self.get_birthday(entity)\n person.occupation = self.get_occupation(entity)\n person.nationality = self.get_country_of_citizenship(entity)\n res_domicile = self.get_domicile(entity)\n if res_domicile:\n person.domicile = res_domicile\n elif person.nationality == self.get_birthcountry(entity):\n person.domicile = person.nationality # this is an assumption!\n birth_name = self.get_birth_name(entity)\n person.middle_name = self.get_middle_name(birth_name, person)\n if page:\n person.is_famous = 'True'\n else:\n person.is_famous = ''\n person.net_worth = self.get_networth(entity)\n person.description = page.summary\n person.set_raw()\n except:\n pass","def to_dict(self) -> dict:\n return {\n 'author_id': self.id,\n 'fullname': self.fullname\n }","def all_persons(self):\n all_persons = {}\n all_persons.update(self.staff)\n all_persons.update(self.fellows)\n return all_persons","def get_personal_info(self):\n self.get(\"INFO\",\"GetPersonalInfo\")\n response = self.send()\n return response","def get_person(self, requestId):\n return self.get_json('/verification/%s/person' % str(requestId))","def get_persons(self):\n response = self.do_request('/management/persons/export/json/')\n if response:\n return response.json()","def info(self) -> dict:","def fetch_extra_data(resource):\n person_id = resource.get(\"cern_person_id\")\n return dict(person_id=person_id)","def get_people(self):\n url = self.base_url + 'memberships'\n\n req = requests.get(headers=self.headers, url=url)\n\n return req.json()","def get_donor_info(self):\n name = self.get_donor()\n if name in self.all_donors:\n person = self.r.hgetall(name)\n print(f\"Person: {name}\")\n for key, value in person.items():\n print(f\"{key}: {value}\")\n else:\n print(\"Name not in database.\")","def _to_dict(self):\n\t\treturn {'id': self.id,\n\t\t\t\t'name': self.name,\n\t\t\t\t'surname': self.surname}","def get_info_dict(self):\n return {\n 'bidi': self.bidi,\n 'code': self.code,\n 'name': self.name,\n 'name_local': self.name_local\n }","def describe(self):\n return {\n 'id': self.id,\n 'name': self.name,\n 'age': calculate_current_age(self.birth_date),\n 'gender': self.gender,\n 'filmography': [appearance.movies.title for appearance in\n Appearance.query.filter(Appearance.actor_id == self.id).all()]\n }","def info():\n if g.party_id is None:\n # No party is configured for the current site.\n abort(404)\n\n party = party_service.get_party(g.party_id)\n\n return {\n 'party': party,\n }","def get_contact_info(self):\n outputDict = {\"USERNAME\": consts.USERNAME,\n \"IP\": consts.IPADDRESS, \n \"MACHINE\": consts.HOSTNAME, \n \"EMAIL\": 'ckenne24@student.scad.edu', \n \"PHONE\": '203-722-6620'} # ::: TO DO::: dynamically get phone and email info automatically\n return outputDict","def get_user_info_by_id(self, user_id: int) -> dict:","def info():\n # -------- Task 1 -------------------------\n # Please complete the following information\n\n return {\"agent name\": \"?\", # COMPLETE HERE\n \"student name\": [\"?\"], # COMPLETE HERE\n \"student number\": [\"?\"]} # COMPLETE HERE","def get_details_for_email(email):\n try:\n result = dict(clearbit.Enrichment.find(email=email, stream=True))\n except HTTPError as e:\n logging.info('Skipping clearbit.com services. REASON %s', str(e))\n\n return {}\n\n return {\n 'first_name': result.get('person', {}).get('name', {}).get('givenName') or '',\n 'last_name': result.get('person', {}).get('name', {}).get('familyName') or '',\n 'gender': result.get('person', {}).get('gender') or '',\n 'bio': result.get('person', {}).get('bio') or ''\n }","def select_person():\r\n body = request.get_json()\r\n\r\n try:\r\n SELECT_PERSON_SCHEMA.validate(body)\r\n except SchemaError as err:\r\n raise ServiceBodyError(str(err))\r\n\r\n with sqlite_client:\r\n message = get_person(sqlite_client, body.get('id'))\r\n\r\n return jsonify({'name': message[0][1], 'cpf': message[0][2]})","def to_cff_person(person: pybtex.database.Person) -> dict:\n # Map BibTeX to CFF fields\n name_fields = {\n \"last\": \"family-names\",\n \"bibtex_first\": \"given-names\",\n \"prelast\": \"name-particle\",\n \"lineage\": \"name-suffix\",\n }\n result = {\n cff_field: \" \".join(person.get_part(bibtex_field))\n for bibtex_field, cff_field in name_fields.items()\n if person.get_part(bibtex_field)\n }\n # Use CFF \"entity\" format if BibTex has no first & last names\n if list(result.keys()) == [\"family-names\"]:\n return {\"name\": result[\"family-names\"]}\n return result","def person(self, person_id):\r\n return persons.Person(self, person_id)","def person_object_factory():\n person = {\n 'lastName': rl_fake().last_name(),\n 'gender': random.choice(('M', 'F'))\n }\n\n # Make the person's name match their gender.\n person['firstName'] = rl_fake().first_name_male() if person['gender'] == 'M' else rl_fake().first_name_female()\n\n # These are all optional in the DB. Over time, we'll try all possibilities.\n if flip():\n person['birthday'] = rl_fake().date_of_birth(minimum_age=18).strftime('%Y-%m-%d')\n if flip():\n person['phone'] = rl_fake().phone_number()\n if flip():\n person['email'] = rl_fake().email()\n return person","def get_author_info(self, author: str):\n for writer_word in self._writer_words:\n data = json.loads(requests.get(WIKIDATA_SEARCH + \"&srsearch=\" + author + \" \" + writer_word).text)\n pages = data.get(\"query\").get(\"search\")\n if len(pages) >= 1:\n pageid = pages[0].get(\"title\")\n author_details = self._reference.author_map.get(author)\n if author_details:\n return author_details\n if pageid == -1:\n continue\n\n else:\n response = requests.get(WIKIDATA_PARSE + pageid + \".json\")\n data = json.loads(response.text)\n if author.lower() not in data.get(\"entities\").get(pageid).get(\"labels\").get(\"en\").get(\"value\").lower():\n continue\n else:\n try:\n id = data.get(\"entities\").get(pageid).get(\"claims\").get(\"P31\")[0].get(\"mainsnak\").get(\"datavalue\").get(\"value\").get(\"id\")\n if str(id) != \"Q5\": # the id for human\n continue\n except IndexError:\n continue\n properties = data.get(\"entities\").get(pageid).get(\"claims\")\n author_details = {\"id\": pageid, \"gender\": self.get_gender(properties)}\n country_details = self.get_country(properties)\n author_details[\"country\"] = country_details\n self._reference.author_map[author] = author_details\n return author_details\n return {\"id\": \"Unknown\", \"gender\": \"Unknown\", \"country\": [{\"name\": \"Unknown\", \"region\": \"Unknown\"}]}","def build_person(first_name, last_name, age=''):\r\n person = {'first':first_name, 'last':last_name}\r\n if age:\r\n person['age'] = age\r\n return person","def __getstate__(self):\n\n # Get data in long format\n long = self.long_format()\n return {\"date\": self.date,\n \"persons\": long\n }","def get_persons():\n resp = requests.get(API_URL).content\n persons = json.loads(resp)\n return persons","def get_info(self):\n return {}","def _to_dict(self):\n\t\tauthor = Author.query.get(self.authors_id)\n\t\treturn {'id': self.id,\n\t\t\t\t'name': self.name,\n\t\t\t\t'author_id': self.authors_id,\n\t\t\t\t'author_name': author.name,\n\t\t\t\t'author_surname': author.surname}","def build_person(first_name, last_name, middle_name='', age=None): \n person = {'first': first_name, 'middle': middle_name, 'last': last_name}\n if age:\n person['age'] = age\n return person","def dictify(self):\n return {\n \"name\" : self.name,\n \"lastname\" : self.lastname,\n \"phone\" : self.phone,\n \"email\" : self.email\n }","def get_person(request):\n\n email = request.args.get(\"email\", None, str)\n # log_info(\"email is \" + email)\n\n if not email:\n log_info(\"get_person was called, but no email was provided in request\")\n return None\n\n if validators.email(email) and (email_requester := auth.check_teacher(request)):\n if email_requester and validators.email(email_requester):\n db = database.Database()\n student = db.get_student(email)\n return dict(student)\n\n elif validators.email(email) and (email_requester := auth.check_login(request)):\n if email_requester and validators.email(email_requester) and email == email_requester:\n db = database.Database()\n student = db.get_student(email)\n if 'notes' in student:\n del student['notes']\n\n return dict(student)\n\n log_info(\"No person with email \" + email + \" found in database\")\n return None","def person_fields(self):\r\n return persons.PersonFields(self)","def read_person(person_id):\n try:\n conn = sqlite3.connect(settings.database_name)\n conn.row_factory = sqlite3.Row\n c = conn.cursor()\n c.execute(\"PRAGMA foreign_keys = ON\")\n c.execute(\"SELECT * FROM person WHERE personid =?\", (person_id,))\n _person = None\n for row in c:\n _person = Person()\n _person.person_id = row[\"personid\"]\n _person.first_name = row[\"firstname\"]\n _person.last_name = row[\"lastname\"]\n _person.middle_initial = row[\"middleinitial\"]\n _person.nick_name = row[\"nickname\"]\n _person.date_of_birth = row[\"dateofbirth\"]\n _person.date_of_death = row[\"dateofdeath\"]\n conn.close()\n return _person\n except:\n return None","def infos(self):\r\n\t\tname = name\r\n\t\tlast_name = last_name","def build_person(first_name,last_name, age =''):\n person = { 'first': first_name.title(), 'last' : last_name.title()}\n if age:\n person['age'] = age\n return person","def parse_person(person):\n parsed = person_parser(person)\n if not parsed:\n parsed = person_parser_only_name(person)\n name = parsed.group('name')\n email = None\n else:\n name = parsed.group('name')\n email = parsed.group('email')\n\n return name, email","def who():\n cleanup()\n return {'available': userlist(), 'eta': data['etas'], 'etd': data['etds'], 'lastlocation': data['lastlocation'], 'ceitloch': ceitloch(), 'reminder': data['reminder']}","def details(self):\n details = ProfileDetailsParser(self.details_string())\n\n return dict(\n follows=details.follows(),\n favorites=details.favorites(),\n rating=details.rating(),\n language=details.language(),\n genres=details.genres(),\n characters=details.characters(),\n )","def get_person(self, user_id):\n endpoint = '/user/{}'.format(user_id)\n return self.get_request(endpoint)","def extract_user_info(user):\r\n return {\r\n 'username': user.username,\r\n 'email': user.email,\r\n 'first_name': user.first_name,\r\n 'last_name': user.last_name,\r\n }","def extract_user_info(user):\r\n return {\r\n 'username': user.username,\r\n 'email': user.email,\r\n 'first_name': user.first_name,\r\n 'last_name': user.last_name,\r\n }","def get_user_details(self, response):\n name = response.get(\"name\")\n return {\n \"username\": str(response.get(\"account_id\")),\n \"email\": response.get(\"email\"),\n \"fullname\": name.get(\"display_name\"),\n \"first_name\": name.get(\"given_name\"),\n \"last_name\": name.get(\"surname\"),\n }","def get_author_info_from_people_collection(info):\n # TODO: probably we will need to extract this somewhere else\n URL = ('https://cds.cern.ch/submit/get_authors?'\n 'query={0}&relative_curdir=cdslabs%2Fvideos')\n if '0' in info or not info.get('a'):\n # There is already enough information or we don't have a name to query\n return info\n author_name = info.get('a')\n if PY2:\n # In Python 3, encoded name will change type to bytes and this will\n # cause query to CDS to fail\n author_name = author_name.encode('utf-8')\n author_info = _get_http_request(url=URL.format(author_name), retry=10)\n if not author_info or len(author_info) > 1:\n # Didn't find anything or find to many matches\n return info\n\n # Prepare author name\n author_info = author_info[0]\n if 'name' not in author_info:\n author_info['name'] = '{0}, {1}'.format(author_info['lastname'],\n author_info['firstname'])\n return MementoDict([\n (k, v) for k, v in chain(info.items(), iteritems(author_info))])","def seat_profile(first_name, last_name, **passenger_info):\n\tprofile = {}\n\tprofile['first_name'] = first\n\tprofile['last_name'] = last\n\tfor key, value in passenger_info.items():\n\t\tprofile[key] = value\n\treturn profile","def to_dict(self):\n return {\n \"id\":self.id,\n \"username\":self.email,\n \"email\":self.email,\n \"firstname\":self.firstname,\n \"lastname\":self.lastname\n }","def to_dict(self):\n return {\n \"id\": self.id,\n \"first_name\": self.first_name,\n \"last_name\": self.last_name,\n \"company\": self.company,\n \"member_since\": self.member_since,\n \"email\": self.email,\n \"job_title\": self.job_title,\n \"website\": self.website,\n \"about\": self.about,\n \"profile_photo_path\": self.profile_photo_path,\n \"events\": self.events,\n \"saved_events\": self.saved_events,\n \"sponsorships\": self.sponsorships,\n \"role\": self.role\n }","def get_person_name(self, person_id):\n res = requests.get(url=\"https://api.ciscospark.com/v1/people/{}\".format(person_id),\n headers=self.headers)\n\n try:\n class person(object):\n firstName = res.json()['firstName']\n lastName = res.json()['lastName']\n\n return person\n except AttributeError as e:\n print(res.text)\n return None","def identify_user(picture: str) -> Optional[dict]:\n data = api.identify_person_api(picture)\n return data.json()","def to_dict(self):\n result = {\n \"id\": self.get_id(),\n \"name\": self.get_name(),\n \"email\": self.get_email(),\n \"google_id\": self.get_google_id(),\n \"creation_date\": self.get_creation_date(),\n \"last_updated\": self.get_last_updated(),\n \"berechtigung\": self.get_berechtigung(),\n \"student\": self.get_student(),\n }\n return result","def get_profile_info(self):\n\n drill_path = str(Path.home())+\"/Documents/ball_e_profiles/drill_profiles/{drill_name}/{drill_name}.csv\".format(\n drill_name=self.drill_name)\n with open(drill_path) as file:\n csv_reader = csv.reader(file, delimiter=',')\n row_count = 0\n info_dict = dict()\n for row in csv_reader:\n if row_count == 0:\n row_count += 1\n else:\n info_dict[row[0]] = [row[1], row[2], row[3]]\n row_count += 1\n\n return info_dict","def info(self):\n return f\"{self.get_first_name}, {self.get_last_name}. {self.get_age} y.o. #{self.get_id_number}\"","def _get_userinfo(self):\n if not hasattr(self, \"_userinfo\"):\n self._userinfo = {\n \"name\" : self.user_name,\n \"email\" : self.user_email\n }\n if self.user_id:\n u = self.user\n if u.email:\n self._userinfo[\"email\"] = u.email\n\n # If the user has a full name, use that for the user name.\n # However, a given user_name overrides the raw user.username,\n # so only use that if this review has no associated name.\n if u.get_full_name():\n self._userinfo[\"name\"] = self.user.get_full_name()\n elif not self.user_name:\n self._userinfo[\"name\"] = u.username\n return self._userinfo","def __repr__(self):\r\n return {'name':self.name, 'weight':self.organ_weight_grams, 'vital organ': self.vital_organ, 'organ system': self.organ_system}","def user_data(self, access_token, *args, **kwargs):\n fields_selectors = ','.join(set(['id', 'first-name', 'last-name'] +\n self.setting('FIELD_SELECTORS', [])))\n # use set() over fields_selectors since LinkedIn fails when values are\n # duplicated\n url = 'https://api.linkedin.com/v1/people/~:(%s)' % fields_selectors\n raw_xml = self.oauth_request(access_token, url).content\n try:\n return to_dict(ElementTree.fromstring(raw_xml))\n except (ExpatError, KeyError, IndexError):\n return None","def get_user_details(self, response):\n fullname, first_name, last_name = self.get_user_names(\n response.get(\"fullName\"),\n response.get(\"firstName\"),\n response.get(\"lastName\"),\n )\n return {\n \"username\": response.get(\"username\"),\n \"email\": response.get(\"email\") or \"\",\n \"fullname\": fullname,\n \"first_name\": first_name,\n \"last_name\": last_name,\n }","def show_all_information(self):\n return self.__dict__\n # print(self.first_name)\n # print(self.last_name)\n # print(self.age)\n # print(self.name)\n # print(self.gender)\n # print(self.number_of_children)","def format_person(adj, dict):\n name = dict['name']\n net = int(dict['net_worth (USD)'])\n return \"The {0} person is {1}. They have a net worth of ${2:,}\".format(adj, name, net)","def seat_profile(first, last, **passenger_info):\n profile = {}\n profile['first_name'] = first\n profile['last_name'] = last\n for key, value in passenger_info.items():\n profile[key] = value\n return profile","def get_details(self):\n owner = self.fake.random_element(elements=self.owners)\n return {\n 'jurisdiction_property_id': self.fake.numerify(text='#####'),\n 'pm_parent_property_id': self.fake.numerify(text='#####'),\n 'lot_number': self.fake.numerify(text='#####'),\n 'address_line_1': self.address_line_1(),\n 'city': 'Boring',\n 'state': 'Oregon',\n 'postal_code': \"970{}\".format(self.fake.numerify(text='##')),\n 'year_built': self.fake.random_int(min=1880, max=2015),\n 'site_eui': self.fake.random_int(min=50, max=600),\n 'owner': owner.name,\n 'owner_email': owner.email,\n 'owner_telephone': owner.telephone,\n 'owner_address': owner.address,\n 'owner_city_state': owner.city_state,\n 'owner_postal_code': owner.postal_code,\n }","def user_dict(self):\n return {\n \"user_id\": self.user_id,\n \"firstname\": self.firstname,\n \"lastname\": self.lastname,\n \"othernames\": self.othernames,\n \"username\": self.username,\n \"email\": self.email,\n \"phonenumber\": self.phonenumber,\n \"is_admin\": self.is_admin,\n \"password\": self.password,\n \"registered_on\": self.registered_on\n }","def get_pers_trans(lang: Lang) -> dict:\n return read_json(f'languages/{lang}/persons')","def user_info(self):\n response = self.query('user_info')\n return response","def seat_profile(first, last, **passenger_info):\n\tprofile = {}\n\tprofile['first_name'] = first\n\tprofile['last_name'] = last\n\tfor key, value in passenger_info.items():\n\t\tprofile[key] = value\n\treturn profile","def serialize(self):\n return {\n \"first_name\" : self.first_name.capitalize(),\n \"last_name\" : self.last_name.capitalize(),\n \"name\" : self.first_name.capitalize() + ' ' + self.last_name.capitalize(),\n \"user_id\" : self.id,\n }","def person_name(self):\n return self._person_name","def serialize(self):\n return {\n 'name': self.name,\n 'year_of_birth': self.year_of_birth,\n 'location': self.location,\n 'telephone': self.telephone,\n 'primary_publisher': self.primary_publisher,\n }","def info(self):\n return {}","def get_patient_dict():\r\n return common.get_dict_all(get_patient_filename(), None)","def enumerate_person(hf=0.5, age=(18, 60), n=100):\n for i in range(n):\n hfi = random.random() <= hf\n agei = random.randint(*age)\n namei = first_names[hfi]\n yield dict(gender=(1 if hfi else 0), age=agei, name=namei, idc=uuid.uuid4())","def get_user_details(self, response):\n\n return {\n 'email': response.get('email'),\n 'id': response.get('id'),\n 'full_name': response.get('name')\n }","def get_details(self):\n owner = self.fake.random_element(elements=self.owners)\n return {\n 'jurisdiction_property_id': self.fake.numerify(text='#####'),\n 'pm_parent_property_id': self.fake.numerify(text='#####'),\n 'lot_number': self.fake.numerify(text='#####'),\n 'address_line_1': self.address_line_1(),\n 'city': 'Boring',\n 'state': 'Oregon',\n 'postal_code': \"970{}\".format(self.fake.numerify(text='##')),\n 'year_built': self.fake.random_int(min=1880, max=2015),\n 'site_eui': self.fake.random_int(min=50, max=600),\n 'gross_floor_area': self.fake.random_number(digits=6),\n 'owner': owner.name,\n 'owner_email': owner.email,\n 'owner_telephone': owner.telephone,\n 'owner_address': owner.address,\n 'owner_city_state': owner.city_state,\n 'owner_postal_code': owner.postal_code,\n }","def __str__(self):\n return \"Person: {}, {},{}\".format(self.get_id(),self.get_creation_date(),self.get_name())","def get_user_details(self, response):\n first_name, last_name = response['first-name'], response['last-name']\n email = response.get('email-address', '')\n return {'username': first_name + last_name,\n 'fullname': first_name + ' ' + last_name,\n 'first_name': first_name,\n 'last_name': last_name,\n 'email': email}","def userinfo(self, access_token: str) -> dict[str, Any]:\n data: dict[str, Any] = self.client.get(\n url=f\"{self.protocol}://{self.domain}/userinfo\",\n headers={\"Authorization\": f\"Bearer {access_token}\"},\n )\n return data","def get_person(request, person_id):\n person = get_object_or_404(Person, pk=person_id)\n\n\n return render_to_response('people/person_detail.html', {\n 'person': person,\n })","def persons(self):\r\n return persons.Persons(self)","def getInfo(self):\n request = self._connection.get('bookmarklet')\n userdata = self._userinfo_regex.search(request.text)\n if userdata is None: userdata = self._userinfo_regex_2.search(request.text)\n if userdata is None: raise errors.DiaspyError('cannot find user data')\n userdata = userdata.group(1)\n return json.loads(userdata)","def get_user_details(self, response):\n values = {\n 'username': unquote(response['nick']),\n 'email': unquote(response['email']),\n 'first_name': unquote(response['first_name']),\n 'last_name': unquote(response['last_name'])\n }\n\n if values['first_name'] and values['last_name']:\n values['fullname'] = '%s %s' % (values['first_name'],\n values['last_name'])\n return values","def _get_information(self):\n info_dict = {}\n table = self._tab.find('table', class_='details')\n for row in table.find_all('tr'):\n row_key, row_value = row.find(class_='key'), row.find(class_='value')\n key_with_emoji, value = self._get_key(row_key), self._get_value(row_value)\n split_key = key_with_emoji.split(\" \", 1)\n\n if len(split_key):\n key = split_key[-1]\n info_dict.update({key: value})\n\n return info_dict","def get_people(self):\n return self._people","def who_handler(self, data, suffix=''):\n # Just to show data coming in...\n assert data['requested'] == 'name'\n\n return {\n 'name': self.get_current_user_full_name(),\n 'email': self.get_current_user_emails()\n }","def __repr__(self):\n return f\"<Person {self.first_name.title()} {self.last_name.title()}>\"","def describe_user(self):\n print(self.first_name.title() + \" \" + self.last_name.title() +\n \" is a \" + str(self.age) + \" year old who identifies as \" +\n self.gender + \".