= time[1]:\\n table[day].insert(0, to_insert)\\n\\n else:\\n # inserting during the day\\n for i in range(len(table[day]) - 1):\\n if table[day][i][1] <= time[0] and table[day][i + 1][0] >= time[1]:\\n table[day].insert(i + 1, to_insert)\\n break\\n\\n # inserting at end of day\\n else:\\n if table[day][-1][1] <= time[0]:\\n table[day].append(to_insert)\\n else:\\n raise NotFit()\\n\\n table.sections.append([section])\\n\\n return table\",\n \"def check_time(self,data,data_orginal):\\n if data['start_time'] > data['end_time']:\\n raise ValidationError('event end time should be greater than start time.')\",\n \"def _validate_time_fields(cls, item):\\n if item.time_started_msec and (\\n item.time_queued_msec > item.time_started_msec):\\n cls._add_error(\\n 'time queued check',\\n 'Entity id %s: time queued %s is greater '\\n 'than time started %s' % (\\n item.id, item.time_queued_msec, item.time_started_msec))\\n\\n if item.time_finished_msec and (\\n item.time_started_msec > item.time_finished_msec):\\n cls._add_error(\\n 'time started check',\\n 'Entity id %s: time started %s is greater '\\n 'than time finished %s' % (\\n item.id, item.time_started_msec, item.time_finished_msec))\\n\\n current_time_msec = utils.get_current_time_in_millisecs()\\n if item.time_finished_msec > current_time_msec:\\n cls._add_error(\\n 'time finished check',\\n 'Entity id %s: time finished %s is greater '\\n 'than the current time' % (\\n item.id, item.time_finished_msec))\",\n \"def filter_dt(tp,ts, show_plot, lower_delta,min_len):\\n import numpy\\n import matplotlib.pyplot as plt\\n ####################################\\n def array_none_removal(array_dt):\\n output=[]\\n for index in range(len(array_dt)):\\n if array_dt[index]!=None:\\n output.append(array_dt[index])\\n return(output)\\n \\n ####################################\\n # Calculate delta t based in P and S1 arrival\\n delta_t=[]\\n for gph_index in range(len(tp)):\\n # verify is the pp and sp1 are NOT nan\\n if tp[gph_index]!=None and ts[gph_index]!=None:\\n #if (not math.isnan(tp[gph_index])) and (not math.isnan(ts[gph_index])):\\n delta_t.append(ts[gph_index]-tp[gph_index])\\n else:\\n delta_t.append(None)\\n\\n ####################################\\n #%% Filter delta_t\\n \\n # Remove Nones from delta t to calculate its stats\\n dt_numbers=array_none_removal(delta_t)\\n dt_numbers=list(filter(lambda x:x>0.25, dt_numbers)) # remove values lower than 0.2\\n \\n # Build the new delta_t array with outliers removed\\n dt_filtered=[]\\n \\n for dt_index in range(len(delta_t)):\\n if delta_t[dt_index]!= None:\\n if delta_t[dt_index] <= (numpy.median(dt_numbers)+numpy.std(dt_numbers)) and delta_t[dt_index] >= (numpy.median(dt_numbers)-numpy.std(dt_numbers)) and delta_t[dt_index]>=lower_delta:\\n dt_filtered.append(delta_t[dt_index])\\n else:\\n dt_filtered.append(None)\\n else:\\n dt_filtered.append(None)\\n \\n dt_filtered_numbers=array_none_removal(dt_filtered)\\n #print('Len filtered ',len(dt_filtered_numbers))\\n \\n ####################################\\n if show_plot==True:# and len(dt_filtered_numbers)>=min_len: \\n plt.figure(1, figsize=(8,1))\\n plt.plot(dt_filtered,'.k')\\n plt.axhline(y=numpy.median(dt_numbers),c='g', linestyle='--')#, lw=0.5)\\n plt.axhline(y=numpy.median(dt_numbers)+numpy.std(dt_numbers),c='r', linestyle=':')#, lw=0.5)\\n plt.axhline(y=numpy.median(dt_numbers)-numpy.std(dt_numbers),c='r', linestyle=':')#,lw=0.5)\\n plt.ylim(0.5,1.5)\\n plt.xlabel('Gph id')\\n plt.ylabel('ts -tp (s)')\\n plt.title('ATP ts-tp') \\n plt.show()\\n plt.close()\\n #################################### \\n return(dt_filtered,dt_filtered_numbers)\",\n \"def validate(self, data):\\n l = len(data[\\\"start_times\\\"])\\n for i in range(l):\\n if data[\\\"start_times\\\"][i]>=data['end_times'][i]:\\n raise serializers.ValidationError(\\\"Start times should come before end times\\\") \\n return data\",\n \"def sort_restos(filtered_table):\\n\\tdf = pd.DataFrame(filtered_table).T\\n\\tdf = df.sort(columns=columns['time_to_resto'])\\n\\n\\treturn df.index\",\n \"def times_to_axis(times):\\r\\n #Hour mode if there are 24 times and no date information\\r\\n hour_mode = len(times) == 24 and np.all(times[:, 0:3] == 0)\\r\\n \\r\\n #If hour mode, convert to 24-hour strings\\r\\n if hour_mode:\\r\\n axis_times = [hour_format.format(*time[3:5])\\r\\n for time in times]\\r\\n #Else, convert times to \\\"datetime\\\" objects\\r\\n else:\\r\\n axis_times = [datetime.strptime(date_format.format(*time), \\r\\n \\\"%Y-%m-%dT%H:%M:%S\\\")\\r\\n for time in times]\\r\\n\\r\\n #Return converted times and whether times are in hour mode\\r\\n return (axis_times, hour_mode)\",\n \"def is_data(i):\\n keys = ['_id', '_time']\\n return all(i != k for k in keys)\",\n \"def get_time_cols(self):\\n # Retrieve first column only\\n time_cols = list()\\n n = self.col_count\\n for i in range(n): # check every column/attribute for time format\\n row_data = str(self.data[0][i])\\n try:\\n time_ok, t_stamp = DataGP.test_time(row_data)\\n if time_ok:\\n time_cols.append(i)\\n except ValueError:\\n continue\\n return np.array(time_cols)\",\n \"def split_by_timegap(X, timename='time', hours=1):\\n \\n time = X[timename].values\\n dt = np.diff(time)\\n\\n # print(len(time))\\n \\n i = [int(ii) for ii in np.where(dt>np.timedelta64(hours, 'h'))[0]] + [len(time)-1]\\n i = [-1] + list(set(i))\\n i.sort()\\n \\n # print('Split index')\\n # print(i)\\n \\n Xs = [X.isel({timename: np.arange(i[j]+1, i[j+1])}) for j in np.arange(0, len(i)-1)]\\n \\n return Xs\",\n \"def sort_time(self):\\n self.entries.sort(key=lambda x: x.date_stamp_utc)\",\n \"def _type_data(self, row, index):\\n typed_row = []\\n for i, (entry, entry_type) in enumerate(zip(row, self.column_types)):\\n try:\\n typed_row.append(entry_type(entry))\\n except ValueError:\\n if (entry_type == int or entry_type == float) and self.missing_to_zero:\\n typed_row.append(entry_type(0))\\n else:\\n if [i + 1, index + 2, entry, entry_type] not in self.invalid_typed and self.print_warnings:\\n self.invalid_typed.append([i + 1, index + 2, entry, entry_type])\\n typed_row.append(entry)\\n return typed_row\",\n \"def convert_to_fixed_timesteps(trajectories, timestep_size=60):\\n\\n def time_to_timestep(row):\\n h, m, s = map(int, row[\\\"Time\\\"].split(':'))\\n timestep = round((h*3600+m*60+s)/timestep_size)\\n return timestep\\n\\n for i, t in trajectories.items():\\n t[\\\"Timestep\\\"] = t.apply(time_to_timestep, axis=1)\\n t = t.drop_duplicates(\\\"Timestep\\\")\\n t = t.set_index(\\\"Timestep\\\")\\n trajectories[i] = t\\n \\n return trajectories\",\n \"def sum_time_cells(self, column_time, column_hold):\\n column_sum = []\\n for row in range(0, (len(column_time))):\\n cell_sum = column_time[row] + column_hold[row]\\n column_sum.append(cell_sum)\\n return column_sum\",\n \"def update_data(self, data):\\n start_time = data.index[-1].strftime(\\\"%Y-%m-%dT%H:%M:%S.000000Z\\\")\\n temp_data = self.gather_data(start=start_time)\\n temp_data = self._list_to_df(temp_data)\\n if (len(temp_data) > 1):\\n # temp_data[0] is the same as data[-1]\\n out_data = data.append(temp_data[1:])\\n return out_data\",\n \"def clean_types(data: Iterable[dict]) -> List[dict]:\\n data_copy = []\\n for row in data:\\n row_copy = {}\\n for col, val in row.items():\\n if type(val) == date:\\n row_copy[col] = datetime.combine(val, time())\\n elif type(val) == list:\\n if not val:\\n row_copy[col] = None\\n else:\\n row_copy[col] = ','.join(str(el) if el is not None else 'NULL' for el in val)\\n elif type(val) == dict:\\n row_copy[col] = str(val)\\n else:\\n row_copy[col] = val\\n\\n data_copy.append(row_copy)\\n\\n return data_copy\",\n \"def with_time(self):\\n if self.time_slices is None:\\n raise FeatureError(\\\"Feature has no time reference.\\\")\\n\\n for i, datum in enumerate(self.data[self.name]):\\n yield (self.time_slices[i], datum)\",\n \"def test_no_timestamp(self):\\n self.assertRaises(PyntsError, extract_columns, self.data[['a', 'b']], ['a'], ['timestamp'])\",\n \"def import_swipe_data(filename):\\n\\t# initialize date dictionary\\n\\tdate_dict = {'1':'Jan', '2':'Feb', '3':'Mar', '4':'Apr', '5':'May',\\n\\t\\t'6':'Jun', '7':'Jul', '8':'Aug', '9':'Sept', '10':'Oct',\\n\\t\\t'11':'Nov', '12':'Dec'}\\n\\t# read in swipe report data and rename columns\\n\\tswipe_df = pd.read_csv(filename, usecols=['Textbox20',\\n\\t\\t'Textbox12', 'Textbox14', 'Type'])\\n\\tswipe_df = swipe_df.rename(index=int, columns={\\n\\t\\t\\\"Textbox20\\\": \\\"ID\\\", \\\"Textbox12\\\": \\\"date\\\",\\n\\t\\t\\\"Textbox14\\\": \\\"swipe_time\\\"})\\n\\t# keep only student ID number in ID column\\n\\tswipe_df['ID'] = swipe_df['ID'].apply(lambda x: int(x.split(\\\" \\\")[0]))\\n\\tdrop_list = []\\n\\tfor row in swipe_df.itertuples():\\n\\t\\tindex, time = row[0], row[3]\\n\\t\\th, m, s = time.split(\\\":\\\")\\n\\t\\tcut_off = int(h+m)\\n\\t\\t# count only students swiping between 900-1030am\\n\\t\\tif (cut_off < 900) or (cut_off > 1030):\\n\\t\\t\\tdrop_list.append(index)\\n\\t\\t\\tswipe_df1 = swipe_df.drop(drop_list)\\n\\tswipe_df1.set_index('ID', inplace=True)\\n\\t# initialize defualt dictionaries to put indiv. data into single row\\n\\td_date = defaultdict(list)\\n\\td_time = defaultdict(list)\\n\\tfor t in swipe_df1.itertuples():\\n\\t\\ti, d, s, x = t\\n\\t\\t# rename dates and append\\n\\t\\tmonth = date_dict[d[0]]\\n\\t\\tday = d.split('/')\\n\\t\\tfinal_date = month + \\\" \\\" + day[1]\\n\\t\\td_date[i].append(final_date)\\n\\t\\t# truncate times and append\\n\\t\\thrs, mins, sec = s.split(\\\":\\\")\\n\\t\\tfinal_time = hrs + \\\":\\\" + mins + \\\" \\\" + \\\"AM\\\"\\t\\t\\n\\t\\td_time[i].append(final_time)\\n\\t# make values a string\\n\\td_date = str_list(d_date)\\n\\td_time = str_list(d_time)\\n\\t# put into data frames\\n\\tdf_date = pd.DataFrame.from_dict(d_date, orient='index')\\n\\tdf_time = pd.DataFrame.from_dict(d_time, orient='index')\\n\\tfinal_swipe_df = pd.merge(df_date, df_time, left_index=True, \\n\\t\\tright_index=True)\\n\\t# rename columns\\n\\tfinal_swipe_df = final_swipe_df.rename(index=int, \\n\\t\\tcolumns={\\\"0_x\\\": \\\"late_date\\\", \\\"0_y\\\":\\\"late_time\\\"})\\n\\n\\treturn final_swipe_df\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.62110686","0.5617712","0.5604052","0.55013937","0.5485576","0.54825485","0.5480284","0.53317887","0.5248092","0.5174748","0.5161101","0.51461595","0.51112086","0.51031595","0.50956035","0.50943315","0.5072948","0.5051467","0.49987826","0.4959382","0.4954812","0.49388316","0.49366808","0.49317747","0.49240822","0.49146155","0.48880044","0.48789334","0.48692712","0.48650798","0.486249","0.48569593","0.4845104","0.48440167","0.48161244","0.480984","0.4807167","0.47774404","0.47614393","0.47552708","0.4753312","0.47348666","0.47314203","0.4722699","0.47105026","0.47095594","0.4703562","0.46924928","0.46750173","0.46739215","0.46671063","0.46549153","0.46283227","0.46247247","0.46174413","0.46133375","0.46116102","0.46078357","0.460563","0.46001187","0.45991805","0.459874","0.45927837","0.45894432","0.45810354","0.45793483","0.45786175","0.45729113","0.45614257","0.45575207","0.45570996","0.45540887","0.45531496","0.45485425","0.45474565","0.45452285","0.4542567","0.45362636","0.45274734","0.45252386","0.45176816","0.4515006","0.45135835","0.45108896","0.45092013","0.4507223","0.45056975","0.44994926","0.44846648","0.44838113","0.4480868","0.44805315","0.44713137","0.44712695","0.4469608","0.44670266","0.44602835","0.445977","0.44547462","0.4454079","0.4452103"],"string":"[\n \"0.62110686\",\n \"0.5617712\",\n \"0.5604052\",\n \"0.55013937\",\n \"0.5485576\",\n \"0.54825485\",\n \"0.5480284\",\n \"0.53317887\",\n \"0.5248092\",\n \"0.5174748\",\n \"0.5161101\",\n \"0.51461595\",\n \"0.51112086\",\n \"0.51031595\",\n \"0.50956035\",\n \"0.50943315\",\n \"0.5072948\",\n \"0.5051467\",\n \"0.49987826\",\n \"0.4959382\",\n \"0.4954812\",\n \"0.49388316\",\n \"0.49366808\",\n \"0.49317747\",\n \"0.49240822\",\n \"0.49146155\",\n \"0.48880044\",\n \"0.48789334\",\n \"0.48692712\",\n \"0.48650798\",\n \"0.486249\",\n \"0.48569593\",\n \"0.4845104\",\n \"0.48440167\",\n \"0.48161244\",\n \"0.480984\",\n \"0.4807167\",\n \"0.47774404\",\n \"0.47614393\",\n \"0.47552708\",\n \"0.4753312\",\n \"0.47348666\",\n \"0.47314203\",\n \"0.4722699\",\n \"0.47105026\",\n \"0.47095594\",\n \"0.4703562\",\n \"0.46924928\",\n \"0.46750173\",\n \"0.46739215\",\n \"0.46671063\",\n \"0.46549153\",\n \"0.46283227\",\n \"0.46247247\",\n \"0.46174413\",\n \"0.46133375\",\n \"0.46116102\",\n \"0.46078357\",\n \"0.460563\",\n \"0.46001187\",\n \"0.45991805\",\n \"0.459874\",\n \"0.45927837\",\n \"0.45894432\",\n \"0.45810354\",\n \"0.45793483\",\n \"0.45786175\",\n \"0.45729113\",\n \"0.45614257\",\n \"0.45575207\",\n \"0.45570996\",\n \"0.45540887\",\n \"0.45531496\",\n \"0.45485425\",\n \"0.45474565\",\n \"0.45452285\",\n \"0.4542567\",\n \"0.45362636\",\n \"0.45274734\",\n \"0.45252386\",\n \"0.45176816\",\n \"0.4515006\",\n \"0.45135835\",\n \"0.45108896\",\n \"0.45092013\",\n \"0.4507223\",\n \"0.45056975\",\n \"0.44994926\",\n \"0.44846648\",\n \"0.44838113\",\n \"0.4480868\",\n \"0.44805315\",\n \"0.44713137\",\n \"0.44712695\",\n \"0.4469608\",\n \"0.44670266\",\n \"0.44602835\",\n \"0.445977\",\n \"0.44547462\",\n \"0.4454079\",\n \"0.4452103\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":10691,"cells":{"query":{"kind":"string","value":"ExportResponseMetadata a model defined in Swagger"},"document":{"kind":"string","value":"def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\n\n self._export_host = None\n self._export_date = None\n self._requested_object_list = None\n self._exported_object_list = None\n self.discriminator = None\n\n if export_host is not None:\n self.export_host = export_host\n if export_date is not None:\n self.export_date = export_date\n if requested_object_list is not None:\n self.requested_object_list = requested_object_list\n if exported_object_list is not None:\n self.exported_object_list = exported_object_list"},"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":["async def get_model_metadata(\n self,\n model_name: str,\n model_version: str = ...,\n headers: dict[str, t.Any] = ...,\n as_json: t.Literal[False] = ...,\n ) -> service_pb2.ModelMetadataResponse:","def api_documentation(api: str, summary: str, in_model: BaseModel,\n out_model: BaseModel, out_description: str) -> Callable:\n for model, name in ((in_model, 'Input'), (out_model, 'Output')):\n doc.Object(\n make_dataclass(\n f'Api{api[1:].title()}{name}',\n [(key, val.type_, val.type_)\n for key, val in model.__dict__['__fields__'].items()]))\n im_returns = doc.JsonBody({\n key: val.type_\n for key, val in in_model.__dict__['__fields__'].items()\n })\n\n om_returns = {\n key: val.type_\n for key, val in out_model.__dict__['__fields__'].items()\n }\n\n def decorator(func):\n @doc.summary(summary)\n @doc.response(412,\n 'Error: Precondition Failed',\n description='The passed request-parameters are invalid')\n @doc.response(500,\n 'Error: Server-Error occured',\n description='An internal error occured')\n @doc.consumes(im_returns,\n content_type='application/json',\n location='body')\n @doc.produces(om_returns,\n content_type='application/json',\n description=out_description)\n @wraps(func)\n async def function_wrapper(request, *args, **kwargs):\n return await func(request=request, *args, **kwargs)\n\n return function_wrapper\n\n return decorator","def to_dict(self):\n result = {}\n\n for attr, _ in six.iteritems(self.swagger_types):\n value = getattr(self, attr)\n if isinstance(value, list):\n result[attr] = list(map(\n lambda x: x.to_dict() if hasattr(x, \"to_dict\") else x,\n value\n ))\n elif hasattr(value, \"to_dict\"):\n result[attr] = value.to_dict()\n elif isinstance(value, dict):\n result[attr] = dict(map(\n lambda item: (item[0], item[1].to_dict())\n if hasattr(item[1], \"to_dict\") else item,\n value.items()\n ))\n else:\n result[attr] = value\n if issubclass(ExportResponseMetadata, dict):\n for key, value in self.items():\n result[key] = value\n\n return result","def export_model(self):\n\n model_pkg = dict()\n\n for k, v in self.__dict__.items():\n if k not in ['datas'] and not k.startswith('_'):\n model_pkg[k] = v\n\n for i in range(len(self.datas)):\n for k, v in self.datas[i].__dict__.items():\n model_pkg['datas_%d_%s' % (i, k)] = v\n\n return model_pkg","def GetModelOutputInfo(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def make_response(self):\n params = {\n 'tweet.fields': 'created_at,public_metrics,entities',\n 'expansions': 'author_id',\n 'user.fields': 'description'\n }\n return self.response_limit(params)","def test_metadata(self):\n class ExampleView(views.APIView):\n \"\"\"Example view.\"\"\"\n pass\n\n view = ExampleView.as_view()\n response = view(request=request)\n expected = {\n 'name': 'Example',\n 'description': 'Example view.',\n 'renders': [\n 'application/json',\n 'text/html'\n ],\n 'parses': [\n 'application/json',\n 'application/x-www-form-urlencoded',\n 'multipart/form-data'\n ]\n }\n assert response.status_code == status.HTTP_200_OK\n assert response.data == expected","def metadata(self) -> 'outputs.DataCollectionEndpointResponseMetadata':\n return pulumi.get(self, \"metadata\")","def get_metadata_v2(session):\n LOG.debug(\"Exporting metadata for SFS augur build\")\n\n metadata = datastore.fetch_rows_from_table(session, (\"shipping\", \"metadata_for_augur_build_v2\"))\n\n return Response((row[0] + '\\n' for row in metadata), mimetype=\"application/x-ndjson\")","def metadata():\n req = prepare_onelogin_request(request)\n saml_auth = init_saml_auth(req)\n settings = saml_auth.get_settings()\n metadata = settings.get_sp_metadata()\n errors = settings.validate_metadata(metadata)\n\n if len(errors) == 0:\n resp = make_response(metadata, 200)\n resp.headers[\"Content-Type\"] = \"text/xml\"\n else:\n resp = make_response(\", \".join(errors), 500)\n return resp","def __metadata__(self):\n raise NotImplementedError","def metadata():\n req = prepare_flask_request(request)\n auth = init_saml_auth(req)\n settings = auth.get_settings()\n sp_metadata = settings.get_sp_metadata()\n errors = settings.validate_metadata(sp_metadata)\n\n if len(errors) == 0:\n resp = make_response(sp_metadata, 200)\n resp.headers[\"Content-Type\"] = \"text/xml\"\n else:\n resp = make_response(\", \".join(errors), 500)\n return resp","def metadata(self) -> global___SummaryMetadata:","def metadata(self): # -> None:\n ...","def GetMetadata(self):\n return self.dict['meta']","def _create_output_metadata(self):\n\n # Create output info.\n output_meta = _metadata_fb.TensorMetadataT()\n output_meta.name = \"probability\"\n output_meta.description = \"Probabilities of labels respectively.\"\n output_meta.content = _metadata_fb.ContentT()\n output_meta.content.contentProperties = _metadata_fb.FeaturePropertiesT()\n output_meta.content.contentPropertiesType = (\n _metadata_fb.ContentProperties.FeatureProperties)\n label_file = _metadata_fb.AssociatedFileT()\n label_file.name = os.path.basename(self.model_info.label_file)\n label_file.description = (\"Labels for classification categories.\")\n label_file.type = _metadata_fb.AssociatedFileType.TENSOR_AXIS_LABELS\n output_meta.associatedFiles = [label_file]\n return [output_meta]","def fetch_ml_model_info() -> ApiResponse:\n return _api_response(settings.ML_MODELS)","def model(self) -> 'outputs.ModelDefinitionResponse':\n return pulumi.get(self, \"model\")","def gen_response_object(description, media_type, api_type, path):\n\n response = {\n 'description': description,\n 'content': gen_media_type_object(media_type, api_type, path)\n }\n\n return response","def get_response_model_ctor(self):\n return self._response_model_ctor","def api_outputmodel(api: str, model: BaseModel, servicename: str,\n service_logger: logger) -> Callable:\n\n def decorator(func):\n @wraps(func)\n async def function_wrapper(request, *args, **kwargs):\n service_result = await func(request, *args, **kwargs)\n try:\n if isinstance(service_result, model):\n result = service_result\n else:\n result = model(**service_result)\n output = response.json(result.dict())\n except Exception as err:\n msg = ('an internal error occured (service: '\n f'{servicename}, api: {api}): {err}')\n raise ServerError(msg)\n service_logger.info(f'processed result {result} => '\n f'{output.content_type} [{output.status}] '\n f'{output.body}')\n return output\n\n return function_wrapper\n\n return decorator","def _create_response_model(self, data):\n pass","def test_api_can_get_metadata(self):\n response = self.client.get('/metadata/', format=\"json\")\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def _generate_model_metadata(out_file, model):\n # Define which FirstLevelModel attributes are BIDS compliant and which\n # should be bundled in a new \"ModelParameters\" field.\n DATA_ATTRIBUTES = [\n \"t_r\",\n ]\n PARAMETER_ATTRIBUTES = [\n \"drift_model\",\n \"hrf_model\",\n \"standardize\",\n \"high_pass\",\n \"target_shape\",\n \"signal_scaling\",\n \"drift_order\",\n \"scaling_axis\",\n \"smoothing_fwhm\",\n \"target_affine\",\n \"slice_time_ref\",\n \"fir_delays\",\n ]\n ATTRIBUTE_RENAMING = {\n \"t_r\": \"RepetitionTime\",\n }\n\n # Fields for the top level of the dictionary\n DATA_ATTRIBUTES.sort()\n data_attributes = {\n attr_name: getattr(model, attr_name)\n for attr_name in DATA_ATTRIBUTES\n if hasattr(model, attr_name)\n }\n data_attributes = {\n ATTRIBUTE_RENAMING.get(k, k): v for k, v in data_attributes.items()\n }\n\n # Fields for a nested section of the dictionary\n # The ModelParameters field is an ad-hoc way to retain useful info.\n PARAMETER_ATTRIBUTES.sort()\n model_attributes = {\n attr_name: getattr(model, attr_name)\n for attr_name in PARAMETER_ATTRIBUTES\n if hasattr(model, attr_name)\n }\n model_attributes = {\n ATTRIBUTE_RENAMING.get(k, k): v for k, v in model_attributes.items()\n }\n\n model_metadata = {\n \"Description\": \"A statistical map generated by Nilearn.\",\n **data_attributes,\n \"ModelParameters\": model_attributes,\n }\n\n with open(out_file, \"w\") as f_obj:\n json.dump(model_metadata, f_obj, indent=4, sort_keys=True)","def get_metadata(self):\n\n\t\t#see redcap api documentation -- https://redcap.wustl.edu/redcap/srvrs/prod_v3_1_0_001/redcap/api/help/\n\t\tbuf = io.BytesIO()\n\n\t\tfields = {\n\t\t 'token': config['api_token'],\n\t\t 'content': 'metadata',\n\t\t 'format': 'json'\n\t\t}\n\n\t\tch = pycurl.Curl()\n\t\tch.setopt(ch.URL, config['api_url'])\n\t\tch.setopt(ch.HTTPPOST, list(fields.items()))\n\t\tch.setopt(ch.WRITEFUNCTION, buf.write)\n\t\tch.perform()\n\t\tch.close()\n\n\t\tmetadata = json.loads(buf.getvalue().decode())\n\t\tbuf.close()\n\t\treturn metadata","def get_metadata_v3(session):\n LOG.debug(\"Exporting metadata for SFS augur build\")\n\n metadata = datastore.fetch_rows_from_table(session, (\"shipping\", \"metadata_for_augur_build_v3\"))\n\n return Response((row[0] + '\\n' for row in metadata), mimetype=\"application/x-ndjson\")","def swagger_definition(self, base_path=None, **kwargs):\n return Swagger(\n {\n \"info\": Info(\n {\n key: kwargs.get(key, self.DEFAULT_INFO.get(key))\n for key in Info.fields.keys()\n if key in kwargs or key in self.DEFAULT_INFO\n }\n ),\n \"paths\": self.paths,\n \"swagger\": \"2.0\",\n \"basePath\": base_path,\n }\n ).to_primitive()","def get_metadata():\n\n module = __name__.split('.', 1)\n\n try:\n pkg = pkg_resources.get_distribution(module[0])\n except pkg_resources.RequirementParseError:\n # if called from CLI, try to get pkg from the path\n distros = list(pkg_resources.find_distributions(cfg.BASE_DIR, \n only=True))\n if len(distros) == 1:\n pkg = distros[0]\n except Exception as e:\n raise HTTPBadRequest(reason=e)\n\n # deserialize key-word arguments\n train_args = _fields_to_dict(get_train_args())\n # make 'type' JSON serializable\n for key, val in train_args.items():\n train_args[key]['type'] = str(val['type'])\n\n predict_args = _fields_to_dict(get_predict_args())\n # make 'type' JSON serializable\n for key, val in predict_args.items():\n predict_args[key]['type'] = str(val['type'])\n\n meta = {\n 'name' : None,\n 'version' : None,\n 'summary' : None,\n 'home-page' : None,\n 'author' : None,\n 'author-email' : None,\n 'license' : None,\n 'help-train' : train_args,\n 'help-predict' : predict_args\n }\n for line in pkg.get_metadata_lines(\"PKG-INFO\"):\n line_low = line.lower() # to avoid inconsistency due to letter cases\n for par in meta:\n if line_low.startswith(par.lower() + \":\"):\n _, value = line.split(\": \", 1)\n meta[par] = value\n\n return meta","def meta(self) -> api.Meta:\n return self._get_model(model=api.Meta)","def __init__(self, **kwargs):\n self.swagger_types = {\n 'id': 'str',\n 'name': 'str',\n 'version': 'str',\n 'tagline': 'str',\n 'keywords': 'str',\n 'short_description': 'str',\n 'usage_information': 'str',\n 'long_description': 'str',\n 'license_model_description': 'str',\n 'system_requirements': 'str',\n 'time_released': 'datetime',\n 'release_notes': 'str',\n 'categories': 'list[str]',\n 'publisher': 'Publisher',\n 'languages': 'list[Item]',\n 'screenshots': 'list[Screenshot]',\n 'videos': 'list[NamedLink]',\n 'support_contacts': 'list[SupportContact]',\n 'support_links': 'list[NamedLink]',\n 'documentation_links': 'list[DocumentationLink]',\n 'icon': 'UploadData',\n 'banner': 'UploadData',\n 'regions': 'list[Region]',\n 'package_type': 'str',\n 'default_package_version': 'str',\n 'links': 'list[Link]',\n 'is_featured': 'bool'\n }\n\n self.attribute_map = {\n 'id': 'id',\n 'name': 'name',\n 'version': 'version',\n 'tagline': 'tagline',\n 'keywords': 'keywords',\n 'short_description': 'shortDescription',\n 'usage_information': 'usageInformation',\n 'long_description': 'longDescription',\n 'license_model_description': 'licenseModelDescription',\n 'system_requirements': 'systemRequirements',\n 'time_released': 'timeReleased',\n 'release_notes': 'releaseNotes',\n 'categories': 'categories',\n 'publisher': 'publisher',\n 'languages': 'languages',\n 'screenshots': 'screenshots',\n 'videos': 'videos',\n 'support_contacts': 'supportContacts',\n 'support_links': 'supportLinks',\n 'documentation_links': 'documentationLinks',\n 'icon': 'icon',\n 'banner': 'banner',\n 'regions': 'regions',\n 'package_type': 'packageType',\n 'default_package_version': 'defaultPackageVersion',\n 'links': 'links',\n 'is_featured': 'isFeatured'\n }\n\n self._id = None\n self._name = None\n self._version = None\n self._tagline = None\n self._keywords = None\n self._short_description = None\n self._usage_information = None\n self._long_description = None\n self._license_model_description = None\n self._system_requirements = None\n self._time_released = None\n self._release_notes = None\n self._categories = None\n self._publisher = None\n self._languages = None\n self._screenshots = None\n self._videos = None\n self._support_contacts = None\n self._support_links = None\n self._documentation_links = None\n self._icon = None\n self._banner = None\n self._regions = None\n self._package_type = None\n self._default_package_version = None\n self._links = None\n self._is_featured = None","def output_metadata(self, metadata = None):\n return True","def build_metadata(results):\n\n print('Building metadata...')\n\n fields = set(['name', 'timestamp', 'value', 'scrape_timestamp'])\n metadata = connector_pb2.GetDataResponse()\n\n for result in results:\n for metric in result['metric'].keys():\n if metric != '__name__':\n fields.add(metric)\n\n for field in fields:\n metadata.fieldInfo.extend([connector_pb2.FieldInfo(name = field)])\n\n return metadata","def get_metadata_as_dict(self):\n try:\n return json.loads(self._env.lab_handler.lab_obj_to_json(self.exp_metadata))\n except:\n # lab handler not initialized\n import lab_api.swagger_client as swagger_client\n json.loads(json.dumps(swagger_client.ApiClient().sanitize_for_serialization(self.exp_metadata)))","def get_openapi_spec(self):\n\n spec = {\"operationId\": snake_to_camel(self._wrapped_function.__name__), \"responses\": {}}\n\n if self._doc.short_description:\n spec[\"summary\"] = self._doc.short_description\n\n if self._doc.long_description:\n spec[\"description\"] = self._doc.long_description\n\n if self._tags:\n spec[\"tags\"] = self._tags\n\n if self._path_parameters or self._query_parameters:\n spec[\"parameters\"] = []\n\n for name, param_type in self._path_parameters.items():\n if self._is_param_ignored(name):\n continue\n\n param_spec = {\n \"name\": name,\n \"in\": \"path\",\n \"required\": True,\n \"schema\": {\"type\": self._extension.PARAMETER_TYPE_MAP.get(param_type, \"string\")},\n }\n\n param_doc = self._get_param_doc(name)\n if param_doc is not None:\n param_spec[\"description\"] = param_doc.description\n\n spec[\"parameters\"].append(param_spec)\n\n for name, param_type in self._query_parameters.items():\n param_refl: inspect.Parameter = self._signature.parameters[name]\n param_spec = {\n \"name\": name,\n \"in\": \"query\",\n \"required\": param_refl.default == inspect.Parameter.empty,\n \"schema\": {\"type\": self._extension.PARAMETER_TYPE_MAP.get(param_type, \"string\")},\n }\n\n param_doc = self._get_param_doc(name)\n if param_doc is not None:\n param_spec[\"description\"] = param_doc.description\n\n spec[\"parameters\"].append(param_spec)\n\n if self._request_body_parameter:\n mimetypes = self._request_body_content_types\n\n spec[\"requestBody\"] = {\n \"content\": {\n mimetype: {\"schema\": self._process_model_schema(self._request_body_class)} for mimetype in mimetypes\n },\n \"required\": True,\n }\n\n if issubclass(self._request_body_class, ExamplesMixin):\n for mimetype in mimetypes:\n spec[\"requestBody\"][\"content\"][mimetype][\"examples\"] = model_examples_to_openapi_dict(\n self._request_body_class\n )\n\n param_doc = self._get_param_doc(self._request_body_parameter)\n if param_doc is not None and param_doc.description:\n spec[\"requestBody\"][\"description\"] = param_doc.description\n\n spec[\"x-codegen-request-body-name\"] = \"body\"\n elif self._request_body_file_type:\n spec[\"requestBody\"] = {\n \"content\": {self._request_body_file_type: {\"schema\": {\"type\": \"string\", \"format\": \"binary\"}}}\n }\n\n if self._security:\n spec[\"security\"] = self._security\n\n for response_class, codes in self._responses.items():\n for code, response_data in codes.items():\n if issubclass(response_class, FileResponse):\n mime = response_data.mimetype or \"application/octet-stream\"\n spec[\"responses\"][str(code)] = {\n \"description\": response_data.description or response_class.__name__,\n \"content\": {mime: {\"schema\": {\"type\": \"string\", \"format\": \"binary\"}}},\n }\n else:\n spec[\"responses\"][str(code)] = {\n \"description\": response_data.description or response_class.__name__,\n \"content\": {\"application/json\": {\"schema\": self._process_model_schema(response_class)}},\n }\n\n if issubclass(response_class, ExamplesMixin):\n # fmt: off\n spec[\"responses\"][str(code)][\"content\"][\"application/json\"][\"examples\"] = \\\n model_examples_to_openapi_dict(response_class)\n # fmt: on\n\n return spec","def to_api_data(self):\n raise NotImplementedError()","def _get_response_from_annotation(self) -> Generator[Tuple[Type[BaseModel], int, ResponseData], None, None]:\n annotation = self._signature.return_annotation\n\n if annotation is inspect.Signature.empty:\n return\n\n annotation = resolve_fw_decl(self._wrapped_function, annotation)\n\n if not issubclass(annotation, BaseModel):\n raise TypeError(\"Unsupported return type\")\n\n yield annotation, 200, ResponseData(self._doc.returns.description if self._doc.returns else None)","def test_api_schema(self):\n response = self.client.get(\"/api/schema/\")\n self.assertEqual(response.status_code, 200)\n self.assertEqual(\n response.get(\"Content-Type\"), \"application/vnd.oai.openapi; charset=utf-8\"\n )\n self.assertEqual(\n response.get(\"Content-Disposition\"), 'inline; filename=\"Marsha API.yaml\"'\n )","def meta(self):\n return self.spec.meta","def swagger():\n return jsonify(current_app.spec.to_dict())","def model_info():\n pass","def metadata(self):\r\n return resources.Metadata(self)","def get_metadata(self):\n return {}","def emit_swagger_spec(ctx, modules, fd, path):\n\n printed_header = False\n model = OrderedDict()\n definitions = OrderedDict()\n augments = list()\n # Go through all modules and extend the model.\n for module in modules:\n if not printed_header:\n model = print_header(module, fd)\n printed_header = True\n path = '/'\n\n typdefs = [module.i_typedefs[element] for element in module.i_typedefs]\n models = list(module.i_groupings.values())\n referenced_types = list()\n referenced_types = findTypedefs(ctx, module, models, referenced_types)\n for element in referenced_types:\n typdefs.append(element)\n\n # The attribute definitions are processed and stored in the \"typedefs\" data structure for further use.\n gen_typedefs(typdefs)\n\n # list() needed for python 3 compatibility\n referenced_models = list()\n referenced_models = findModels(ctx, module, models, referenced_models)\n for element in referenced_models:\n models.append(element)\n # Print the swagger definitions of the Yang groupings.\n definitions = gen_model(models, definitions)\n\n # If a model at runtime was dependant of another model which had been encounter yet, it is generated 'a posteriori'.\n if pending_models:\n gen_model(pending_models, definitions)\n\n if PARENT_MODELS:\n for element in PARENT_MODELS:\n if PARENT_MODELS[element]['models']:\n definitions[element]['discriminator'] = PARENT_MODELS[element]['discriminator']\n # extract children which contain data definition keywords\n chs = [ch for ch in module.i_children\n if ch.keyword in (statements.data_definition_keywords + ['rpc','notification'])]\n\n # generate the APIs for all children\n if len(chs) > 0:\n model['paths'] = OrderedDict()\n gen_apis(chs, path, model['paths'], definitions)\n\n model['definitions'] = definitions\n fd.write(json.dumps(model, indent=4, separators=(',', ': ')))","def test_schema_dump_metadata(\n self,\n schema_url: str,\n title: str,\n description: str\n ):\n json_schema = JSONSchema(schema_url, title, description)\n result = json_schema.dump(self.schema_to_serialize)\n\n self.assertEqual(\n description, result['description']\n )\n self.assertEqual(\n title, result['title']\n )\n self.assertEqual(\n schema_url, result['$schema']\n )","def get_sample_metadata(request, pk):\n sample = Sample.objects.get(pk=pk)\n mygrp = sample.library.group\n if not mygrp.is_public:\n try:\n membership_queryset = request.user.organization_set.filter(pk=mygrp.organization.pk)\n authorized = membership_queryset.exists()\n except AttributeError: # occurs if user is not logged in\n authorized = False\n if not authorized:\n raise PermissionDenied(_('Insufficient permissions to get group manifest.'))\n blob = SampleSerializer(sample).data\n blob['versioned_metadata'] = [\n {\n 'created_at': vm.created_at,\n 'updated_at': vm.updated_at,\n 'metadata': vm.metadata,\n }\n for vm in sample.versioned_metadata.all()\n ]\n\n return Response(blob)","def create_model(self, ApiId: str, Name: str, Schema: str, ContentType: str = None, Description: str = None) -> Dict:\n pass","def introspectionResponse(self):\n return self._introspectionResponse","def schema(self):\n # TODO The schema of a container resource...