\")"],"string":"[\n \"def get_person(self):\\n person_dict = {\\n 'firstname': self.__firstname,\\n 'lastname': self.__lastname,\\n 'height': self.__height,\\n 'weight': self.__weight,\\n 'age': self.__age\\n }\\n return person_dict\",\n \"def who_am_i():\\n return {'name': 'Jonathan Martinez', 'id': '201095569', 'email': 'martijon@post.bgu.ac.il'}\",\n \"def get_person(self, url: str) -> dict:\\n person = self.read_html(url)\\n\\n return {\\n # TODO: There's a better way of doing this.\\n self._columns[0]: person.select_one(\\\"h1\\\").text.strip(),\\n self._columns[1]: person.select_one(\\\".party-membership--party\\\").text,\\n self._columns[2]: \\\"; \\\".join(\\n [a.text for a in person.select('[href^=\\\"tel:\\\"]')]\\n ),\\n self._columns[3]: \\\"; \\\".join(\\n [a.text for a in person.select(\\\".email-address a\\\")]\\n ),\\n self._columns[4]: \\\"; \\\".join(\\n [a.text.strip() for a in person.select(\\\".contact-actions__twitter\\\")]\\n ),\\n }\",\n \"def parse_person(person):\\n person_name = person['name']\\n person_id = person['id']\\n\\n pages = get_pages_from_wiki_search(person_name)\\n page = select_page_like_person(pages, person)\\n\\n wiki_person = {\\n 'id': person_id, 'fullname': person_name,\\n 'url': page.get('fullurl', None), \\n 'declarator_profile': page.get('declarator_profile', None),\\n 'words_intersection': page.get('words_intersection', None),\\n }\\n\\n # if page with image\\n if 'pageimage' in page:\\n try:\\n image = page['pageimage']\\n url = page['original']['source']\\n license = get_license_from_wiki(image, is_file=True)\\n\\n photo = {'title': image, 'url': url, 'license': license}\\n wiki_person['photo'] = photo\\n except KeyError as e:\\n message = \\\"person_id: %i, Not found key: %s\\\" % (person_id, e)\\n Querylog.error(message)\\n return wiki_person\",\n \"def get_person(self, id):\\n try:\\n person = Person.get(Person.id == id)\\n data = model_to_dict(person)\\n except DoesNotExist:\\n response.status = 404\\n data = \\\"Not found\\\"\\n return dict(name='Person', data=data)\",\n \"def get_person_like_json(self):\\n return json.dumps(self.get_person())\",\n \"def display_person(person):\\n name = person['name']\\n followers = person['follower_count']\\n description = person['description']\\n country = person['country']\\n print(f'{name}, a(n) {description}, from {country}.')\\n return followers\",\n \"def showInfo(p,personDict):\\n info1 = personDict['EnterpriseID'][p[0]]\\n info2 = personDict['EnterpriseID'][p[1]]\\n print (\\\"Person A:\\\",info1)\\n print (\\\"Person B:\\\",info2)\",\n \"def getData(self):\\r\\n return personData(\\r\\n self.title.getVal(),\\r\\n self.first.getVal(),\\r\\n self.middle.getVal(),\\r\\n self.last.getVal(),\\r\\n self.suffix.getVal(),\\r\\n self.phone.getVal(),\\r\\n self.ext.getVal(),\\r\\n self.email.getVal(),\\r\\n self.affiliation.getVal())\",\n \"def get_user_info_by_name(self, username: str) -> dict:\",\n \"def info() -> Dict[str, Any]:\",\n \"def get_persons(self):\\n response = self.do_request('/misc/user/export/json')\\n if response:\\n return response.json()\",\n \"def current_person(self):\\n d = self.people_table_data[self.row_i]\\n\\n # \\\"fullname\\\", \\\"lunaid\\\", \\\"age\\\", \\\"dob\\\", \\\"sex\\\", \\\"lastvisit\\\", \\\"maxdrop\\\", \\\"studies\\\",\\n info = dict(zip(self.person_columns, d))\\n info[\\\"pid\\\"] = d[8] # pid not shown\\n\\n # dont get fname and lname from table\\n # could word split, but need to be accurate at least for edit module\\n if self.sql:\\n res = self.sql.query.get_name(pid=info[\\\"pid\\\"])\\n info[\\\"fname\\\"] = res[0][0]\\n info[\\\"lname\\\"] = res[0][1]\\n return info\\n # # main model\\n # self.checkin_button.setEnabled(False)\\n # print('people table: subject selected: %s' % d[8])\\n # self.render_person(pid=d[8], fullname=d[0], age=d[2],\\n # sex=d[4], lunaid=d[1])\\n # self.render_schedule(ScheduleFrom.PERSON)\",\n \"def get_dictionary(self):\\n data = {\\n \\\"user_first_name\\\": self.user.first_name,\\n \\\"user_last_name\\\": self.user.last_name,\\n }\\n dct = provider.Provider.get_dictionary(self)\\n dct.update(data)\\n return dct\",\n \"def _build_person_data(request):\\n if hasattr(request, 'rollbar_person'):\\n rollbar_person_prop = request.rollbar_person\\n person = rollbar_person_prop() if callable(rollbar_person_prop) else rollbar_person_prop\\n if person and isinstance(person, dict):\\n return person\\n else:\\n return None\\n\\n if StarletteRequest:\\n from rollbar.contrib.starlette.requests import hasuser\\n else:\\n def hasuser(request): return True\\n\\n if hasuser(request) and hasattr(request, 'user'):\\n user_prop = request.user\\n user = user_prop() if callable(user_prop) else user_prop\\n if not user:\\n return None\\n elif isinstance(user, dict):\\n return user\\n else:\\n retval = {}\\n if getattr(user, 'id', None):\\n retval['id'] = str(user.id)\\n elif getattr(user, 'user_id', None):\\n retval['id'] = str(user.user_id)\\n\\n # id is required, so only include username/email if we have an id\\n if retval.get('id'):\\n username = getattr(user, 'username', None)\\n email = getattr(user, 'email', None)\\n retval.update({\\n 'username': username,\\n 'email': email\\n })\\n return retval\\n\\n if hasattr(request, 'user_id'):\\n user_id_prop = request.user_id\\n user_id = user_id_prop() if callable(user_id_prop) else user_id_prop\\n if not user_id:\\n return None\\n return {'id': str(user_id)}\",\n \"def get_info(self) -> Optional[Dict[str, Any]]:\",\n \"def find(self, person):\\n page = self.find_page(person)\\n try:\\n entity_id = self.get_entity_id(page.title)\\n entity = self.get_entity(entity_id)\\n person.dob = self.get_birthday(entity)\\n person.occupation = self.get_occupation(entity)\\n person.nationality = self.get_country_of_citizenship(entity)\\n res_domicile = self.get_domicile(entity)\\n if res_domicile:\\n person.domicile = res_domicile\\n elif person.nationality == self.get_birthcountry(entity):\\n person.domicile = person.nationality # this is an assumption!\\n birth_name = self.get_birth_name(entity)\\n person.middle_name = self.get_middle_name(birth_name, person)\\n if page:\\n person.is_famous = 'True'\\n else:\\n person.is_famous = ''\\n person.net_worth = self.get_networth(entity)\\n person.description = page.summary\\n person.set_raw()\\n except:\\n pass\",\n \"def to_dict(self) -> dict:\\n return {\\n 'author_id': self.id,\\n 'fullname': self.fullname\\n }\",\n \"def all_persons(self):\\n all_persons = {}\\n all_persons.update(self.staff)\\n all_persons.update(self.fellows)\\n return all_persons\",\n \"def get_personal_info(self):\\n self.get(\\\"INFO\\\",\\\"GetPersonalInfo\\\")\\n response = self.send()\\n return response\",\n \"def get_person(self, requestId):\\n return self.get_json('/verification/%s/person' % str(requestId))\",\n \"def get_persons(self):\\n response = self.do_request('/management/persons/export/json/')\\n if response:\\n return response.json()\",\n \"def info(self) -> dict:\",\n \"def fetch_extra_data(resource):\\n person_id = resource.get(\\\"cern_person_id\\\")\\n return dict(person_id=person_id)\",\n \"def get_people(self):\\n url = self.base_url + 'memberships'\\n\\n req = requests.get(headers=self.headers, url=url)\\n\\n return req.json()\",\n \"def get_donor_info(self):\\n name = self.get_donor()\\n if name in self.all_donors:\\n person = self.r.hgetall(name)\\n print(f\\\"Person: {name}\\\")\\n for key, value in person.items():\\n print(f\\\"{key}: {value}\\\")\\n else:\\n print(\\\"Name not in database.\\\")\",\n \"def _to_dict(self):\\n\\t\\treturn {'id': self.id,\\n\\t\\t\\t\\t'name': self.name,\\n\\t\\t\\t\\t'surname': self.surname}\",\n \"def get_info_dict(self):\\n return {\\n 'bidi': self.bidi,\\n 'code': self.code,\\n 'name': self.name,\\n 'name_local': self.name_local\\n }\",\n \"def describe(self):\\n return {\\n 'id': self.id,\\n 'name': self.name,\\n 'age': calculate_current_age(self.birth_date),\\n 'gender': self.gender,\\n 'filmography': [appearance.movies.title for appearance in\\n Appearance.query.filter(Appearance.actor_id == self.id).all()]\\n }\",\n \"def info():\\n if g.party_id is None:\\n # No party is configured for the current site.\\n abort(404)\\n\\n party = party_service.get_party(g.party_id)\\n\\n return {\\n 'party': party,\\n }\",\n \"def get_contact_info(self):\\n outputDict = {\\\"USERNAME\\\": consts.USERNAME,\\n \\\"IP\\\": consts.IPADDRESS, \\n \\\"MACHINE\\\": consts.HOSTNAME, \\n \\\"EMAIL\\\": 'ckenne24@student.scad.edu', \\n \\\"PHONE\\\": '203-722-6620'} # ::: TO DO::: dynamically get phone and email info automatically\\n return outputDict\",\n \"def get_user_info_by_id(self, user_id: int) -> dict:\",\n \"def info():\\n # -------- Task 1 -------------------------\\n # Please complete the following information\\n\\n return {\\\"agent name\\\": \\\"?\\\", # COMPLETE HERE\\n \\\"student name\\\": [\\\"?\\\"], # COMPLETE HERE\\n \\\"student number\\\": [\\\"?\\\"]} # COMPLETE HERE\",\n \"def get_details_for_email(email):\\n try:\\n result = dict(clearbit.Enrichment.find(email=email, stream=True))\\n except HTTPError as e:\\n logging.info('Skipping clearbit.com services. REASON %s', str(e))\\n\\n return {}\\n\\n return {\\n 'first_name': result.get('person', {}).get('name', {}).get('givenName') or '',\\n 'last_name': result.get('person', {}).get('name', {}).get('familyName') or '',\\n 'gender': result.get('person', {}).get('gender') or '',\\n 'bio': result.get('person', {}).get('bio') or ''\\n }\",\n \"def select_person():\\r\\n body = request.get_json()\\r\\n\\r\\n try:\\r\\n SELECT_PERSON_SCHEMA.validate(body)\\r\\n except SchemaError as err:\\r\\n raise ServiceBodyError(str(err))\\r\\n\\r\\n with sqlite_client:\\r\\n message = get_person(sqlite_client, body.get('id'))\\r\\n\\r\\n return jsonify({'name': message[0][1], 'cpf': message[0][2]})\",\n \"def to_cff_person(person: pybtex.database.Person) -> dict:\\n # Map BibTeX to CFF fields\\n name_fields = {\\n \\\"last\\\": \\\"family-names\\\",\\n \\\"bibtex_first\\\": \\\"given-names\\\",\\n \\\"prelast\\\": \\\"name-particle\\\",\\n \\\"lineage\\\": \\\"name-suffix\\\",\\n }\\n result = {\\n cff_field: \\\" \\\".join(person.get_part(bibtex_field))\\n for bibtex_field, cff_field in name_fields.items()\\n if person.get_part(bibtex_field)\\n }\\n # Use CFF \\\"entity\\\" format if BibTex has no first & last names\\n if list(result.keys()) == [\\\"family-names\\\"]:\\n return {\\\"name\\\": result[\\\"family-names\\\"]}\\n return result\",\n \"def person(self, person_id):\\r\\n return persons.Person(self, person_id)\",\n \"def person_object_factory():\\n person = {\\n 'lastName': rl_fake().last_name(),\\n 'gender': random.choice(('M', 'F'))\\n }\\n\\n # Make the person's name match their gender.\\n person['firstName'] = rl_fake().first_name_male() if person['gender'] == 'M' else rl_fake().first_name_female()\\n\\n # These are all optional in the DB. Over time, we'll try all possibilities.\\n if flip():\\n person['birthday'] = rl_fake().date_of_birth(minimum_age=18).strftime('%Y-%m-%d')\\n if flip():\\n person['phone'] = rl_fake().phone_number()\\n if flip():\\n person['email'] = rl_fake().email()\\n return person\",\n \"def get_author_info(self, author: str):\\n for writer_word in self._writer_words:\\n data = json.loads(requests.get(WIKIDATA_SEARCH + \\\"&srsearch=\\\" + author + \\\" \\\" + writer_word).text)\\n pages = data.get(\\\"query\\\").get(\\\"search\\\")\\n if len(pages) >= 1:\\n pageid = pages[0].get(\\\"title\\\")\\n author_details = self._reference.author_map.get(author)\\n if author_details:\\n return author_details\\n if pageid == -1:\\n continue\\n\\n else:\\n response = requests.get(WIKIDATA_PARSE + pageid + \\\".json\\\")\\n data = json.loads(response.text)\\n if author.lower() not in data.get(\\\"entities\\\").get(pageid).get(\\\"labels\\\").get(\\\"en\\\").get(\\\"value\\\").lower():\\n continue\\n else:\\n try:\\n id = data.get(\\\"entities\\\").get(pageid).get(\\\"claims\\\").get(\\\"P31\\\")[0].get(\\\"mainsnak\\\").get(\\\"datavalue\\\").get(\\\"value\\\").get(\\\"id\\\")\\n if str(id) != \\\"Q5\\\": # the id for human\\n continue\\n except IndexError:\\n continue\\n properties = data.get(\\\"entities\\\").get(pageid).get(\\\"claims\\\")\\n author_details = {\\\"id\\\": pageid, \\\"gender\\\": self.get_gender(properties)}\\n country_details = self.get_country(properties)\\n author_details[\\\"country\\\"] = country_details\\n self._reference.author_map[author] = author_details\\n return author_details\\n return {\\\"id\\\": \\\"Unknown\\\", \\\"gender\\\": \\\"Unknown\\\", \\\"country\\\": [{\\\"name\\\": \\\"Unknown\\\", \\\"region\\\": \\\"Unknown\\\"}]}\",\n \"def build_person(first_name, last_name, age=''):\\r\\n person = {'first':first_name, 'last':last_name}\\r\\n if age:\\r\\n person['age'] = age\\r\\n return person\",\n \"def __getstate__(self):\\n\\n # Get data in long format\\n long = self.long_format()\\n return {\\\"date\\\": self.date,\\n \\\"persons\\\": long\\n }\",\n \"def get_persons():\\n resp = requests.get(API_URL).content\\n persons = json.loads(resp)\\n return persons\",\n \"def get_info(self):\\n return {}\",\n \"def _to_dict(self):\\n\\t\\tauthor = Author.query.get(self.authors_id)\\n\\t\\treturn {'id': self.id,\\n\\t\\t\\t\\t'name': self.name,\\n\\t\\t\\t\\t'author_id': self.authors_id,\\n\\t\\t\\t\\t'author_name': author.name,\\n\\t\\t\\t\\t'author_surname': author.surname}\",\n \"def build_person(first_name, last_name, middle_name='', age=None): \\n person = {'first': first_name, 'middle': middle_name, 'last': last_name}\\n if age:\\n person['age'] = age\\n return person\",\n \"def dictify(self):\\n return {\\n \\\"name\\\" : self.name,\\n \\\"lastname\\\" : self.lastname,\\n \\\"phone\\\" : self.phone,\\n \\\"email\\\" : self.email\\n }\",\n \"def get_person(request):\\n\\n email = request.args.get(\\\"email\\\", None, str)\\n # log_info(\\\"email is \\\" + email)\\n\\n if not email:\\n log_info(\\\"get_person was called, but no email was provided in request\\\")\\n return None\\n\\n if validators.email(email) and (email_requester := auth.check_teacher(request)):\\n if email_requester and validators.email(email_requester):\\n db = database.Database()\\n student = db.get_student(email)\\n return dict(student)\\n\\n elif validators.email(email) and (email_requester := auth.check_login(request)):\\n if email_requester and validators.email(email_requester) and email == email_requester:\\n db = database.Database()\\n student = db.get_student(email)\\n if 'notes' in student:\\n del student['notes']\\n\\n return dict(student)\\n\\n log_info(\\\"No person with email \\\" + email + \\\" found in database\\\")\\n return None\",\n \"def person_fields(self):\\r\\n return persons.PersonFields(self)\",\n \"def read_person(person_id):\\n try:\\n conn = sqlite3.connect(settings.database_name)\\n conn.row_factory = sqlite3.Row\\n c = conn.cursor()\\n c.execute(\\\"PRAGMA foreign_keys = ON\\\")\\n c.execute(\\\"SELECT * FROM person WHERE personid =?\\\", (person_id,))\\n _person = None\\n for row in c:\\n _person = Person()\\n _person.person_id = row[\\\"personid\\\"]\\n _person.first_name = row[\\\"firstname\\\"]\\n _person.last_name = row[\\\"lastname\\\"]\\n _person.middle_initial = row[\\\"middleinitial\\\"]\\n _person.nick_name = row[\\\"nickname\\\"]\\n _person.date_of_birth = row[\\\"dateofbirth\\\"]\\n _person.date_of_death = row[\\\"dateofdeath\\\"]\\n conn.close()\\n return _person\\n except:\\n return None\",\n \"def infos(self):\\r\\n\\t\\tname = name\\r\\n\\t\\tlast_name = last_name\",\n \"def build_person(first_name,last_name, age =''):\\n person = { 'first': first_name.title(), 'last' : last_name.title()}\\n if age:\\n person['age'] = age\\n return person\",\n \"def parse_person(person):\\n parsed = person_parser(person)\\n if not parsed:\\n parsed = person_parser_only_name(person)\\n name = parsed.group('name')\\n email = None\\n else:\\n name = parsed.group('name')\\n email = parsed.group('email')\\n\\n return name, email\",\n \"def who():\\n cleanup()\\n return {'available': userlist(), 'eta': data['etas'], 'etd': data['etds'], 'lastlocation': data['lastlocation'], 'ceitloch': ceitloch(), 'reminder': data['reminder']}\",\n \"def details(self):\\n details = ProfileDetailsParser(self.details_string())\\n\\n return dict(\\n follows=details.follows(),\\n favorites=details.favorites(),\\n rating=details.rating(),\\n language=details.language(),\\n genres=details.genres(),\\n characters=details.characters(),\\n )\",\n \"def get_person(self, user_id):\\n endpoint = '/user/{}'.format(user_id)\\n return self.get_request(endpoint)\",\n \"def extract_user_info(user):\\r\\n return {\\r\\n 'username': user.username,\\r\\n 'email': user.email,\\r\\n 'first_name': user.first_name,\\r\\n 'last_name': user.last_name,\\r\\n }\",\n \"def extract_user_info(user):\\r\\n return {\\r\\n 'username': user.username,\\r\\n 'email': user.email,\\r\\n 'first_name': user.first_name,\\r\\n 'last_name': user.last_name,\\r\\n }\",\n \"def get_user_details(self, response):\\n name = response.get(\\\"name\\\")\\n return {\\n \\\"username\\\": str(response.get(\\\"account_id\\\")),\\n \\\"email\\\": response.get(\\\"email\\\"),\\n \\\"fullname\\\": name.get(\\\"display_name\\\"),\\n \\\"first_name\\\": name.get(\\\"given_name\\\"),\\n \\\"last_name\\\": name.get(\\\"surname\\\"),\\n }\",\n \"def get_author_info_from_people_collection(info):\\n # TODO: probably we will need to extract this somewhere else\\n URL = ('https://cds.cern.ch/submit/get_authors?'\\n 'query={0}&relative_curdir=cdslabs%2Fvideos')\\n if '0' in info or not info.get('a'):\\n # There is already enough information or we don't have a name to query\\n return info\\n author_name = info.get('a')\\n if PY2:\\n # In Python 3, encoded name will change type to bytes and this will\\n # cause query to CDS to fail\\n author_name = author_name.encode('utf-8')\\n author_info = _get_http_request(url=URL.format(author_name), retry=10)\\n if not author_info or len(author_info) > 1:\\n # Didn't find anything or find to many matches\\n return info\\n\\n # Prepare author name\\n author_info = author_info[0]\\n if 'name' not in author_info:\\n author_info['name'] = '{0}, {1}'.format(author_info['lastname'],\\n author_info['firstname'])\\n return MementoDict([\\n (k, v) for k, v in chain(info.items(), iteritems(author_info))])\",\n \"def seat_profile(first_name, last_name, **passenger_info):\\n\\tprofile = {}\\n\\tprofile['first_name'] = first\\n\\tprofile['last_name'] = last\\n\\tfor key, value in passenger_info.items():\\n\\t\\tprofile[key] = value\\n\\treturn profile\",\n \"def to_dict(self):\\n return {\\n \\\"id\\\":self.id,\\n \\\"username\\\":self.email,\\n \\\"email\\\":self.email,\\n \\\"firstname\\\":self.firstname,\\n \\\"lastname\\\":self.lastname\\n }\",\n \"def to_dict(self):\\n return {\\n \\\"id\\\": self.id,\\n \\\"first_name\\\": self.first_name,\\n \\\"last_name\\\": self.last_name,\\n \\\"company\\\": self.company,\\n \\\"member_since\\\": self.member_since,\\n \\\"email\\\": self.email,\\n \\\"job_title\\\": self.job_title,\\n \\\"website\\\": self.website,\\n \\\"about\\\": self.about,\\n \\\"profile_photo_path\\\": self.profile_photo_path,\\n \\\"events\\\": self.events,\\n \\\"saved_events\\\": self.saved_events,\\n \\\"sponsorships\\\": self.sponsorships,\\n \\\"role\\\": self.role\\n }\",\n \"def get_person_name(self, person_id):\\n res = requests.get(url=\\\"https://api.ciscospark.com/v1/people/{}\\\".format(person_id),\\n headers=self.headers)\\n\\n try:\\n class person(object):\\n firstName = res.json()['firstName']\\n lastName = res.json()['lastName']\\n\\n return person\\n except AttributeError as e:\\n print(res.text)\\n return None\",\n \"def identify_user(picture: str) -> Optional[dict]:\\n data = api.identify_person_api(picture)\\n return data.json()\",\n \"def to_dict(self):\\n result = {\\n \\\"id\\\": self.get_id(),\\n \\\"name\\\": self.get_name(),\\n \\\"email\\\": self.get_email(),\\n \\\"google_id\\\": self.get_google_id(),\\n \\\"creation_date\\\": self.get_creation_date(),\\n \\\"last_updated\\\": self.get_last_updated(),\\n \\\"berechtigung\\\": self.get_berechtigung(),\\n \\\"student\\\": self.get_student(),\\n }\\n return result\",\n \"def get_profile_info(self):\\n\\n drill_path = str(Path.home())+\\\"/Documents/ball_e_profiles/drill_profiles/{drill_name}/{drill_name}.csv\\\".format(\\n drill_name=self.drill_name)\\n with open(drill_path) as file:\\n csv_reader = csv.reader(file, delimiter=',')\\n row_count = 0\\n info_dict = dict()\\n for row in csv_reader:\\n if row_count == 0:\\n row_count += 1\\n else:\\n info_dict[row[0]] = [row[1], row[2], row[3]]\\n row_count += 1\\n\\n return info_dict\",\n \"def info(self):\\n return f\\\"{self.get_first_name}, {self.get_last_name}. {self.get_age} y.o. #{self.get_id_number}\\\"\",\n \"def _get_userinfo(self):\\n if not hasattr(self, \\\"_userinfo\\\"):\\n self._userinfo = {\\n \\\"name\\\" : self.user_name,\\n \\\"email\\\" : self.user_email\\n }\\n if self.user_id:\\n u = self.user\\n if u.email:\\n self._userinfo[\\\"email\\\"] = u.email\\n\\n # If the user has a full name, use that for the user name.\\n # However, a given user_name overrides the raw user.username,\\n # so only use that if this review has no associated name.