\n # This is the same as the leaf.\n # However, this isn't actually the schema of the response\n return {\n \"$id\": f\"{self.request.resource_url(self)}#schema\",\n \"type\": \"object\",\n \"properties\": {\n \"foo\": {\"type\": \"string\"},\n # generated fields shouldn't be submitted or in forms\n \"url\": {\"type\": \"string\", \"generated\": True},\n }\n }","def to_api_repr(self):\n raise NotImplementedError","def get_annotations(self):\n entity = self.get_object()\n serializer = AnnotationValueSerializer(entity.annotations.all(), many=True)\n return Response(serializer.data)","def describe(model_element, **kwargs):\n model_descriptor = ModelDescriptor(**kwargs)\n return model_descriptor.describe(model_element)","def process_metadata(self):\n\n self._responses = self._get_responses()\n\n (\n self._request_body_parameter,\n self._request_body_class,\n self._request_body_content_types,\n ) = self._get_request_body_parameter()\n\n if self._request_body_content_types is None:\n self._request_body_content_types = [\"application/json\"]\n\n self._request_body_file_type = self._get_request_body_file_type()\n if self._request_body_parameter is not None and self._request_body_file_type is not None:\n raise TypeError(\"An endpoint cannot accept both a file and a model\")\n\n self._query_parameters = dict(self._get_query_string_parameters())\n self._path_parameters = dict(self._get_path_parameters())\n\n self._security = [*self._get_security_requirements()]\n self._tags = [*self._get_tags()]","def response_helper(self, response, **kwargs):\n self.resolve_schema(response)\n if \"headers\" in response:\n for header in response[\"headers\"].values():\n self.resolve_schema(header)\n return response","def extract_http_metadata(wrapped, instance, args, kwargs, return_value):\n response = return_value\n LOGGER.debug(\n \"Extracting HTTP metadata\", args=args, kwargs=kwargs,\n )\n if \"request\" in kwargs:\n request = kwargs[\"request\"]\n else:\n request = args[0]\n\n metadata = {\n \"http\": {\"request\": {\"method\": request.method.upper(), \"url\": request.url}},\n }\n if response is not None:\n metadata[\"http\"][\"response\"] = {\n \"status\": response.status_code,\n }\n\n return metadata","def __init__(self): # noqa: E501\n self.openapi_types = {\n }\n\n self.attribute_map = {\n }","def opt_model_create_rest_api():\n request_json = request.get_json()\n OptimModelRequestAPI(request_json).validate()\n return create_model_data(request_json)","def response(schema):\n def _response(function):\n @wraps(function)\n def wrapper(*args, **kwargs):\n if issubclass(schema, BaseModel):\n has_root = True if '__root__' in schema.__fields__ else False\n function_res = function(*args, **kwargs)\n\n if not function_res:\n if has_root is True:\n return jsonify([])\n return jsonify({})\n\n if type(function_res) == list:\n res = schema.parse_obj(function_res)\n else:\n res = schema.from_orm(function_res)\n\n res = res.dict()\n\n if has_root is True:\n return jsonify(res['__root__'])\n\n return jsonify(res)\n elif isinstance(schema, dict):\n return jsonify(schema)\n else:\n raise CustomException('invalid response type', code=400)\n\n return wrapper\n return _response","def extract_metadata(res):\n d = OrderedDict()\n\n d['type'] = res['type']\n d['authors'] = make_author_list(res)\n d['citation-authors'] = make_citation_authors(res)\n d['citation'] = make_citation(res)\n d['source-title'] = res['title'].strip(\" \").capitalize()\n d['title'] = \"Notes on '\" + d['source-title'] + \"', by \" + \", \".join(d['authors'][0:-1])\n if len(d['authors']) > 1:\n d['title'] = d['title'] + \", and \" + d['authors'][-1] \n d['citation-authors']\n d['container'] = make_container(res)\n d['publisher'] = res['publisher'] if 'publisher' in res.keys() else '' \n d['issn'] = res['issn'] if 'issn' in res.keys() else ''\n d['year'] = make_year(res)\n d['issue'] = res['issue'] if \"issue\" in res.keys() else \"\"\n d['volume'] = res['volume'] if \"volume\" in res.keys() else \"\"\n d['pages'] = res['page'] if \"page\" in res.keys() else \"\"\n d['subjects'] = make_subject(res)\n d['doi'] = res['DOI']\n d['link'] = res['URL']\n d['citationkey'] = make_citation_key(res)\n d['fetched'] = date.today().strftime(\"%Y%m%d\")\n return d","def responses(resp_def):\n def decorator(fn): # pylint: disable=missing-docstring\n meta = RouteMeta.load(fn)\n meta.responses = resp_def\n meta.save()\n return fn\n return decorator","def test_add_model_with_resource_fields_nested_swagger_metadata(model_class,):\n pdst = patch_deduce_swagger_type\n pr = patch_registry\n ppd = patch_parse_doc\n pha = patch_hasattr\n\n with pr(), ppd(), patch_isinstance(True) as mock_isinstance:\n with pha() as mock_hasattr:\n with patch_dir([\"resource_fields\"]) as mock_dir:\n with pdst() as mock_deduce_swagger_type:\n swagger.add_model(model_class)\n\n mock_dir.assert_called_with(model_class)\n assert mock_dir.call_count == 2\n mock_hasattr.assert_called_once_with(\n model_class, \"required\")\n mock_isinstance.assert_called_with(\n model_class, swagger._Nested)\n assert mock_deduce_swagger_type.call_count == len(\n model_class.resource_fields.items()\n )","def metadata(self):\n return self.meta.metadata","def dump_model(self):","def __init__(self):\n self.swagger_types = {\n 'detail_type': 'str',\n 'name': 'str',\n 'store_data': 'object',\n 'discovered': 'datetime',\n 'extraction_failure': 'bool',\n 'in_trash': 'bool',\n 'is_extracted': 'bool',\n 'meta_available': 'bool',\n 'size': 'int',\n 'start_time': 'datetime',\n 'end_time': 'datetime',\n 'duration': 'float',\n 'messages': 'int',\n 'tags': 'list[Tag]'\n }\n\n self.attribute_map = {\n 'detail_type': 'detail_type',\n 'name': 'name',\n 'store_data': 'store_data',\n 'discovered': 'discovered',\n 'extraction_failure': 'extraction_failure',\n 'in_trash': 'in_trash',\n 'is_extracted': 'is_extracted',\n 'meta_available': 'meta_available',\n 'size': 'size',\n 'start_time': 'start_time',\n 'end_time': 'end_time',\n 'duration': 'duration',\n 'messages': 'messages',\n 'tags': 'tags'\n }\n\n self._detail_type = None\n self._name = None\n self._store_data = None\n self._discovered = None\n self._extraction_failure = None\n self._in_trash = None\n self._is_extracted = None\n self._meta_available = None\n self._size = None\n self._start_time = None\n self._end_time = None\n self._duration = None\n self._messages = None\n self._tags = None","def serve_metadata():\n xml = generate_xml_metadata()\n return Response(xml, mimetype=\"application/gzip\")","def metadata(self) -> \"ObjectMeta\":\n return typing.cast(\n \"ObjectMeta\",\n self._properties.get(\"metadata\"),\n )","def __init__(self, type=None, metadata=None): # noqa: E501\n self.openapi_types = {\"type\": str, \"metadata\": Metadata}\n\n self.attribute_map = {\"type\": \"type\", \"metadata\": \"metadata\"}\n\n self._type = type\n self._metadata = metadata","def api_metadata_properties(self) -> Optional[pulumi.Input['GatewayApiMetadataPropertiesArgs']]:\n return pulumi.get(self, \"api_metadata_properties\")","def test_custom_action_response_descriptor_octopus_server_web_api_actions_defect_reported_responder(self):\n pass","def metadata(self): # -> list[Unknown]:\n ...","def metadata(self): # -> list[Unknown]:\n ...","def _metadata(self) -> Dict[str, Any]:\n return self.__metadata","def meta_data(self):\r\n return simplejson.dumps(self.__resource_meta)","def PostModelOutputs(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def expose_models(app, HOST=\"localhost\", PORT=5000, API_PREFIX=\"/api\"):\n\n api = SAFRSAPI(app, host=HOST, port=PORT)\n api.expose_object(models.Category)\n api.expose_object(models.CustomerCustomerDemo)\n api.expose_object(models.OrderDetail)\n api.expose_object(models.Order)\n api.expose_object(models.Customer)\n api.expose_object(models.CustomerDemographic)\n api.expose_object(models.EmployeeAudit)\n api.expose_object(models.EmployeeTerritory)\n api.expose_object(models.Employee)\n api.expose_object(models.Product)\n api.expose_object(models.Region)\n api.expose_object(models.Shipper)\n api.expose_object(models.Supplier)\n api.expose_object(models.Territory)\n return api","def describe_model(ModelName=None):\n pass","def _metadata(self):\n meta = super()._metadata\n meta.update({\n \"name\": self.name,\n \"lead_in_time\": self.lead_in_time,\n \"amplification\": self.amplification,\n \"amplifier_clipping\": self.amplifier_clipping,\n \"power_threshold\": self.power_threshold,\n })\n return meta","def handle_models_request():\n # TODO: add sort and filter by creation/modification date\n return (\n json.dumps({\"models\": {\n k: d[\"data\"] for k, d in app.models.items()\n }}), 200,\n {'ContentType': 'application/json'}\n )","def _generate_implicit_api_resource(self):\n return ImplicitHttpApiResource().to_dict()","def to_dict(model):\n result = {}\n for attr, _ in six.iteritems(model.swagger_types):\n value = getattr(model, attr)\n result[attr] = to_dict_value(value)\n return result","def extract_metadata(self):\n if self.is_generatable_file:\n logger.debug(\"Converting collected details to dict..\")\n if self.metadata_collector:\n self.metadata = MetadataToDict(\n metadata_collector=self.metadata_collector,\n file_import=self.file_import,\n )\n self.metadata.build_integration_dict()","def __init__(self):\n self.swagger_types = {\n 'id_conta': 'int',\n 'id_produto': 'int',\n 'id_pessoa': 'int',\n 'id_parentesco': 'int',\n 'tipo_portador': 'str',\n 'nome_impresso': 'str',\n 'id_tipo_cartao': 'int',\n 'flag_ativo': 'int',\n 'data_cadastro_portador': 'str',\n 'data_cancelamento_portador': 'str'\n }\n\n self.attribute_map = {\n 'id_conta': 'idConta',\n 'id_produto': 'idProduto',\n 'id_pessoa': 'idPessoa',\n 'id_parentesco': 'idParentesco',\n 'tipo_portador': 'tipoPortador',\n 'nome_impresso': 'nomeImpresso',\n 'id_tipo_cartao': 'idTipoCartao',\n 'flag_ativo': 'flagAtivo',\n 'data_cadastro_portador': 'dataCadastroPortador',\n 'data_cancelamento_portador': 'dataCancelamentoPortador'\n }\n\n self._id_conta = None\n self._id_produto = None\n self._id_pessoa = None\n self._id_parentesco = None\n self._tipo_portador = None\n self._nome_impresso = None\n self._id_tipo_cartao = None\n self._flag_ativo = None\n self._data_cadastro_portador = None\n self._data_cancelamento_portador = None","async def get_inference_statistics(\n self,\n model_name: str = ...,\n model_version: str = ...,\n headers: dict[str, t.Any] = ...,\n as_json: t.Literal[False] = ...,\n ) -> service_pb2.ModelStatisticsResponse:","def test_model_metadata_type(self):\n self.assertTrue(type(self.meta) is dict)","def test_getMetadata_full(self):\n metadata = self.resolver.getMetadata()\n self.assertIsInstance(\n metadata, Collection,\n \"Resolver should return a collection object\"\n )\n self.assertIsInstance(\n metadata.members[0], Collection,\n \"Members of Inventory should be TextGroups\"\n )\n self.assertEqual(\n len(metadata.descendants), 43,\n \"There should be as many descendants as there is edition, translation, works and textgroup + 1 for \"\n \"default inventory\"\n )\n self.assertEqual(\n len(metadata.readableDescendants), 25,\n \"There should be as many readable descendants as there is edition, translation(25 ed+tr)\"\n )\n self.assertEqual(\n len([x for x in metadata.readableDescendants if isinstance(x, TextMetadata)]), 25,\n \"There should be 24 editions + 1 translations in readableDescendants\"\n )\n self.assertEqual(\n len(metadata.export(output=Mimetypes.PYTHON.ETREE).xpath(\n \"//ti:edition[@urn='urn:cts:latinLit:phi1294.phi002.perseus-lat2']\", namespaces=NS)), 1,\n \"There should be one node in exported format corresponding to lat2\"\n )\n self.assertCountEqual(\n [x[\"@id\"] for x in metadata.export(output=Mimetypes.JSON.DTS.Std)[\"@graph\"][\"dts:members\"]],\n [\"urn:cts:latinLit:phi1294\", \"urn:cts:latinLit:phi0959\",\n \"urn:cts:greekLit:tlg0003\", \"urn:cts:latinLit:phi1276\"],\n \"There should be 4 Members in DTS JSON\"\n )","def export_model(self, save_path: str, save_format: Optional[str] = None) -> None:","def test_add_model_with_resource_fields_without_swagger_metadata(\n mock_nested, mock_model_class,\n):\n pdst = patch_deduce_swagger_type\n pr = patch_registry\n ppd = patch_parse_doc\n pha = patch_hasattr\n\n with pr(), ppd(), patch_isinstance(False) as mock_isinstance:\n with pha() as mock_hasattr, patch_dir([\"resource_fields\"]) as mock_dir:\n with pdst() as mock_deduce_swagger_type:\n\n swagger.add_model(mock_model_class)\n mock_dir.assert_called_with(mock_model_class)\n assert mock_dir.call_count == 2\n mock_hasattr.assert_called_once_with(\n mock_model_class, \"required\")\n mock_isinstance.assert_called_with(\n mock_model_class, mock_nested)\n assert mock_deduce_swagger_type.call_count == len(\n mock_model_class.resource_fields.items()\n )","def describe_model_package(ModelPackageName=None):\n pass","def get_interaction_model_metadata_v1(self, skill_id, stage_v2, locale, **kwargs):\n # type: (str, str, str, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\n operation_name = \"get_interaction_model_metadata_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'stage_v2' is set\n if ('stage_v2' not in params) or (params['stage_v2'] is None):\n raise ValueError(\n \"Missing the required parameter `stage_v2` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'locale' is set\n if ('locale' not in params) or (params['locale'] is None):\n raise ValueError(\n \"Missing the required parameter `locale` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/stages/{stageV2}/interactionModel/locales/{locale}'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n if 'stage_v2' in params:\n path_params['stageV2'] = params['stage_v2']\n if 'locale' in params:\n path_params['locale'] = params['locale']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=204, message=\"Success. There is no content but returns etag.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The specified skill or stage or locale does not exist\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"HEAD\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=None)\n\n if full_response:\n return api_response\n \n return None","def get_dataset_meta(self, output_name, dataset_id):\n return {}","def write(self, model):\n\n # Initialize json_dump\n json_dump = {\"model\": [], \"metadata\": {}}\n\n # Set timestamp in metadata\n json_dump[\"metadata\"][\"time\"] = str(datetime.now())\n\n # Set the size of the model in metadata\n json_dump[\"metadata\"][\"model_size\"] = len(model.models)\n\n for obj in model.models:\n _class = type(obj).__name__\n if _class in [\n Winding,\n PhaseWinding,\n Wire,\n PhaseCapacitor,\n Position,\n PhaseLoad,\n ]:\n continue\n json_dump[\"model\"].append({})\n json_dump[\"model\"][-1][\"class\"] = _class\n\n try:\n json_dump[\"model\"][-1][\"name\"] = {\"class\": \"str\", \"value\": obj.name}\n except:\n json_dump[\"model\"][-1][\"name\"] = {\"class\": \"str\", \"value\": None}\n pass\n\n for key, value in obj._trait_values.items():\n if key in [\"capacitance_matrix\", \"impedance_matrix\", \"reactances\"]:\n json_dump[\"model\"][-1][key] = {\"class\": \"list\", \"value\": []}\n for v in value:\n if isinstance(v, complex):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"complex\", \"value\": [v.real, v.imag]}\n )\n elif isinstance(v, list):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"list\", \"value\": []}\n )\n for vv in v:\n if isinstance(vv, complex):\n json_dump[\"model\"][-1][key][\"value\"][-1][\n \"value\"\n ].append(\n {\n \"class\": \"complex\",\n \"value\": [vv.real, vv.imag],\n }\n )\n else:\n json_dump[\"model\"][-1][key][\"value\"][-1][\n \"value\"\n ].append(\n {\n \"class\": str(type(vv)).split(\"'\")[1],\n \"value\": vv,\n }\n )\n else:\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": str(type(v)).split(\"'\")[1], \"value\": v}\n )\n continue\n if isinstance(value, list):\n json_dump[\"model\"][-1][key] = {\"class\": \"list\", \"value\": []}\n for v in value:\n\n if isinstance(v, complex):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"complex\", \"value\": [v.real, v.imag]}\n )\n\n elif isinstance(v, Position):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"Position\"}\n )\n for kkk, vvv in v._trait_values.items():\n json_dump[\"model\"][-1][key][\"value\"][-1][kkk] = {\n \"class\": str(type(vvv)).split(\"'\")[1],\n \"value\": vvv,\n }\n\n elif isinstance(v, Unicode):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"Unicode\", \"value\": v.default_value}\n )\n\n elif isinstance(v, Wire):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"Wire\"}\n )\n for kkk, vvv in v._trait_values.items():\n json_dump[\"model\"][-1][key][\"value\"][-1][kkk] = {\n \"class\": str(type(vvv)).split(\"'\")[1],\n \"value\": vvv,\n }\n\n elif isinstance(v, PhaseCapacitor):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"PhaseCapacitor\"}\n )\n for kkk, vvv in v._trait_values.items():\n json_dump[\"model\"][-1][key][\"value\"][-1][kkk] = {\n \"class\": str(type(vvv)).split(\"'\")[1],\n \"value\": vvv,\n }\n\n elif isinstance(v, Winding):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"Winding\"}\n )\n for kkk, vvv in v._trait_values.items():\n if kkk != \"phase_windings\":\n json_dump[\"model\"][-1][key][\"value\"][-1][kkk] = {\n \"class\": str(type(vvv)).split(\"'\")[1],\n \"value\": vvv,\n }\n json_dump[\"model\"][-1][key][\"value\"][-1][\n \"phase_windings\"\n ] = {\"class\": \"list\", \"value\": []}\n for phw in v.phase_windings:\n json_dump[\"model\"][-1][key][\"value\"][-1][\n \"phase_windings\"\n ][\"value\"].append({\"class\": \"PhaseWinding\"})\n for kkkk, vvvv in phw._trait_values.items():\n json_dump[\"model\"][-1][key][\"value\"][-1][\n \"phase_windings\"\n ][\"value\"][-1][kkkk] = {\n \"class\": str(type(vvvv)).split(\"'\")[1],\n \"value\": vvvv,\n }\n\n elif isinstance(v, PhaseLoad):\n json_dump[\"model\"][-1][key][\"value\"].append(\n {\"class\": \"PhaseLoad\"}\n )\n for kkk, vvv in v._trait_values.items():\n json_dump[\"model\"][-1][key][\"value\"][-1][kkk] = {\n \"class\": str(type(vvv)).split(\"'\")[1],\n \"value\": vvv,\n }\n\n continue\n\n if isinstance(value, complex):\n json_dump[\"model\"][-1][key] = {\n \"class\": \"complex\",\n \"value\": [value.real, value.imag],\n }\n continue\n\n json_dump[\"model\"][-1][key] = {\n \"class\": str(type(value)).split(\"'\")[1],\n \"value\": value,\n }\n\n with open(os.path.join(self.output_path, self.filename), \"w\") as f:\n f.write(\n json_tricks.dumps(json_dump, allow_nan=True, sort_keys=True, indent=4)\n )","def to_dict(self):\n result = {}\n\n for attr, _ in six.iteritems(self.swagger_types):\n value = getattr(self, attr)\n if isinstance(value, list):\n result[attr] = list(map(\n lambda x: x.to_dict() if hasattr(x, \"to_dict\") else x,\n value\n ))\n elif hasattr(value, \"to_dict\"):\n result[attr] = value.to_dict()\n elif isinstance(value, dict):\n result[attr] = dict(map(\n lambda item: (item[0], item[1].to_dict())\n if hasattr(item[1], \"to_dict\") else item,\n value.items()\n ))\n else:\n result[attr] = value\n if issubclass(Metadata, dict):\n for key, value in self.items():\n result[key] = value\n\n return result","def __init__(self):\n self.swagger_types = {\n 'id': 'str',\n 'name': 'str',\n 'date_created': 'datetime',\n 'date_modified': 'datetime',\n 'version': 'int',\n 'division': 'DomainEntityRef',\n 'campaign_status': 'str',\n 'callable_time_set': 'DomainEntityRef',\n 'contact_list': 'DomainEntityRef',\n 'dnc_lists': 'list[DomainEntityRef]',\n 'always_running': 'bool',\n 'contact_sorts': 'list[ContactSort]',\n 'messages_per_minute': 'int',\n 'errors': 'list[RestErrorDetail]',\n 'sms_config': 'SmsConfig',\n 'self_uri': 'str'\n }\n\n self.attribute_map = {\n 'id': 'id',\n 'name': 'name',\n 'date_created': 'dateCreated',\n 'date_modified': 'dateModified',\n 'version': 'version',\n 'division': 'division',\n 'campaign_status': 'campaignStatus',\n 'callable_time_set': 'callableTimeSet',\n 'contact_list': 'contactList',\n 'dnc_lists': 'dncLists',\n 'always_running': 'alwaysRunning',\n 'contact_sorts': 'contactSorts',\n 'messages_per_minute': 'messagesPerMinute',\n 'errors': 'errors',\n 'sms_config': 'smsConfig',\n 'self_uri': 'selfUri'\n }\n\n self._id = None\n self._name = None\n self._date_created = None\n self._date_modified = None\n self._version = None\n self._division = None\n self._campaign_status = None\n self._callable_time_set = None\n self._contact_list = None\n self._dnc_lists = None\n self._always_running = None\n self._contact_sorts = None\n self._messages_per_minute = None\n self._errors = None\n self._sms_config = None\n self._self_uri = None","def schema(self):\n # NOTE This is exactly the same as the other thing.\n return {\n \"$id\": f\"{self.request.resource_url(self)}#schema\",\n \"type\": \"object\",\n \"properties\": {\n \"foo\": {\"type\": \"string\"},\n # generated fields shouldn't be submitted or in forms\n \"url\": {\"type\": \"string\", \"generated\": True},\n }\n }","def metadata(self, metadata):\n return Metadata(metadata)","def test_metadata(self):\n self.assertEquals(self.testObject.metadata, {})","def test_custom_action_response_descriptor_octopus_server_web_api_actions_defect_resolved_responder(self):\n pass","def metadata(self) -> dict:\n meta = {}\n meta['filename'] = self.filename\n meta['label'] = self.label\n meta['url'] = self.url\n\n return meta","def test_swagger(self):\n response = self.client.get(\"/api/v1/swagger\", query_string=dict(validate_schema=True))\n assert_that(response.status_code, is_(equal_to(200)))\n swagger = loads(response.get_data().decode(\"utf-8\"))\n # we have the swagger docs endpoint too, which is implemented as a query.\n # ignore it here for now.\n del swagger[\"paths\"][\"/swagger/docs\"]\n assert_that(swagger[\"paths\"], is_(equal_to({\n \"/foo/get\": {\n \"get\": {\n \"description\": \"My doc string\",\n \"tags\": [\"foo\"],\n \"responses\": {\n \"default\": {\n \"description\": \"An error occurred\", \"schema\": {\n \"$ref\": \"#/definitions/Error\",\n }\n },\n \"200\": {\n \"description\": \"My doc string\",\n \"schema\": {\n \"$ref\": \"#/definitions/QueryResult\",\n }\n }\n },\n \"parameters\": [\n {\n \"in\": \"header\",\n \"name\": \"X-Response-Skip-Null\",\n \"required\": False,\n \"type\": \"string\",\n \"description\": \"Remove fields with null values from the response.\"\n },\n {\n \"required\": False,\n \"type\": \"string\",\n \"name\": \"optional_value\",\n \"in\": \"query\",\n },\n {\n \"required\": True,\n \"type\": \"string\",\n \"name\": \"required_value\",\n \"in\": \"query\",\n },\n ],\n \"operationId\": \"query\",\n }\n }\n })))","def __init__(self):\n self.swagger_types = {\n 'id_conta': 'int',\n 'id_pessoa': 'int',\n 'id_cartao': 'int',\n 'id_bandeira': 'int',\n 'id_tipo_cartao': 'int',\n 'numero_cartao': 'str',\n 'nome_plastico': 'str',\n 'cvv2': 'str',\n 'data_geracao': 'str',\n 'data_validade': 'str',\n 'cpf': 'str',\n 'tipo_portador': 'str',\n 'trilha1': 'str',\n 'trilha2': 'str',\n 'trilha_cvv1': 'str',\n 'trilha_cvv2': 'str',\n 'flag_virtual': 'int',\n 'nome_bandeira': 'str',\n 'flag_titular': 'int',\n 'sequencial_cartao': 'int',\n 'id_status': 'int',\n 'descricao_status_cartao': 'str',\n 'data_status': 'str',\n 'id_estagio': 'int',\n 'descricao_estagio': 'str',\n 'data_estagio': 'str',\n 'numero_bin': 'str',\n 'id_produto': 'int',\n 'descricao_produto': 'str',\n 'id_status_conta': 'int',\n 'descricao_status_conta': 'int',\n 'data_embossing': 'str',\n 'codigo_desbloqueio': 'str',\n 'nome_pessoa': 'str',\n 'tipo_pessoa': 'str',\n 'data_nascimento': 'str',\n 'id_endereco': 'int',\n 'id_tipo_endereco': 'int',\n 'descricao_tipo_endereco': 'str',\n 'cep': 'str',\n 'logradouro': 'str',\n 'numero_endereco': 'str',\n 'complemento_endereco': 'str',\n 'bairro': 'str',\n 'cidade': 'str',\n 'uf': 'str',\n 'pais': 'str',\n 'senha_criptografada': 'str',\n 'icvv': 'str',\n 'id_status_impressao': 'int'\n }\n\n self.attribute_map = {\n 'id_conta': 'idConta',\n 'id_pessoa': 'idPessoa',\n 'id_cartao': 'idCartao',\n 'id_bandeira': 'idBandeira',\n 'id_tipo_cartao': 'idTipoCartao',\n 'numero_cartao': 'numeroCartao',\n 'nome_plastico': 'nomePlastico',\n 'cvv2': 'cvv2',\n 'data_geracao': 'dataGeracao',\n 'data_validade': 'dataValidade',\n 'cpf': 'cpf',\n 'tipo_portador': 'tipoPortador',\n 'trilha1': 'trilha1',\n 'trilha2': 'trilha2',\n 'trilha_cvv1': 'trilhaCVV1',\n 'trilha_cvv2': 'trilhaCVV2',\n 'flag_virtual': 'flagVirtual',\n 'nome_bandeira': 'nomeBandeira',\n 'flag_titular': 'flagTitular',\n 'sequencial_cartao': 'sequencialCartao',\n 'id_status': 'idStatus',\n 'descricao_status_cartao': 'descricaoStatusCartao',\n 'data_status': 'dataStatus',\n 'id_estagio': 'idEstagio',\n 'descricao_estagio': 'descricaoEstagio',\n 'data_estagio': 'dataEstagio',\n 'numero_bin': 'numeroBin',\n 'id_produto': 'idProduto',\n 'descricao_produto': 'descricaoProduto',\n 'id_status_conta': 'idStatusConta',\n 'descricao_status_conta': 'descricaoStatusConta',\n 'data_embossing': 'dataEmbossing',\n 'codigo_desbloqueio': 'codigoDesbloqueio',\n 'nome_pessoa': 'nomePessoa',\n 'tipo_pessoa': 'tipoPessoa',\n 'data_nascimento': 'dataNascimento',\n 'id_endereco': 'idEndereco',\n 'id_tipo_endereco': 'idTipoEndereco',\n 'descricao_tipo_endereco': 'descricaoTipoEndereco',\n 'cep': 'cep',\n 'logradouro': 'logradouro',\n 'numero_endereco': 'numeroEndereco',\n 'complemento_endereco': 'complementoEndereco',\n 'bairro': 'bairro',\n 'cidade': 'cidade',\n 'uf': 'uf',\n 'pais': 'pais',\n 'senha_criptografada': 'senhaCriptografada',\n 'icvv': 'icvv',\n 'id_status_impressao': 'idStatusImpressao'\n }\n\n self._id_conta = None\n self._id_pessoa = None\n self._id_cartao = None\n self._id_bandeira = None\n self._id_tipo_cartao = None\n self._numero_cartao = None\n self._nome_plastico = None\n self._cvv2 = None\n self._data_geracao = None\n self._data_validade = None\n self._cpf = None\n self._tipo_portador = None\n self._trilha1 = None\n self._trilha2 = None\n self._trilha_cvv1 = None\n self._trilha_cvv2 = None\n self._flag_virtual = None\n self._nome_bandeira = None\n self._flag_titular = None\n self._sequencial_cartao = None\n self._id_status = None\n self._descricao_status_cartao = None\n self._data_status = None\n self._id_estagio = None\n self._descricao_estagio = None\n self._data_estagio = None\n self._numero_bin = None\n self._id_produto = None\n self._descricao_produto = None\n self._id_status_conta = None\n self._descricao_status_conta = None\n self._data_embossing = None\n self._codigo_desbloqueio = None\n self._nome_pessoa = None\n self._tipo_pessoa = None\n self._data_nascimento = None\n self._id_endereco = None\n self._id_tipo_endereco = None\n self._descricao_tipo_endereco = None\n self._cep = None\n self._logradouro = None\n self._numero_endereco = None\n self._complemento_endereco = None\n self._bairro = None\n self._cidade = None\n self._uf = None\n self._pais = None\n self._senha_criptografada = None\n self._icvv = None\n self._id_status_impressao = None","def test_custom_query_response_descriptor_octopus_server_web_api_actions_list_defects_responder(self):\n pass","def _openapi_json(self):\n # We don't use Flask.jsonify here as it would sort the keys\n # alphabetically while we want to preserve the order.\n from pprint import pprint\n pprint(self.to_dict())\n return current_app.response_class(json.dumps(self.to_dict(), indent=4),\n mimetype='application/json')"],"string":"[\n \"async def get_model_metadata(\\n self,\\n model_name: str,\\n model_version: str = ...,\\n headers: dict[str, t.Any] = ...,\\n as_json: t.Literal[False] = ...,\\n ) -> service_pb2.ModelMetadataResponse:\",\n \"def api_documentation(api: str, summary: str, in_model: BaseModel,\\n out_model: BaseModel, out_description: str) -> Callable:\\n for model, name in ((in_model, 'Input'), (out_model, 'Output')):\\n doc.Object(\\n make_dataclass(\\n f'Api{api[1:].title()}{name}',\\n [(key, val.type_, val.type_)\\n for key, val in model.__dict__['__fields__'].items()]))\\n im_returns = doc.JsonBody({\\n key: val.type_\\n for key, val in in_model.__dict__['__fields__'].items()\\n })\\n\\n om_returns = {\\n key: val.type_\\n for key, val in out_model.__dict__['__fields__'].items()\\n }\\n\\n def decorator(func):\\n @doc.summary(summary)\\n @doc.response(412,\\n 'Error: Precondition Failed',\\n description='The passed request-parameters are invalid')\\n @doc.response(500,\\n 'Error: Server-Error occured',\\n description='An internal error occured')\\n @doc.consumes(im_returns,\\n content_type='application/json',\\n location='body')\\n @doc.produces(om_returns,\\n content_type='application/json',\\n description=out_description)\\n @wraps(func)\\n async def function_wrapper(request, *args, **kwargs):\\n return await func(request=request, *args, **kwargs)\\n\\n return function_wrapper\\n\\n return decorator\",\n \"def to_dict(self):\\n result = {}\\n\\n for attr, _ in six.iteritems(self.swagger_types):\\n value = getattr(self, attr)\\n if isinstance(value, list):\\n result[attr] = list(map(\\n lambda x: x.to_dict() if hasattr(x, \\\"to_dict\\\") else x,\\n value\\n ))\\n elif hasattr(value, \\\"to_dict\\\"):\\n result[attr] = value.to_dict()\\n elif isinstance(value, dict):\\n result[attr] = dict(map(\\n lambda item: (item[0], item[1].to_dict())\\n if hasattr(item[1], \\\"to_dict\\\") else item,\\n value.items()\\n ))\\n else:\\n result[attr] = value\\n if issubclass(ExportResponseMetadata, dict):\\n for key, value in self.items():\\n result[key] = value\\n\\n return result\",\n \"def export_model(self):\\n\\n model_pkg = dict()\\n\\n for k, v in self.__dict__.items():\\n if k not in ['datas'] and not k.startswith('_'):\\n model_pkg[k] = v\\n\\n for i in range(len(self.datas)):\\n for k, v in self.datas[i].__dict__.items():\\n model_pkg['datas_%d_%s' % (i, k)] = v\\n\\n return model_pkg\",\n \"def GetModelOutputInfo(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 make_response(self):\\n params = {\\n 'tweet.fields': 'created_at,public_metrics,entities',\\n 'expansions': 'author_id',\\n 'user.fields': 'description'\\n }\\n return self.response_limit(params)\",\n \"def test_metadata(self):\\n class ExampleView(views.APIView):\\n \\\"\\\"\\\"Example view.\\\"\\\"\\\"\\n pass\\n\\n view = ExampleView.as_view()\\n response = view(request=request)\\n expected = {\\n 'name': 'Example',\\n 'description': 'Example view.',\\n 'renders': [\\n 'application/json',\\n 'text/html'\\n ],\\n 'parses': [\\n 'application/json',\\n 'application/x-www-form-urlencoded',\\n 'multipart/form-data'\\n ]\\n }\\n assert response.status_code == status.HTTP_200_OK\\n assert response.data == expected\",\n \"def metadata(self) -> 'outputs.DataCollectionEndpointResponseMetadata':\\n return pulumi.get(self, \\\"metadata\\\")\",\n \"def get_metadata_v2(session):\\n LOG.debug(\\\"Exporting metadata for SFS augur build\\\")\\n\\n metadata = datastore.fetch_rows_from_table(session, (\\\"shipping\\\", \\\"metadata_for_augur_build_v2\\\"))\\n\\n return Response((row[0] + '\\\\n' for row in metadata), mimetype=\\\"application/x-ndjson\\\")\",\n \"def metadata():\\n req = prepare_onelogin_request(request)\\n saml_auth = init_saml_auth(req)\\n settings = saml_auth.get_settings()\\n metadata = settings.get_sp_metadata()\\n errors = settings.validate_metadata(metadata)\\n\\n if len(errors) == 0:\\n resp = make_response(metadata, 200)\\n resp.headers[\\\"Content-Type\\\"] = \\\"text/xml\\\"\\n else:\\n resp = make_response(\\\", \\\".join(errors), 500)\\n return resp\",\n \"def __metadata__(self):\\n raise NotImplementedError\",\n \"def metadata():\\n req = prepare_flask_request(request)\\n auth = init_saml_auth(req)\\n settings = auth.get_settings()\\n sp_metadata = settings.get_sp_metadata()\\n errors = settings.validate_metadata(sp_metadata)\\n\\n if len(errors) == 0:\\n resp = make_response(sp_metadata, 200)\\n resp.headers[\\\"Content-Type\\\"] = \\\"text/xml\\\"\\n else:\\n resp = make_response(\\\", \\\".join(errors), 500)\\n return resp\",\n \"def metadata(self) -> global___SummaryMetadata:\",\n \"def metadata(self): # -> None:\\n ...\",\n \"def GetMetadata(self):\\n return self.dict['meta']\",\n \"def _create_output_metadata(self):\\n\\n # Create output info.\\n output_meta = _metadata_fb.TensorMetadataT()\\n output_meta.name = \\\"probability\\\"\\n output_meta.description = \\\"Probabilities of labels respectively.\\\"\\n output_meta.content = _metadata_fb.ContentT()\\n output_meta.content.contentProperties = _metadata_fb.FeaturePropertiesT()\\n output_meta.content.contentPropertiesType = (\\n _metadata_fb.ContentProperties.FeatureProperties)\\n label_file = _metadata_fb.AssociatedFileT()\\n label_file.name = os.path.basename(self.model_info.label_file)\\n label_file.description = (\\\"Labels for classification categories.\\\")\\n label_file.type = _metadata_fb.AssociatedFileType.TENSOR_AXIS_LABELS\\n output_meta.associatedFiles = [label_file]\\n return [output_meta]\",\n \"def fetch_ml_model_info() -> ApiResponse:\\n return _api_response(settings.ML_MODELS)\",\n \"def model(self) -> 'outputs.ModelDefinitionResponse':\\n return pulumi.get(self, \\\"model\\\")\",\n \"def gen_response_object(description, media_type, api_type, path):\\n\\n response = {\\n 'description': description,\\n 'content': gen_media_type_object(media_type, api_type, path)\\n }\\n\\n return response\",\n \"def get_response_model_ctor(self):\\n return self._response_model_ctor\",\n \"def api_outputmodel(api: str, model: BaseModel, servicename: str,\\n service_logger: logger) -> Callable:\\n\\n def decorator(func):\\n @wraps(func)\\n async def function_wrapper(request, *args, **kwargs):\\n service_result = await func(request, *args, **kwargs)\\n try:\\n if isinstance(service_result, model):\\n result = service_result\\n else:\\n result = model(**service_result)\\n output = response.json(result.dict())\\n except Exception as err:\\n msg = ('an internal error occured (service: '\\n f'{servicename}, api: {api}): {err}')\\n raise ServerError(msg)\\n service_logger.info(f'processed result {result} => '\\n f'{output.content_type} [{output.status}] '\\n f'{output.body}')\\n return output\\n\\n return function_wrapper\\n\\n return decorator\",\n \"def _create_response_model(self, data):\\n pass\",\n \"def test_api_can_get_metadata(self):\\n response = self.client.get('/metadata/', format=\\\"json\\\")\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def _generate_model_metadata(out_file, model):\\n # Define which FirstLevelModel attributes are BIDS compliant and which\\n # should be bundled in a new \\\"ModelParameters\\\" field.