\\n if u.get_full_name():\\n self._userinfo[\\\"name\\\"] = self.user.get_full_name()\\n elif not self.user_name:\\n self._userinfo[\\\"name\\\"] = u.username\\n return self._userinfo\",\n \"def __repr__(self):\\r\\n return {'name':self.name, 'weight':self.organ_weight_grams, 'vital organ': self.vital_organ, 'organ system': self.organ_system}\",\n \"def user_data(self, access_token, *args, **kwargs):\\n fields_selectors = ','.join(set(['id', 'first-name', 'last-name'] +\\n self.setting('FIELD_SELECTORS', [])))\\n # use set() over fields_selectors since LinkedIn fails when values are\\n # duplicated\\n url = 'https://api.linkedin.com/v1/people/~:(%s)' % fields_selectors\\n raw_xml = self.oauth_request(access_token, url).content\\n try:\\n return to_dict(ElementTree.fromstring(raw_xml))\\n except (ExpatError, KeyError, IndexError):\\n return None\",\n \"def get_user_details(self, response):\\n fullname, first_name, last_name = self.get_user_names(\\n response.get(\\\"fullName\\\"),\\n response.get(\\\"firstName\\\"),\\n response.get(\\\"lastName\\\"),\\n )\\n return {\\n \\\"username\\\": response.get(\\\"username\\\"),\\n \\\"email\\\": response.get(\\\"email\\\") or \\\"\\\",\\n \\\"fullname\\\": fullname,\\n \\\"first_name\\\": first_name,\\n \\\"last_name\\\": last_name,\\n }\",\n \"def show_all_information(self):\\n return self.__dict__\\n # print(self.first_name)\\n # print(self.last_name)\\n # print(self.age)\\n # print(self.name)\\n # print(self.gender)\\n # print(self.number_of_children)\",\n \"def format_person(adj, dict):\\n name = dict['name']\\n net = int(dict['net_worth (USD)'])\\n return \\\"The {0} person is {1}. They have a net worth of ${2:,}\\\".format(adj, name, net)\",\n \"def seat_profile(first, last, **passenger_info):\\n profile = {}\\n profile['first_name'] = first\\n profile['last_name'] = last\\n for key, value in passenger_info.items():\\n profile[key] = value\\n return profile\",\n \"def get_details(self):\\n owner = self.fake.random_element(elements=self.owners)\\n return {\\n 'jurisdiction_property_id': self.fake.numerify(text='#####'),\\n 'pm_parent_property_id': self.fake.numerify(text='#####'),\\n 'lot_number': self.fake.numerify(text='#####'),\\n 'address_line_1': self.address_line_1(),\\n 'city': 'Boring',\\n 'state': 'Oregon',\\n 'postal_code': \\\"970{}\\\".format(self.fake.numerify(text='##')),\\n 'year_built': self.fake.random_int(min=1880, max=2015),\\n 'site_eui': self.fake.random_int(min=50, max=600),\\n 'owner': owner.name,\\n 'owner_email': owner.email,\\n 'owner_telephone': owner.telephone,\\n 'owner_address': owner.address,\\n 'owner_city_state': owner.city_state,\\n 'owner_postal_code': owner.postal_code,\\n }\",\n \"def user_dict(self):\\n return {\\n \\\"user_id\\\": self.user_id,\\n \\\"firstname\\\": self.firstname,\\n \\\"lastname\\\": self.lastname,\\n \\\"othernames\\\": self.othernames,\\n \\\"username\\\": self.username,\\n \\\"email\\\": self.email,\\n \\\"phonenumber\\\": self.phonenumber,\\n \\\"is_admin\\\": self.is_admin,\\n \\\"password\\\": self.password,\\n \\\"registered_on\\\": self.registered_on\\n }\",\n \"def get_pers_trans(lang: Lang) -> dict:\\n return read_json(f'languages/{lang}/persons')\",\n \"def user_info(self):\\n response = self.query('user_info')\\n return response\",\n \"def seat_profile(first, last, **passenger_info):\\n\\tprofile = {}\\n\\tprofile['first_name'] = first\\n\\tprofile['last_name'] = last\\n\\tfor key, value in passenger_info.items():\\n\\t\\tprofile[key] = value\\n\\treturn profile\",\n \"def serialize(self):\\n return {\\n \\\"first_name\\\" : self.first_name.capitalize(),\\n \\\"last_name\\\" : self.last_name.capitalize(),\\n \\\"name\\\" : self.first_name.capitalize() + ' ' + self.last_name.capitalize(),\\n \\\"user_id\\\" : self.id,\\n }\",\n \"def person_name(self):\\n return self._person_name\",\n \"def serialize(self):\\n return {\\n 'name': self.name,\\n 'year_of_birth': self.year_of_birth,\\n 'location': self.location,\\n 'telephone': self.telephone,\\n 'primary_publisher': self.primary_publisher,\\n }\",\n \"def info(self):\\n return {}\",\n \"def get_patient_dict():\\r\\n return common.get_dict_all(get_patient_filename(), None)\",\n \"def enumerate_person(hf=0.5, age=(18, 60), n=100):\\n for i in range(n):\\n hfi = random.random() <= hf\\n agei = random.randint(*age)\\n namei = first_names[hfi]\\n yield dict(gender=(1 if hfi else 0), age=agei, name=namei, idc=uuid.uuid4())\",\n \"def get_user_details(self, response):\\n\\n return {\\n 'email': response.get('email'),\\n 'id': response.get('id'),\\n 'full_name': response.get('name')\\n }\",\n \"def get_details(self):\\n owner = self.fake.random_element(elements=self.owners)\\n return {\\n 'jurisdiction_property_id': self.fake.numerify(text='#####'),\\n 'pm_parent_property_id': self.fake.numerify(text='#####'),\\n 'lot_number': self.fake.numerify(text='#####'),\\n 'address_line_1': self.address_line_1(),\\n 'city': 'Boring',\\n 'state': 'Oregon',\\n 'postal_code': \\\"970{}\\\".format(self.fake.numerify(text='##')),\\n 'year_built': self.fake.random_int(min=1880, max=2015),\\n 'site_eui': self.fake.random_int(min=50, max=600),\\n 'gross_floor_area': self.fake.random_number(digits=6),\\n 'owner': owner.name,\\n 'owner_email': owner.email,\\n 'owner_telephone': owner.telephone,\\n 'owner_address': owner.address,\\n 'owner_city_state': owner.city_state,\\n 'owner_postal_code': owner.postal_code,\\n }\",\n \"def __str__(self):\\n return \\\"Person: {}, {},{}\\\".format(self.get_id(),self.get_creation_date(),self.get_name())\",\n \"def get_user_details(self, response):\\n first_name, last_name = response['first-name'], response['last-name']\\n email = response.get('email-address', '')\\n return {'username': first_name + last_name,\\n 'fullname': first_name + ' ' + last_name,\\n 'first_name': first_name,\\n 'last_name': last_name,\\n 'email': email}\",\n \"def userinfo(self, access_token: str) -> dict[str, Any]:\\n data: dict[str, Any] = self.client.get(\\n url=f\\\"{self.protocol}://{self.domain}/userinfo\\\",\\n headers={\\\"Authorization\\\": f\\\"Bearer {access_token}\\\"},\\n )\\n return data\",\n \"def get_person(request, person_id):\\n person = get_object_or_404(Person, pk=person_id)\\n\\n\\n return render_to_response('people/person_detail.html', {\\n 'person': person,\\n })\",\n \"def persons(self):\\r\\n return persons.Persons(self)\",\n \"def getInfo(self):\\n request = self._connection.get('bookmarklet')\\n userdata = self._userinfo_regex.search(request.text)\\n if userdata is None: userdata = self._userinfo_regex_2.search(request.text)\\n if userdata is None: raise errors.DiaspyError('cannot find user data')\\n userdata = userdata.group(1)\\n return json.loads(userdata)\",\n \"def get_user_details(self, response):\\n values = {\\n 'username': unquote(response['nick']),\\n 'email': unquote(response['email']),\\n 'first_name': unquote(response['first_name']),\\n 'last_name': unquote(response['last_name'])\\n }\\n\\n if values['first_name'] and values['last_name']:\\n values['fullname'] = '%s %s' % (values['first_name'],\\n values['last_name'])\\n return values\",\n \"def _get_information(self):\\n info_dict = {}\\n table = self._tab.find('table', class_='details')\\n for row in table.find_all('tr'):\\n row_key, row_value = row.find(class_='key'), row.find(class_='value')\\n key_with_emoji, value = self._get_key(row_key), self._get_value(row_value)\\n split_key = key_with_emoji.split(\\\" \\\", 1)\\n\\n if len(split_key):\\n key = split_key[-1]\\n info_dict.update({key: value})\\n\\n return info_dict\",\n \"def get_people(self):\\n return self._people\",\n \"def who_handler(self, data, suffix=''):\\n # Just to show data coming in...\\n assert data['requested'] == 'name'\\n\\n return {\\n 'name': self.get_current_user_full_name(),\\n 'email': self.get_current_user_emails()\\n }\",\n \"def __repr__(self):\\n return f\\\"<Person {self.first_name.title()} {self.last_name.title()}>\\\"\",\n \"def describe_user(self):\\n print(self.first_name.title() + \\\" \\\" + self.last_name.title() +\\n \\\" is a \\\" + str(self.age) + \\\" year old who identifies as \\\" +\\n self.gender + \\\".\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78430605","0.69874537","0.68447304","0.67983556","0.6684294","0.6533277","0.64916706","0.6416313","0.64020026","0.63483405","0.63206047","0.62963533","0.6294688","0.6291786","0.6261915","0.6250636","0.62482584","0.62299424","0.62139595","0.61749566","0.6166419","0.6141492","0.6128635","0.61096424","0.61090773","0.60918844","0.60778916","0.6075775","0.6061554","0.6049044","0.60467345","0.6007558","0.59948546","0.59868145","0.59776676","0.59728974","0.5965312","0.59625274","0.5961576","0.5955198","0.59268564","0.5914678","0.59141594","0.59012234","0.5889845","0.5862512","0.5857002","0.5842631","0.5825038","0.5824619","0.58236694","0.5823201","0.5813905","0.581051","0.5804377","0.5804243","0.5804243","0.5793926","0.57915103","0.57892233","0.5787595","0.57847065","0.5779743","0.5774924","0.5755235","0.57475406","0.57376105","0.57331","0.5732158","0.5726344","0.57232374","0.5716009","0.57027775","0.5696364","0.56840235","0.5678872","0.5663425","0.5652523","0.56507766","0.56466895","0.56264484","0.5616449","0.5610548","0.56087047","0.5607547","0.56049436","0.5602947","0.55985063","0.5598037","0.55908924","0.55825245","0.55601716","0.55574024","0.55556625","0.55534","0.5550851","0.55495816","0.55462015","0.55394095"],"string":"[\n \"0.78430605\",\n \"0.69874537\",\n \"0.68447304\",\n \"0.67983556\",\n \"0.6684294\",\n \"0.6533277\",\n \"0.64916706\",\n \"0.6416313\",\n \"0.64020026\",\n \"0.63483405\",\n \"0.63206047\",\n \"0.62963533\",\n \"0.6294688\",\n \"0.6291786\",\n \"0.6261915\",\n \"0.6250636\",\n \"0.62482584\",\n \"0.62299424\",\n \"0.62139595\",\n \"0.61749566\",\n \"0.6166419\",\n \"0.6141492\",\n \"0.6128635\",\n \"0.61096424\",\n \"0.61090773\",\n \"0.60918844\",\n \"0.60778916\",\n \"0.6075775\",\n \"0.6061554\",\n \"0.6049044\",\n \"0.60467345\",\n \"0.6007558\",\n \"0.59948546\",\n \"0.59868145\",\n \"0.59776676\",\n \"0.59728974\",\n \"0.5965312\",\n \"0.59625274\",\n \"0.5961576\",\n \"0.5955198\",\n \"0.59268564\",\n \"0.5914678\",\n \"0.59141594\",\n \"0.59012234\",\n \"0.5889845\",\n \"0.5862512\",\n \"0.5857002\",\n \"0.5842631\",\n \"0.5825038\",\n \"0.5824619\",\n \"0.58236694\",\n \"0.5823201\",\n \"0.5813905\",\n \"0.581051\",\n \"0.5804377\",\n \"0.5804243\",\n \"0.5804243\",\n \"0.5793926\",\n \"0.57915103\",\n \"0.57892233\",\n \"0.5787595\",\n \"0.57847065\",\n \"0.5779743\",\n \"0.5774924\",\n \"0.5755235\",\n \"0.57475406\",\n \"0.57376105\",\n \"0.57331\",\n \"0.5732158\",\n \"0.5726344\",\n \"0.57232374\",\n \"0.5716009\",\n \"0.57027775\",\n \"0.5696364\",\n \"0.56840235\",\n \"0.5678872\",\n \"0.5663425\",\n \"0.5652523\",\n \"0.56507766\",\n \"0.56466895\",\n \"0.56264484\",\n \"0.5616449\",\n \"0.5610548\",\n \"0.56087047\",\n \"0.5607547\",\n \"0.56049436\",\n \"0.5602947\",\n \"0.55985063\",\n \"0.5598037\",\n \"0.55908924\",\n \"0.55825245\",\n \"0.55601716\",\n \"0.55574024\",\n \"0.55556625\",\n \"0.55534\",\n \"0.5550851\",\n \"0.55495816\",\n \"0.55462015\",\n \"0.55394095\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.58440995"},"document_rank":{"kind":"string","value":"48"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":22,"numItemsPerPage":100,"numTotalItems":95772,"offset":2200,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3MjY2MTc2OCwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3NzI2NjUzNjgsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.Y8tZxvgu60kxlvpNp3LGLDTYPgcD_SrlBNJFo6w64kBxgfdCy8gO2lbvNL91YiSbbG2nH-FqD0u4qQCCRUa_Bw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102 values |
|---|---|---|---|---|---|---|
Send the commmit notification to CIA. The message is created incrementally using lxml's "E" builder. | def notify(self, builder):
# Build the <files> section for the template...
commit = builder.commit
files = E.files()
commit_msg = commit.message.strip()
commit_msg = re.sub(r'[\x00-\x09\x0B-\x1f\x7f-\xff]', '', commit_msg)
for filename in commit.files_changed:
safe_filename = re.sub(r'[\x00-\x09\x0B-\x1f\x7f-\xff]', '', filename)
file_element = E.file(safe_filename)
files.append(file_element)
# Build the message
cia_message = self.MESSAGE()
cia_message.append(self._generator)
source = self.SOURCE(E.project("KDE"))
source.append(E.module(self.repository.path))
source.append(E.branch(self.repository.ref_name))
cia_message.append(source)
cia_message.append(self.TIMESTAMP(commit.date))
body = self.BODY()
commit_data = self.COMMIT()
commit_data.append(E.author(commit.author_name))
commit_data.append(E.revision(commit.description))
commit_data.append(files)
commit_data.append(E.log(commit_msg))
commit_data.append(E.url(commit.url))
body.append(commit_data)
cia_message.append(body)
# Convert to a string
commit_xml = etree.tostring(cia_message)
# Craft the email....
message = MIMEText( commit_xml, 'xml', 'utf-8' )
message['Subject'] = "DeliverXML"
message['From'] = "sysadmin@kde.org"
message['To'] = "commits@platna.kde.org"
# Send email...
self.smtp.sendmail("sysadmin@kde.org", ["commits@platna.kde.org"],
message.as_string()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def notify(guid, message):",
"def notify(self, id, command, data = None):\n print \"sending:\", id, command, data\n if command == Code.START: data = [id]\n try:\n msg = Message(command = command, data = data)\n self.contacts[id].send(msg.encode())\n except:\n ... | [
"0.5887094",
"0.5750634",
"0.57312334",
"0.57009876",
"0.5486229",
"0.54457545",
"0.5437605",
"0.53316367",
"0.5314361",
"0.52677506",
"0.52383125",
"0.5220476",
"0.52009946",
"0.5194496",
"0.5170836",
"0.51647365",
"0.51592344",
"0.51445454",
"0.5126826",
"0.5122613",
"0.511... | 0.5796216 | 1 |
Check for potential problems in a commit. | def check_commit_problems(self, commit, diff):
# Initialise
self._license_problem = False
self._commit_problem = False
self._commit_notes = defaultdict(list)
# Unsafe regex checks...
unsafe_matches = list()
unsafe_matches.append( r"\b(KRun::runCommand|K3?ShellProcess|setUseShell|setShellCommand)\b\s*[\(\r\n]" )
unsafe_matches.append( r"\b(system|popen|mktemp|mkstemp|tmpnam|gets|syslog|strptime)\b\s*[\(\r\n]" )
unsafe_matches.append( r"(scanf)\b\s*[\(\r\n]" )
valid_filename_regex = r"\.(cpp|cc|cxx|C|c\+\+|c|l|y||h|H|hh|hxx|hpp|h\+\+|qml)$"
# Retrieve the diff and do the problem checks...
filename = unicode("")
filediff = list()
for line in diff:
file_change = re.match( "^diff --(cc |git a\/.+ b\/)(.+)$", line )
if file_change:
# Are we changing file? If so, we have the full diff, so do a license check....
if filename != "" and commit.files_changed[ filename ]["change"] in ['A'] and re.search(valid_filename_regex, filename):
self.check_commit_license(filename, ''.join(filediff))
filediff = list()
filename = file_change.group(2)
continue
# Diff headers are bogus
if re.match("@@ -\d+,\d+ \+\d+ @@", line):
filediff = list()
continue
# Do an incremental check for *.desktop syntax errors....
if re.search("\.desktop$", filename) and re.search("[^=]+=.*[ \t]$", line) and line.startswith("+") and not re.match("^\+#", line):
self._commit_notes[filename].append( "[TRAILING SPACE] **" )
self._commit_problem = True
# Check for things which are unsafe...
for safety_match in unsafe_matches:
match = re.match(safety_match, line)
if match:
note = "[POSSIBLY UNSAFE: {0}] **".format( match.group(1) )
self._commit_notes[filename].append(note)
self._commit_problem = True
# Store the diff....
filediff.append(line)
if filename != "" and commit.files_changed[ filename ]["change"] in ['A'] and re.search(valid_filename_regex, filename):
self.check_commit_license(filename, ''.join(filediff)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def commit_check(ctx):\n result = ctx.run(f\"{VENV_PREFIX} cz check --rev-range master..\", warn=True)\n if result.exited == 3: # NO_COMMIT_FOUND\n exit(0)\n else:\n exit(result.exited)",
"def verify_git_clean(path):\n\n sys.stdout.write(\" - Checking for uncommitted changes:\")\n r... | [
"0.7050094",
"0.69747615",
"0.6810369",
"0.6753324",
"0.67024326",
"0.66566247",
"0.6637356",
"0.65921104",
"0.65602815",
"0.65418464",
"0.6462754",
"0.6436193",
"0.6383709",
"0.6378951",
"0.62852246",
"0.6269505",
"0.6268365",
"0.6259074",
"0.6205398",
"0.6135695",
"0.609353... | 0.800173 | 0 |
Returns index of the resource to use for making requests to get data if none of the resources are available, then send number of seconds until the resource is not available | def get_resource_index(self):
result = -1
max_sleep_time = self.time_window
with self._lock:
while result == -1:
for i in range(0, self.num_keys):
curr_sleep_time = max((self.timers[i][0] + self.time_window) - time.time(), 0)
max_sleep_time = min(max_sleep_time, curr_sleep_time)
if self.timers[i][1] >= self.window_limit and self.timers[i][0] + self.time_window < time.time():
self.timers[i][0] = 0
self.timers[i][1] = 0
if self.timers[i][1] < self.window_limit:
result = i
break
if result == -1: # case when all streams are rate limited
# logging.warning('sleeping for %d seconds.' % max_sleep_time)
# time.sleep(max_sleep_time)
return -1 * max_sleep_time
if self.timers[result][0] == 0:
self.timers[result][0] = time.time()
self.timers[result][1] += 1
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handle_get():\n for resource in resources:\n\n # acquire lock\n res_lock = resource.get(\"lock\")\n res_lock.acquire()\n\n # Get if available\n if resource.get(\"available\") == \"true\":\n # Available - acquire resource and return\n resource.update({... | [
"0.6093405",
"0.5707536",
"0.56445384",
"0.5552679",
"0.55315655",
"0.54823583",
"0.5422522",
"0.5402123",
"0.5400669",
"0.538704",
"0.5379008",
"0.5378094",
"0.53733474",
"0.535927",
"0.5357638",
"0.53508085",
"0.53386307",
"0.5338582",
"0.5338395",
"0.53344756",
"0.5322996"... | 0.67190135 | 0 |
Test Chronos GR Config plugin writes new config when config has changed | def test_chronos_gr_config_changed(self, mock_run_command, mock_safely_write):
# Create the plugin
plugin = ChronosGRConfigPlugin({})
# Set up the config strings to be tested
old_config_string = "Old Chronos GR config"
new_config_string = "New Chronos GR config"
# Call 'on_config_changed' with file.open mocked out
with mock.patch('clearwater_etcd_plugins.chronos.chronos_gr_config_plugin.open', \
mock.mock_open(read_data=old_config_string), create=True) as mock_open:
plugin.on_config_changed(new_config_string, None)
# Test assertions
mock_open.assert_called_once_with(plugin.file(), "r")
mock_safely_write.assert_called_once_with(plugin.file(), new_config_string)
mock_run_command.assert_called_once_with("/usr/share/clearwater/clearwater-queue-manager/scripts/modify_nodes_in_queue add apply_chronos_gr_config") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_config_update(get_config):\n cfg = get_config(Config, {'test': 'main'})\n update_from = {\"name\": \"new_name\"}\n cfg.update(update_from)\n\n assert cfg.data.get('name') == \"new_name\", \"config was not updated\"",
"def test_update_wait():\n wait = '10 seconds'\n config_info = read_c... | [
"0.72591335",
"0.72113305",
"0.71514034",
"0.7107235",
"0.7026826",
"0.69808435",
"0.69801",
"0.6910698",
"0.6887558",
"0.68464094",
"0.6824999",
"0.68176496",
"0.67969394",
"0.67067325",
"0.6699056",
"0.6610438",
"0.6609877",
"0.6593223",
"0.6569542",
"0.6516883",
"0.6515605... | 0.75435835 | 0 |
Returns 3d matrix of sizes [257,301,2] | def process(self, data):
spectr = stft(data, n_fft=512, hop_length=160)
return np.concatenate((spectr.real[:, :, np.newaxis], spectr.imag[:, :, np.newaxis]), axis=2) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def matrix_2d_to_3d(matrix: np.matrix) -> np.matrix:\n return np.matrix([\n [matrix.item(0, 0), matrix.item(0, 1), 0, matrix.item(0, 2)],\n [matrix.item(1, 0), matrix.item(1, 1), 0, matrix.item(1, 2)],\n [0, 0, 1, 0],\n [matrix.item(2, 0), matrix.item(... | [
"0.64607185",
"0.6292983",
"0.6173402",
"0.6133898",
"0.6117917",
"0.6092436",
"0.60344905",
"0.601531",
"0.6014885",
"0.60019165",
"0.5841986",
"0.58119726",
"0.5777618",
"0.5760934",
"0.57527536",
"0.57133275",
"0.5710595",
"0.56664544",
"0.56459385",
"0.5627127",
"0.559783... | 0.0 | -1 |
Finds the intersection of two lines given in Hesse normal form. Returns closest integer pixel locations. | def intersection(line1, line2):
rho1, theta1 = line1
rho2, theta2 = line2
A = np.array([
[np.cos(theta1), np.sin(theta1)],
[np.cos(theta2), np.sin(theta2)]
])
b = np.array([[rho1], [rho2]])
x0, y0 = np.linalg.solve(A, b)
x0, y0 = int(np.round(x0)), int(np.round(y0))
return [x0, y0] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getIntersection(line1, line2):\r\n\r\n rho1, theta1 = line1[0]\r\n rho2, theta2 = line2[0]\r\n\r\n a = np.array([\r\n [np.cos(theta1), np.sin(theta1)],\r\n [np.cos(theta2), np.sin(theta2)]\r\n ])\r\n\r\n b = np.array([[rho1], [rho2]])\r\n\r\n x, y = np.linalg.solve(a, b)\r\n\r\n... | [
"0.77867657",
"0.76443017",
"0.75186956",
"0.7482537",
"0.74320704",
"0.72984135",
"0.72857475",
"0.7276795",
"0.7244609",
"0.72418344",
"0.71921796",
"0.71198523",
"0.7066881",
"0.70585316",
"0.70348686",
"0.70186913",
"0.7002847",
"0.6971487",
"0.6970397",
"0.6936027",
"0.6... | 0.763136 | 2 |
Check correctness of `limiter` value returned. | def test_identify_limit(limit, all, expected):
assert identify_limit(limit, all) == expected | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _safe_limit_check(self):\n if self.rem == 40:\n self.time_start = time.time()\n elif time.time() - self.time_start >= 11:\n self.rem = 40\n self.time_start = time.time()\n elif self.rem <= 0:\n t = 11 - (time.time() - self.time_start)\n\n ... | [
"0.6411604",
"0.6216477",
"0.6159756",
"0.59867847",
"0.5980849",
"0.5841296",
"0.5840714",
"0.5840501",
"0.58299303",
"0.5824446",
"0.58074856",
"0.57916874",
"0.577796",
"0.5687688",
"0.5626272",
"0.5561189",
"0.5534629",
"0.55233294",
"0.5515274",
"0.55132216",
"0.5506859"... | 0.52793914 | 41 |
Check correctness of iterable returned. | def test_get_row_ids(issues, limiter, expected):
assert get_row_ids(issues, limiter) == expected | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _is_good_iterable(obj):\n return _is_iterable(obj) and _has_str_elems(obj)",