\\n DATA_ATTRIBUTES = [\\n \\\"t_r\\\",\\n ]\\n PARAMETER_ATTRIBUTES = [\\n \\\"drift_model\\\",\\n \\\"hrf_model\\\",\\n \\\"standardize\\\",\\n \\\"high_pass\\\",\\n \\\"target_shape\\\",\\n \\\"signal_scaling\\\",\\n \\\"drift_order\\\",\\n \\\"scaling_axis\\\",\\n \\\"smoothing_fwhm\\\",\\n \\\"target_affine\\\",\\n \\\"slice_time_ref\\\",\\n \\\"fir_delays\\\",\\n ]\\n ATTRIBUTE_RENAMING = {\\n \\\"t_r\\\": \\\"RepetitionTime\\\",\\n }\\n\\n # Fields for the top level of the dictionary\\n DATA_ATTRIBUTES.sort()\\n data_attributes = {\\n attr_name: getattr(model, attr_name)\\n for attr_name in DATA_ATTRIBUTES\\n if hasattr(model, attr_name)\\n }\\n data_attributes = {\\n ATTRIBUTE_RENAMING.get(k, k): v for k, v in data_attributes.items()\\n }\\n\\n # Fields for a nested section of the dictionary\\n # The ModelParameters field is an ad-hoc way to retain useful info.\\n PARAMETER_ATTRIBUTES.sort()\\n model_attributes = {\\n attr_name: getattr(model, attr_name)\\n for attr_name in PARAMETER_ATTRIBUTES\\n if hasattr(model, attr_name)\\n }\\n model_attributes = {\\n ATTRIBUTE_RENAMING.get(k, k): v for k, v in model_attributes.items()\\n }\\n\\n model_metadata = {\\n \\\"Description\\\": \\\"A statistical map generated by Nilearn.\\\",\\n **data_attributes,\\n \\\"ModelParameters\\\": model_attributes,\\n }\\n\\n with open(out_file, \\\"w\\\") as f_obj:\\n json.dump(model_metadata, f_obj, indent=4, sort_keys=True)\",\n \"def get_metadata(self):\\n\\n\\t\\t#see redcap api documentation -- https://redcap.wustl.edu/redcap/srvrs/prod_v3_1_0_001/redcap/api/help/\\n\\t\\tbuf = io.BytesIO()\\n\\n\\t\\tfields = {\\n\\t\\t 'token': config['api_token'],\\n\\t\\t 'content': 'metadata',\\n\\t\\t 'format': 'json'\\n\\t\\t}\\n\\n\\t\\tch = pycurl.Curl()\\n\\t\\tch.setopt(ch.URL, config['api_url'])\\n\\t\\tch.setopt(ch.HTTPPOST, list(fields.items()))\\n\\t\\tch.setopt(ch.WRITEFUNCTION, buf.write)\\n\\t\\tch.perform()\\n\\t\\tch.close()\\n\\n\\t\\tmetadata = json.loads(buf.getvalue().decode())\\n\\t\\tbuf.close()\\n\\t\\treturn metadata\",\n \"def get_metadata_v3(session):\\n LOG.debug(\\\"Exporting metadata for SFS augur build\\\")\\n\\n metadata = datastore.fetch_rows_from_table(session, (\\\"shipping\\\", \\\"metadata_for_augur_build_v3\\\"))\\n\\n return Response((row[0] + '\\\\n' for row in metadata), mimetype=\\\"application/x-ndjson\\\")\",\n \"def swagger_definition(self, base_path=None, **kwargs):\\n return Swagger(\\n {\\n \\\"info\\\": Info(\\n {\\n key: kwargs.get(key, self.DEFAULT_INFO.get(key))\\n for key in Info.fields.keys()\\n if key in kwargs or key in self.DEFAULT_INFO\\n }\\n ),\\n \\\"paths\\\": self.paths,\\n \\\"swagger\\\": \\\"2.0\\\",\\n \\\"basePath\\\": base_path,\\n }\\n ).to_primitive()\",\n \"def get_metadata():\\n\\n module = __name__.split('.', 1)\\n\\n try:\\n pkg = pkg_resources.get_distribution(module[0])\\n except pkg_resources.RequirementParseError:\\n # if called from CLI, try to get pkg from the path\\n distros = list(pkg_resources.find_distributions(cfg.BASE_DIR, \\n only=True))\\n if len(distros) == 1:\\n pkg = distros[0]\\n except Exception as e:\\n raise HTTPBadRequest(reason=e)\\n\\n # deserialize key-word arguments\\n train_args = _fields_to_dict(get_train_args())\\n # make 'type' JSON serializable\\n for key, val in train_args.items():\\n train_args[key]['type'] = str(val['type'])\\n\\n predict_args = _fields_to_dict(get_predict_args())\\n # make 'type' JSON serializable\\n for key, val in predict_args.items():\\n predict_args[key]['type'] = str(val['type'])\\n\\n meta = {\\n 'name' : None,\\n 'version' : None,\\n 'summary' : None,\\n 'home-page' : None,\\n 'author' : None,\\n 'author-email' : None,\\n 'license' : None,\\n 'help-train' : train_args,\\n 'help-predict' : predict_args\\n }\\n for line in pkg.get_metadata_lines(\\\"PKG-INFO\\\"):\\n line_low = line.lower() # to avoid inconsistency due to letter cases\\n for par in meta:\\n if line_low.startswith(par.lower() + \\\":\\\"):\\n _, value = line.split(\\\": \\\", 1)\\n meta[par] = value\\n\\n return meta\",\n \"def meta(self) -> api.Meta:\\n return self._get_model(model=api.Meta)\",\n \"def __init__(self, **kwargs):\\n self.swagger_types = {\\n 'id': 'str',\\n 'name': 'str',\\n 'version': 'str',\\n 'tagline': 'str',\\n 'keywords': 'str',\\n 'short_description': 'str',\\n 'usage_information': 'str',\\n 'long_description': 'str',\\n 'license_model_description': 'str',\\n 'system_requirements': 'str',\\n 'time_released': 'datetime',\\n 'release_notes': 'str',\\n 'categories': 'list[str]',\\n 'publisher': 'Publisher',\\n 'languages': 'list[Item]',\\n 'screenshots': 'list[Screenshot]',\\n 'videos': 'list[NamedLink]',\\n 'support_contacts': 'list[SupportContact]',\\n 'support_links': 'list[NamedLink]',\\n 'documentation_links': 'list[DocumentationLink]',\\n 'icon': 'UploadData',\\n 'banner': 'UploadData',\\n 'regions': 'list[Region]',\\n 'package_type': 'str',\\n 'default_package_version': 'str',\\n 'links': 'list[Link]',\\n 'is_featured': 'bool'\\n }\\n\\n self.attribute_map = {\\n 'id': 'id',\\n 'name': 'name',\\n 'version': 'version',\\n 'tagline': 'tagline',\\n 'keywords': 'keywords',\\n 'short_description': 'shortDescription',\\n 'usage_information': 'usageInformation',\\n 'long_description': 'longDescription',\\n 'license_model_description': 'licenseModelDescription',\\n 'system_requirements': 'systemRequirements',\\n 'time_released': 'timeReleased',\\n 'release_notes': 'releaseNotes',\\n 'categories': 'categories',\\n 'publisher': 'publisher',\\n 'languages': 'languages',\\n 'screenshots': 'screenshots',\\n 'videos': 'videos',\\n 'support_contacts': 'supportContacts',\\n 'support_links': 'supportLinks',\\n 'documentation_links': 'documentationLinks',\\n 'icon': 'icon',\\n 'banner': 'banner',\\n 'regions': 'regions',\\n 'package_type': 'packageType',\\n 'default_package_version': 'defaultPackageVersion',\\n 'links': 'links',\\n 'is_featured': 'isFeatured'\\n }\\n\\n self._id = None\\n self._name = None\\n self._version = None\\n self._tagline = None\\n self._keywords = None\\n self._short_description = None\\n self._usage_information = None\\n self._long_description = None\\n self._license_model_description = None\\n self._system_requirements = None\\n self._time_released = None\\n self._release_notes = None\\n self._categories = None\\n self._publisher = None\\n self._languages = None\\n self._screenshots = None\\n self._videos = None\\n self._support_contacts = None\\n self._support_links = None\\n self._documentation_links = None\\n self._icon = None\\n self._banner = None\\n self._regions = None\\n self._package_type = None\\n self._default_package_version = None\\n self._links = None\\n self._is_featured = None\",\n \"def output_metadata(self, metadata = None):\\n return True\",\n \"def build_metadata(results):\\n\\n print('Building metadata...')\\n\\n fields = set(['name', 'timestamp', 'value', 'scrape_timestamp'])\\n metadata = connector_pb2.GetDataResponse()\\n\\n for result in results:\\n for metric in result['metric'].keys():\\n if metric != '__name__':\\n fields.add(metric)\\n\\n for field in fields:\\n metadata.fieldInfo.extend([connector_pb2.FieldInfo(name = field)])\\n\\n return metadata\",\n \"def get_metadata_as_dict(self):\\n try:\\n return json.loads(self._env.lab_handler.lab_obj_to_json(self.exp_metadata))\\n except:\\n # lab handler not initialized\\n import lab_api.swagger_client as swagger_client\\n json.loads(json.dumps(swagger_client.ApiClient().sanitize_for_serialization(self.exp_metadata)))\",\n \"def get_openapi_spec(self):\\n\\n spec = {\\\"operationId\\\": snake_to_camel(self._wrapped_function.__name__), \\\"responses\\\": {}}\\n\\n if self._doc.short_description:\\n spec[\\\"summary\\\"] = self._doc.short_description\\n\\n if self._doc.long_description:\\n spec[\\\"description\\\"] = self._doc.long_description\\n\\n if self._tags:\\n spec[\\\"tags\\\"] = self._tags\\n\\n if self._path_parameters or self._query_parameters:\\n spec[\\\"parameters\\\"] = []\\n\\n for name, param_type in self._path_parameters.items():\\n if self._is_param_ignored(name):\\n continue\\n\\n param_spec = {\\n \\\"name\\\": name,\\n \\\"in\\\": \\\"path\\\",\\n \\\"required\\\": True,\\n \\\"schema\\\": {\\\"type\\\": self._extension.PARAMETER_TYPE_MAP.get(param_type, \\\"string\\\")},\\n }\\n\\n param_doc = self._get_param_doc(name)\\n if param_doc is not None:\\n param_spec[\\\"description\\\"] = param_doc.description\\n\\n spec[\\\"parameters\\\"].append(param_spec)\\n\\n for name, param_type in self._query_parameters.items():\\n param_refl: inspect.Parameter = self._signature.parameters[name]\\n param_spec = {\\n \\\"name\\\": name,\\n \\\"in\\\": \\\"query\\\",\\n \\\"required\\\": param_refl.default == inspect.Parameter.empty,\\n \\\"schema\\\": {\\\"type\\\": self._extension.PARAMETER_TYPE_MAP.get(param_type, \\\"string\\\")},\\n }\\n\\n param_doc = self._get_param_doc(name)\\n if param_doc is not None:\\n param_spec[\\\"description\\\"] = param_doc.description\\n\\n spec[\\\"parameters\\\"].append(param_spec)\\n\\n if self._request_body_parameter:\\n mimetypes = self._request_body_content_types\\n\\n spec[\\\"requestBody\\\"] = {\\n \\\"content\\\": {\\n mimetype: {\\\"schema\\\": self._process_model_schema(self._request_body_class)} for mimetype in mimetypes\\n },\\n \\\"required\\\": True,\\n }\\n\\n if issubclass(self._request_body_class, ExamplesMixin):\\n for mimetype in mimetypes:\\n spec[\\\"requestBody\\\"][\\\"content\\\"][mimetype][\\\"examples\\\"] = model_examples_to_openapi_dict(\\n self._request_body_class\\n )\\n\\n param_doc = self._get_param_doc(self._request_body_parameter)\\n if param_doc is not None and param_doc.description:\\n spec[\\\"requestBody\\\"][\\\"description\\\"] = param_doc.description\\n\\n spec[\\\"x-codegen-request-body-name\\\"] = \\\"body\\\"\\n elif self._request_body_file_type:\\n spec[\\\"requestBody\\\"] = {\\n \\\"content\\\": {self._request_body_file_type: {\\\"schema\\\": {\\\"type\\\": \\\"string\\\", \\\"format\\\": \\\"binary\\\"}}}\\n }\\n\\n if self._security:\\n spec[\\\"security\\\"] = self._security\\n\\n for response_class, codes in self._responses.items():\\n for code, response_data in codes.items():\\n if issubclass(response_class, FileResponse):\\n mime = response_data.mimetype or \\\"application/octet-stream\\\"\\n spec[\\\"responses\\\"][str(code)] = {\\n \\\"description\\\": response_data.description or response_class.__name__,\\n \\\"content\\\": {mime: {\\\"schema\\\": {\\\"type\\\": \\\"string\\\", \\\"format\\\": \\\"binary\\\"}}},\\n }\\n else:\\n spec[\\\"responses\\\"][str(code)] = {\\n \\\"description\\\": response_data.description or response_class.__name__,\\n \\\"content\\\": {\\\"application/json\\\": {\\\"schema\\\": self._process_model_schema(response_class)}},\\n }\\n\\n if issubclass(response_class, ExamplesMixin):\\n # fmt: off\\n spec[\\\"responses\\\"][str(code)][\\\"content\\\"][\\\"application/json\\\"][\\\"examples\\\"] = \\\\\\n model_examples_to_openapi_dict(response_class)\\n # fmt: on\\n\\n return spec\",\n \"def to_api_data(self):\\n raise NotImplementedError()\",\n \"def _get_response_from_annotation(self) -> Generator[Tuple[Type[BaseModel], int, ResponseData], None, None]:\\n annotation = self._signature.return_annotation\\n\\n if annotation is inspect.Signature.empty:\\n return\\n\\n annotation = resolve_fw_decl(self._wrapped_function, annotation)\\n\\n if not issubclass(annotation, BaseModel):\\n raise TypeError(\\\"Unsupported return type\\\")\\n\\n yield annotation, 200, ResponseData(self._doc.returns.description if self._doc.returns else None)\",\n \"def test_api_schema(self):\\n response = self.client.get(\\\"/api/schema/\\\")\\n self.assertEqual(response.status_code, 200)\\n self.assertEqual(\\n response.get(\\\"Content-Type\\\"), \\\"application/vnd.oai.openapi; charset=utf-8\\\"\\n )\\n self.assertEqual(\\n response.get(\\\"Content-Disposition\\\"), 'inline; filename=\\\"Marsha API.yaml\\\"'\\n )\",\n \"def meta(self):\\n return self.spec.meta\",\n \"def swagger():\\n return jsonify(current_app.spec.to_dict())\",\n \"def model_info():\\n pass\",\n \"def metadata(self):\\r\\n return resources.Metadata(self)\",\n \"def get_metadata(self):\\n return {}\",\n \"def emit_swagger_spec(ctx, modules, fd, path):\\n\\n printed_header = False\\n model = OrderedDict()\\n definitions = OrderedDict()\\n augments = list()\\n # Go through all modules and extend the model.\\n for module in modules:\\n if not printed_header:\\n model = print_header(module, fd)\\n printed_header = True\\n path = '/'\\n\\n typdefs = [module.i_typedefs[element] for element in module.i_typedefs]\\n models = list(module.i_groupings.values())\\n referenced_types = list()\\n referenced_types = findTypedefs(ctx, module, models, referenced_types)\\n for element in referenced_types:\\n typdefs.append(element)\\n\\n # The attribute definitions are processed and stored in the \\\"typedefs\\\" data structure for further use.\\n gen_typedefs(typdefs)\\n\\n # list() needed for python 3 compatibility\\n referenced_models = list()\\n referenced_models = findModels(ctx, module, models, referenced_models)\\n for element in referenced_models:\\n models.append(element)\\n # Print the swagger definitions of the Yang groupings.\\n definitions = gen_model(models, definitions)\\n\\n # If a model at runtime was dependant of another model which had been encounter yet, it is generated 'a posteriori'.\\n if pending_models:\\n gen_model(pending_models, definitions)\\n\\n if PARENT_MODELS:\\n for element in PARENT_MODELS:\\n if PARENT_MODELS[element]['models']:\\n definitions[element]['discriminator'] = PARENT_MODELS[element]['discriminator']\\n # extract children which contain data definition keywords\\n chs = [ch for ch in module.i_children\\n if ch.keyword in (statements.data_definition_keywords + ['rpc','notification'])]\\n\\n # generate the APIs for all children\\n if len(chs) > 0:\\n model['paths'] = OrderedDict()\\n gen_apis(chs, path, model['paths'], definitions)\\n\\n model['definitions'] = definitions\\n fd.write(json.dumps(model, indent=4, separators=(',', ': ')))\",\n \"def test_schema_dump_metadata(\\n self,\\n schema_url: str,\\n title: str,\\n description: str\\n ):\\n json_schema = JSONSchema(schema_url, title, description)\\n result = json_schema.dump(self.schema_to_serialize)\\n\\n self.assertEqual(\\n description, result['description']\\n )\\n self.assertEqual(\\n title, result['title']\\n )\\n self.assertEqual(\\n schema_url, result['$schema']\\n )\",\n \"def get_sample_metadata(request, pk):\\n sample = Sample.objects.get(pk=pk)\\n mygrp = sample.library.group\\n if not mygrp.is_public:\\n try:\\n membership_queryset = request.user.organization_set.filter(pk=mygrp.organization.pk)\\n authorized = membership_queryset.exists()\\n except AttributeError: # occurs if user is not logged in\\n authorized = False\\n if not authorized:\\n raise PermissionDenied(_('Insufficient permissions to get group manifest.'))\\n blob = SampleSerializer(sample).data\\n blob['versioned_metadata'] = [\\n {\\n 'created_at': vm.created_at,\\n 'updated_at': vm.updated_at,\\n 'metadata': vm.metadata,\\n }\\n for vm in sample.versioned_metadata.all()\\n ]\\n\\n return Response(blob)\",\n \"def create_model(self, ApiId: str, Name: str, Schema: str, ContentType: str = None, Description: str = None) -> Dict:\\n pass\",\n \"def introspectionResponse(self):\\n return self._introspectionResponse\",\n \"def schema(self):\\n # TODO The schema of a container resource...\\n # This is the same as the leaf.\\n # However, this isn't actually the schema of the response\\n return {\\n \\\"$id\\\": f\\\"{self.request.resource_url(self)}#schema\\\",\\n \\\"type\\\": \\\"object\\\",\\n \\\"properties\\\": {\\n \\\"foo\\\": {\\\"type\\\": \\\"string\\\"},\\n # generated fields shouldn't be submitted or in forms\\n \\\"url\\\": {\\\"type\\\": \\\"string\\\", \\\"generated\\\": True},\\n }\\n }\",\n \"def to_api_repr(self):\\n raise NotImplementedError\",\n \"def get_annotations(self):\\n entity = self.get_object()\\n serializer = AnnotationValueSerializer(entity.annotations.all(), many=True)\\n return Response(serializer.data)\",\n \"def describe(model_element, **kwargs):\\n model_descriptor = ModelDescriptor(**kwargs)\\n return model_descriptor.describe(model_element)\",\n \"def process_metadata(self):\\n\\n self._responses = self._get_responses()\\n\\n (\\n self._request_body_parameter,\\n self._request_body_class,\\n self._request_body_content_types,\\n ) = self._get_request_body_parameter()\\n\\n if self._request_body_content_types is None:\\n self._request_body_content_types = [\\\"application/json\\\"]\\n\\n self._request_body_file_type = self._get_request_body_file_type()\\n if self._request_body_parameter is not None and self._request_body_file_type is not None:\\n raise TypeError(\\\"An endpoint cannot accept both a file and a model\\\")\\n\\n self._query_parameters = dict(self._get_query_string_parameters())\\n self._path_parameters = dict(self._get_path_parameters())\\n\\n self._security = [*self._get_security_requirements()]\\n self._tags = [*self._get_tags()]\",\n \"def response_helper(self, response, **kwargs):\\n self.resolve_schema(response)\\n if \\\"headers\\\" in response:\\n for header in response[\\\"headers\\\"].values():\\n self.resolve_schema(header)\\n return response\",\n \"def extract_http_metadata(wrapped, instance, args, kwargs, return_value):\\n response = return_value\\n LOGGER.debug(\\n \\\"Extracting HTTP metadata\\\", args=args, kwargs=kwargs,\\n )\\n if \\\"request\\\" in kwargs:\\n request = kwargs[\\\"request\\\"]\\n else:\\n request = args[0]\\n\\n metadata = {\\n \\\"http\\\": {\\\"request\\\": {\\\"method\\\": request.method.upper(), \\\"url\\\": request.url}},\\n }\\n if response is not None:\\n metadata[\\\"http\\\"][\\\"response\\\"] = {\\n \\\"status\\\": response.status_code,\\n }\\n\\n return metadata\",\n \"def __init__(self): # noqa: E501\\n self.openapi_types = {\\n }\\n\\n self.attribute_map = {\\n }\",\n \"def opt_model_create_rest_api():\\n request_json = request.get_json()\\n OptimModelRequestAPI(request_json).validate()\\n return create_model_data(request_json)\",\n \"def response(schema):\\n def _response(function):\\n @wraps(function)\\n def wrapper(*args, **kwargs):\\n if issubclass(schema, BaseModel):\\n has_root = True if '__root__' in schema.