"def _check_iterable(self):\n if self.theoretical_size is None:\n raise TypeError(\"This `fixture_ref` has not yet been initialized, so it cannot be unpacked/iterated upon. \"\n \"This... | [
"0.7090814",
"0.7074417",
"0.69252294",
"0.6905731",
"0.6872017",
"0.6810469",
"0.68096995",
"0.68096995",
"0.68021095",
"0.66896445",
"0.6655056",
"0.65693426",
"0.65589577",
"0.65366095",
"0.6519211",
"0.65080535",
"0.6505808",
"0.6505808",
"0.6505169",
"0.647377",
"0.64608... | 0.0 | -1 |
Load the draft results. | def test_load_draft(league):
draft = league.draft_results()
assert(len(draft) == 144)
#mcdavid 1st
assert(draft[0]['player_key'] == '396.p.6743')
# carter hart 67th
assert(draft[66]['player_key'] == '396.p.7156')
# zadorov last
assert(draft[-1]['player_key'] == '396.p.5995') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_enriched_results(self):\n return super().load_results()",
"def load(self):\n self.results = pickle_load('results', self.main_dir)",
"def run(self):\n results = self.fetch()\n return results",
"def load_results_internal(self):\r\n filename = f\"{self.search_interna... | [
"0.6382324",
"0.6246874",
"0.5810889",
"0.5807111",
"0.57492447",
"0.56064266",
"0.5601259",
"0.55607885",
"0.54455495",
"0.5442246",
"0.5427821",
"0.5390353",
"0.53654075",
"0.5347294",
"0.53464603",
"0.53339255",
"0.53226596",
"0.53156066",
"0.5312531",
"0.5308264",
"0.5294... | 0.6256367 | 1 |
Return dataframe of all free agents. | def test_get_free_agents_season_start(league, season_start_date):
# equals all players minus drafted players
# make sure none of the draft players in list
free_agents = league.as_of(season_start_date).free_agents()
drafted = league.draft_results(format='Pandas')
assert(len(free_agents.index.intersection(drafted.index)) == 0), "Should be no drafted players as free agents"
# could make sure all 'all_players' that weren't drafted are here | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def getFreeAgentRoles(self, ctx):\n server = ctx.message.server\n server_dict = self.get_server_dict(ctx)\n free_agent_dict = server_dict.setdefault(\"Free agent roles\", {})\n\n if(len(free_agent_dict.items()) > 0):\n for key, value in free_agent_dict.items():\n ... | [
"0.5804655",
"0.5775972",
"0.56420845",
"0.55906963",
"0.54590887",
"0.54168296",
"0.5397101",
"0.5394799",
"0.5385905",
"0.5349997",
"0.5243113",
"0.5241917",
"0.5230085",
"0.5196623",
"0.5092877",
"0.5069075",
"0.5068402",
"0.50677747",
"0.5053582",
"0.5020693",
"0.5011909"... | 0.5439093 | 5 |
Return dataframe of all free agents. | def test_fantasy_status_nov_1(league):
nov_1 = datetime.datetime(2019,11,1)
players = league.as_of(nov_1).all_players()
# make sure sammy blais is not a free agent, he was picked up oct 31
assert(players.loc[6544, 'fantasy_status'] != 'FA') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def getFreeAgentRoles(self, ctx):\n server = ctx.message.server\n server_dict = self.get_server_dict(ctx)\n free_agent_dict = server_dict.setdefault(\"Free agent roles\", {})\n\n if(len(free_agent_dict.items()) > 0):\n for key, value in free_agent_dict.items():\n ... | [
"0.5804655",
"0.5775972",
"0.56420845",
"0.55906963",
"0.54590887",
"0.5439093",
"0.54168296",
"0.5397101",
"0.5394799",
"0.5385905",
"0.5349997",
"0.5243113",
"0.5241917",
"0.5230085",
"0.5196623",
"0.5092877",
"0.5069075",
"0.5068402",
"0.50677747",
"0.5053582",
"0.5020693"... | 0.0 | -1 |
Return player on waivers for given time. | def test_get_waivers(league):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def player(self):\n return self.players[self.tictactoe.turn]",
"def get_player(self,p):\n self._validate(p)\n return p.player()",
"async def get_player(self) -> Optional[andesite.Player]:\n ...",
"def get_player(self):\n return self.player",
"def get_player(self):\n ... | [
"0.6203599",
"0.61011946",
"0.59679496",
"0.59320474",
"0.59320474",
"0.5928937",
"0.5890586",
"0.5869932",
"0.5858092",
"0.58263284",
"0.5819567",
"0.5788687",
"0.57525885",
"0.573477",
"0.57151794",
"0.57138526",
"0.56666094",
"0.5606717",
"0.5583962",
"0.5573942",
"0.55579... | 0.0 | -1 |
Return team roster at given date. | def get_team_roster(league):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def roster(\n self, ctx: commands.Context, season: Optional[YearFinder] = None, *, search: HockeyTeams\n ) -> None:\n season_str = None\n season_url = \"\"\n if season:\n if season.group(3):\n if (int(season.group(3)) - int(season.group(1))) > 1:\n ... | [
"0.6794363",
"0.63804543",
"0.5813007",
"0.5741318",
"0.57277983",
"0.5647605",
"0.5467505",
"0.5346135",
"0.5336544",
"0.53275824",
"0.53005236",
"0.5272862",
"0.5261342",
"0.521931",
"0.5192084",
"0.514297",
"0.51121926",
"0.50987285",
"0.5097064",
"0.50702137",
"0.50670063... | 0.65519655 | 1 |
Detect which spins in each peak make up spin anchors. | def anchors(self):
dims = self.dims
anchors = []
for peak in self:
possible_anchors = []
for combination in combinations(range(dims), 2):
spins = [peak[i] for i in combination]
if any(s.res_num is None or s.atom is None for s in spins):
continue
res_nums = [spin.res_num for spin in spins]
atoms = [spin.atom for spin in spins]
elements = [atom[0] for atom in atoms]
positions = [atom[1:] for atom in atoms]
same_res_num = res_nums[0] == res_nums[1]
valid_pairs = [set(('H', 'N')), set(('H', 'C'))]
is_proton_heavy_pair = set(elements) in valid_pairs
same_position = all(c[0] == c[1] for c in zip(*positions))
if same_res_num and is_proton_heavy_pair and same_position:
if '' in positions and set(elements) != set(('H', 'N')):
# One of the atom names must have been 'H', 'N' or 'C'
# Of these, only the amide proton anchor is valid
continue
if elements[0] == 'H':
possible_anchors.append(combination)
else:
possible_anchors.append(combination[::-1])
if len(possible_anchors) > 1:
pa_sets = [set(pa) for pa in possible_anchors]
overlap = set.intersection(*pa_sets)
if overlap:
# Ambiguous, overlapping anchors
continue
for poss_anc in possible_anchors:
if poss_anc not in anchors:
anchors.append(poss_anc)
anchors = tuple(anchors)
return anchors | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def inPointing(self, pulsar):\n # initialise offset_deg to be a big old number\n # FWHM is in arcmin so always multiply by 60\n offset_deg = 5.\n\n # loop over pointings\n for point in self.pointingslist:\n # do a really basic check first\n\n glterm = (pulsa... | [
"0.595715",
"0.59206724",
"0.57927513",
"0.57917154",
"0.5787008",
"0.5730863",
"0.57080287",
"0.5705941",
"0.569645",
"0.5671896",
"0.56714284",
"0.5667955",
"0.5589922",
"0.55761975",
"0.55648017",
"0.5513475",
"0.55061954",
"0.5487037",
"0.547641",
"0.54698986",
"0.5455498... | 0.5789159 | 4 |
Calibrate the chemical shifts of each spin in the peak list. | def calibrate_peaklist(peaklist, calibration, attr='shift'):
if len(calibration) != peaklist.dims:
raise ValueError('incorrect calibration list length')
for peak in peaklist:
for spin, cal in zip(peak, calibration):
shift = getattr(spin, attr)
shift -= cal
setattr(spin, attr, shift)
return peaklist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def updatePeakShifts(peak):\n\n for peakDim in peak.peakDims:\n for contrib in peakDim.peakDimContribs:\n if contrib.peakDimComponent:\n continue\n updateResonShift(contrib.resonance,peakDim)",
"def apply_calibration(self, cal):\n\n n_edges = len(self.channels) + 1\n channel_ed... | [
"0.61754125",
"0.56453633",
"0.5504699",
"0.5399412",
"0.5393503",
"0.5272751",
"0.5264761",
"0.5158035",
"0.5157666",
"0.51486784",
"0.51470107",
"0.5123972",
"0.51041424",
"0.50907195",
"0.5079858",
"0.5070017",
"0.5054352",
"0.50522673",
"0.5047045",
"0.50407064",
"0.50199... | 0.6538406 | 0 |
Map each unique spin link to all of its corresponding peaks. NOESY peak lists represent spin links between Hydrogen atoms. Whether 2D, 3D or 4D, each peak in a NOESY peak list has exactly two Hydrogen spins. Here, a spin link is represented by a frozenset containing the spin.assignment tuples for each Hydrogen atom. This function returns a dictionary mapping each unique spin link to a list of the Peaks in the PeakList that contain those two Hydrogen atoms. Examples >>> spin_link_dict = peaklist.spin_link_dict() >>> spin_link, peaks = spin_link_dict.popitem() >>> spin_link frozenset([Assignment(res_type='Q', res_num=21, atom='HN'), Assignment( res_type='G', res_num=17, atom='HN')]) >>> print(peaks[0]) Peak(spins=[ Spin(res_type=G, res_num=17, atom=HN), Spin(res_type=G, res_num=17, atom=N), Spin(res_type=Q, res_num=21, atom=HN)]) >>> print(peaks[1]) Peak(spins=[ Spin(res_type=Q, res_num=21, atom=HN), Spin(res_type=Q, res_num=21, atom=N), Spin(res_type=G, res_num=17, atom=HN)]) Returns | def get_spin_link_dict(peaklist):
spin_link_dict = {}
for peak in peaklist:
spins = [spin for spin in peak
if spin.atom is not None and spin.atom[0] == 'H']
if len(spins) != 2:
err = ('expected 2 Hydrogens in each peak, '
'found %d' % len(spins))
raise ValueError(err)
link = frozenset(spin.assignment for spin in spins)
spin_link_dict.setdefault(link, []).append(peak)
return spin_link_dict | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mod_map(mods, plinkmap):\n modmap = {}\n for chrom in plinkmap:\n if chrom not in modmap:\n modmap[chrom] = []\n markers = plinkmap[chrom]\n modif = mods[chrom]\n for i, m in enumerate(modif):\n if m == 'I':\n p2 = float(markers[i+1][3])\n ... | [
"0.4860738",
"0.4834604",
"0.48159462",
"0.4767646",
"0.47199568",
"0.46659744",
"0.46064976",
"0.4587481",
"0.4538893",
"0.45380697",
"0.45124298",
"0.44684395",
"0.44490376",
"0.4414482",
"0.4384815",
"0.43777874",
"0.4372807",
"0.43616307",
"0.43376932",
"0.43176925",
"0.4... | 0.7973843 | 0 |
Sort peaks by the assignments of their constituent spins. Sort the peaks by the assignments of spins in particular dimensions. The default order sorts the peaks by the dimensions associated with spin anchors first then by the remaining dimensions in the order they appear in each peak. Optionally place all commented peaks at the end of the peak list. | def sort_by_assignments(peaklist, order=None, commented_at_end=False):
anchors = peaklist.anchors
anchored = tuple(i for anchor in anchors for i in anchor)
unanchored = set(range(peaklist.dims)) - set(anchored)
default_order = anchored + tuple(sorted(unanchored))
order = order if order is not None else default_order
peaklist.sort(key=lambda peak: tuple(peak[i] for i in order))
if commented_at_end:
peaklist.sort(key=lambda peak: peak.commented)
return peaklist | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _sort_cubelist(self, cubelist):\n sorted_cubelist = []\n realization_num = 1\n cubelist = cubelist.merge(unique=False)\n for cube in cubelist:\n # If time is a scalar coordinate, promote it to a dimension \n # coordinate, this is because all cubes must have the... | [
"0.5235512",
"0.51029795",
"0.5057203",
"0.50256133",
"0.4997207",
"0.49645668",
"0.49587327",
"0.49490315",
"0.4915132",
"0.4911893",
"0.48918042",
"0.4875538",
"0.4869072",
"0.48368287",
"0.4831977",
"0.48246452",
"0.48140344",
"0.47824505",
"0.47735858",
"0.4757741",
"0.47... | 0.73416525 | 0 |
Return an shellescaped version of the string using single quotes. Reliably quote a string which may contain unsafe characters (e.g. space, quote, or other special characters such as '$'). The returned value can be used in a shell command line as one token that gets to be interpreted literally. | def SingleQuote(s):
return pipes.quote(s) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def shlex_quote(s):\n if not s:\n return \"''\"\n # PKGW: builtin not available in Python 2\n ###if _find_unsafe(s) is None:\n ### return s\n\n # use single quotes, and put single quotes into double quotes\n # the string $'b is then quoted as '$'\"'\"'b'\n return \"'\" + s.replace(\"... | [
"0.7403372",
"0.74031615",
"0.71584487",
"0.71584487",
"0.7133629",
"0.71020097",
"0.7097107",
"0.7079384",
"0.6891607",
"0.683838",
"0.6683751",
"0.66462994",
"0.6627006",
"0.6565741",
"0.6501744",
"0.64522266",
"0.63975513",
"0.6358231",
"0.63522434",
"0.6346998",
"0.632059... | 0.7261007 | 2 |
Return an shellescaped version of the string using double quotes. Reliably quote a string which may contain unsafe characters (e.g. space or quote characters), while retaining some shell features such as variable interpolation. The returned value can be used in a shell command line as one token that gets to be further interpreted by the shell. The set of characters that retain their special meaning may depend on the | def DoubleQuote(s):
if not s:
return '""'
elif all(c in _SafeShellChars for c in s):
return s
else:
return '"' + s.replace('"', '\\"') + '"' | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def shlex_quote(s):\n if not s:\n return \"''\"\n if _find_unsafe(s) is None:\n return s\n\n # use single quotes, and put single quotes into double quotes\n # the string $'b is then quoted as '$'\"'\"'b'\n return \"'\" + s.replace(\"'\", \"'\\\"'\\\"'\") + \"'\"",
"def shlex_quote(s)... | [
"0.7271046",
"0.7253869",
"0.72336555",
"0.7229503",
"0.70458126",
"0.6944718",
"0.6929941",
"0.69232047",
"0.69232047",
"0.6779495",
"0.67524135",
"0.6597111",
"0.65538913",
"0.6536574",
"0.65330154",
"0.65087634",
"0.6507119",
"0.64975196",
"0.64822",
"0.646473",
"0.644913"... | 0.7298411 | 0 |
Constructs a shell snippet for a command using a variable to shrink it. Takes into account all quoting that needs to happen. | def ShrinkToSnippet(cmd_parts, var_name, var_value):
def shrink(value):
parts = (x and SingleQuote(x) for x in value.split(var_value))
with_substitutions = ('"$%s"' % var_name).join(parts)
return with_substitutions or "''"
return ' '.join(shrink(part) for part in cmd_parts) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def substshell(command, path=None, output=os.devnull, mode='w'):\n _compile = SubstCommandCompiler(path)\n _compile.init_command(command)\n return functools.partial(_compile, output, mode)",
"def make_shell_cmd(self, locals):\n\t\tdef cmd_shell():\n\t\t\timport code\n\t\t\tcode.interact(banner=self.shel... | [
"0.5757063",
"0.53830165",
"0.53762203",
"0.5325956",
"0.53113496",
"0.5278688",
"0.518739",
"0.5154804",
"0.51409817",
"0.5108147",
"0.50834435",
"0.50418144",
"0.5036694",
"0.49932173",
"0.49862692",
"0.4973778",
"0.49597052",
"0.49114555",
"0.49044985",
"0.4899245",
"0.489... | 0.7213392 | 0 |
Opens a subprocess to execute a program and returns its return value. | def RunCmd(args, cwd=None):
logger.debug(str(args) + ' ' + (cwd or ''))
return Call(args, cwd=cwd) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def runProgram(cmd):\n try:\n p=subprocess.Popen(cmd,shell=False,stdout=subprocess.PIPE,stderr=subprocess.PIPE)\n (stdout, stderr) = p.communicate()\n except Exception as e:\n print(\"Error running program because: {0}\".format(e), file=errorOutput)\n return None\n else:\n ... | [
"0.7069853",
"0.70137537",
"0.6977988",
"0.69574434",
"0.69218326",
"0.6837311",
"0.68356645",
"0.678155",
"0.6761188",
"0.6706355",
"0.6686737",
"0.66564906",
"0.6626361",
"0.66172713",
"0.65875185",
"0.65428317",
"0.6520404",
"0.6509777",
"0.6488528",
"0.6487521",
"0.648116... | 0.0 | -1 |
Open a subprocess to execute a program and returns its output. | def GetCmdOutput(args, cwd=None, shell=False, env=None):
(_, output) = GetCmdStatusAndOutput(args, cwd, shell, env)
return output | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_subprocess(command):\n if verbose:\n print \"Running \" + str(command)\n proc = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)\n output = proc.communicate()[0]\n if verbose:\n print \"Output: \" + output\n\n if proc.returncode != 0:\n raise C... | [
"0.73115253",
"0.7231892",
"0.7162937",
"0.7034998",
"0.69283974",
"0.6902304",
"0.6880463",
"0.68566847",
"0.67947245",
"0.6765262",
"0.6710852",
"0.66885346",
"0.66741914",
"0.6659031",
"0.66580534",
"0.6635002",
"0.66338694",
"0.6633255",
"0.65943277",
"0.6593683",
"0.6587... | 0.0 | -1 |
Executes a subprocess and returns its exit code and output. | def GetCmdStatusAndOutput(args,
cwd=None,
shell=False,
env=None,
merge_stderr=False):
status, stdout, stderr = GetCmdStatusOutputAndError(
args, cwd=cwd, shell=shell, env=env, merge_stderr=merge_stderr)
if stderr:
logger.critical('STDERR: %s', stderr)
logger.debug('STDOUT: %s%s', stdout[:4096].rstrip(),
'<truncated>' if len(stdout) > 4096 else '')
return (status, stdout) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def execute(cmd):\n\n process = subprocess.Popen(cmd,\n shell=True,\n stdin=subprocess.PIPE,\n stdout=subprocess.PIPE,\n stderr=subprocess.PIPE)\n out = ''\n err = ''\n exitcode = 0\n... | [
"0.75895786",
"0.7547545",
"0.7526934",
"0.7474151",
"0.7464935",
"0.73460895",
"0.72808135",
"0.723191",
"0.7178856",
"0.71782106",
"0.71392924",
"0.71354",
"0.7107621",
"0.70249635",
"0.6990342",
"0.6971521",
"0.6964739",
"0.69470686",
"0.6945275",
"0.69408506",
"0.69314843... | 0.0 | -1 |
Starts a subprocess and returns a handle to the process. | def StartCmd(args, cwd=None, shell=False, env=None):
_ValidateAndLogCommand(args, cwd, shell)
return Popen(
args,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=shell,
cwd=cwd,
env=env) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def start(self):\n self._proc = self._get_subprocess()\n self._pid = self._proc.pid\n self._return_code = None",
"def Start(self):\n\n\n\n assert not self._process, 'Start() can only be called once'\n self._process = subprocess.Popen(self._args)",
"def start_process():\n global co... | [
"0.76355433",
"0.7024509",
"0.6961524",
"0.6918989",
"0.6882473",
"0.68161005",
"0.68090093",
"0.6789304",
"0.6741872",
"0.6730431",
"0.66940457",
"0.66635656",
"0.6652612",
"0.66523474",
"0.66228956",
"0.64822423",
"0.642592",
"0.64208853",
"0.63632655",
"0.6342233",
"0.6317... | 0.68733007 | 5 |
Executes a subprocess and returns its exit code, output, and errors. | def GetCmdStatusOutputAndError(args,
cwd=None,
shell=False,
env=None,
merge_stderr=False):
_ValidateAndLogCommand(args, cwd, shell)
stderr = subprocess.STDOUT if merge_stderr else subprocess.PIPE
pipe = Popen(
args,
stdout=subprocess.PIPE,
stderr=stderr,
shell=shell,
cwd=cwd,
env=env)
stdout, stderr = pipe.communicate()
return (pipe.returncode, stdout, stderr) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_subprocess(command):\n if verbose:\n print \"Running \" + str(command)\n proc = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)\n output = proc.communicate()[0]\n if verbose:\n print \"Output: \" + output\n\n if proc.returncode != 0:\n raise C... | [
"0.7698771",
"0.76585543",
"0.7596537",
"0.75804675",
"0.75774103",
"0.75148445",
"0.7452843",
"0.73803294",
"0.72769535",
"0.72733176",
"0.7248266",
"0.723106",
"0.7226016",
"0.7157534",
"0.71220666",
"0.711173",
"0.7100731",
"0.707238",
"0.70716333",
"0.70658004",
"0.706432... | 0.65505224 | 77 |
An fcntlbased implementation of _IterProcessStdout. | def _IterProcessStdoutFcntl(process,
iter_timeout=None,
timeout=None,
buffer_size=4096,
poll_interval=1):
# pylint: disable=too-many-nested-blocks
import fcntl
try:
# Enable non-blocking reads from the child's stdout.
child_fd = process.stdout.fileno()
fl = fcntl.fcntl(child_fd, fcntl.F_GETFL)
fcntl.fcntl(child_fd, fcntl.F_SETFL, fl | os.O_NONBLOCK)
end_time = (time.time() + timeout) if timeout else None
iter_end_time = (time.time() + iter_timeout) if iter_timeout else None
while True:
if end_time and time.time() > end_time:
raise TimeoutError()
if iter_end_time and time.time() > iter_end_time:
yield None
iter_end_time = time.time() + iter_timeout
if iter_end_time:
iter_aware_poll_interval = min(poll_interval,
max(0, iter_end_time - time.time()))
else:
iter_aware_poll_interval = poll_interval
read_fds, _, _ = select.select([child_fd], [], [],
iter_aware_poll_interval)
if child_fd in read_fds:
data = _read_and_decode(child_fd, buffer_size)
if not data:
break
yield data
if process.poll() is not None:
# If process is closed, keep checking for output data (because of timing
# issues).
while True:
read_fds, _, _ = select.select([child_fd], [], [],
iter_aware_poll_interval)
if child_fd in read_fds:
data = _read_and_decode(child_fd, buffer_size)
if data:
yield data
continue
break
break
finally:
try:
if process.returncode is None:
# Make sure the process doesn't stick around if we fail with an
# exception.
process.kill()
except OSError:
pass
process.wait() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _stdout_reader(self):\n self._is_launched.wait()\n stdout_iterator = iter(self._popen.stdout.readline, b\"\")\n for line in stdout_iterator:\n self._log(\"raw\", \"stdout : {0}\".format(line.strip()))\n self.stdout_queue.put_nowait(line.strip())\n self.stdout_q... | [
"0.6449587",
"0.6135046",
"0.60871077",
"0.595699",
"0.594129",
"0.58840406",
"0.5684317",
"0.5682602",
"0.5677694",
"0.5666196",
"0.565126",
"0.55647177",
"0.5556993",
"0.55479926",
"0.54802346",
"0.5458966",
"0.5452489",
"0.54261523",
"0.5415573",
"0.539853",
"0.53972363",
... | 0.67283905 | 0 |
A Queue.Queuebased implementation of _IterProcessStdout. | def _IterProcessStdoutQueue(process,
iter_timeout=None,
timeout=None,
buffer_size=4096,
poll_interval=1):
# pylint: disable=unused-argument
if six.PY3:
import queue
else:
import Queue as queue
import threading
stdout_queue = queue.Queue()
def read_process_stdout():
# TODO(jbudorick): Pick an appropriate read size here.
while True:
try:
output_chunk = _read_and_decode(process.stdout.fileno(), buffer_size)
except IOError:
break
stdout_queue.put(output_chunk, True)
if not output_chunk and process.poll() is not None:
break
reader_thread = threading.Thread(target=read_process_stdout)
reader_thread.start()
end_time = (time.time() + timeout) if timeout else None
try:
while True:
if end_time and time.time() > end_time:
raise TimeoutError()
try:
s = stdout_queue.get(True, iter_timeout)
if not s:
break
yield s
except queue.Empty:
yield None
finally:
try:
if process.returncode is None:
# Make sure the process doesn't stick around if we fail with an
# exception.
process.kill()
except OSError:
pass
process.wait()
reader_thread.join() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _stdout_reader(self):\n self._is_launched.wait()\n stdout_iterator = iter(self._popen.stdout.readline, b\"\")\n for line in stdout_iterator:\n self._log(\"raw\", \"stdout : {0}\".format(line.strip()))\n self.stdout_queue.put_nowait(line.strip())\n self.stdout_q... | [
"0.7584206",
"0.74641174",
"0.68386096",
"0.6770728",
"0.6437304",
"0.63062155",
"0.6296086",
"0.62914383",
"0.6253849",
"0.62142974",
"0.62142974",
"0.62142974",
"0.62142974",
"0.62142974",
"0.62142974",
"0.61727333",
"0.61600655",
"0.61525756",
"0.61478114",
"0.6145392",
"0... | 0.7113257 | 2 |
Executes a subprocess with a timeout. | def GetCmdStatusAndOutputWithTimeout(args,
timeout,
cwd=None,
shell=False,
logfile=None,
env=None):
_ValidateAndLogCommand(args, cwd, shell)
output = six.StringIO()
process = Popen(
args,
cwd=cwd,
shell=shell,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
env=env)
try:
for data in _IterProcessStdout(process, timeout=timeout):
if logfile:
logfile.write(data)
output.write(data)
except TimeoutError:
raise TimeoutError(output.getvalue())
str_output = output.getvalue()
logger.debug('STDOUT+STDERR: %s%s', str_output[:4096].rstrip(),
'<truncated>' if len(str_output) > 4096 else '')
return process.returncode, str_output | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def call_timeout(args, **kwargs):\n\n timeout = kwargs.pop('timeout', 20)\n assert timeout > 0\n\n endtime = time.time() + timeout\n\n proc = subprocess.Popen(args, **kwargs)\n \n try:\n while time.time() < endtime:\n if proc.poll() != None:\n return proc.returnco... | [
"0.7861095",
"0.74641967",
"0.72873646",
"0.7224932",
"0.72131467",
"0.7131527",
"0.7093006",
"0.70907867",
"0.7079524",
"0.70083195",
"0.6727389",
"0.65759695",
"0.65237683",
"0.6510072",
"0.6489184",
"0.6449738",
"0.64226705",
"0.63744366",
"0.63308406",
"0.6277528",
"0.627... | 0.566922 | 57 |
Executes a subprocess and continuously yields lines from its output. | def IterCmdOutputLines(args,
iter_timeout=None,
timeout=None,
cwd=None,
shell=False,
env=None,
check_status=True):
cmd = _ValidateAndLogCommand(args, cwd, shell)
process = Popen(
args,
cwd=cwd,
shell=shell,
env=env,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
return _IterCmdOutputLines(
process,
cmd,
iter_timeout=iter_timeout,
timeout=timeout,
check_status=check_status) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_command(self):\n\n while True:\n current_line = self.process.stdout.readline().rstrip()\n\n if not current_line:\n break\n\n yield self.decode_output(current_line)",
"def runCommand(command):\n p = subprocess.Popen(command, std... | [
"0.74790484",
"0.7069593",
"0.69885415",
"0.6885744",
"0.6884901",
"0.68284523",
"0.6759169",
"0.67222494",
"0.65148145",
"0.64916754",
"0.63683236",
"0.63626593",
"0.6347323",
"0.62500584",
"0.6244789",
"0.6235298",
"0.6210111",
"0.62086326",
"0.6171837",
"0.61539686",
"0.61... | 0.6275099 | 13 |
Create an AutoEncoder object. | def __init__(self, n_inpt, n_hidden, hidden_transfer='identity',
out_transfer='identity', loss='squared', tied_weights=True,
batch_size=None,
optimizer='lbfgs', max_iter=1000, verbose=False):
super(AutoEncoder, self).__init__(
n_inpt, n_hidden, hidden_transfer, out_transfer, loss, tied_weights)
self.batch_size = batch_size
self.optimizer = optimizer
self.f_transform = None
self.f_reconstruct = None
self.parameters.data[:] = np.random.standard_normal(
self.parameters.data.shape).astype(theano.config.floatX)
self.max_iter = max_iter
self.verbose = verbose | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _define_encoder(self):\n raise NotImplementedError",
"def build_autoencoder(input_dim):\r\n input_layer = Input(shape=(input_dim, 1))\r\n enc = Conv1D(filters=16, kernel_size=2, padding='same', activation='relu')(input_layer)\r\n enc = MaxPooling1D(pool_size=2, padding='same')(enc)\r\n enc = C... | [
"0.62622386",
"0.6247434",
"0.62234795",
"0.6113021",
"0.59711206",
"0.59430516",
"0.5825264",
"0.5779037",
"0.56837624",
"0.56632996",
"0.56139284",
"0.5593676",
"0.5560463",
"0.55399996",
"0.55361104",
"0.5501795",
"0.54680336",
"0.54680336",
"0.5461032",
"0.54492253",
"0.5... | 0.5244221 | 29 |
Create a SparseAutoEncoder object. | def __init__(self, n_inpt, n_hidden, hidden_transfer='sigmoid',
out_transfer='identity', reconstruct_loss='squared',
c_sparsity=1, sparsity_loss='bern_bern_kl',
sparsity_target=0.01,
tied_weights=True, batch_size=None,
optimizer='lbfgs', max_iter=1000, verbose=False):
super(SparseAutoEncoder, self).__init__(
n_inpt, n_hidden, hidden_transfer, out_transfer,
reconstruct_loss, c_sparsity, sparsity_loss, sparsity_target,
tied_weights)
self.batch_size = batch_size
self.optimizer = optimizer
self.f_transform = None
self.f_reconstruct = None
self.parameters.data[:] = np.random.standard_normal(
self.parameters.data.shape).astype(theano.config.floatX)
self.max_iter = max_iter
self.verbose = verbose | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_sparseDB():\n datas = data.Kmercount_to_matrix()\n datas.run()\n print('***Sparse matrix created***')",
"def make_sparse(data):\n assert data.train_pos_edge_index is not None\n\n (row, col), N = data.train_pos_edge_index, data.num_nodes\n perm = (col * N + row).argsort()\n row, co... | [
"0.63621956",
"0.62124324",
"0.60858965",
"0.59326434",
"0.5876335",
"0.5779511",
"0.576974",
"0.5758959",
"0.5684206",
"0.56325567",
"0.56308913",
"0.5587562",
"0.55547976",
"0.5466962",
"0.5456364",
"0.52503127",
"0.5241987",
"0.5203801",
"0.5184267",
"0.51695746",
"0.51491... | 0.63101643 | 1 |
Create a ContractiveAutoEncoder object. | def __init__(self, n_inpt, n_hidden, hidden_transfer='sigmoid',
out_transfer='identity', reconstruct_loss='squared',
c_jacobian=1, tied_weights=True, batch_size=None,
optimizer='lbfgs', max_iter=1000, verbose=False):
super(ContractiveAutoEncoder, self).__init__(
n_inpt, n_hidden, hidden_transfer, out_transfer,
reconstruct_loss, c_jacobian,
tied_weights)
self.batch_size = batch_size
self.optimizer = optimizer
self.f_transform = None
self.f_reconstruct = None
self.parameters.data[:] = np.random.standard_normal(
self.parameters.data.shape).astype(theano.config.floatX)
self.max_iter = max_iter
self.verbose = verbose | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _construct_ae(self):\n if self.joint_train:\n self.critic.trainable = False\n autoencoder = Model(self.encoder.input,\n [self.decoder(self.encoder.output),\n self.critic(self.encoder.output)])\n autoencoder.c... | [
"0.59766114",
"0.5971633",
"0.58636886",
"0.57971674",
"0.565155",
"0.5615126",
"0.54221565",
"0.53008664",
"0.52868307",
"0.5247722",
"0.524635",
"0.52189344",
"0.52125883",
"0.51889825",
"0.51658624",
"0.51599807",
"0.5148567",
"0.5141506",
"0.51331234",
"0.511349",
"0.5087... | 0.5832884 | 3 |
Create a DenoisingAutoEncoder object. | def __init__(self, n_inpt, n_hidden, hidden_transfer='sigmoid',
out_transfer='identity', reconstruct_loss='squared',
noise_type='gauss', c_noise=.2,
tied_weights=True, batch_size=None,
optimizer='lbfgs', max_iter=1000, verbose=False):
super(DenoisingAutoEncoder, self).__init__(
n_inpt, n_hidden, hidden_transfer, out_transfer,
reconstruct_loss, noise_type, c_noise,
tied_weights)
self.batch_size = batch_size
self.optimizer = optimizer
self.f_transform = None
self.f_reconstruct = None
climin.initialize.randomize_normal(self.parameters.data)
self.max_iter = max_iter
self.verbose = verbose | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _define_encoder(self):\n raise NotImplementedError",
"def build_autoencoder(input_dim):\r\n input_layer = Input(shape=(input_dim, 1))\r\n enc = Conv1D(filters=16, kernel_size=2, padding='same', activation='relu')(input_layer)\r\n enc = MaxPooling1D(pool_size=2, padding='same')(enc)\r\n enc = C... | [
"0.6016746",
"0.55889976",
"0.545366",
"0.54502213",
"0.5415948",
"0.54003376",
"0.54001844",
"0.53689516",
"0.534991",
"0.5316329",
"0.5203007",
"0.51553774",
"0.5107471",
"0.5106341",
"0.5100852",
"0.50989753",
"0.5094069",
"0.5073897",
"0.50694823",
"0.5016635",
"0.5007310... | 0.6117516 | 0 |
restrict to the content's language | def test_languages(self, client):
root = Node.root()
en = Type1(title="Hello World", state="published",
node=root, language="en").save()
nl = Type1(title="Hoi Wereld", state="published",
node=root, language="nl").save()
enspoke = en.spoke()
feed = WheelFeed(enspoke)
assert en.content_ptr in feed.items()
assert nl.content_ptr not in feed.items() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_forced(self, lang):\r\n return False",
"def process_request(self, request):\n\n if request.COOKIES.get('site_language'):\n if request.COOKIES['site_language'] == '':\n language = 'fr'\n else:\n language = request.COOKIES['site_language']\n ... | [
"0.6518715",
"0.6337609",
"0.62430346",
"0.61772054",
"0.6115925",
"0.6033609",
"0.60031694",
"0.60027224",
"0.59728533",
"0.59191805",
"0.5822976",
"0.5796649",
"0.5761532",
"0.5755782",
"0.5725612",
"0.57049775",
"0.5696995",
"0.56784564",
"0.56742376",
"0.5659563",
"0.5643... | 0.52251047 | 81 |
Eliminate duplicates in a sorted list. Returns a new sorted list with the same elements in list1, but with no duplicates. This function can be iterative. | def remove_duplicates(list1):
tample = [float('inf')]
for elem in list1:
if elem in tample:
continue
tample.append(elem)
return tample[1:] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove_duplicates(list1):\n temp_list = []\n\n # for each element in list1 check if is already in the temp list\n # if it is not yet there, copy it.\n for item in list1:\n if item not in temp_list:\n temp_list.append(item)\n\n return temp_list",
"def remove_duplicates(list1):... | [
"0.82367706",
"0.8172117",
"0.8020477",
"0.7850647",
"0.76956123",
"0.76429844",
"0.7602725",
"0.750563",
"0.74992764",
"0.742413",
"0.73368996",
"0.7323583",
"0.7320335",
"0.7309752",
"0.7279414",
"0.7272679",
"0.72361135",
"0.72262025",
"0.721125",
"0.718744",
"0.7170773",
... | 0.8031551 | 2 |
Compute the intersection of two sorted lists. Returns a new sorted list containing only elements that are in both list1 and list2. This function can be iterative. | def intersect(list1, list2):
intersection_list = []
list1_idx = 0
list2_idx = 0
while list2_idx < len(list2) and list1_idx < len(list1):
if list2[list2_idx] == list1[list1_idx]:
intersection_list.append(list2[list2_idx])
list1_idx += 1
list2_idx += 1
elif list2[list2_idx] > list1[list1_idx]:
list1_idx += 1
else:
list2_idx += 1
return intersection_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def intersection(list1, list2):\n list3 = [value for value in list1 if value in list2]\n return list3",
"def intersect(list1, list2):\r\n if len(list1) == 0 or len(list2) == 0:\r\n return []\r\n else:\r\n if list1[0] == list2[0]:\r\n new_list = list([list1[0]])\r\n ... | [
"0.81946236",
"0.8157978",
"0.8081259",
"0.802535",
"0.79895693",
"0.7963669",
"0.79506075",
"0.7948855",
"0.7923734",
"0.7879321",
"0.7839831",
"0.7740573",
"0.76637924",
"0.76356244",
"0.76244",
"0.75989366",
"0.7588414",
"0.75148344",
"0.75115436",
"0.74970204",
"0.7495804... | 0.8113677 | 2 |
Merge two sorted lists. Returns a new sorted list containing those elements that are in either list1 or list2. This function can be iterative. | def merge(list1, list2):
res = []
index_i, index_j = 0, 0
while index_i < len(list1) and index_j < len(list2):
if list1[index_i] <= list2[index_j]:
res.append(list1[index_i])
index_i += 1
else:
res.append(list2[index_j])
index_j += 1
res += list1[index_i:]
res += list2[index_j:]
return res | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def merge_lists(list_1, list_2):\n if len(list_1) == 0:\n return list_2\n if len(list_2) == 0:\n return list_1\n\n new_list = []\n length = len(list_1) + len(list_2)\n while len(new_list) < length:\n if len(list_1) == 0:\n new_list = new_list + list_2\n elif le... | [
"0.81090695",
"0.80801195",
"0.8072913",
"0.80316395",
"0.8031528",
"0.8013592",
"0.8011788",
"0.7974852",
"0.795297",
"0.7931757",
"0.7878907",
"0.7860104",
"0.7858302",
"0.78444135",
"0.78015894",
"0.7787144",
"0.7747671",
"0.7741996",
"0.7730882",
"0.76854265",
"0.76350236... | 0.7963335 | 8 |
Sort the elements of list1. Return a new sorted list with the same elements as list1. This function should be recursive. | def merge_sort(list1):
if len(list1) <= 1:
return list1
left = merge_sort(list1[:len(list1)/2])
right = merge_sort(list1[len(list1)/2:])
return merge(left, right) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def merge_sort(in_list1: list) -> list:\n if in_list1 is None:\n return []\n if len(in_list1) == 1:\n return [in_list1[0]]\n _list1,_list2= in_list1[:int(((len(in_list1)+1)/2))],\\\n in_list1[int(((len(in_list1)+1)/2)):]\n _ordered_list1 = merge_sort(_list1)\n _o... | [
"0.76767325",
"0.732384",
"0.7290804",
"0.7187142",
"0.7152374",
"0.71103555",
"0.7107798",
"0.7064439",
"0.6912521",
"0.6830091",
"0.6827197",
"0.67525494",
"0.66716707",
"0.6565023",
"0.6531662",
"0.6518769",
"0.65044874",
"0.64856726",
"0.6469198",
"0.6412194",
"0.6409195"... | 0.70278823 | 8 |
Generate all strings that can be composed from the letters in word in any order. Returns a list of all strings that can be formed from the letters in word. This function should be recursive. | def gen_all_strings(word):
if word == '':
return ['']
else:
first = word[0]
rest = word[1:]
rest_strings = gen_all_strings(rest)
all_words = []
for string in rest_strings:
for leter in range(len(string)+1):
all_words.append(string[0:leter]+first+string[leter:])
return rest_strings + all_words | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gen_all_strings(word):\n if not word:\n return [\"\"]\n \n all_strings = []\n for string in gen_all_strings(word[1:]):\n for letter_idx in range(len(string) + 1):\n all_strings.append(string[letter_idx:] + word[0] + string[:letter_idx])\n \n return gen_all_strings(wor... | [
"0.8034503",
"0.7417961",
"0.7359351",
"0.7112968",
"0.7106626",
"0.68921024",
"0.6748245",
"0.6620748",
"0.64630806",
"0.63716835",
"0.6366732",
"0.6345676",
"0.63174015",
"0.6314541",
"0.62938344",
"0.6261687",
"0.62095034",
"0.6180001",
"0.61566484",
"0.61404824",
"0.61245... | 0.7376517 | 2 |
Load word list from the file named filename. Returns a list of strings. | def load_words(filename):
url = codeskulptor.file2url(filename)
netfile = urllib2.urlopen(
"http://codeskulptor-assets.commondatastorage.googleapis.com/assets_scrabble_words3.txt")
words_file = netfile.readlines()
words = [word[:-2] for word in words_file]
return words | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_wordlist(filename):\n with open(filename) as f:\n \tdata = f.read().splitlines()\n return data",
"def loadWords():\n inFile = open(wordFile, 'r')\n wordlist = []\n for line in inFile:\n wordlist.append(line)\n return wordlist",
"def loadWords():\n # inFile: file\n inF... | [
"0.8982847",
"0.85380477",
"0.85197324",
"0.84018725",
"0.8372622",
"0.8360392",
"0.8360392",
"0.8360392",
"0.83501935",
"0.83436346",
"0.83436346",
"0.8328561",
"0.8309319",
"0.82969534",
"0.82897973",
"0.82897973",
"0.8267962",
"0.8260606",
"0.8249803",
"0.8249803",
"0.8249... | 0.812224 | 43 |
Fixture for setting up configuration parser | def setup_config():
config = configparser.ConfigParser()
config.read(CONFIG_PATH)
return config | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setUp(self):\n self.parser = create_parser()",
"def setup(self):\n file_under_test = os.path.join(os.curdir, 'application-core',\n 'app.core.config.xml')\n with open(file_under_test) as f:\n config = f.read()\n self.config = objecti... | [
"0.70605105",
"0.7017709",
"0.7011017",
"0.692149",
"0.692149",
"0.690285",
"0.68758297",
"0.68144774",
"0.6782708",
"0.6702887",
"0.66660374",
"0.6653196",
"0.66530657",
"0.6643987",
"0.6641886",
"0.6610034",
"0.6574361",
"0.65678746",
"0.6562894",
"0.6540612",
"0.6537637",
... | 0.7371306 | 0 |
Fixture for retrieving mock event | def get_mock_event():
event = {
"httpMethod": "GET",
"//body": "{\"name\": \"Sam\"}",
"resource": "/{proxy+}",
"queryStringParameters": {},
"pathParameters": {
"proxy": "users"
},
"requestContext": {
"accountId": "222222222",
"identity": {
"sourceIp": "2a02:a445:6d36:1:1e3:a188:313c:1d31",
"userAgent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_1_6) "
"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2743.116 Safari/537.36",
},
"resourcePath": "/{proxy+}",
"httpMethod": "GET",
"apiId": "xxxxxxxxxx"
}
}
return event | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def event_factory_fixture():\n def _factory(device_id, event_type=\"DEVICE_EVENT\", capability='',\n attribute='Updated', value='Value', data=None):\n event = Mock()\n event.event_type = event_type\n event.device_id = device_id\n event.component_id = 'main'\n e... | [
"0.74541396",
"0.724666",
"0.72374237",
"0.71662945",
"0.7073701",
"0.7027783",
"0.68203604",
"0.68195695",
"0.680202",
"0.6784378",
"0.6762648",
"0.67611665",
"0.66722715",
"0.66431737",
"0.6619424",
"0.65345937",
"0.65251654",
"0.65242076",
"0.65172464",
"0.6512973",
"0.650... | 0.74155563 | 1 |
Unit test get_ip_type_by_address method of the Bad Bots class | def test_get_ip_type_by_address(setup_config, get_mock_event):
# !ARRANGE!
bad_bots = BadBots(setup_config, get_mock_event)
ipv4_address_1 = '1.1.1.1'
ipv4_address_2 = '11.22.33.44'
ipv4_address_3 = '123.123.123.123'
ipv6_address_1 = '2a02:a445:6d36:1:1e3:a188:313c:1d31'
ipv6_address_2 = '3731:54:65fe:2::a7'
ipv6_address_3 = 'fd07:a47c:3742:823e:3b02:76:982b:463'
# !ACT!
# Detect the IP type of provided IP addresses
ipv4_address_1_type = bad_bots.get_ip_type_by_address(ipv4_address_1)
ipv4_address_2_type = bad_bots.get_ip_type_by_address(ipv4_address_2)
ipv4_address_3_type = bad_bots.get_ip_type_by_address(ipv4_address_3)
ipv6_address_1_type = bad_bots.get_ip_type_by_address(ipv6_address_1)
ipv6_address_2_type = bad_bots.get_ip_type_by_address(ipv6_address_2)
ipv6_address_3_type = bad_bots.get_ip_type_by_address(ipv6_address_3)
# !ASSERT!
# Assert IP addresses are of type IPv4
assert ipv4_address_1_type.value == BadBots.SourceIPType.IPV4.value
assert ipv4_address_2_type.value == BadBots.SourceIPType.IPV4.value
assert ipv4_address_3_type.value == BadBots.SourceIPType.IPV4.value
# Assert IP addresses are of type IPv6
assert ipv6_address_1_type.value == BadBots.SourceIPType.IPV6.value
assert ipv6_address_2_type.value == BadBots.SourceIPType.IPV6.value
assert ipv6_address_3_type.value == BadBots.SourceIPType.IPV6.value | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_ip_addresses_exists():\n load_ips()\n validate_names()",
"def test_external_ip_get_kind(self):\n assert_equal(self.test_external_ip.get_kind(), 'mpexternalip')",
"def test_ipam_ip_addresses_read(self):\n pass",
"def test_get_source_ip(self):\n pass",
"def test_ip(self):\n ... | [
"0.67973435",
"0.6795078",
"0.67154825",
"0.66857165",
"0.66440994",
"0.6609387",
"0.65462726",
"0.6507168",
"0.649237",
"0.6404722",
"0.63306016",
"0.6302462",
"0.6274524",
"0.6213682",
"0.6204644",
"0.62016076",
"0.61814064",
"0.6152368",
"0.6097284",
"0.60947865",
"0.60787... | 0.78166175 | 0 |
Unit test check_bot_confidence method of the Bad Bots class | def test_check_bot_confidence(setup_config, get_mock_event):
# !ARRANGE!
bad_bots = BadBots(setup_config, get_mock_event)
bot_1 = Bot()
bot_1.source_ip = '1.1.1.1'
bot_1.http_query_string_parameters = '<script></script>'
bot_1.http_body = 'EXEC'
bot_1.geolocation = 'United States'
bot_1.source_ip_type = BadBots.SourceIPType.IPV4
bot_1.http_method = "CONNECT"
bot_1.http_user_agent = "Mozilla/5.0 (compatible; Sosospider/2.0; +http://help.soso.com/webspider.htm)"
bot_2 = Bot()
bot_2.source_ip = '77.168.51.231'
bot_2.http_query_string_parameters = 'hello'
bot_2.http_body = 'hello!'
bot_2.geolocation = 'Netherlands'
bot_2.source_ip_type = BadBots.SourceIPType.IPV4
bot_2.http_method = "GET"
bot_2.http_user_agent = "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
bot_3 = Bot()
bot_3.source_ip = '2a02:a445:6d36:1:1e3:a188:313c:1d33'
bot_3.http_query_string_parameters = 'param=true'
bot_3.http_body = 'username=xxx'
bot_3.geolocation = 'United States'
bot_3.source_ip_type = BadBots.SourceIPType.IPV6
bot_3.http_method = "GET"
bot_3.http_user_agent = "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
# !ACT!
# Do confidence check on potential bots
confidence_score_bot_1 = bad_bots.check_bot_confidence(bot_1)
confidence_score_bot_2 = bad_bots.check_bot_confidence(bot_2)
confidence_score_bot_3 = bad_bots.check_bot_confidence(bot_3)
# !ASSERT!
# Assert IP addresses are of type IPv4
assert(confidence_score_bot_1 == 25)
assert(confidence_score_bot_2 == 0)
assert(confidence_score_bot_3 == 5) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_word_confidences(self):\n self._api.SetImageFile(self._image_file)\n words = self._api.AllWords()\n self.assertEqual(words, [])\n self._api.Recognize()\n words = self._api.AllWords()\n confidences = self._api.AllWordConfidences()\n self.assertEqual(len(word... | [
"0.67971265",
"0.6142417",
"0.61158496",
"0.6029153",
"0.57504106",
"0.572192",
"0.56564856",
"0.5608764",
"0.5544521",
"0.554337",
"0.55383706",
"0.55253214",
"0.54930353",
"0.5490882",
"0.5488589",
"0.54793096",
"0.5459387",
"0.5425729",
"0.540067",
"0.5386406",
"0.5373596"... | 0.7511095 | 0 |
Generates IDL files from a template for user and system marshaling. | def _Main():
cmd_parser = argparse.ArgumentParser(
description='Tool to generate IDL from template.')
cmd_parser.add_argument('--idl_template_file',
dest='idl_template_file',
type=str,
required=True,
help='Input IDL template file.')
cmd_parser.add_argument('--idl_output_file',
type=str,
required=True,
help='Output IDL file.')