__fields__ else False\\n function_res = function(*args, **kwargs)\\n\\n if not function_res:\\n if has_root is True:\\n return jsonify([])\\n return jsonify({})\\n\\n if type(function_res) == list:\\n res = schema.parse_obj(function_res)\\n else:\\n res = schema.from_orm(function_res)\\n\\n res = res.dict()\\n\\n if has_root is True:\\n return jsonify(res['__root__'])\\n\\n return jsonify(res)\\n elif isinstance(schema, dict):\\n return jsonify(schema)\\n else:\\n raise CustomException('invalid response type', code=400)\\n\\n return wrapper\\n return _response\",\n \"def extract_metadata(res):\\n d = OrderedDict()\\n\\n d['type'] = res['type']\\n d['authors'] = make_author_list(res)\\n d['citation-authors'] = make_citation_authors(res)\\n d['citation'] = make_citation(res)\\n d['source-title'] = res['title'].strip(\\\" \\\").capitalize()\\n d['title'] = \\\"Notes on '\\\" + d['source-title'] + \\\"', by \\\" + \\\", \\\".join(d['authors'][0:-1])\\n if len(d['authors']) > 1:\\n d['title'] = d['title'] + \\\", and \\\" + d['authors'][-1] \\n d['citation-authors']\\n d['container'] = make_container(res)\\n d['publisher'] = res['publisher'] if 'publisher' in res.keys() else '' \\n d['issn'] = res['issn'] if 'issn' in res.keys() else ''\\n d['year'] = make_year(res)\\n d['issue'] = res['issue'] if \\\"issue\\\" in res.keys() else \\\"\\\"\\n d['volume'] = res['volume'] if \\\"volume\\\" in res.keys() else \\\"\\\"\\n d['pages'] = res['page'] if \\\"page\\\" in res.keys() else \\\"\\\"\\n d['subjects'] = make_subject(res)\\n d['doi'] = res['DOI']\\n d['link'] = res['URL']\\n d['citationkey'] = make_citation_key(res)\\n d['fetched'] = date.today().strftime(\\\"%Y%m%d\\\")\\n return d\",\n \"def responses(resp_def):\\n def decorator(fn): # pylint: disable=missing-docstring\\n meta = RouteMeta.load(fn)\\n meta.responses = resp_def\\n meta.save()\\n return fn\\n return decorator\",\n \"def test_add_model_with_resource_fields_nested_swagger_metadata(model_class,):\\n pdst = patch_deduce_swagger_type\\n pr = patch_registry\\n ppd = patch_parse_doc\\n pha = patch_hasattr\\n\\n with pr(), ppd(), patch_isinstance(True) as mock_isinstance:\\n with pha() as mock_hasattr:\\n with patch_dir([\\\"resource_fields\\\"]) as mock_dir:\\n with pdst() as mock_deduce_swagger_type:\\n swagger.add_model(model_class)\\n\\n mock_dir.assert_called_with(model_class)\\n assert mock_dir.call_count == 2\\n mock_hasattr.assert_called_once_with(\\n model_class, \\\"required\\\")\\n mock_isinstance.assert_called_with(\\n model_class, swagger._Nested)\\n assert mock_deduce_swagger_type.call_count == len(\\n model_class.resource_fields.items()\\n )\",\n \"def metadata(self):\\n return self.meta.metadata\",\n \"def dump_model(self):\",\n \"def __init__(self):\\n self.swagger_types = {\\n 'detail_type': 'str',\\n 'name': 'str',\\n 'store_data': 'object',\\n 'discovered': 'datetime',\\n 'extraction_failure': 'bool',\\n 'in_trash': 'bool',\\n 'is_extracted': 'bool',\\n 'meta_available': 'bool',\\n 'size': 'int',\\n 'start_time': 'datetime',\\n 'end_time': 'datetime',\\n 'duration': 'float',\\n 'messages': 'int',\\n 'tags': 'list[Tag]'\\n }\\n\\n self.attribute_map = {\\n 'detail_type': 'detail_type',\\n 'name': 'name',\\n 'store_data': 'store_data',\\n 'discovered': 'discovered',\\n 'extraction_failure': 'extraction_failure',\\n 'in_trash': 'in_trash',\\n 'is_extracted': 'is_extracted',\\n 'meta_available': 'meta_available',\\n 'size': 'size',\\n 'start_time': 'start_time',\\n 'end_time': 'end_time',\\n 'duration': 'duration',\\n 'messages': 'messages',\\n 'tags': 'tags'\\n }\\n\\n self._detail_type = None\\n self._name = None\\n self._store_data = None\\n self._discovered = None\\n self._extraction_failure = None\\n self._in_trash = None\\n self._is_extracted = None\\n self._meta_available = None\\n self._size = None\\n self._start_time = None\\n self._end_time = None\\n self._duration = None\\n self._messages = None\\n self._tags = None\",\n \"def serve_metadata():\\n xml = generate_xml_metadata()\\n return Response(xml, mimetype=\\\"application/gzip\\\")\",\n \"def metadata(self) -> \\\"ObjectMeta\\\":\\n return typing.cast(\\n \\\"ObjectMeta\\\",\\n self._properties.get(\\\"metadata\\\"),\\n )\",\n \"def __init__(self, type=None, metadata=None): # noqa: E501\\n self.openapi_types = {\\\"type\\\": str, \\\"metadata\\\": Metadata}\\n\\n self.attribute_map = {\\\"type\\\": \\\"type\\\", \\\"metadata\\\": \\\"metadata\\\"}\\n\\n self._type = type\\n self._metadata = metadata\",\n \"def api_metadata_properties(self) -> Optional[pulumi.Input['GatewayApiMetadataPropertiesArgs']]:\\n return pulumi.get(self, \\\"api_metadata_properties\\\")\",\n \"def test_custom_action_response_descriptor_octopus_server_web_api_actions_defect_reported_responder(self):\\n pass\",\n \"def metadata(self): # -> list[Unknown]:\\n ...\",\n \"def metadata(self): # -> list[Unknown]:\\n ...\",\n \"def _metadata(self) -> Dict[str, Any]:\\n return self.__metadata\",\n \"def meta_data(self):\\r\\n return simplejson.dumps(self.__resource_meta)\",\n \"def PostModelOutputs(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 expose_models(app, HOST=\\\"localhost\\\", PORT=5000, API_PREFIX=\\\"/api\\\"):\\n\\n api = SAFRSAPI(app, host=HOST, port=PORT)\\n api.expose_object(models.Category)\\n api.expose_object(models.CustomerCustomerDemo)\\n api.expose_object(models.OrderDetail)\\n api.expose_object(models.Order)\\n api.expose_object(models.Customer)\\n api.expose_object(models.CustomerDemographic)\\n api.expose_object(models.EmployeeAudit)\\n api.expose_object(models.EmployeeTerritory)\\n api.expose_object(models.Employee)\\n api.expose_object(models.Product)\\n api.expose_object(models.Region)\\n api.expose_object(models.Shipper)\\n api.expose_object(models.Supplier)\\n api.expose_object(models.Territory)\\n return api\",\n \"def describe_model(ModelName=None):\\n pass\",\n \"def _metadata(self):\\n meta = super()._metadata\\n meta.update({\\n \\\"name\\\": self.name,\\n \\\"lead_in_time\\\": self.lead_in_time,\\n \\\"amplification\\\": self.amplification,\\n \\\"amplifier_clipping\\\": self.amplifier_clipping,\\n \\\"power_threshold\\\": self.power_threshold,\\n })\\n return meta\",\n \"def handle_models_request():\\n # TODO: add sort and filter by creation/modification date\\n return (\\n json.dumps({\\\"models\\\": {\\n k: d[\\\"data\\\"] for k, d in app.models.items()\\n }}), 200,\\n {'ContentType': 'application/json'}\\n )\",\n \"def _generate_implicit_api_resource(self):\\n return ImplicitHttpApiResource().to_dict()\",\n \"def to_dict(model):\\n result = {}\\n for attr, _ in six.iteritems(model.swagger_types):\\n value = getattr(model, attr)\\n result[attr] = to_dict_value(value)\\n return result\",\n \"def extract_metadata(self):\\n if self.is_generatable_file:\\n logger.debug(\\\"Converting collected details to dict..\\\")\\n if self.metadata_collector:\\n self.metadata = MetadataToDict(\\n metadata_collector=self.metadata_collector,\\n file_import=self.file_import,\\n )\\n self.metadata.build_integration_dict()\",\n \"def __init__(self):\\n self.swagger_types = {\\n 'id_conta': 'int',\\n 'id_produto': 'int',\\n 'id_pessoa': 'int',\\n 'id_parentesco': 'int',\\n 'tipo_portador': 'str',\\n 'nome_impresso': 'str',\\n 'id_tipo_cartao': 'int',\\n 'flag_ativo': 'int',\\n 'data_cadastro_portador': 'str',\\n 'data_cancelamento_portador': 'str'\\n }\\n\\n self.attribute_map = {\\n 'id_conta': 'idConta',\\n 'id_produto': 'idProduto',\\n 'id_pessoa': 'idPessoa',\\n 'id_parentesco': 'idParentesco',\\n 'tipo_portador': 'tipoPortador',\\n 'nome_impresso': 'nomeImpresso',\\n 'id_tipo_cartao': 'idTipoCartao',\\n 'flag_ativo': 'flagAtivo',\\n 'data_cadastro_portador': 'dataCadastroPortador',\\n 'data_cancelamento_portador': 'dataCancelamentoPortador'\\n }\\n\\n self._id_conta = None\\n self._id_produto = None\\n self._id_pessoa = None\\n self._id_parentesco = None\\n self._tipo_portador = None\\n self._nome_impresso = None\\n self._id_tipo_cartao = None\\n self._flag_ativo = None\\n self._data_cadastro_portador = None\\n self._data_cancelamento_portador = None\",\n \"async def get_inference_statistics(\\n self,\\n model_name: str = ...,\\n model_version: str = ...,\\n headers: dict[str, t.Any] = ...,\\n as_json: t.Literal[False] = ...,\\n ) -> service_pb2.ModelStatisticsResponse:\",\n \"def test_model_metadata_type(self):\\n self.assertTrue(type(self.meta) is dict)\",\n \"def test_getMetadata_full(self):\\n metadata = self.resolver.getMetadata()\\n self.assertIsInstance(\\n metadata, Collection,\\n \\\"Resolver should return a collection object\\\"\\n )\\n self.assertIsInstance(\\n metadata.members[0], Collection,\\n \\\"Members of Inventory should be TextGroups\\\"\\n )\\n self.assertEqual(\\n len(metadata.descendants), 43,\\n \\\"There should be as many descendants as there is edition, translation, works and textgroup + 1 for \\\"\\n \\\"default inventory\\\"\\n )\\n self.assertEqual(\\n len(metadata.readableDescendants), 25,\\n \\\"There should be as many readable descendants as there is edition, translation(25 ed+tr)\\\"\\n )\\n self.assertEqual(\\n len([x for x in metadata.readableDescendants if isinstance(x, TextMetadata)]), 25,\\n \\\"There should be 24 editions + 1 translations in readableDescendants\\\"\\n )\\n self.assertEqual(\\n len(metadata.export(output=Mimetypes.PYTHON.ETREE).xpath(\\n \\\"//ti:edition[@urn='urn:cts:latinLit:phi1294.phi002.perseus-lat2']\\\", namespaces=NS)), 1,\\n \\\"There should be one node in exported format corresponding to lat2\\\"\\n )\\n self.assertCountEqual(\\n [x[\\\"@id\\\"] for x in metadata.export(output=Mimetypes.JSON.DTS.Std)[\\\"@graph\\\"][\\\"dts:members\\\"]],\\n [\\\"urn:cts:latinLit:phi1294\\\", \\\"urn:cts:latinLit:phi0959\\\",\\n \\\"urn:cts:greekLit:tlg0003\\\", \\\"urn:cts:latinLit:phi1276\\\"],\\n \\\"There should be 4 Members in DTS JSON\\\"\\n )\",\n \"def export_model(self, save_path: str, save_format: Optional[str] = None) -> None:\",\n \"def test_add_model_with_resource_fields_without_swagger_metadata(\\n mock_nested, mock_model_class,\\n):\\n pdst = patch_deduce_swagger_type\\n pr = patch_registry\\n ppd = patch_parse_doc\\n pha = patch_hasattr\\n\\n with pr(), ppd(), patch_isinstance(False) as mock_isinstance:\\n with pha() as mock_hasattr, patch_dir([\\\"resource_fields\\\"]) as mock_dir:\\n with pdst() as mock_deduce_swagger_type:\\n\\n swagger.add_model(mock_model_class)\\n mock_dir.assert_called_with(mock_model_class)\\n assert mock_dir.call_count == 2\\n mock_hasattr.assert_called_once_with(\\n mock_model_class, \\\"required\\\")\\n mock_isinstance.assert_called_with(\\n mock_model_class, mock_nested)\\n assert mock_deduce_swagger_type.call_count == len(\\n mock_model_class.resource_fields.items()\\n )\",\n \"def describe_model_package(ModelPackageName=None):\\n pass\",\n \"def get_interaction_model_metadata_v1(self, skill_id, stage_v2, locale, **kwargs):\\n # type: (str, str, str, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\\n operation_name = \\\"get_interaction_model_metadata_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'stage_v2' is set\\n if ('stage_v2' not in params) or (params['stage_v2'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `stage_v2` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'locale' is set\\n if ('locale' not in params) or (params['locale'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `locale` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/stages/{stageV2}/interactionModel/locales/{locale}'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n if 'stage_v2' in params:\\n path_params['stageV2'] = params['stage_v2']\\n if 'locale' in params:\\n path_params['locale'] = params['locale']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=204, message=\\\"Success. There is no content but returns etag.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The specified skill or stage or locale does not exist\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"HEAD\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=None)\\n\\n if full_response:\\n return api_response\\n \\n return None\",\n \"def get_dataset_meta(self, output_name, dataset_id):\\n return {}\",\n \"def write(self, model):\\n\\n # Initialize json_dump\\n json_dump = {\\\"model\\\": [], \\\"metadata\\\": {}}\\n\\n # Set timestamp in metadata\\n json_dump[\\\"metadata\\\"][\\\"time\\\"] = str(datetime.now())\\n\\n # Set the size of the model in metadata\\n json_dump[\\\"metadata\\\"][\\\"model_size\\\"] = len(model.models)\\n\\n for obj in model.models:\\n _class = type(obj).__name__\\n if _class in [\\n Winding,\\n PhaseWinding,\\n Wire,\\n PhaseCapacitor,\\n Position,\\n PhaseLoad,\\n ]:\\n continue\\n json_dump[\\\"model\\\"].append({})\\n json_dump[\\\"model\\\"][-1][\\\"class\\\"] = _class\\n\\n try:\\n json_dump[\\\"model\\\"][-1][\\\"name\\\"] = {\\\"class\\\": \\\"str\\\", \\\"value\\\": obj.name}\\n except:\\n json_dump[\\\"model\\\"][-1][\\\"name\\\"] = {\\\"class\\\": \\\"str\\\", \\\"value\\\": None}\\n pass\\n\\n for key, value in obj._trait_values.items():\\n if key in [\\\"capacitance_matrix\\\", \\\"impedance_matrix\\\", \\\"reactances\\\"]:\\n json_dump[\\\"model\\\"][-1][key] = {\\\"class\\\": \\\"list\\\", \\\"value\\\": []}\\n for v in value:\\n if isinstance(v, complex):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"complex\\\", \\\"value\\\": [v.real, v.imag]}\\n )\\n elif isinstance(v, list):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"list\\\", \\\"value\\\": []}\\n )\\n for vv in v:\\n if isinstance(vv, complex):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][\\n \\\"value\\\"\\n ].append(\\n {\\n \\\"class\\\": \\\"complex\\\",\\n \\\"value\\\": [vv.real, vv.imag],\\n }\\n )\\n else:\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][\\n \\\"value\\\"\\n ].append(\\n {\\n \\\"class\\\": str(type(vv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vv,\\n }\\n )\\n else:\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": str(type(v)).split(\\\"'\\\")[1], \\\"value\\\": v}\\n )\\n continue\\n if isinstance(value, list):\\n json_dump[\\\"model\\\"][-1][key] = {\\\"class\\\": \\\"list\\\", \\\"value\\\": []}\\n for v in value:\\n\\n if isinstance(v, complex):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"complex\\\", \\\"value\\\": [v.real, v.imag]}\\n )\\n\\n elif isinstance(v, Position):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"Position\\\"}\\n )\\n for kkk, vvv in v._trait_values.items():\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][kkk] = {\\n \\\"class\\\": str(type(vvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvv,\\n }\\n\\n elif isinstance(v, Unicode):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"Unicode\\\", \\\"value\\\": v.default_value}\\n )\\n\\n elif isinstance(v, Wire):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"Wire\\\"}\\n )\\n for kkk, vvv in v._trait_values.items():\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][kkk] = {\\n \\\"class\\\": str(type(vvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvv,\\n }\\n\\n elif isinstance(v, PhaseCapacitor):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"PhaseCapacitor\\\"}\\n )\\n for kkk, vvv in v._trait_values.items():\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][kkk] = {\\n \\\"class\\\": str(type(vvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvv,\\n }\\n\\n elif isinstance(v, Winding):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"Winding\\\"}\\n )\\n for kkk, vvv in v._trait_values.items():\\n if kkk != \\\"phase_windings\\\":\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][kkk] = {\\n \\\"class\\\": str(type(vvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvv,\\n }\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][\\n \\\"phase_windings\\\"\\n ] = {\\\"class\\\": \\\"list\\\", \\\"value\\\": []}\\n for phw in v.phase_windings:\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][\\n \\\"phase_windings\\\"\\n ][\\\"value\\\"].append({\\\"class\\\": \\\"PhaseWinding\\\"})\\n for kkkk, vvvv in phw._trait_values.items():\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][\\n \\\"phase_windings\\\"\\n ][\\\"value\\\"][-1][kkkk] = {\\n \\\"class\\\": str(type(vvvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvvv,\\n }\\n\\n elif isinstance(v, PhaseLoad):\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"].append(\\n {\\\"class\\\": \\\"PhaseLoad\\\"}\\n )\\n for kkk, vvv in v._trait_values.items():\\n json_dump[\\\"model\\\"][-1][key][\\\"value\\\"][-1][kkk] = {\\n \\\"class\\\": str(type(vvv)).split(\\\"'\\\")[1],\\n \\\"value\\\": vvv,\\n }\\n\\n continue\\n\\n if isinstance(value, complex):\\n json_dump[\\\"model\\\"][-1][key] = {\\n \\\"class\\\": \\\"complex\\\",\\n \\\"value\\\": [value.real, value.imag],\\n }\\n continue\\n\\n json_dump[\\\"model\\\"][-1][key] = {\\n \\\"class\\\": str(type(value)).split(\\\"'\\\")[1],\\n \\\"value\\\": value,\\n }\\n\\n with open(os.path.join(self.output_path, self.filename), \\\"w\\\") as f:\\n f.write(\\n json_tricks.dumps(json_dump, allow_nan=True, sort_keys=True, indent=4)\\n )\",\n \"def to_dict(self):\\n result = {}\\n\\n for attr, _ in six.iteritems(self.swagger_types):\\n value = getattr(self, attr)\\n if isinstance(value, list):\\n result[attr] = list(map(\\n lambda x: x.to_dict() if hasattr(x, \\\"to_dict\\\") else x,\\n value\\n ))\\n elif hasattr(value, \\\"to_dict\\\"):\\n result[attr] = value.to_dict()\\n elif isinstance(value, dict):\\n result[attr] = dict(map(\\n lambda item: (item[0], item[1].to_dict())\\n if hasattr(item[1], \\\"to_dict\\\") else item,\\n value.items()\\n ))\\n else:\\n result[attr] = value\\n if issubclass(Metadata, dict):\\n for key, value in self.items():\\n result[key] = value\\n\\n return result\",\n \"def __init__(self):\\n self.swagger_types = {\\n 'id': 'str',\\n 'name': 'str',\\n 'date_created': 'datetime',\\n 'date_modified': 'datetime',\\n 'version': 'int',\\n 'division': 'DomainEntityRef',\\n 'campaign_status': 'str',\\n 'callable_time_set': 'DomainEntityRef',\\n 'contact_list': 'DomainEntityRef',\\n 'dnc_lists': 'list[DomainEntityRef]',\\n 'always_running': 'bool',\\n 'contact_sorts': 'list[ContactSort]',\\n 'messages_per_minute': 'int',\\n 'errors': 'list[RestErrorDetail]',\\n 'sms_config': 'SmsConfig',\\n 'self_uri': 'str'\\n }\\n\\n self.attribute_map = {\\n 'id': 'id',\\n 'name': 'name',\\n 'date_created': 'dateCreated',\\n 'date_modified': 'dateModified',\\n 'version': 'version',\\n 'division': 'division',\\n 'campaign_status': 'campaignStatus',\\n 'callable_time_set': 'callableTimeSet',\\n 'contact_list': 'contactList',\\n 'dnc_lists': 'dncLists',\\n 'always_running': 'alwaysRunning',\\n 'contact_sorts': 'contactSorts',\\n 'messages_per_minute': 'messagesPerMinute',\\n 'errors': 'errors',\\n 'sms_config': 'smsConfig',\\n 'self_uri': 'selfUri'\\n }\\n\\n self._id = None\\n self._name = None\\n self._date_created = None\\n self._date_modified = None\\n self._version = None\\n self._division = None\\n self._campaign_status = None\\n self._callable_time_set = None\\n self._contact_list = None\\n self._dnc_lists = None\\n self._always_running = None\\n self._contact_sorts = None\\n self._messages_per_minute = None\\n self._errors = None\\n self._sms_config = None\\n self._self_uri = None\",\n \"def schema(self):\\n # NOTE This is exactly the same as the other thing.