flags = cmd_parser.parse_args()
_GenerateIDLFile(flags.idl_template_file, flags.idl_output_file) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def buildAutogenContents(self):\n if len(self.mTemplates) == 0:\n return None\n \n content = \"/** Autogenerated temporary file for template instantiation. */\\n\"\n for t in self.mTemplates:\n template_type = t.mTemplateType\n typedef_name = t.mTypedefName\n con... | [
"0.60924524",
"0.5882521",
"0.5875414",
"0.5807833",
"0.57298577",
"0.5695035",
"0.56720126",
"0.55950695",
"0.55856544",
"0.55830556",
"0.557712",
"0.55616045",
"0.555261",
"0.5524907",
"0.5512638",
"0.5499624",
"0.5496154",
"0.5461171",
"0.54406464",
"0.54035246",
"0.540047... | 0.6245206 | 0 |
add rankig to each node using google pagerank algorithm | def add_pagerank(self):
query = '''
MATCH (c1:)-[r:INTERACTS]->(c2:)
RETURN c1.name, c2.name, r.weight AS weight
'''
ig = IGraph.TupleList(self.graph.run(query), weights=True)
pg = ig.pagerank()
pgvs = []
for p in zip(ig.vs, pg):
print(p)
pgvs.append({"name": p[0]["name"], "pg": p[1]})
write_clusters_query = '''
UNWIND {nodes} AS n
MATCH (c:) WHERE c.name = n.name
SET c.pagerank = n.pg
'''
self.graph.run(write_clusters_query, nodes=pgvs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_rank(self):\n self.__rank += 1",
"def rank():\n return 0",
"def set_rank_order(self):\n for k in self._run:\n self._run[k].sort(key=lambda x:x.get_rank(),reverse=False)\n tot_res = len(self._run[k])\n for r in self._run[k]:\n r.set_sco... | [
"0.6782681",
"0.6664084",
"0.6492858",
"0.64766073",
"0.6452059",
"0.6438518",
"0.64112085",
"0.6404493",
"0.62282807",
"0.6224711",
"0.62225074",
"0.61820155",
"0.6177658",
"0.61345315",
"0.61322975",
"0.6032352",
"0.6016183",
"0.59991485",
"0.59905785",
"0.5985397",
"0.5966... | 0.75397 | 0 |
add community membership to each node using walktrap algorithm implemented in igraph | def add_communites(self):
query = '''
MATCH (c1:)-[r:INTERACTS]->(c2:)
RETURN c1.name, c2.name, r.weight AS weight
'''
ig = IGraph.TupleList(self.graph.run(query), weights=True)
clusters = IGraph.community_walktrap(ig, weights="weight").as_clustering()
nodes = [{"name": node["name"]} for node in ig.vs]
for node in nodes:
idx = ig.vs.find(name=node["name"]).index
node["community"] = clusters.membership[idx]
write_clusters_query = '''
UNWIND {nodes} AS n
MATCH (c:) WHERE c.name = n.name
SET c.community = toInt(n.community)
'''
self.graph.run(write_clusters_query, nodes=nodes) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def assign_communities(graph):\n communities = nx.algorithms.community\\\n .greedy_modularity_communities(nx.Graph(graph))\n for node in graph.nodes:\n graph.nodes[node]['community'] = [i for i,c in enumerate(communities)\n ... | [
"0.5967038",
"0.5503575",
"0.54628575",
"0.5436496",
"0.54320776",
"0.54097146",
"0.53649384",
"0.53567284",
"0.5344505",
"0.53354657",
"0.5303637",
"0.5284366",
"0.52824575",
"0.52807456",
"0.525839",
"0.52522177",
"0.52431047",
"0.52199847",
"0.5210583",
"0.51947844",
"0.51... | 0.6357265 | 0 |
Advance the time reference by the given amount. | def advance_by(self, amount: float):
if amount < 0:
raise ValueError("cannot retreat time reference: amount {} < 0"
.format(amount))
self.__delta += amount | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def advance(self, amount):\n raise NotImplementedError()",
"def advance(self, amount=1):\n self._current += amount\n if self._current - self._updateRate >= self._lastUpdated:\n self.redraw()\n # go to nearest multiple of updateRate less than current\n self._l... | [
"0.74948883",
"0.7390248",
"0.7373512",
"0.72310776",
"0.7102698",
"0.70964295",
"0.688938",
"0.6812329",
"0.6760769",
"0.6728943",
"0.64948493",
"0.6393024",
"0.6281656",
"0.6251204",
"0.619589",
"0.61536574",
"0.6126449",
"0.60908896",
"0.6087889",
"0.6015486",
"0.60153484"... | 0.8371448 | 0 |
Advance the time reference so that now is the given timestamp. | def advance_to(self, timestamp: float):
now = self.__original_time()
if timestamp < now:
raise ValueError("cannot retreat time reference: "
"target {} < now {}"
.format(timestamp, now))
self.__delta = timestamp - now | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def change_time(self, new_time):\r\n self.when = new_time",
"def update_timestamp(self):\n self._timestamp = datetime.datetime.now()",
"def advance_time(self, set_to=None, increment_by=None):\n self._time_condition.acquire()\n if set_to is not None:\n self._time = set_to\... | [
"0.6708446",
"0.6519798",
"0.63856924",
"0.63803643",
"0.6373168",
"0.63460845",
"0.6326127",
"0.62440217",
"0.62124366",
"0.6148152",
"0.614451",
"0.61350346",
"0.6095682",
"0.604849",
"0.6047468",
"0.60337085",
"0.60114896",
"0.6003276",
"0.6003276",
"0.6003276",
"0.6003276... | 0.7582537 | 0 |
Email the given document to the given email address. | def email_document(document, to, template='django_dms/email.txt', subject=''):
# Start a new thread to email the document
# This avoids a frozen screen while the email is being sent (particularly if the document is big).
t = threading.Thread(target=_email_document, args=[document, to, template, subject])
t.setDaemon(True)
t.start() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _email_document(document, to, template='django_dms/email.txt', subject=''): \n # TODO: A really cool system would delay sending the email for 10 seconds or so, \n # to allow the user to quickly undo :-) This could probably also be done client-side (ie JS)\n # Create the message\n message = EmailMes... | [
"0.7192423",
"0.62836236",
"0.6040218",
"0.6037075",
"0.59470624",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.591903",
"0.58806413",
"0.58806413",
"0.58301985",
"0.5820901",
"0.5814947",
"0.5814947",
"0.581... | 0.7277005 | 0 |
Helper function to email document in another thread. | def _email_document(document, to, template='django_dms/email.txt', subject=''):
# TODO: A really cool system would delay sending the email for 10 seconds or so,
# to allow the user to quickly undo :-) This could probably also be done client-side (ie JS)
# Create the message
message = EmailMessage(to=to, subject=subject)
message.to = to
message.subject = subject
message.body = render_to_string(template, {'document': document})
message.attach(document.friendly_filename, document.file.read(), document.file_mimetype)
# Send the message
message.send() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def email_document(document, to, template='django_dms/email.txt', subject=''):\n # Start a new thread to email the document\n # This avoids a frozen screen while the email is being sent (particularly if the document is big).\n t = threading.Thread(target=_email_document, args=[document, to, template, subj... | [
"0.7538517",
"0.6329317",
"0.5854818",
"0.57976854",
"0.57880086",
"0.57461154",
"0.57316077",
"0.5677812",
"0.56468177",
"0.56263226",
"0.5602722",
"0.5572509",
"0.55519354",
"0.554117",
"0.55247223",
"0.5500545",
"0.546613",
"0.5464859",
"0.5459716",
"0.5438996",
"0.5438996... | 0.662225 | 1 |
Get the list of url patterns for this view. | def get_urls(self):
return patterns('',
url(r'^$', self.list, name="%s_document_list" % self.name),
url(r'^upload/$', self.new_upload, name="%s_document_upload" % self.name),
url(r'^([^\/]+)/download/$', self.download, name="%s_document_download" % self.name),
url(r'^([^\/]+)/send/$', self.send, name="%s_document_send" % self.name),
url(r'^([^\/]+)/send/ajax/$', self.send_ajax, name="%s_document_send_ajax" % self.name),
url(r'^([^\/]+)/detail/$', self.detail, name="%s_document_detail" % self.name),
url(r'^([^\/]+)/view/$', self.view, name="%s_document_view" % self.name),
url(r'^([^\/]+)/delete/$', self.delete, name="%s_document_delete" % self.name),
url(r'^(?P<object_id>([^\/]+))/detail/(?P<direction>up|down|clear)vote/?$', self.vote, name="%s_document_vote" % self.name),
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def urlpatterns(self) -> list:\n raise NotImplementedError()",
"def get_urlpatterns(cls):\n cls.validate_urlpattern_with_options()\n return map(lambda s: s.format(**cls.urlpattern_options), cls.urlpatterns)",
"def get_urls(self):\n return patterns('')",
"def urls(self):\n p... | [
"0.8027784",
"0.79029524",
"0.78296137",
"0.7634182",
"0.69524354",
"0.6944128",
"0.67643464",
"0.6622399",
"0.6592495",
"0.6579387",
"0.653932",
"0.64818805",
"0.6450613",
"0.6444061",
"0.6438293",
"0.64050204",
"0.6334296",
"0.6327021",
"0.63207394",
"0.62634665",
"0.623646... | 0.6526326 | 11 |
Send the specified document to the user's email address (HTML version). | def send(self, request, id, tribe_slug):
tribe = get_object_or_404(Tribe, slug=tribe_slug)
document = self.get_document(id, tribe_slug)
form = self._set_user_email_address(request)
email = self._get_user_email_address(request)
if form or not email:
return render_to_response('django_dms/send.html', locals(), context_instance=RequestContext(request))
# NB: Temporarily disabling actual email sending for development
#email_document(document, to=[email], subject='Document: %s' % document.title)
print "Sending email to %s" % email
# Send a signal to let everyone know about this document interaction
document_interaction.send(sender=self, document=document, mode="sent", request=request, recipient=email)
return HttpResponseRedirect(reverse('%s_document_list' % self.name, args=(tribe_slug, ) )) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _email_document(document, to, template='django_dms/email.txt', subject=''): \n # TODO: A really cool system would delay sending the email for 10 seconds or so, \n # to allow the user to quickly undo :-) This could probably also be done client-side (ie JS)\n # Create the message\n message = EmailMes... | [
"0.7611227",
"0.73684156",
"0.67148703",
"0.6527169",
"0.6408137",
"0.6307394",
"0.6218779",
"0.6209792",
"0.61815774",
"0.6166898",
"0.616678",
"0.6158147",
"0.60088944",
"0.5979466",
"0.5952957",
"0.5952957",
"0.59498113",
"0.59447414",
"0.5928036",
"0.59016263",
"0.5876797... | 0.6786847 | 2 |
Send the specified document to the user's email address (AJAX version). | def send_ajax(self, request, id, tribe_slug):
document = self.get_document(id, tribe_slug)
form = self._set_user_email_address(request)
email = self._get_user_email_address(request)
if not email and not form:
form = EmailForm()
if form:
content = '<form class="ajax_update_email" action="%s" method="post">' % reverse('%s_document_send' % self.name, args=[getattr(document, self.url_identifier_field)])
content += '%s<input type="submit" value="Send"/></form>' % form['email']
return HttpResponse(content)
print "Sending email to %s" % email
#email_document(document, to=[email], subject='Document: %s' % document.title)
# Send a signal to let everyone know about this document interaction
document_interaction.send(sender=self, document=document, mode="sent", request=request, recipient=email)
return HttpResponse('Email sent to %s' % email) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def send(self, request, id, tribe_slug):\n tribe = get_object_or_404(Tribe, slug=tribe_slug)\n document = self.get_document(id, tribe_slug)\n \n form = self._set_user_email_address(request)\n email = self._get_user_email_address(request)\n if form or not email:\n ... | [
"0.7083903",
"0.6592813",
"0.6592162",
"0.6246286",
"0.5818268",
"0.58028346",
"0.5787325",
"0.5658083",
"0.56290865",
"0.5581146",
"0.55060256",
"0.5494548",
"0.5458515",
"0.54515415",
"0.544656",
"0.5391331",
"0.5326866",
"0.53013676",
"0.52664655",
"0.5242208",
"0.5226229"... | 0.7920855 | 0 |
Gets a custom defined or default email address for the current user. | def _get_user_email_address(self, request):
return request.session.get(SESSION_VAR_EMAIL_ADDRESS, not request.user.is_anonymous() and request.user.email) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_user_email(self):\n member = self.get_user()\n if member:\n return member.getProperty('email')",
"def get_email(self):\n return self.reference[REF_EMAIL_ADDRESS][REF_VALUE]",
"def user_email(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"user_email\")",
... | [
"0.79681355",
"0.77469647",
"0.7720694",
"0.76566875",
"0.7597106",
"0.75681674",
"0.7504296",
"0.74986595",
"0.74986595",
"0.74986595",
"0.74986595",
"0.7492597",
"0.7372196",
"0.7372196",
"0.7372196",
"0.7372132",
"0.73386735",
"0.72807336",
"0.72577626",
"0.7211655",
"0.72... | 0.793554 | 1 |
If a new email address is posted, remember it. | def _set_user_email_address(self, request):
if request.method == 'POST':
form = EmailForm(request.POST)
if form.is_valid():
request.session[SESSION_VAR_EMAIL_ADDRESS] = form.cleaned_data['email']
else:
return form | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_duplicate_email(self, email):\r\n request = self.req_factory.post('unused_url', data={\r\n 'new_email': email,\r\n 'password': 'test',\r\n })\r\n request.user = self.user\r\n self.assertFailedRequest(self.run_request(request), 'An account with this e-mail... | [
"0.65422535",
"0.64260054",
"0.63118654",
"0.63064903",
"0.60563016",
"0.6038557",
"0.6014613",
"0.5898787",
"0.58314365",
"0.5781677",
"0.577932",
"0.5769288",
"0.575497",
"0.5719079",
"0.57139456",
"0.5708547",
"0.5708547",
"0.5700854",
"0.5699276",
"0.56723505",
"0.5661490... | 0.6590844 | 0 |
Get an item for the template, containing the document. | def _get_list_item(self, document):
list_item = Item()
list_item.document = document
# TODO: call callables?
list_item.display_fields = [self._prepare_field(document, field) for field in self.list_display]
return list_item | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_object(self):\n if not self._item:\n self._item = get_object_or_404(Item, pk=self.kwargs['item_id'])\n return self._item",
"def getItemTemplate(self):\n self.update()\n if self.resource_item_template is None:\n return None\n\n return ResourceItem(s... | [
"0.6883214",
"0.6577675",
"0.6520346",
"0.6520346",
"0.63746023",
"0.6368625",
"0.6285564",
"0.6244785",
"0.61841923",
"0.61830777",
"0.6121958",
"0.61106426",
"0.60945314",
"0.6082757",
"0.60224175",
"0.6003464",
"0.59755844",
"0.59741163",
"0.59633183",
"0.5937414",
"0.5898... | 0.55808055 | 54 |
Get the list of url patterns for this view. | def get_urls(self):
return patterns('',
#url(r'^$', self.new_upload, name="%s_document_list" % self.name),
url(r'^([^\/]+)/edit/$', self.edit, name="%s_document_edit" % self.name),
url(r'^([\w\d-]+)/confirm/$', self.confirm, name="%s_document_confirm" % self.name)
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def urlpatterns(self) -> list:\n raise NotImplementedError()",
"def get_urlpatterns(cls):\n cls.validate_urlpattern_with_options()\n return map(lambda s: s.format(**cls.urlpattern_options), cls.urlpatterns)",
"def get_urls(self):\n return patterns('')",
"def urls(self):\n p... | [
"0.8027784",
"0.79029524",
"0.78296137",
"0.7634182",
"0.69524354",
"0.6944128",
"0.67643464",
"0.6622399",
"0.6592495",
"0.6579387",
"0.653932",
"0.6526326",
"0.64818805",
"0.6450613",
"0.6444061",
"0.6438293",
"0.64050204",
"0.6334296",
"0.6327021",
"0.63207394",
"0.6263466... | 0.6040245 | 37 |
Print list of instances with their attached volume id/size to console, ie | def list_ebss_by_instance():
ec2 = u.create_ec2_resource()
instances = [(u.seconds_from_datetime(i.launch_time), i) for i in ec2.instances.all()]
sorted_instances = sorted(instances, key=itemgetter(0))
for (seconds, instance) in sorted_instances:
volumes = instance.volumes.all()
volume_strs = []
for v in volumes:
volume_strs.append("%s (%s)"%(v.id, v.size))
print("%s: %s" % (u.get_name(instance.tags), ','.join(volume_strs))) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def show_asm_volumes(self):\n sql = \"select NAME from v$asm_diskgroup_stat ORDER BY 1\"\n self.cur.execute(sql)\n res = self.cur.fetchall()\n key = ['{#ASMVOLUME}']\n lst = []\n for i in res:\n d = dict(zip(key, i))\n lst.append(d)\n print(jso... | [
"0.66387",
"0.65122116",
"0.64756095",
"0.6264545",
"0.61685747",
"0.61603457",
"0.6125444",
"0.61109924",
"0.6072397",
"0.60526633",
"0.60198474",
"0.59469944",
"0.5940197",
"0.5938797",
"0.59375834",
"0.5925745",
"0.5900101",
"0.5888648",
"0.58722466",
"0.5867416",
"0.58226... | 0.6720033 | 0 |
Grows EBS volume for given task. | def grow_ebs_for_task(task_fragment, target_size_gb):
ec2 = u.create_ec2_resource()
client = u.create_ec2_client()
# todo: don't crash on missing/duplicate names
instances = {u.get_name(i.tags): i for i in ec2.instances.all()}
ec2 = u.create_ec2_resource()
instances = [(u.seconds_from_datetime(i.launch_time), i) for i in ec2.instances.all()]
sorted_instances = reversed(sorted(instances, key=itemgetter(0)))
for (seconds, instance) in sorted_instances:
task_name = u.get_name(instance.tags)
hours_ago = (time.time()-seconds)/3600
hours_ago+=8 # adjust for time being in UTC
if task_fragment in task_name:
print("Found instance %s launched %.1f hours ago" %( task_name, hours_ago))
break
print(instance.id)
volumes = list(instance.volumes.all())
assert len(volumes)==1, "Must have 1 volume"
print("Growing %s to %s"%(volumes[0].id, target_size_gb))
response = client.modify_volume(
VolumeId=volumes[0].id,
Size=target_size_gb,
)
assert u.is_good_response(response) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def grow_volume(self, volume, growth, async=False):\n\n assert isinstance(volume, dict), \"volume configuration is invalid, 'dict' type expected\"\n assert volume.get('id'), \"volume.id can't be blank\"\n\n async_result = __node__['bollard'].apply_async('api.postgresql.grow-volume',\n ... | [
"0.64236933",
"0.6261913",
"0.60468847",
"0.587187",
"0.5659941",
"0.5560449",
"0.53718984",
"0.534629",
"0.5339353",
"0.53099704",
"0.52602965",
"0.5249011",
"0.518899",
"0.5125479",
"0.50864977",
"0.5082796",
"0.5080378",
"0.50407803",
"0.50402933",
"0.5031618",
"0.5022762"... | 0.69317895 | 0 |
This class tests the PyTorchYolo object detector. | def get_pytorch_yolo(get_default_cifar10_subset):
import cv2
import torch
from pytorchyolo import models
from pytorchyolo.utils.loss import compute_loss
from art.estimators.object_detection.pytorch_yolo import PyTorchYolo
model_path = "/tmp/PyTorch-YOLOv3/config/yolov3.cfg"
weights_path = "/tmp/PyTorch-YOLOv3/weights/yolov3.weights"
model = models.load_model(model_path=model_path, weights_path=weights_path)
class YoloV3(torch.nn.Module):
def __init__(self, model):
super().__init__()
self.model = model
def forward(self, x, targets=None):
if self.training:
outputs = self.model(x)
# loss is averaged over a batch. Thus, for patch generation use batch_size = 1
loss, loss_components = compute_loss(outputs, targets, self.model)
loss_components_dict = {"loss_total": loss}
return loss_components_dict
else:
return self.model(x)
model = YoloV3(model)
object_detector = PyTorchYolo(
model=model, input_shape=(3, 416, 416), clip_values=(0, 1), attack_losses=("loss_total",)
)
n_test = 10
(_, _), (x_test_cifar10, y_test_cifar10) = get_default_cifar10_subset
x_test_cifar10 = x_test_cifar10[0:n_test]
x_test = cv2.resize(
x_test_cifar10[0].transpose((1, 2, 0)), dsize=(416, 416), interpolation=cv2.INTER_CUBIC
).transpose((2, 0, 1))
x_test = np.expand_dims(x_test, axis=0)
x_test = np.repeat(x_test, repeats=2, axis=0)
# Create labels
result = object_detector.predict(x=x_test)
y_test = [
{
"boxes": result[0]["boxes"],
"labels": result[0]["labels"],
"scores": np.ones_like(result[0]["labels"]),
},
{
"boxes": result[1]["boxes"],
"labels": result[1]["labels"],
"scores": np.ones_like(result[1]["labels"]),
},
]
yield object_detector, x_test, y_test | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def detection(input_path, output_path, yolo_model_path):\n detector = VideoObjectDetection()\n # this function sets the model type of the object detection instance you created to the YOLOv3 model\n detector.setModelTypeAsYOLOv3()\n # this function accepts a string that must be the path to the model fil... | [
"0.6627789",
"0.6447896",
"0.6315877",
"0.62284786",
"0.6174531",
"0.61566085",
"0.6096233",
"0.60372835",
"0.58174103",
"0.5799088",
"0.5774036",
"0.5773982",
"0.57679653",
"0.56752574",
"0.5674558",
"0.5668986",
"0.5649171",
"0.5648845",
"0.5647306",
"0.5644756",
"0.5634993... | 0.7094565 | 0 |
Splits image into tiles by size of tile. tile_w tile width tile_h tile height | def split_image_into_tiles_of_size(arr: Image, tile_w: int, tile_h: int, overlap: int):
x_axis = -1
y_axis = -2
arr_width, arr_height = arr.shape[x_axis], arr.shape[y_axis]
x_ntiles = (
arr_width // tile_w if arr_width % tile_w == 0 else (arr_width // tile_w) + 1
)
y_ntiles = (
arr_height // tile_h if arr_height % tile_h == 0 else (arr_height // tile_h) + 1
)
tiles = []
# row
for i in range(0, y_ntiles):
# height of this tile
ver_f = tile_h * i
ver_t = ver_f + tile_h
# col
for j in range(0, x_ntiles):
# width of this tile
hor_f = tile_w * j
hor_t = hor_f + tile_w
tile = get_tile(arr, hor_f, hor_t, ver_f, ver_t, overlap)
tiles.append(tile)
tile_shape = [tile_h, tile_w]
ntiles = dict(x=x_ntiles, y=y_ntiles)
padding = dict(left=0, right=0, top=0, bottom=0)
if arr_width % tile_w == 0:
padding["right"] = 0
else:
padding["right"] = tile_w - (arr_width % tile_w)
if arr_height % tile_h == 0:
padding["bottom"] = 0
else:
padding["bottom"] = tile_h - (arr_height % tile_h)
info = dict(tile_shape=tile_shape, ntiles=ntiles, overlap=overlap, padding=padding)
return tiles, info | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _split_image_into_tiles(\n self, image: np.ndarray\n ) -> t.Sequence[t.Tuple[t.Tuple[t.Any, ...], np.ndarray]]:\n h, w, c = image.shape\n tile_height = (\n math.ceil(h / (self._n_tiles // 2 - 1))\n if self._n_tiles > 4\n else math.ceil(h / (self._n_tiles... | [
"0.76203066",
"0.71610355",
"0.69022644",
"0.6677268",
"0.6614609",
"0.6609202",
"0.6596505",
"0.6574447",
"0.6529179",
"0.652334",
"0.650743",
"0.650743",
"0.6493861",
"0.6485636",
"0.64644873",
"0.6450046",
"0.644942",
"0.6383776",
"0.6369156",
"0.634634",
"0.63084143",
"... | 0.7902135 | 0 |
Splits image into tiles by number of tile. x_ntiles number of tiles horizontally y_ntiles number of tiles vertically | def split_image_into_number_of_tiles(
arr: Image, x_ntiles: int, y_ntiles: int, overlap: int
):
img_width, img_height = arr.shape[-1], arr.shape[-2]
tile_w = img_width // x_ntiles
tile_h = img_height // y_ntiles
return split_image_into_tiles_of_size(arr, tile_w, tile_h, overlap) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _split_image_into_tiles(\n self, image: np.ndarray\n ) -> t.Sequence[t.Tuple[t.Tuple[t.Any, ...], np.ndarray]]:\n h, w, c = image.shape\n tile_height = (\n math.ceil(h / (self._n_tiles // 2 - 1))\n if self._n_tiles > 4\n else math.ceil(h / (self._n_tiles... | [
"0.7743909",
"0.7442206",
"0.7223278",
"0.6875224",
"0.6805701",
"0.6805701",
"0.68043333",
"0.6783657",
"0.67152864",
"0.6648476",
"0.6550898",
"0.6506808",
"0.6499578",
"0.644437",
"0.64369965",
"0.64329946",
"0.6417711",
"0.6391121",
"0.6388546",
"0.637921",
"0.6316766",
... | 0.8323475 | 0 |
Draw the contours over a blank array. The function cv2.DrawContours overlays the contours on top of the bitwise array. Which is not ideal if the bitwise array contains some small, noisy contours. Therefore, I created an empty array first and then used this as the base for drawing the contours onto. | def draw_contours(self):
contours, hierarchy = cv2.findContours(self.edged, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_L1)
edged = cv2.bitwise_not(self.edged)
rgb = cv2.cvtColor(edged, cv2.COLOR_GRAY2RGB)
temp_array = np.ones([rgb.shape[0], rgb.shape[1], rgb.shape[2]])
contours_ = cv2.drawContours(temp_array, contours, -1, (0, 0, 0), thickness=1)
ml_filename = 'MLOutputs/' + str(self.file_name) + 'Clusters' + str(self.clusters) + \
'FilterSize' + str(self.filter_size) + 'Sigma' + str(self.sigma) + 'UniqueColours' + \
str(self.unique_colours) + ".png"
plt.imshow(contours_, cmap="gray")
if not os.path.isfile(ml_filename):
imsave(ml_filename, contours_, cmap="gray") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def draw_contours(self, image_path):\n img = cv.imread(image_path, cv.IMREAD_ANYDEPTH)\n contoured = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)\n unique, counts = np.unique(img, return_counts=True)\n for uni in unique:\n if uni == 0:\n continue\n... | [
"0.62755567",
"0.62009114",
"0.60225683",
"0.5922091",
"0.5880212",
"0.58467317",
"0.5801622",
"0.5658485",
"0.56459415",
"0.56298447",
"0.5628904",
"0.5601753",
"0.5587474",
"0.55055207",
"0.5471264",
"0.5443541",
"0.54303265",
"0.54265594",
"0.542418",
"0.54153204",
"0.5408... | 0.5654723 | 8 |
Return True if object is an instance that inherited from specified\ class, otherwise False python3 c 'print(__import__("my_module").my_function.__doc__)' python3 c 'print(__import__("my_module").MyClass.my_function.__doc__)' | def inherits_from(obj, a_class):
if issubclass(type(obj), a_class) and not type(obj) == a_class:
return True
else:
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def isclassinstance(object):\n if not hasattr(object, \"__class__\"):\n return False\n if isbuiltin(object.__class__):\n return False\n return True",
"def isclass(object):\n if not inspect.isclass(object):\n return False\n if isbuiltin(object):\n return False\n retur... | [
"0.6786016",
"0.6415582",
"0.6202909",
"0.6114083",
"0.60608363",
"0.60413224",
"0.6035273",
"0.60166055",
"0.59785694",
"0.59465903",
"0.5944888",
"0.5933893",
"0.59169173",
"0.5910051",
"0.59036976",
"0.5892804",
"0.5881093",
"0.5877024",
"0.5872548",
"0.58636963",
"0.58568... | 0.59816 | 8 |
Compile the .qrc (Qt Designer resource files) into .py files. | def compile_resources(resourcename="images", location="."):
res_count_ok = 0
res_count_ko = 0
for qrc_file in os.listdir(location):
# Loop through directory
if qrc_file.endswith(".qrc"):
# We have a candidate file
print(f"---> Found {qrc_file}")
# get the filename without extension
base_filename, _ = os.path.splitext(os.path.basename(qrc_file))
# Make the target name
target_filename = f"{base_filename}_rc.py"
# Run!
result = subprocess.run(["pyrcc5", "-o", target_filename, f"{location}/{qrc_file}"], capture_output=True)
if result.returncode == 0:
print(f"[v] Resource compiled to {target_filename}")
res_count_ok += 1
else:
print(f"[e] An error occured {result}")
res_count_ko += 1
return res_count_ok, res_count_ko | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_qrc(path, name=\"resources\", prefix=\"icons\"):\n qrc = '<RCC>\\n\\t<qresource prefix=\"{}\">\\n'.format(prefix)\n for each in sorted(os.listdir(path)):\n qrc += \"\\t\\t<file>{0}</file>\\n\".format(each)\n qrc += \"\\t</qresource>\\n</RCC>\\n\"\n\n qrc_file = os.path.join(path, na... | [
"0.67200714",
"0.65681183",
"0.6396254",
"0.6029277",
"0.5712012",
"0.5677451",
"0.56494296",
"0.5627389",
"0.5508585",
"0.5422793",
"0.5350092",
"0.530345",
"0.52731526",
"0.5244704",
"0.5227191",
"0.5177347",
"0.5123454",
"0.5108174",
"0.5087578",
"0.50874686",
"0.5061226",... | 0.6065464 | 3 |
Generates an array of ppxf_util.gaussian emission lines to be used as gas templates in PPXF. Generally, these templates represent the instrumental line spread function (LSF) at the set of wavelengths of each emission line. In this case, pPXF will return the intrinsic (i.e. astrophysical) dispersion of the gas lines. Alternatively, one can input FWHM_gal=0, in which case the emission lines are deltafunctions and pPXF will return a dispersion which includes both the intrumental and the intrinsic disperson. Additional lines can be easily added by editing the code of this procedure, which is meant as a template to be modified by the users where needed. For accuracy the ppxf_util.gaussians are integrated over the pixels boundaries. This can be changed by setting `pixel`=False. The [OI], [OIII] and [NII] doublets are fixed at theoretical flux ratio~3. The [OII] and [SII] doublets can be restricted to physical range of ratios. The Balmet Series can be fixed to the theoretically predicted decrement. | def emission_lines(logLam_temp, lamRange_gal, FWHM_gal, pixel=True,
tie_balmer=False, limit_doublets=False, vacuum=False):
if tie_balmer:
# Balmer decrement for Case B recombination (T=1e4 K, ne=100 cm^-3)
# Table 4.4 of Dopita & Sutherland 2003 https://www.amazon.com/dp/3540433627
# Balmer: Htheta Heta Hzeta Heps Hdelta Hgamma Hbeta Halpha
wave = np.array([3797.90, 3835.39, 3889.05, 3970.07, 4101.76, 4340.47, 4861.33, 6562.80]) # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
gauss = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel)
ratios = np.array([0.0530, 0.0731, 0.105, 0.159, 0.259, 0.468, 1, 2.86])
ratios *= wave[-2]/wave # Account for varying pixel size in Angstrom
emission_lines = gauss @ ratios
line_names = ['Balmer']
w = (wave > lamRange_gal[0]) & (wave < lamRange_gal[1])
line_wave = np.mean(wave[w]) if np.any(w) else np.mean(wave)
else:
# Use fewer lines here, as the weak ones are difficult to measure
# Balmer: Hdelta Hgamma Hbeta Halpha
line_wave = [4101.76, 4340.47, 4861.33, 6562.80] # air wavelengths
if vacuum:
line_wave = ppxf_util.air_to_vac(line_wave)
line_names = ['Hdelta', 'Hgamma', 'Hbeta', 'Halpha']
emission_lines = ppxf_util.gaussian(logLam_temp, line_wave, FWHM_gal, pixel)
if limit_doublets:
# The line ratio of this doublet lam3729/lam3726 is constrained by
# atomic physics to lie in the range 0.28--1.47 (e.g. fig.5.8 of
# Osterbrock & Ferland 2005 https://www.amazon.co.uk/dp/1891389343/).
# We model this doublet as a linear combination of two doublets with the
# maximum and minimum ratios, to limit the ratio to the desired range.
# -----[OII]-----
wave = [3726.03, 3728.82] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
names = ['[OII]3726_d1', '[OII]3726_d2']
gauss = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel)
doublets = gauss @ [[1, 1], [0.28, 1.47]] # produces *two* doublets
emission_lines = np.column_stack([emission_lines, doublets])
line_names = np.append(line_names, names)
line_wave = np.append(line_wave, wave)
# The line ratio of this doublet lam6716/lam6731 is constrained by
# atomic physics to lie in the range 0.44--1.43 (e.g. fig.5.8 of
# Osterbrock & Ferland 2005 https://www.amazon.co.uk/dp/1891389343/).
# We model this doublet as a linear combination of two doublets with the
# maximum and minimum ratios, to limit the ratio to the desired range.
# -----[SII]-----
wave = [6716.47, 6730.85] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
names = ['[SII]6731_d1', '[SII]6731_d2']
gauss = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel)
doublets = gauss @ [[0.44, 1.43], [1, 1]] # produces *two* doublets
emission_lines = np.column_stack([emission_lines, doublets])
line_names = np.append(line_names, names)
line_wave = np.append(line_wave, wave)
else:
# Here the doublets are free to have any ratio
# -----[OII]----- -----[SII]-----
wave = [3726.03, 3728.82, 6716.47, 6730.85] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
names = ['[OII]3726', '[OII]3729', '[SII]6716', '[SII]6731']
gauss = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel)
emission_lines = np.column_stack([emission_lines, gauss])
line_names = np.append(line_names, names)
line_wave = np.append(line_wave, wave)
# To keep the flux ratio of a doublet fixed, we place the two lines in a single template
# -----[OIII]-----
wave = [4958.92, 5006.84] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
doublet = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel) @ [0.33, 1]
emission_lines = np.column_stack([emission_lines, doublet])
line_names = np.append(line_names, '[OIII]5007_d') # single template for this doublet
line_wave = np.append(line_wave, wave[1])
# To keep the flux ratio of a doublet fixed, we place the two lines in a single template
# -----[OI]-----
wave = [6300.30, 6363.67] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
doublet = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel) @ [1, 0.33]
emission_lines = np.column_stack([emission_lines, doublet])
line_names = np.append(line_names, '[OI]6300_d') # single template for this doublet
line_wave = np.append(line_wave, wave[0])
# To keep the flux ratio of a doublet fixed, we place the two lines in a single template
# -----[NII]-----
wave = [6548.03, 6583.41] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
doublet = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel) @ [0.33, 1]
emission_lines = np.column_stack([emission_lines, doublet])
line_names = np.append(line_names, '[NII]6583_d') # single template for this doublet
line_wave = np.append(line_wave, wave[1])
#added by anja to ppxf_util.emission_lines version
# To keep the flux ratio of a doublet fixed, we place the two lines in a single template
# -----[NI]-----
wave = [5197.90, 5200.39] # air wavelengths
if vacuum:
wave = ppxf_util.air_to_vac(wave)
doublet = ppxf_util.gaussian(logLam_temp, wave, FWHM_gal, pixel) @ [1, 0.7]
emission_lines = np.column_stack([emission_lines, doublet])
line_names = np.append(line_names, '[NI]5200_d') # single template for this doublet
line_wave = np.append(line_wave, wave[1])
#----------------------
# Only include lines falling within the estimated fitted wavelength range.
#
w = (line_wave > lamRange_gal[0]) & (line_wave < lamRange_gal[1])
emission_lines = emission_lines[:, w]
line_names = line_names[w]
line_wave = line_wave[w]
print('Emission lines included in gas templates:')
print(line_names)
return emission_lines, line_names, line_wave | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Generate_BG_Template(outputSize=300, angularSize = 10, fileOut = 'BGRateMap.pickle' ):\r\n template = np.zeros((outputSize,outputSize))\r\n ppd=float(outputSize)/float(angularSize) # pixels per deg\r\n \r\n events110 = ParseFermi.Import_File('photons.txt', energyRange = (120000,140000),lonRange=(-... | [
"0.5699116",
"0.5599356",
"0.5230809",
"0.5207666",
"0.5170641",
"0.5158478",
"0.51580274",
"0.5144128",
"0.5076723",
"0.5075624",
"0.50331193",
"0.50331193",
"0.5024959",
"0.49573076",
"0.49408728",
"0.49217612",
"0.48975858",
"0.48955354",
"0.48943654",
"0.48930743",
"0.487... | 0.58730155 | 0 |
Defining prior distributions for the model. | def set_priors(parnames, limits, linenames, vsyst, nssps=1):
priors = {}
for parname in parnames:
name = parname.split("_")[0]
if name in limits: #all the CvD ssp parameters
vmin, vmax = limits[name]
# print(parname,vmin,vmax)
delta = vmax - vmin
priors[parname] = stats.uniform(loc=vmin, scale=delta)
elif parname in vsyst:
priors[parname] = stats.norm(loc=vsyst[parname], scale=500)
elif parname == "eta": #what does eta do?
priors["eta"] = stats.uniform(loc=1., scale=19)#uniform distribution in range [1,19]
elif parname == "nu": #what does nu do?
priors["nu"] = stats.uniform(loc=2, scale=20)#uniform distribution in range [2,20]
elif parname == "sigma":
priors["sigma"] = stats.uniform(loc=50, scale=300)#obtains the uniform distribution on [loc, loc + scale]. i.e. uniform in range [50,300]
elif parname == "sigma_gas":
priors[parname] = stats.uniform(loc=50, scale=100)#uniform between [50,100]km/s
elif name == "w":
priors[parname] = stats.uniform(loc=0, scale=1)#weights uniform between 0 and 1
elif name in linenames:
# priors[parname] = stats.expon(loc=0, scale=0.5)#favors low values>~0; make even stronger by decreasing scale.
priors[parname] = stats.expon(loc=0, scale=0.2)#favors low values>~0; make even stronger by decreasing scale.
elif name in ["pred", "pblue"]:
porder = int(parname.split("_")[1])
if porder == 0:
mu, sd = 1 / nssps, 1
a, b = (0 - mu) / sd, (np.infty - mu) / sd
priors[parname] = stats.truncnorm(a, b, mu, sd)
else:
priors[parname] = stats.norm(0, 0.05)
else:
print(f"parameter without prior: {parname}")
return priors | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gaussian_prior(self):\n self.prior = sps.multivariate_normal(self.m0,self.S0)",
"def prior_distribution(self):\n out = self.model.forward(self.inducing_points)\n return MultivariateNormal(out.mean, out.lazy_covariance_matrix.evaluate_kernel())",
"def get_prior(self):\n assert se... | [
"0.7287337",
"0.7219811",
"0.698138",
"0.69521374",
"0.6878878",
"0.6738291",
"0.65607095",
"0.65233296",
"0.6507224",
"0.64965516",
"0.6484119",
"0.64804757",
"0.64787775",
"0.6447634",
"0.6433855",
"0.6417294",
"0.6408151",
"0.64017296",
"0.6352515",
"0.6351014",
"0.6346401... | 0.0 | -1 |
Calculates the probability of a model. | def log_probability(theta):
global priors
global logp
lp = np.sum([priors[p].logpdf(x) for p, x in zip(logp.parnames, theta)])
if not np.isfinite(lp) or np.isnan(lp):
return -np.inf
ll = logp(theta)
if not np.isfinite(ll):
return -np.inf
return lp + ll | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _compute_model_prob(self, per_list_logodds):\n with tf.compat.v1.name_scope(name='compute_model_prob'):\n return tf.stop_gradient(\n tf.exp(-self._alpha *\n (per_list_logodds -\n tf.reduce_min(per_list_logodds, axis=2, keepdims=True))))",
"def calculate_proba... | [
"0.7188488",
"0.7145453",
"0.6747787",
"0.67278534",
"0.65877354",
"0.6577112",
"0.6537247",
"0.6531125",
"0.6514498",
"0.65023434",
"0.64306843",
"0.63726646",
"0.63619375",
"0.63538843",
"0.62945044",
"0.6287746",
"0.62856567",
"0.62772304",
"0.62686586",
"0.62612885",
"0.6... | 0.0 | -1 |
Combine SSP traces to have mass/luminosity weighted properties | def weighted_traces(parnames, trace, nssps):
weights = np.array([trace["w_{}".format(i+1)].data for i in range(
nssps)])
wtrace = []
for param in parnames:
data = np.array([trace["{}_{}".format(param, i+1)].data
for i in range(nssps)])
t = np.average(data, weights=weights, axis=0)
wtrace.append(Table([t], names=["{}_weighted".format(param)]))
return hstack(wtrace) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plot_combined_variation(nums, SSC, band, rms):\n\n def get_spectra(nums, SSC, band, rms):\n spectrum = spectra[str(SSC['no'])][band]\n frequency = spectrum['frequency'].to(u.GHz)\n intensity = spectrum['spectrum'].to(u.K)\n # shift spectrum to rest frequency\n velshift =... | [
"0.53677773",
"0.52855563",
"0.52082103",
"0.5192049",
"0.50655925",
"0.50220954",
"0.5019231",
"0.4980716",
"0.496982",
"0.49639016",
"0.496379",
"0.49591964",
"0.49528778",
"0.49409777",
"0.4926693",
"0.49150053",
"0.48961598",
"0.4841809",
"0.48396593",
"0.48142034",
"0.48... | 0.5468182 | 1 |
Call function to transform and format common fields in results. | def __call__(self, results):
if 'img' in results:
img = results['img']
if len(img.shape) < 3:
img = np.expand_dims(img, -1)
img = np.ascontiguousarray(img.transpose(2, 0, 1))
results['img'] = DC(to_tensor(img), stack=True)
if 'gt_semantic_seg' in results:
# convert to long
results['gt_semantic_seg'] = DC(to_tensor(
results['gt_semantic_seg'][None, ...].astype(np.int64)),
stack=True)
if 'gt_masks' in results:
results['gt_masks'] = DC(to_tensor(results['gt_masks']))
if 'gt_labels' in results:
results['gt_labels'] = DC(to_tensor(results['gt_labels']))
return results | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def transform():",
"def transform():\n pass",
"def transform(self):",
"def _apply_transform(self):\n pass",
"def _output_format(cls, func, override=None):\n @wraps(func)\n def _format_wrapper(self, *args, **kwargs):\n json_response, data_key, meta_data_key = func(self... | [
"0.6625306",
"0.6302095",
"0.6020546",
"0.59190804",
"0.5870707",
"0.5793297",
"0.573849",
"0.57165796",
"0.56867325",
"0.56854814",
"0.56783605",
"0.5602666",
"0.55980164",
"0.5573735",
"0.55417204",
"0.55297184",
"0.5522978",
"0.5522028",
"0.54894423",
"0.5454132",
"0.54165... | 0.0 | -1 |
update learning rate of optimizers | def updatelearningrate(self, epoch):
self.lr = getlearningrate(epoch=epoch, opt=self.opt)
# update learning rate of model optimizer
if isinstance(self.model, list):
count = 0
for param_group in self.optimzer.param_groups:
# if type(model) is <list> then update modules with different learning rate
param_group['lr'] = self.lr
count += 1
# print ">>> count is:", count-1
else:
for param_group in self.optimzer.param_groups:
param_group['lr'] = self.lr | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _update_learning_rate(self):\r\n\r\n self.n_steps += 1\r\n lr = self.factor * self._get_lr_scale()\r\n for param_group in self._optimizer.param_groups:\r\n param_group['lr'] = lr",
"def update_learning_rate(self):\n self.scheduler.step()\n lr = self.optimizer.par... | [
"0.82430375",
"0.8091104",
"0.8081948",
"0.8057003",
"0.7882125",
"0.7729992",
"0.7728464",
"0.7728464",
"0.77180463",
"0.7680515",
"0.7672647",
"0.7670474",
"0.76550764",
"0.76442766",
"0.762199",
"0.76109266",
"0.7595715",
"0.758477",
"0.7532394",
"0.7522077",
"0.75184435",... | 0.81921303 | 1 |
construct any person or destroyable object | def __init__(
self,
id: int,
coordinates: Tuple[int, int],
name: str,
health: 'Health',
ai: 'Ai',
parts: Dict[str, 'Part'],
actions: Set['Action'],
skills: Set['Skill'] = None,
effects: Effects = None,
team: 'Team' = None,
) -> None:
self.id = id
self.position = coordinates
self.name = name
self.health = health
self.ai = ai
self.parts = parts
self.actions = actions
self.skills = skills or set()
self.effects = effects or Effects()
self.team = team | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def construct_persona(x):\n return Persona(x)",
"def make_object():\n return object()",
"def create_person(person: Person = Body(...)):\n return person",
"def new_object(self):\r\n\t\tpass",
"def new(self, obj):\n pass",
"def instantiate(obj):\n return obj() if isinstance(obj, type) el... | [
"0.726856",
"0.7046766",
"0.6489531",
"0.6340825",
"0.6317375",
"0.62946725",
"0.6185293",
"0.61081696",
"0.6088009",
"0.6050287",
"0.59465456",
"0.59465456",
"0.59365165",
"0.5905628",
"0.5864767",
"0.58611476",
"0.585532",
"0.5852625",
"0.58511806",
"0.58508277",
"0.5850827... | 0.0 | -1 |
choose targets and actions | def do_action(self, ally: Set['Entity'], enemy: Set['Entity']) -> None:
self.effects.update()
available_actions, available_ally_targets, available_enemy_targets = self.get_actions(ally, enemy)
action, target = self.ai.choose_action(self, available_actions, available_ally_targets, available_enemy_targets)
if not action:
action = pass_action
target = self
action.do(self, target) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def execute(self, targets):",
"def choose_action(self):\r\n pass",
"def Action(self):\n for target in self._targets:\n target.Action()",
"def choose_action(self, board, possible_actions):\r\n pass",
"def target_act(self, obs_all_agents, noise=0.0):\n target_actions = ... | [
"0.6905978",
"0.66720754",
"0.64456934",
"0.64400035",
"0.6392093",
"0.6392093",
"0.63541424",
"0.63423127",
"0.6292723",
"0.6272857",
"0.6237775",
"0.6205516",
"0.61756647",
"0.6061701",
"0.6053934",
"0.6031384",
"0.6015014",
"0.59976435",
"0.59927475",
"0.596754",
"0.591768... | 0.0 | -1 |
get list of available actions | def get_actions(self, ally: Set['Entity'], enemy: Set['Entity']) -> Tuple[
Set['Action'], Set['Entity'], Set['Entity']]:
available_actions = set()
for action in self.actions:
if action.cool_down.name not in [effect.name for effect in self.effects.effects]:
available_actions.add(action)
# print(f'{self.name_color} has {[action.name for action in available_actions]}')
return available_actions, ally, enemy | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_available_actions(self):\n return self.actions",
"def get_actions(self):\n return []",
"def get_list_of_actions(self):\n return self.actions",
"def actions(self):\n return self._action_list",
"def get_available_actions(self, state):\n pass",
"def _get_actions(self):... | [
"0.88604504",
"0.8727885",
"0.8649391",
"0.8512479",
"0.8356988",
"0.8249469",
"0.8249469",
"0.8249469",
"0.8200832",
"0.80950415",
"0.80412275",
"0.7978333",
"0.7978333",
"0.7912648",
"0.7903887",
"0.7893374",
"0.78658706",
"0.77716225",
"0.77087396",
"0.7706551",
"0.7704463... | 0.0 | -1 |
Measure distance between two entities | def measure_distance(actor: Entity, target: Entity) -> int:
dst = int(actor is not target)
return dst | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def distance(self, other):\n ...",
"def dist(gene1, gene2):\n return abs(len(gene1.goal) - len(gene2.goal))",
"def _object_distance(self, object1, object2):\n return np.linalg.norm(np.array(object1) - np.array(object2))",
"def __distance_to(self, other: Any) -> float:\n return... | [
"0.7556397",
"0.74695444",
"0.74531186",
"0.7383299",
"0.7376668",
"0.7279911",
"0.72782665",
"0.72525454",
"0.72392297",
"0.72290546",
"0.72261333",
"0.7214202",
"0.7161101",
"0.7153692",
"0.7150545",
"0.7123836",
"0.7117742",
"0.71136373",
"0.71060133",
"0.7101069",
"0.7084... | 0.0 | -1 |
Return apitools message object for give message name. | def GetApiMessage(message_name):
messages = apis.GetMessagesModule(_BQ_API, _BQ_API_VERSION)
return getattr(messages, message_name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def msg(name):\n msg = Message.ByKeys(name)\n if msg is not None:\n txt = msg.message_ml\n if msg_is_ignored(name):\n txt = IGNORE_PREFIX + txt\n else:\n misc.cdblogv(misc.kLogErr, 0,\n \"bomcreator: could not find message '%s'\" % name)\n txt = n... | [
"0.69583714",
"0.65979904",
"0.64236474",
"0.62720525",
"0.62713873",
"0.625511",
"0.6236496",
"0.6140541",
"0.61393994",
"0.6108671",
"0.6034471",
"0.6006937",
"0.5988172",
"0.5965715",
"0.5953879",
"0.5941471",
"0.5921525",
"0.5919041",
"0.5918195",
"0.590729",
"0.5900649",... | 0.80781776 | 0 |
Builds a bigquery AccessValueListEntry array from input file. Expects YAML or JSON formatted file. | def PermissionsFileProcessor(input_file):
access_value_msg = GetApiMessage('Dataset').AccessValueListEntry
try:
permissions_array = []
permissions_from_file = yaml.load(input_file[0])
permissions_from_file = permissions_from_file.get('access', None)
if not permissions_from_file or not isinstance(permissions_from_file, list):
raise PermissionsFileError(
'Error parsing permissions file: no access list defined in file')
for access_yaml in permissions_from_file:
permission = encoding.PyValueToMessage(access_value_msg, access_yaml)
if _ValidatePermission(permission):
permissions_array.append(permission)
else:
raise PermissionsFileError(('Error parsing permissions file:'
' invalid permission definition'
' [{}]'.format(permission)))
return sorted(permissions_array, key=lambda x: x.role)
except yaml.YAMLParseError as ype:
raise PermissionsFileError('Error parsing permissions file [{}]'.format(
ype)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_from_file(self, file):\n self.value = []\n with open(file, \"r\") as f:\n fl = f.readlines()\n\n for l in fl:\n self.value.append([int(x) for x in l.split()])",
"def load_vals(txtfile):\n import ast\n \n data = []\n li = load_help(txtfile)\n ... | [
"0.56744987",
"0.5283599",
"0.5243404",
"0.5234778",
"0.5156196",
"0.51066506",
"0.5005265",
"0.5005265",
"0.49895862",
"0.4981226",
"0.49759138",
"0.49112916",
"0.49017558",
"0.48792005",
"0.48355103",
"0.48244855",
"0.48244855",
"0.48212677",
"0.4802652",
"0.47956467",
"0.4... | 0.5508567 | 1 |
Convert commandline duration into epoch timeoffset (in ms). | def ProcessTableExpiration(expire_duration):
t = times.GetDateTimePlusDuration(datetime.datetime.now(), expire_duration)
return int(time.mktime(t.timetuple())) * 1000 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_epoch_duration(self):\n\n now = time.time()\n epoch_duration = datetime.datetime.fromtimestamp(now - self.prev_time).strftime(\"%M:%S.%f\")[:-4]\n self.prev_time = now\n return epoch_duration",
"def ms2pts(ms, dt):\n return int(ms/dt)",
"def np_dt_epoch_msec(value):\n ... | [
"0.5740035",
"0.56960464",
"0.55968964",
"0.5498718",
"0.54860854",
"0.5484328",
"0.5429148",
"0.54070693",
"0.53953534",
"0.53865397",
"0.53487533",
"0.5276387",
"0.52748066",
"0.52547956",
"0.52436954",
"0.52381575",
"0.5197884",
"0.5156624",
"0.51419455",
"0.5118423",
"0.5... | 0.0 | -1 |
Convert Input JSON file into TableSchema message. | def BqTableSchemaFileProcessor(file_arg):
table_schema_type = GetApiMessage('TableSchema')
schema_field_type = GetApiMessage('TableFieldSchema')
try:
schema_json = yaml.load(file_arg)
schema_json = schema_json.get('schema', None)
if not schema_json or not isinstance(schema_json, list):
raise SchemaFileError(
'Error parsing schema file: no schema field list defined in file')
all_fields = []
for field in schema_json:
new_field = schema_field_type(name=field['name'],
type=field['type'],
mode=field.get('mode', 'NULLABLE'))
all_fields.append(new_field)