\\n return {\\n \\\"$id\\\": f\\\"{self.request.resource_url(self)}#schema\\\",\\n \\\"type\\\": \\\"object\\\",\\n \\\"properties\\\": {\\n \\\"foo\\\": {\\\"type\\\": \\\"string\\\"},\\n # generated fields shouldn't be submitted or in forms\\n \\\"url\\\": {\\\"type\\\": \\\"string\\\", \\\"generated\\\": True},\\n }\\n }\",\n \"def metadata(self, metadata):\\n return Metadata(metadata)\",\n \"def test_metadata(self):\\n self.assertEquals(self.testObject.metadata, {})\",\n \"def test_custom_action_response_descriptor_octopus_server_web_api_actions_defect_resolved_responder(self):\\n pass\",\n \"def metadata(self) -> dict:\\n meta = {}\\n meta['filename'] = self.filename\\n meta['label'] = self.label\\n meta['url'] = self.url\\n\\n return meta\",\n \"def test_swagger(self):\\n response = self.client.get(\\\"/api/v1/swagger\\\", query_string=dict(validate_schema=True))\\n assert_that(response.status_code, is_(equal_to(200)))\\n swagger = loads(response.get_data().decode(\\\"utf-8\\\"))\\n # we have the swagger docs endpoint too, which is implemented as a query.\\n # ignore it here for now.\\n del swagger[\\\"paths\\\"][\\\"/swagger/docs\\\"]\\n assert_that(swagger[\\\"paths\\\"], is_(equal_to({\\n \\\"/foo/get\\\": {\\n \\\"get\\\": {\\n \\\"description\\\": \\\"My doc string\\\",\\n \\\"tags\\\": [\\\"foo\\\"],\\n \\\"responses\\\": {\\n \\\"default\\\": {\\n \\\"description\\\": \\\"An error occurred\\\", \\\"schema\\\": {\\n \\\"$ref\\\": \\\"#/definitions/Error\\\",\\n }\\n },\\n \\\"200\\\": {\\n \\\"description\\\": \\\"My doc string\\\",\\n \\\"schema\\\": {\\n \\\"$ref\\\": \\\"#/definitions/QueryResult\\\",\\n }\\n }\\n },\\n \\\"parameters\\\": [\\n {\\n \\\"in\\\": \\\"header\\\",\\n \\\"name\\\": \\\"X-Response-Skip-Null\\\",\\n \\\"required\\\": False,\\n \\\"type\\\": \\\"string\\\",\\n \\\"description\\\": \\\"Remove fields with null values from the response.\\\"\\n },\\n {\\n \\\"required\\\": False,\\n \\\"type\\\": \\\"string\\\",\\n \\\"name\\\": \\\"optional_value\\\",\\n \\\"in\\\": \\\"query\\\",\\n },\\n {\\n \\\"required\\\": True,\\n \\\"type\\\": \\\"string\\\",\\n \\\"name\\\": \\\"required_value\\\",\\n \\\"in\\\": \\\"query\\\",\\n },\\n ],\\n \\\"operationId\\\": \\\"query\\\",\\n }\\n }\\n })))\",\n \"def __init__(self):\\n self.swagger_types = {\\n 'id_conta': 'int',\\n 'id_pessoa': 'int',\\n 'id_cartao': 'int',\\n 'id_bandeira': 'int',\\n 'id_tipo_cartao': 'int',\\n 'numero_cartao': 'str',\\n 'nome_plastico': 'str',\\n 'cvv2': 'str',\\n 'data_geracao': 'str',\\n 'data_validade': 'str',\\n 'cpf': 'str',\\n 'tipo_portador': 'str',\\n 'trilha1': 'str',\\n 'trilha2': 'str',\\n 'trilha_cvv1': 'str',\\n 'trilha_cvv2': 'str',\\n 'flag_virtual': 'int',\\n 'nome_bandeira': 'str',\\n 'flag_titular': 'int',\\n 'sequencial_cartao': 'int',\\n 'id_status': 'int',\\n 'descricao_status_cartao': 'str',\\n 'data_status': 'str',\\n 'id_estagio': 'int',\\n 'descricao_estagio': 'str',\\n 'data_estagio': 'str',\\n 'numero_bin': 'str',\\n 'id_produto': 'int',\\n 'descricao_produto': 'str',\\n 'id_status_conta': 'int',\\n 'descricao_status_conta': 'int',\\n 'data_embossing': 'str',\\n 'codigo_desbloqueio': 'str',\\n 'nome_pessoa': 'str',\\n 'tipo_pessoa': 'str',\\n 'data_nascimento': 'str',\\n 'id_endereco': 'int',\\n 'id_tipo_endereco': 'int',\\n 'descricao_tipo_endereco': 'str',\\n 'cep': 'str',\\n 'logradouro': 'str',\\n 'numero_endereco': 'str',\\n 'complemento_endereco': 'str',\\n 'bairro': 'str',\\n 'cidade': 'str',\\n 'uf': 'str',\\n 'pais': 'str',\\n 'senha_criptografada': 'str',\\n 'icvv': 'str',\\n 'id_status_impressao': 'int'\\n }\\n\\n self.attribute_map = {\\n 'id_conta': 'idConta',\\n 'id_pessoa': 'idPessoa',\\n 'id_cartao': 'idCartao',\\n 'id_bandeira': 'idBandeira',\\n 'id_tipo_cartao': 'idTipoCartao',\\n 'numero_cartao': 'numeroCartao',\\n 'nome_plastico': 'nomePlastico',\\n 'cvv2': 'cvv2',\\n 'data_geracao': 'dataGeracao',\\n 'data_validade': 'dataValidade',\\n 'cpf': 'cpf',\\n 'tipo_portador': 'tipoPortador',\\n 'trilha1': 'trilha1',\\n 'trilha2': 'trilha2',\\n 'trilha_cvv1': 'trilhaCVV1',\\n 'trilha_cvv2': 'trilhaCVV2',\\n 'flag_virtual': 'flagVirtual',\\n 'nome_bandeira': 'nomeBandeira',\\n 'flag_titular': 'flagTitular',\\n 'sequencial_cartao': 'sequencialCartao',\\n 'id_status': 'idStatus',\\n 'descricao_status_cartao': 'descricaoStatusCartao',\\n 'data_status': 'dataStatus',\\n 'id_estagio': 'idEstagio',\\n 'descricao_estagio': 'descricaoEstagio',\\n 'data_estagio': 'dataEstagio',\\n 'numero_bin': 'numeroBin',\\n 'id_produto': 'idProduto',\\n 'descricao_produto': 'descricaoProduto',\\n 'id_status_conta': 'idStatusConta',\\n 'descricao_status_conta': 'descricaoStatusConta',\\n 'data_embossing': 'dataEmbossing',\\n 'codigo_desbloqueio': 'codigoDesbloqueio',\\n 'nome_pessoa': 'nomePessoa',\\n 'tipo_pessoa': 'tipoPessoa',\\n 'data_nascimento': 'dataNascimento',\\n 'id_endereco': 'idEndereco',\\n 'id_tipo_endereco': 'idTipoEndereco',\\n 'descricao_tipo_endereco': 'descricaoTipoEndereco',\\n 'cep': 'cep',\\n 'logradouro': 'logradouro',\\n 'numero_endereco': 'numeroEndereco',\\n 'complemento_endereco': 'complementoEndereco',\\n 'bairro': 'bairro',\\n 'cidade': 'cidade',\\n 'uf': 'uf',\\n 'pais': 'pais',\\n 'senha_criptografada': 'senhaCriptografada',\\n 'icvv': 'icvv',\\n 'id_status_impressao': 'idStatusImpressao'\\n }\\n\\n self._id_conta = None\\n self._id_pessoa = None\\n self._id_cartao = None\\n self._id_bandeira = None\\n self._id_tipo_cartao = None\\n self._numero_cartao = None\\n self._nome_plastico = None\\n self._cvv2 = None\\n self._data_geracao = None\\n self._data_validade = None\\n self._cpf = None\\n self._tipo_portador = None\\n self._trilha1 = None\\n self._trilha2 = None\\n self._trilha_cvv1 = None\\n self._trilha_cvv2 = None\\n self._flag_virtual = None\\n self._nome_bandeira = None\\n self._flag_titular = None\\n self._sequencial_cartao = None\\n self._id_status = None\\n self._descricao_status_cartao = None\\n self._data_status = None\\n self._id_estagio = None\\n self._descricao_estagio = None\\n self._data_estagio = None\\n self._numero_bin = None\\n self._id_produto = None\\n self._descricao_produto = None\\n self._id_status_conta = None\\n self._descricao_status_conta = None\\n self._data_embossing = None\\n self._codigo_desbloqueio = None\\n self._nome_pessoa = None\\n self._tipo_pessoa = None\\n self._data_nascimento = None\\n self._id_endereco = None\\n self._id_tipo_endereco = None\\n self._descricao_tipo_endereco = None\\n self._cep = None\\n self._logradouro = None\\n self._numero_endereco = None\\n self._complemento_endereco = None\\n self._bairro = None\\n self._cidade = None\\n self._uf = None\\n self._pais = None\\n self._senha_criptografada = None\\n self._icvv = None\\n self._id_status_impressao = None\",\n \"def test_custom_query_response_descriptor_octopus_server_web_api_actions_list_defects_responder(self):\\n pass\",\n \"def _openapi_json(self):\\n # We don't use Flask.jsonify here as it would sort the keys\\n # alphabetically while we want to preserve the order.\\n from pprint import pprint\\n pprint(self.to_dict())\\n return current_app.response_class(json.dumps(self.to_dict(), indent=4),\\n mimetype='application/json')\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6050486","0.5972756","0.5801244","0.56295675","0.5604811","0.55415565","0.5516606","0.5497246","0.54778665","0.54568404","0.5436918","0.54210794","0.5404738","0.53839225","0.5312669","0.5309557","0.53045684","0.52979773","0.5291329","0.52629024","0.52454233","0.5238041","0.52148414","0.5193557","0.51896244","0.51754016","0.5169209","0.51442826","0.51404667","0.51335824","0.51329625","0.5129981","0.5120812","0.51124305","0.5097594","0.50929904","0.50902593","0.5081417","0.5071504","0.50632656","0.5061013","0.50591457","0.5052292","0.50482917","0.5039246","0.50383013","0.5037371","0.5022237","0.5021128","0.5008881","0.5005599","0.50041443","0.5002942","0.49982032","0.49935657","0.49861267","0.49853057","0.49820843","0.49813256","0.4975217","0.49730808","0.496876","0.49686524","0.4967735","0.4956471","0.49492994","0.49486455","0.49420837","0.49419534","0.49419534","0.49383017","0.49364862","0.49334857","0.493339","0.4931849","0.49213785","0.49167174","0.49105874","0.48923162","0.48880506","0.48869303","0.4873197","0.48726633","0.4866917","0.48646548","0.48623872","0.48522824","0.484992","0.48366943","0.48351285","0.48309022","0.4826484","0.48227632","0.48197922","0.48172647","0.48164797","0.48152378","0.48115084","0.48112985","0.4811245","0.48109633"],"string":"[\n \"0.6050486\",\n \"0.5972756\",\n \"0.5801244\",\n \"0.56295675\",\n \"0.5604811\",\n \"0.55415565\",\n \"0.5516606\",\n \"0.5497246\",\n \"0.54778665\",\n \"0.54568404\",\n \"0.5436918\",\n \"0.54210794\",\n \"0.5404738\",\n \"0.53839225\",\n \"0.5312669\",\n \"0.5309557\",\n \"0.53045684\",\n \"0.52979773\",\n \"0.5291329\",\n \"0.52629024\",\n \"0.52454233\",\n \"0.5238041\",\n \"0.52148414\",\n \"0.5193557\",\n \"0.51896244\",\n \"0.51754016\",\n \"0.5169209\",\n \"0.51442826\",\n \"0.51404667\",\n \"0.51335824\",\n \"0.51329625\",\n \"0.5129981\",\n \"0.5120812\",\n \"0.51124305\",\n \"0.5097594\",\n \"0.50929904\",\n \"0.50902593\",\n \"0.5081417\",\n \"0.5071504\",\n \"0.50632656\",\n \"0.5061013\",\n \"0.50591457\",\n \"0.5052292\",\n \"0.50482917\",\n \"0.5039246\",\n \"0.50383013\",\n \"0.5037371\",\n \"0.5022237\",\n \"0.5021128\",\n \"0.5008881\",\n \"0.5005599\",\n \"0.50041443\",\n \"0.5002942\",\n \"0.49982032\",\n \"0.49935657\",\n \"0.49861267\",\n \"0.49853057\",\n \"0.49820843\",\n \"0.49813256\",\n \"0.4975217\",\n \"0.49730808\",\n \"0.496876\",\n \"0.49686524\",\n \"0.4967735\",\n \"0.4956471\",\n \"0.49492994\",\n \"0.49486455\",\n \"0.49420837\",\n \"0.49419534\",\n \"0.49419534\",\n \"0.49383017\",\n \"0.49364862\",\n \"0.49334857\",\n \"0.493339\",\n \"0.4931849\",\n \"0.49213785\",\n \"0.49167174\",\n \"0.49105874\",\n \"0.48923162\",\n \"0.48880506\",\n \"0.48869303\",\n \"0.4873197\",\n \"0.48726633\",\n \"0.4866917\",\n \"0.48646548\",\n \"0.48623872\",\n \"0.48522824\",\n \"0.484992\",\n \"0.48366943\",\n \"0.48351285\",\n \"0.48309022\",\n \"0.4826484\",\n \"0.48227632\",\n \"0.48197922\",\n \"0.48172647\",\n \"0.48164797\",\n \"0.48152378\",\n \"0.48115084\",\n \"0.48112985\",\n \"0.4811245\",\n \"0.48109633\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":10692,"cells":{"query":{"kind":"string","value":"Sets the export_host of this ExportResponseMetadata."},"document":{"kind":"string","value":"def export_host(self, export_host):\n\n self._export_host = export_host"},"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 response_host(self, response_host):\n\n self._response_host = response_host","def response_host(self, response_host):\n\n self._response_host = response_host","def host(self, host):\n\n self._host = host","def host(self, host):\n\n self._host = host","def host(self, host):\n\n self._host = host","def host(self, host):\n\n self._host = host","def host(self, host: str):\n\n self._host = host","def host(self, host):\n if host is None:\n raise ValueError(\"Invalid value for `host`, must not be `None`\")\n\n self._host = host","def host(self, host: str):\n if host is None:\n raise ValueError(\"Invalid value for `host`, must not be `None`\") # noqa: E501\n\n self._host = host","def set_host(self, host: str) -> None:\n _LOGGER.debug(\"Setting host to %s\", host)\n host_url = urlparse(host)\n self.scheme = host_url.scheme or \"http\"\n self.host = host_url.netloc or host_url.path\n self.base_url = f\"{self.scheme}://{self.host}\"\n self.api_url = f\"{self.base_url}/apps/api/{self.app_id}\"","def set_creation_host(self, host: str) -> None:\n self.metadata.data[\"creation_host\"] = host","def host(self, host) :\n\t\ttry :\n\t\t\tself._host = host\n\t\texcept Exception as e:\n\t\t\traise e","def sethost(self, host):\n self.__host = host","def Host(self, h):\r\n\r\n self.host = h\r\n return self","def set_service_host(self, host):\n self._api_host = f\"https://{host}\"","def host_name(self, host_name):\n\n self._host_name = host_name","def host_name(self, host_name):\n\n self._host_name = host_name","def hostname(self, hostname):\n\n self._hostname = hostname","def hostname(self, hostname):\n\n self._hostname = hostname","def registry_host(self, registry_host: str):\n\n self._registry_host = registry_host","def host_num(self, host_num):\n\n self._host_num = host_num","def hostname(self, hostname):\n self._hostname = hostname\n return self","def export_date(self, export_date):\n\n self._export_date = export_date","def admin_host(self, admin_host):\n\n self._admin_host = admin_host","def set_hostname(self, hostname):\n raise NotImplementedError()","def setServerHost(self, serverHost):\n\n _ExceptionUtil.raiseOnError(\n internals.blpapi_SessionOptions_setServerHost(self.__handle,\n serverHost))","def host_version(self, host_version):\n if host_version is None:\n raise ValueError(\"Invalid value for `host_version`, must not be `None`\") # noqa: E501\n\n self._host_version = host_version","def dst_hostname(self, dst_hostname):\n\n self._dst_hostname = dst_hostname","def host_ip(self, host_ip):\n\n self._host_ip = host_ip","def proxy_host(self, proxy_host):\n\n self._proxy_host = proxy_host","def set_address(self, host, port):\n self.host = host\n self.port = port","def set_scribe_host(host):\r\n LogOptions._SCRIBE_HOST = host","def hosts(self, value):\n if not isinstance(value, NodeSet):\n raise TypeError(\"Invalid fio host NodeSet: {} ({})\".format(value, type(value)))\n self._hosts = value.copy()","def set_host_addr(self, addr: str) -> None:\n self.config[\"host_addr\"] = addr","def org_apache_felix_http_host(self, org_apache_felix_http_host: ConfigNodePropertyString):\n\n self._org_apache_felix_http_host = org_apache_felix_http_host","def host_option(self, host_option):\n allowed_values = [\"admin_only\", \"player\", \"non_player\"]\n if host_option not in allowed_values:\n raise ValueError(\n \"Invalid value for `host_option` ({0}), must be one of {1}\"\n .format(host_option, allowed_values)\n )\n\n self._host_option = host_option","def fill_host(self, data):\n check_input_params(data, self.HOST)\n self.host = data[self.HOST]","def fill_host(self, data):\n check_input_params(data, self.HOST)\n self.host = data[self.HOST]","def __init__(self, host='http://localhost:6373'):\n self._host = host","def test_host_header(self):\n hostname = b\"server_name_1\"\n\n def update_expected_server(expected):\n expected[3][\"attributes\"].update(\n {SpanAttributes.HTTP_SERVER_NAME: hostname.decode(\"utf8\")}\n )\n return expected\n\n self.scope[\"headers\"].append([b\"host\", hostname])\n app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)\n self.seed_app(app)\n self.send_default_request()\n outputs = self.get_all_output()\n self.validate_outputs(outputs, modifiers=[update_expected_server])","def proxy_host(self, proxy_host: ConfigNodePropertyString):\n\n self._proxy_host = proxy_host","def set(self, host, **kwargs):\n for p, c in self.configs_:\n if host in c.hosts_:\n c.set(host, **kwargs)\n return\n raise ValueError(\"Host %s: not found\" % host)","def test_host_header(self):\n hostname = b\"server_name_1\"\n\n def update_expected_server(expected):\n expected[3][\"attributes\"].update(\n {\"http.server_name\": hostname.decode(\"utf8\")}\n )\n return expected\n\n self.scope[\"headers\"].append([b\"host\", hostname])\n app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)\n self.seed_app(app)\n self.send_default_request()\n outputs = self.get_all_output()\n self.validate_outputs(outputs, modifiers=[update_expected_server])","def nfs_export(self, nfs_export):\n\n self._nfs_export = nfs_export","def host(self, host: str, fields: str = None) -> dict:\n endpoint = f\"/api/host/{host}\" if host else \"/api/host/\"\n ret = self._request(\n endpoint=endpoint,\n params={\"fields\": fields} if fields else {},\n )\n return ret","def headers_add_host(headers, address):\n\n headers.setdefault('Host', address)\n\n return headers","def set_one(self, host_name, ip_address):\n self.hosts[host_name] = ip_address","def download_url(self, download_url):\n\n self._download_url = download_url","def response_kafka_connection_url(self, response_kafka_connection_url: str):\n\n self._response_kafka_connection_url = response_kafka_connection_url","def SetExportParam(self, name, value):\n parent, subname = self.FindExport(name)\n subname = Handle._FixExportName(parent.obj, subname)\n if not hasattr(parent.obj, subname):\n raise KeyError(name)\n if not parent.obj.dirty:\n parent.obj.StartTransaction()\n parent.obj.dirty = True\n setattr(parent.obj, subname, value)\n return parent.obj","def host(self):\n\n return self._host","def __init__(self, host):\n self.host = host","def __init__(self, host):\n self.host = host","def host(self):\n return self._host","def host(self):\n return self._host","def host(self):\n return self._host","def host(self):\n return self._host","def host(self):\n return self._host","def host(self):\n return self._host","def host(self):\n return self._host","def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\n\n self._export_host = None\n self._export_date = None\n self._requested_object_list = None\n self._exported_object_list = None\n self.discriminator = None\n\n if export_host is not None:\n self.export_host = export_host\n if export_date is not None:\n self.export_date = export_date\n if requested_object_list is not None:\n self.requested_object_list = requested_object_list\n if exported_object_list is not None:\n self.exported_object_list = exported_object_list","def set_download_url(self, download_url):\n\n\t\tif download_url is not None and not isinstance(download_url, str):\n\t\t\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: download_url EXPECTED TYPE: str', None, None)\n\t\t\n\t\tself.