return table_schema_type(fields=sorted(all_fields, key=lambda x: x.name))
except yaml.YAMLParseError as ype:
raise SchemaFileError('Error parsing schema file [{}]'.format(ype))
except (AttributeError, KeyError) as e:
raise SchemaFileError(
'Error parsing schema file, invalid field definition [{}]'.format(e)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ReadSchemaFile(schema_file, bigquery_messages):\n\n if os.path.exists(schema_file):\n with open(schema_file, mode='r') as f:\n try:\n def UpperOrNone(string):\n return string and string.upper()\n field_schemas = [\n bigquery_messages.TableFieldSchema(\n ... | [
"0.6506698",
"0.6255999",
"0.6189637",
"0.59361964",
"0.5880678",
"0.5861754",
"0.5762274",
"0.56616706",
"0.56331164",
"0.5612857",
"0.55776805",
"0.5533528",
"0.55065984",
"0.55045223",
"0.548444",
"0.547434",
"0.54314774",
"0.53971493",
"0.5346988",
"0.5327368",
"0.5307453... | 0.60093594 | 3 |
Convert Input JSON file into TableSchema message. | def BqTableDataFileProcessor(file_arg):
data_insert_request_type = GetApiMessage('TableDataInsertAllRequest')
insert_row_type = data_insert_request_type.RowsValueListEntry
data_row_type = GetApiMessage('JsonObject')
try:
data_json = yaml.load(file_arg)
if not data_json or not isinstance(data_json, list):
raise TableDataFileError(
'Error parsing data file: no data records defined in file')
rows = []
for row in data_json:
rows.append(insert_row_type(json=encoding.DictToMessage(
row, data_row_type)))
return rows
except yaml.YAMLParseError as ype:
raise TableDataFileError('Error parsing data file [{}]'.format(ype)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ReadSchemaFile(schema_file, bigquery_messages):\n\n if os.path.exists(schema_file):\n with open(schema_file, mode='r') as f:\n try:\n def UpperOrNone(string):\n return string and string.upper()\n field_schemas = [\n bigquery_messages.TableFieldSchema(\n ... | [
"0.6506698",
"0.6255999",
"0.6189637",
"0.60093594",
"0.59361964",
"0.5880678",
"0.5861754",
"0.5762274",
"0.56616706",
"0.56331164",
"0.5612857",
"0.55776805",
"0.5533528",
"0.55065984",
"0.55045223",
"0.548444",
"0.547434",
"0.54314774",
"0.5346988",
"0.5327368",
"0.5307453... | 0.53971493 | 18 |
Set projectId value for a BigQueryXXXRequests. | def SetProjectId(ref, args, request):
del ref
project = args.project or properties.VALUES.core.project.Get(required=True)
project_ref = resources.REGISTRY.Parse(project,
collection='bigquery.projects')
request.projectId = project_ref.Name()
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_project_quotas(self, project_id, request_model, extra_headers=None,\n use_auth=True, user_name=None):\n resp = self.client.post(\n 'project-quotas/' + project_id,\n request_model=request_model,\n response_model_type=quota_models.ProjectQuota... | [
"0.61926836",
"0.6037495",
"0.5940458",
"0.58782727",
"0.58782727",
"0.5392154",
"0.53831047",
"0.5383003",
"0.5351515",
"0.5217758",
"0.52084017",
"0.51797605",
"0.51797605",
"0.51708114",
"0.5099718",
"0.5095747",
"0.5076841",
"0.50675255",
"0.50642264",
"0.5054526",
"0.504... | 0.7350548 | 0 |
Ensure that view parameters are set properly tables create request. | def SetViewParameters(ref, args, request):
del ref # unused
if not args.view:
request.table.view = None
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _create(self, tables, views, schema_name, config):\n if not isinstance(tables, dict):\n return False # Raise Exception That Tables Are In A Wrong Format???!!!\n success = True\n if schema_name is not None:\n self._create_schema(schema_name)\n for table_name_in... | [
"0.63214684",
"0.6122003",
"0.60363513",
"0.59719974",
"0.583535",
"0.5826202",
"0.5768594",
"0.57384115",
"0.55392927",
"0.55050695",
"0.54572743",
"0.54387593",
"0.5411729",
"0.53755325",
"0.53628856",
"0.5360331",
"0.5358349",
"0.53566074",
"0.53360575",
"0.5325151",
"0.53... | 0.65944326 | 0 |
Process the ifexists flag on datasets create. | def ProcessDatasetOverwrite(ref, args, request):
del ref
dataset_id = request.dataset.datasetReference.datasetId
project_id = request.projectId
if args.overwrite:
if _DatasetExists(dataset_id, project_id):
_TryDeleteDataset(dataset_id, project_id)
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def isExist(data):\n return True/False",
"def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True",
"def exist(self):",
"def run(**kwargs):\n del kwargs # Unused args\n if os.path.exists(DATASET_PATH):\n LOGGER.info('... Dataset already exists.... | [
"0.61832976",
"0.5865549",
"0.58427125",
"0.5761497",
"0.57018334",
"0.5658679",
"0.55542874",
"0.5486935",
"0.5465586",
"0.54652494",
"0.54532725",
"0.5452605",
"0.5446348",
"0.5409404",
"0.5387412",
"0.5352073",
"0.53434783",
"0.5338109",
"0.53380615",
"0.53380615",
"0.5296... | 0.5203899 | 32 |
Process the overwrite flag on tables create. | def ProcessTableOverwrite(ref, args, request):
dataset_id = ref.datasetId
table_id = ref.Name()
project_id = ref.projectId
if args.overwrite:
if _TableExists(dataset_id, table_id, project_id):
_TryDeleteTable(dataset_id, table_id, project_id)
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_tables_and_apply_patches(self):\n\n if self.authorized and not self.db_tables_initiated:\n with self.connection.cursor() as cursor:\n for statement in self.parse_mysql_sql_file():\n cursor.execute(statement)\n\n PyFunceble.LOGGER.info(\n... | [
"0.6433206",
"0.6371944",
"0.6202041",
"0.61849165",
"0.60638314",
"0.5852797",
"0.580371",
"0.5792183",
"0.5743237",
"0.5713558",
"0.5528236",
"0.5432233",
"0.54164076",
"0.5352115",
"0.5333362",
"0.5304936",
"0.52447927",
"0.5226724",
"0.52159977",
"0.52028906",
"0.5177918"... | 0.6969729 | 0 |
Process the overwrite flag on tables copy. | def ProcessTableCopyOverwrite(ref, args, request):
del ref # Unused
if args.overwrite:
request.job.configuration.copy.writeDisposition = 'WRITE_TRUNCATE'
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ProcessTableOverwrite(ref, args, request):\n dataset_id = ref.datasetId\n table_id = ref.Name()\n project_id = ref.projectId\n\n if args.overwrite:\n if _TableExists(dataset_id, table_id, project_id):\n _TryDeleteTable(dataset_id, table_id, project_id)\n\n return request",
"def process_override... | [
"0.67875683",
"0.5678444",
"0.5599842",
"0.55489415",
"0.53554213",
"0.52686346",
"0.52098215",
"0.5204137",
"0.51888007",
"0.51499987",
"0.5148369",
"0.5104553",
"0.5098129",
"0.5079654",
"0.50565994",
"0.50067544",
"0.49729812",
"0.4921561",
"0.49208447",
"0.49190444",
"0.4... | 0.8015918 | 0 |
Build JobConfigurationTableCopy from request resource args. | def ProcessTableCopyConfiguration(ref, args, request):
del ref # Unused
source_ref = args.CONCEPTS.source.Parse()
destination_ref = args.CONCEPTS.destination.Parse()
arg_utils.SetFieldInMessage(
request, 'job.configuration.copy.destinationTable.datasetId',
destination_ref.Parent().Name())
arg_utils.SetFieldInMessage(
request, 'job.configuration.copy.destinationTable.projectId',
destination_ref.projectId)
arg_utils.SetFieldInMessage(request,
'job.configuration.copy.destinationTable.tableId',
destination_ref.Name())
arg_utils.SetFieldInMessage(request,
'job.configuration.copy.sourceTable.datasetId',
source_ref.Parent().Name())
arg_utils.SetFieldInMessage(request,
'job.configuration.copy.sourceTable.projectId',
source_ref.projectId)
arg_utils.SetFieldInMessage(request,
'job.configuration.copy.sourceTable.tableId',
source_ref.Name())
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def GetTableCopyResourceArgs():\n table_spec_data = yaml_data.ResourceYAMLData.FromPath('bq.table')\n arg_specs = [\n resource_args.GetResourcePresentationSpec(\n verb='to copy from', name='source', required=True, prefixes=True,\n attribute_overrides={'table': 'source'}, positional=False,\... | [
"0.6806518",
"0.51471066",
"0.5135233",
"0.5034788",
"0.4957393",
"0.49131292",
"0.483293",
"0.4809419",
"0.47891185",
"0.47865072",
"0.4757659",
"0.46871853",
"0.46683812",
"0.46534342",
"0.46357578",
"0.46097738",
"0.45914286",
"0.45865327",
"0.457555",
"0.45609608",
"0.455... | 0.73063713 | 0 |
Process schema Updates (additions/mode changes) for the request. Retrieves the current table schema for ref and attempts to merge in the schema provided in the requests. This is necessary since the API backend does not handle PATCH semantics for schema updates (e.g. process the deltas) so we must always send the fully updated schema in the requests. | def ProcessSchemaUpdate(ref, args, request):
table = request.table
relaxed_columns = args.relax_columns
if not table.schema and not relaxed_columns: # if not updating schema,
return request # then just return.
original_schema = _TryGetCurrentSchema(ref.Parent().Name(),
ref.Name(),
ref.projectId)
new_schema_columns = table.schema
updated_fields = _GetUpdatedSchema(original_schema,
new_schema_columns,
relaxed_columns)
table_schema_type = GetApiMessage('TableSchema')
request.table.schema = table_schema_type(fields=updated_fields)
return request | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compute_schema_updates(self):\n data = self.client._perform_json(\n \"GET\", \"/projects/%s/recipes/%s/schema-update\" % (self.project_key, self.recipe_name))\n return RequiredSchemaUpdates(self, data)",
"async def upgradeSchema(self) -> None:",
"def merge_schema_entry(\n se... | [
"0.65370333",
"0.61016726",
"0.59257406",
"0.59054583",
"0.57786834",
"0.5593872",
"0.5549331",
"0.5481114",
"0.5472658",
"0.54690826",
"0.5401272",
"0.5361555",
"0.53470576",
"0.5315268",
"0.5254957",
"0.52487254",
"0.5139043",
"0.50770354",
"0.5074396",
"0.5061819",
"0.5033... | 0.8179473 | 0 |
Try to retrieve the current BigQuery TableSchema for a table_ref. Tries to fetch the schema of an existing table. Raises SchemaUpdateError if table is not found or if table is not of type 'TABLE'. | def _TryGetCurrentSchema(dataset_id, table_id, project_id):
client = GetApiClient()
service = client.tables
get_request_type = GetApiMessage('BigqueryTablesGetRequest')
get_request = get_request_type(datasetId=dataset_id,
tableId=table_id,
projectId=project_id)
try:
table = service.Get(get_request)
if not table or table.type != 'TABLE':
raise SchemaUpdateError('Schema modifications only supported '
'on TABLE objects received [{}]'.format(
table))
except apitools_exceptions.HttpNotFoundError:
raise SchemaUpdateError('Table with id [{}:{}:{}] not found.'.format(
project_id, dataset_id, table_id))
return table.schema | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_table_schema(dataset_id, table_id):\n logging.info('getting table schema')\n bigquery_client = bigquery.Client()\n dataset_ref = bigquery_client.dataset(dataset_id)\n bg_tableref = bigquery.table.TableReference(dataset_ref, table_id)\n bg_table = bigquery_client.get_table(bg_tableref)\n r... | [
"0.73889893",
"0.6379297",
"0.6305416",
"0.6051959",
"0.58043814",
"0.57696646",
"0.56733495",
"0.5627315",
"0.5534374",
"0.5378048",
"0.5363961",
"0.53382576",
"0.5309689",
"0.5298764",
"0.5259146",
"0.52387893",
"0.52369916",
"0.52243495",
"0.52111673",
"0.5200395",
"0.5174... | 0.74110204 | 0 |
Update original_schema by adding and/or relaxing mode on columns. | def _GetUpdatedSchema(
original_schema,
new_columns=None,
relaxed_columns=None):
orig_field_map = (
{f.name: f for f in original_schema.fields} if original_schema else {})
if relaxed_columns:
orig_field_map = _GetRelaxedCols(relaxed_columns, orig_field_map)
if new_columns:
orig_field_map = _AddNewColsToSchema(new_columns.fields, orig_field_map)
return sorted(orig_field_map.values(), key=lambda x: x.name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _GetRelaxedCols(relaxed_columns, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for col in relaxed_columns:\n if col in orig_schema_map:\n updated_schema_map[col].mode = 'NULLABLE'\n else:\n raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)\n return updated_schema_ma... | [
"0.7231359",
"0.7089279",
"0.65710247",
"0.6482866",
"0.64562935",
"0.61638325",
"0.61030746",
"0.5923907",
"0.5808623",
"0.5721755",
"0.56536114",
"0.56280774",
"0.56276286",
"0.5590315",
"0.5581879",
"0.55440784",
"0.5543209",
"0.55420613",
"0.5536027",
"0.55306125",
"0.550... | 0.6559085 | 3 |
Change mode to `NULLABLE` for columns in existing schema. Tries set mode on existing columns in orig_schema_map to `NULLABLE`. Raises SchemaUpdateError if column is not found in orig_schema_map. | def _GetRelaxedCols(relaxed_columns, orig_schema_map):
updated_schema_map = orig_schema_map.copy()
for col in relaxed_columns:
if col in orig_schema_map:
updated_schema_map[col].mode = 'NULLABLE'
else:
raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)
return updated_schema_map | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def merge_mode(self, old_schema_entry, new_schema_entry, base_path):\n old_info = old_schema_entry['info']\n new_info = new_schema_entry['info']\n old_mode = old_info['mode']\n old_name = old_info['name']\n old_type = old_info['type']\n old_status = old_schema_entry['statu... | [
"0.581769",
"0.5178056",
"0.5142687",
"0.5107475",
"0.50148743",
"0.4938137",
"0.49304643",
"0.4709507",
"0.4704251",
"0.4693166",
"0.46439534",
"0.460573",
"0.45949084",
"0.4564342",
"0.45579243",
"0.44939494",
"0.4487079",
"0.44671857",
"0.44571728",
"0.44475183",
"0.442848... | 0.637235 | 0 |
Add new columns to an existing schema. Tries add new fields to an existing schema. Raises SchemaUpdateError if column already exists in the orig_schema_map. | def _AddNewColsToSchema(new_fields, orig_schema_map):
updated_schema_map = orig_schema_map.copy()
for new_field in new_fields:
if new_field.name in orig_schema_map:
raise SchemaUpdateError(_INVALID_SCHEMA_UPDATE_MESSAGE)
updated_schema_map[new_field.name] = new_field
return updated_schema_map | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_column(self, schema):\n self[schema.name] = schema.copy()",
"def _add_to_schema(self, new: dict):\n self._defaults.update(new)\n self._migrate()",
"def _GetRelaxedCols(relaxed_columns, orig_schema_map):\n updated_schema_map = orig_schema_map.copy()\n for col in relaxed_columns:\n... | [
"0.6689222",
"0.6531303",
"0.60537446",
"0.6039341",
"0.60350144",
"0.5883875",
"0.5845651",
"0.5813085",
"0.5690668",
"0.5641946",
"0.56057465",
"0.54915494",
"0.54909086",
"0.5434344",
"0.542425",
"0.5340224",
"0.53072643",
"0.5284575",
"0.52605635",
"0.5229555",
"0.5223570... | 0.82155335 | 0 |
Validate a resource of the given type with specified ID already exists. | def _DatasetExists(dataset_id, project_id):
client = GetApiClient()
service = client.datasets
get_request_type = GetApiMessage('BigqueryDatasetsGetRequest')
get_request = get_request_type(datasetId=dataset_id, projectId=project_id)
try:
service.Get(get_request)
return True
except apitools_exceptions.HttpNotFoundError:
log.info('Dataset with id [{}:{}] not found.'.format(
project_id, dataset_id))
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_id_already_exists(self) -> None:\n with pytest.raises(IntegrityError):\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\n 'description': 'A new filter type.'})",
"def check_id(self, id):",
"def testValidateId(self):\n ... | [
"0.6422405",
"0.64173734",
"0.6142269",
"0.61312246",
"0.5939884",
"0.5908327",
"0.5880398",
"0.5806814",
"0.577634",
"0.5734848",
"0.5730072",
"0.56382006",
"0.55637",
"0.5501549",
"0.5488068",
"0.5485431",
"0.5476124",
"0.5466836",
"0.54339",
"0.5411698",
"0.5398409",
"0.... | 0.0 | -1 |
Validate a resource of the given type with specified ID already exists. | def _TableExists(dataset_id, table_id, project_id):
client = GetApiClient()
service = client.tables
get_request_type = GetApiMessage('BigqueryTablesGetRequest')
get_request = get_request_type(datasetId=dataset_id, tableId=table_id,
projectId=project_id)
try:
service.Get(get_request)
return True
except apitools_exceptions.HttpNotFoundError:
log.info('Table with id [{}:{}:{}] not found.'.format(
project_id, dataset_id, table_id))
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_id_already_exists(self) -> None:\n with pytest.raises(IntegrityError):\n ObservationType.add({'id': 1, 'name': 'New Type', 'units': 'Kilo-Frobnicate',\n 'description': 'A new filter type.'})",
"def check_id(self, id):",
"def testValidateId(self):\n ... | [
"0.6422405",
"0.64173734",
"0.6142269",
"0.61312246",
"0.5939884",
"0.5908327",
"0.5880398",
"0.5806814",
"0.577634",
"0.5734848",
"0.5730072",
"0.56382006",
"0.55637",
"0.5501549",
"0.5488068",
"0.5485431",
"0.5476124",
"0.5466836",
"0.54339",
"0.5411698",
"0.5398409",
"0.... | 0.0 | -1 |
Try to delete a dataset, propagating error on failure. | def _TryDeleteDataset(dataset_id, project_id):
client = GetApiClient()
service = client.datasets
delete_request_type = GetApiMessage('BigqueryDatasetsDeleteRequest')
delete_request = delete_request_type(datasetId=dataset_id,
projectId=project_id,
deleteContents=True)
service.Delete(delete_request)
log.info('Deleted dataset [{}:{}]'.format(project_id, dataset_id)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_dataset(self, dataset):\n raise NotImplementedError('delete_dataset')",
"def _handle_creation_failure(session: Session, stub_dataset: Dataset, error: str):\n try:\n dataset.delete(session, stub_dataset)\n except requests.HTTPError:\n raise CreationFailure(\n f\"Cr... | [
"0.7605005",
"0.7107175",
"0.70523417",
"0.69809973",
"0.6883148",
"0.6740322",
"0.6667521",
"0.65653944",
"0.6536053",
"0.65328515",
"0.65034896",
"0.6410687",
"0.6386324",
"0.6328574",
"0.63253295",
"0.62904114",
"0.6277353",
"0.62735856",
"0.6252367",
"0.61857146",
"0.6168... | 0.74737805 | 1 |
Try to delete a dataset, propagating error on failure. | def _TryDeleteTable(dataset_id, table_id, project_id):
client = GetApiClient()
service = client.tables
delete_request_type = GetApiMessage('BigqueryTablesDeleteRequest')
delete_request = delete_request_type(datasetId=dataset_id, tableId=table_id,
projectId=project_id)
service.Delete(delete_request)
log.info('Deleted table [{}:{}:{}]'.format(project_id, dataset_id, table_id)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_dataset(self, dataset):\n raise NotImplementedError('delete_dataset')",
"def _TryDeleteDataset(dataset_id, project_id):\n client = GetApiClient()\n service = client.datasets\n delete_request_type = GetApiMessage('BigqueryDatasetsDeleteRequest')\n delete_request = delete_request_type(dataset... | [
"0.7605005",
"0.74737805",
"0.7107175",
"0.70523417",
"0.69809973",
"0.6883148",
"0.6740322",
"0.6667521",
"0.65653944",
"0.6536053",
"0.65328515",
"0.65034896",
"0.6410687",
"0.6386324",
"0.6328574",
"0.63253295",
"0.62904114",
"0.6277353",
"0.62735856",
"0.6252367",
"0.6185... | 0.52461874 | 96 |
Get Table resource args (source, destination) for copy command. | def GetTableCopyResourceArgs():
table_spec_data = yaml_data.ResourceYAMLData.FromPath('bq.table')
arg_specs = [
resource_args.GetResourcePresentationSpec(
verb='to copy from', name='source', required=True, prefixes=True,
attribute_overrides={'table': 'source'}, positional=False,
resource_data=table_spec_data.GetData()),
resource_args.GetResourcePresentationSpec(
verb='to copy to', name='destination',
required=True, prefixes=True,
attribute_overrides={'table': 'destination'}, positional=False,
resource_data=table_spec_data.GetData())]
fallthroughs = {
'--source.dataset': ['--destination.dataset'],
'--destination.dataset': ['--source.dataset']
}
return [concept_parsers.ConceptParser(arg_specs, fallthroughs)] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ProcessTableCopyConfiguration(ref, args, request):\n del ref # Unused\n source_ref = args.CONCEPTS.source.Parse()\n destination_ref = args.CONCEPTS.destination.Parse()\n arg_utils.SetFieldInMessage(\n request, 'job.configuration.copy.destinationTable.datasetId',\n destination_ref.Parent().Name(... | [
"0.62132674",
"0.56889355",
"0.55710876",
"0.55588037",
"0.5540921",
"0.54608697",
"0.54608697",
"0.54608697",
"0.53417224",
"0.5325953",
"0.52964944",
"0.52829",
"0.5282849",
"0.52788526",
"0.52047265",
"0.52009565",
"0.51657414",
"0.51652837",
"0.516145",
"0.5143834",
"0.51... | 0.8508633 | 0 |
Print a simple greeting to each user in the list. | def greet_users(names):
for name in names:
msg = "Hello, " + name.title() + "!"
print(msg) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def greet_users(names):\n for name in names:\n print(f\"Hello, {name.title()}!\")",
"def greeting(list_of_guests):\r\n for i in list_of_guests: \r\n print('Witaj ' + i)",
"def greet_users(names):\n for name in names:\n msg = f\"Hello, {name.title()}\"\n print(msg)",
"... | [
"0.7734112",
"0.77260417",
"0.77145106",
"0.76987046",
"0.76987046",
"0.7657923",
"0.7309932",
"0.7257354",
"0.72450185",
"0.71396",
"0.7127663",
"0.71238464",
"0.70934796",
"0.70934796",
"0.7048947",
"0.70248073",
"0.69579583",
"0.69458425",
"0.6898827",
"0.6775238",
"0.6753... | 0.7734813 | 1 |
Return a full name, neatly formatted. | def get_formatted_name(first_name, last_name, middle_name=''):
if middle_name:
full_name = first_name + ' ' + middle_name + ' ' + last_name
else:
full_name = first_name + ' ' + last_name
return full_name.title() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_full_name(self):\n full_name = '{0} {1} {2}'.format(self.last_name, self.first_name, self.patronymic)\n return full_name.strip()",
"def get_full_name(self):\n\t\tfull_name = '%s %s' % (self.first_name, self.last_name)\n\t\treturn full_name.strip()",
"def get_full_name(self):\r\n fu... | [
"0.87166595",
"0.86399925",
"0.860218",
"0.860218",
"0.8595642",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"0.8579464",
"... | 0.8130383 | 83 |
Return a dictionary of information about a person. | def build_person(first_name, last_name, age=''):
person = {'first': first_name, 'last': last_name}
if age:
person['age'] = age
return person | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_person(self):\n person_dict = {\n 'firstname': self.__firstname,\n 'lastname': self.__lastname,\n 'height': self.__height,\n 'weight': self.__weight,\n 'age': self.__age\n }\n return person_dict",
"def who_am_i():\n return {'n... | [
"0.78430605",
"0.69874537",
"0.68447304",
"0.67983556",
"0.6684294",
"0.6533277",
"0.64916706",
"0.6416313",
"0.64020026",
"0.63483405",
"0.63206047",
"0.62963533",
"0.6294688",
"0.6291786",
"0.6261915",
"0.6250636",
"0.62482584",
"0.62299424",
"0.62139595",
"0.61749566",
"0.... | 0.58440995 | 48 |
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