__download_url = download_url\n\t\tself.__key_modified['download_url'] = 1","def src_hostname(self, src_hostname):\n\n self._src_hostname = src_hostname","def report(self, host, **kwargs):\n kwargs.update({'host': host})\n self.dbreport('host', kwargs)","def download_url(self, download_url):\n self._download_url = download_url","def hosts(self, hosts):\n self._hosts = hosts","def host_status_control(self, host_status_control):\n\n self._host_status_control = host_status_control","def host(self) -> str:\n return self._host","def host(self) -> str:\n return self._host","def expose_headers(self, expose_headers):\n\n self._expose_headers = expose_headers","def hostname(self, hostname):\n if hostname is not None and not re.search('^(?=.{1,255}$)[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?(?:\\\\.[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?)*\\\\.?$', hostname): # noqa: E501\n raise ValueError(\"Invalid value for `hostname`, must be a follow pattern or equal to `/^(?=.{1,255}$)[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?(?:\\\\.[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?)*\\\\.?$/`\") # noqa: E501\n\n self._hostname = hostname","def export_to(self, exporter=None):\n if not exporter:\n raise aspecd.exceptions.MissingExporterError(\"No exporter provided\")\n exporter.export_from(self)","def nfs_export_num(self, nfs_export_num):\n\n self._nfs_export_num = nfs_export_num","def set_downloader(self, downloader):\n self._downloader = downloader","def __init__(self, *, host_name: str, protocol: typing.Optional[\"RedirectProtocol\"]=None):\n self._values = {\n 'host_name': host_name,\n }\n if protocol is not None: self._values[\"protocol\"] = protocol","def host(self) -> str:\n return self._builder.host","def address( self, host=None, port=None ):\n if host is not None:\n parts = str( host ).split( ':', 1 )\n self.host = parts[0]\n if len(parts) > 1:\n self.port = int( parts[1] )\n\n if port is not None:\n self.port = int( port )\n\n if not self.host or self.port == self.default_port:\n return self.host\n\n return join( (self.host, str(self.port)), ':' )","def hostname_label(self, hostname_label):\n self._hostname_label = hostname_label","def set_host_ip(self, host, host_ip):\n host.setIP(str(host_ip.ip), prefixLen=self.NETPREFIX)","def __init__(self, hass, host):\n self._hass = hass\n self._host = host\n self.data = {ATTR_DOWNLOAD: None, ATTR_UPLOAD: None, ATTR_VERSION: None}","def host_alias4(self, host_alias4):\n\n self._host_alias4 = host_alias4","def host_alias1(self, host_alias1):\n\n self._host_alias1 = host_alias1","def save_on_host(\n self, host_outputs: Any, writer: SummaryWriter, step: int\n ) -> None:\n raise NotImplementedError","def hpkp(self, hpkp):\n\n self._hpkp = hpkp","def set_hostname(self, new_hostname):\n return self.mycam.devicemgmt.SetHostname(new_hostname)","def set_hostname(hostname=None, deploy=False):\n\n if not hostname:\n raise CommandExecutionError(\"Hostname option must not be none.\")\n\n ret = {}\n\n query = {\n \"type\": \"config\",\n \"action\": \"set\",\n \"xpath\": (\n \"/config/devices/entry[@name='localhost.localdomain']/deviceconfig/system\"\n ),\n \"element\": \"<hostname>{}</hostname>\".format(hostname),\n }\n\n ret.update(__proxy__[\"panos.call\"](query))\n\n if deploy is True:\n ret.update(commit())\n\n return ret","def update(self, host, values):\n body = dict(host=values)\n return self._update(\"/os-hosts/%s\" % host, body, response_key='host')","def proxy_ntlm_host(self, proxy_ntlm_host):\n\n self._proxy_ntlm_host = proxy_ntlm_host","async def _parse_hostname(self, output, cb_token) -> None:\n if not output:\n self.hostname = \"-\"\n return\n\n if output[0][\"status\"] == 0:\n data = output[1][\"data\"]\n try:\n jout = json.loads(data)\n self.hostname = jout[\"hostname\"]\n except:\n self.hostname = \"-\"","def set_host(host_index):\n env.hosts = [public_dns_names[int(host_index)]]\n env.password = [public_pwds[int(host_index)]]","def set(self, host, **kwargs):\n self.__check_host_args(host, kwargs)\n\n for key, values in kwargs.items():\n if type(values) not in [list, tuple]: # pylint: disable=unidiomatic-typecheck\n values = [values]\n\n lower_key = key.lower()\n update_idx = [idx for idx, x in enumerate(self.lines_)\n if x.host == host and x.key.lower() == lower_key]\n extra_remove = []\n for idx in update_idx:\n if values: # values available, update the line\n value = values.pop()\n self.lines_[idx].line = self._new_line(self.lines_[idx].key, value)\n self.lines_[idx].value = value\n else: # no more values available, remove the line\n extra_remove.append(idx)\n\n for idx in reversed(sorted(extra_remove)):\n del self.lines_[idx]\n\n if values:\n mapped_key = _remap_key(key)\n max_idx = max([idx for idx, line in enumerate(self.lines_) if line.host == host])\n for value in values:\n self.lines_.insert(max_idx + 1, ConfigLine(line=self._new_line(mapped_key, value),\n host=host, key=mapped_key,\n value=value))","def getHost(self):\n return self._host","def host_num_in(self, host_num_in):\n\n self._host_num_in = host_num_in","def hosts_none(self, hosts_none):\n\n self._hosts_none = hosts_none","def host_num_gt(self, host_num_gt):\n\n self._host_num_gt = host_num_gt","def esxi_host_count(self, esxi_host_count):\n\n self._esxi_host_count = esxi_host_count","def get_host(self):\n return '{}://{}{}'.format(self.protocol, self.host, self.port)","def setExportWhat(self, buttonNum):\n ExportDialog.exportWhat = buttonNum\n self.initializePage()","def set_target(self, host, port):\r\n pass","def __init__(self, link_dict, target_host, table_output=\"Links_Scraped\"):\n self.link_dict = link_dict\n self.hm = classHostManager.HostManager(target_host=target_host)\n self.headers = dict()\n self.proxies = dict()\n self.key = link_dict['key']\n self.link = link_dict['link']\n self.raw_html = b''\n self.html = ''\n self.delta = -1\n self.status = 0\n self.resp = None\n\n self.table_output = table_output\n\n self.insert_stmnt = \"\"\"\n insert or replace info {table}(\n key,\n headers,\n proxies,\n link,\n delta,\n size,\n status,\n insert_date\n ) values (\n ?--key,\n ?--headers,\n ?--proxies,\n ?--link,\n ?--delta,\n ?--size,\n ?--status,\n ?--insert_date)\n \"\"\".format(table=self.table_output)"],"string":"[\n \"def response_host(self, response_host):\\n\\n self._response_host = response_host\",\n \"def response_host(self, response_host):\\n\\n self._response_host = response_host\",\n \"def host(self, host):\\n\\n self._host = host\",\n \"def host(self, host):\\n\\n self._host = host\",\n \"def host(self, host):\\n\\n self._host = host\",\n \"def host(self, host):\\n\\n self._host = host\",\n \"def host(self, host: str):\\n\\n self._host = host\",\n \"def host(self, host):\\n if host is None:\\n raise ValueError(\\\"Invalid value for `host`, must not be `None`\\\")\\n\\n self._host = host\",\n \"def host(self, host: str):\\n if host is None:\\n raise ValueError(\\\"Invalid value for `host`, must not be `None`\\\") # noqa: E501\\n\\n self._host = host\",\n \"def set_host(self, host: str) -> None:\\n _LOGGER.debug(\\\"Setting host to %s\\\", host)\\n host_url = urlparse(host)\\n self.scheme = host_url.scheme or \\\"http\\\"\\n self.host = host_url.netloc or host_url.path\\n self.base_url = f\\\"{self.scheme}://{self.host}\\\"\\n self.api_url = f\\\"{self.base_url}/apps/api/{self.app_id}\\\"\",\n \"def set_creation_host(self, host: str) -> None:\\n self.metadata.data[\\\"creation_host\\\"] = host\",\n \"def host(self, host) :\\n\\t\\ttry :\\n\\t\\t\\tself._host = host\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def sethost(self, host):\\n self.__host = host\",\n \"def Host(self, h):\\r\\n\\r\\n self.host = h\\r\\n return self\",\n \"def set_service_host(self, host):\\n self._api_host = f\\\"https://{host}\\\"\",\n \"def host_name(self, host_name):\\n\\n self._host_name = host_name\",\n \"def host_name(self, host_name):\\n\\n self._host_name = host_name\",\n \"def hostname(self, hostname):\\n\\n self._hostname = hostname\",\n \"def hostname(self, hostname):\\n\\n self._hostname = hostname\",\n \"def registry_host(self, registry_host: str):\\n\\n self._registry_host = registry_host\",\n \"def host_num(self, host_num):\\n\\n self._host_num = host_num\",\n \"def hostname(self, hostname):\\n self._hostname = hostname\\n return self\",\n \"def export_date(self, export_date):\\n\\n self._export_date = export_date\",\n \"def admin_host(self, admin_host):\\n\\n self._admin_host = admin_host\",\n \"def set_hostname(self, hostname):\\n raise NotImplementedError()\",\n \"def setServerHost(self, serverHost):\\n\\n _ExceptionUtil.raiseOnError(\\n internals.blpapi_SessionOptions_setServerHost(self.__handle,\\n serverHost))\",\n \"def host_version(self, host_version):\\n if host_version is None:\\n raise ValueError(\\\"Invalid value for `host_version`, must not be `None`\\\") # noqa: E501\\n\\n self._host_version = host_version\",\n \"def dst_hostname(self, dst_hostname):\\n\\n self._dst_hostname = dst_hostname\",\n \"def host_ip(self, host_ip):\\n\\n self._host_ip = host_ip\",\n \"def proxy_host(self, proxy_host):\\n\\n self._proxy_host = proxy_host\",\n \"def set_address(self, host, port):\\n self.host = host\\n self.port = port\",\n \"def set_scribe_host(host):\\r\\n LogOptions._SCRIBE_HOST = host\",\n \"def hosts(self, value):\\n if not isinstance(value, NodeSet):\\n raise TypeError(\\\"Invalid fio host NodeSet: {} ({})\\\".format(value, type(value)))\\n self._hosts = value.copy()\",\n \"def set_host_addr(self, addr: str) -> None:\\n self.config[\\\"host_addr\\\"] = addr\",\n \"def org_apache_felix_http_host(self, org_apache_felix_http_host: ConfigNodePropertyString):\\n\\n self._org_apache_felix_http_host = org_apache_felix_http_host\",\n \"def host_option(self, host_option):\\n allowed_values = [\\\"admin_only\\\", \\\"player\\\", \\\"non_player\\\"]\\n if host_option not in allowed_values:\\n raise ValueError(\\n \\\"Invalid value for `host_option` ({0}), must be one of {1}\\\"\\n .format(host_option, allowed_values)\\n )\\n\\n self._host_option = host_option\",\n \"def fill_host(self, data):\\n check_input_params(data, self.HOST)\\n self.host = data[self.HOST]\",\n \"def fill_host(self, data):\\n check_input_params(data, self.HOST)\\n self.host = data[self.HOST]\",\n \"def __init__(self, host='http://localhost:6373'):\\n self._host = host\",\n \"def test_host_header(self):\\n hostname = b\\\"server_name_1\\\"\\n\\n def update_expected_server(expected):\\n expected[3][\\\"attributes\\\"].update(\\n {SpanAttributes.HTTP_SERVER_NAME: hostname.decode(\\\"utf8\\\")}\\n )\\n return expected\\n\\n self.scope[\\\"headers\\\"].append([b\\\"host\\\", hostname])\\n app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)\\n self.seed_app(app)\\n self.send_default_request()\\n outputs = self.get_all_output()\\n self.validate_outputs(outputs, modifiers=[update_expected_server])\",\n \"def proxy_host(self, proxy_host: ConfigNodePropertyString):\\n\\n self._proxy_host = proxy_host\",\n \"def set(self, host, **kwargs):\\n for p, c in self.configs_:\\n if host in c.hosts_:\\n c.set(host, **kwargs)\\n return\\n raise ValueError(\\\"Host %s: not found\\\" % host)\",\n \"def test_host_header(self):\\n hostname = b\\\"server_name_1\\\"\\n\\n def update_expected_server(expected):\\n expected[3][\\\"attributes\\\"].update(\\n {\\\"http.server_name\\\": hostname.decode(\\\"utf8\\\")}\\n )\\n return expected\\n\\n self.scope[\\\"headers\\\"].append([b\\\"host\\\", hostname])\\n app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)\\n self.seed_app(app)\\n self.send_default_request()\\n outputs = self.get_all_output()\\n self.validate_outputs(outputs, modifiers=[update_expected_server])\",\n \"def nfs_export(self, nfs_export):\\n\\n self._nfs_export = nfs_export\",\n \"def host(self, host: str, fields: str = None) -> dict:\\n endpoint = f\\\"/api/host/{host}\\\" if host else \\\"/api/host/\\\"\\n ret = self._request(\\n endpoint=endpoint,\\n params={\\\"fields\\\": fields} if fields else {},\\n )\\n return ret\",\n \"def headers_add_host(headers, address):\\n\\n headers.setdefault('Host', address)\\n\\n return headers\",\n \"def set_one(self, host_name, ip_address):\\n self.hosts[host_name] = ip_address\",\n \"def download_url(self, download_url):\\n\\n self._download_url = download_url\",\n \"def response_kafka_connection_url(self, response_kafka_connection_url: str):\\n\\n self._response_kafka_connection_url = response_kafka_connection_url\",\n \"def SetExportParam(self, name, value):\\n parent, subname = self.FindExport(name)\\n subname = Handle._FixExportName(parent.obj, subname)\\n if not hasattr(parent.obj, subname):\\n raise KeyError(name)\\n if not parent.obj.dirty:\\n parent.obj.StartTransaction()\\n parent.obj.dirty = True\\n setattr(parent.obj, subname, value)\\n return parent.obj\",\n \"def host(self):\\n\\n return self._host\",\n \"def __init__(self, host):\\n self.host = host\",\n \"def __init__(self, host):\\n self.host = host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def host(self):\\n return self._host\",\n \"def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\\n\\n self._export_host = None\\n self._export_date = None\\n self._requested_object_list = None\\n self._exported_object_list = None\\n self.discriminator = None\\n\\n if export_host is not None:\\n self.export_host = export_host\\n if export_date is not None:\\n self.export_date = export_date\\n if requested_object_list is not None:\\n self.requested_object_list = requested_object_list\\n if exported_object_list is not None:\\n self.exported_object_list = exported_object_list\",\n \"def set_download_url(self, download_url):\\n\\n\\t\\tif download_url is not None and not isinstance(download_url, str):\\n\\t\\t\\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: download_url EXPECTED TYPE: str', None, None)\\n\\t\\t\\n\\t\\tself.__download_url = download_url\\n\\t\\tself.__key_modified['download_url'] = 1\",\n \"def src_hostname(self, src_hostname):\\n\\n self._src_hostname = src_hostname\",\n \"def report(self, host, **kwargs):\\n kwargs.update({'host': host})\\n self.dbreport('host', kwargs)\",\n \"def download_url(self, download_url):\\n self._download_url = download_url\",\n \"def hosts(self, hosts):\\n self._hosts = hosts\",\n \"def host_status_control(self, host_status_control):\\n\\n self._host_status_control = host_status_control\",\n \"def host(self) -> str:\\n return self._host\",\n \"def host(self) -> str:\\n return self._host\",\n \"def expose_headers(self, expose_headers):\\n\\n self._expose_headers = expose_headers\",\n \"def hostname(self, hostname):\\n if hostname is not None and not re.search('^(?=.{1,255}$)[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?(?:\\\\\\\\.[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?)*\\\\\\\\.?$', hostname): # noqa: E501\\n raise ValueError(\\\"Invalid value for `hostname`, must be a follow pattern or equal to `/^(?=.{1,255}$)[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?(?:\\\\\\\\.[0-9A-Za-z](?:(?:[0-9A-Za-z]|-){0,61}[0-9A-Za-z])?)*\\\\\\\\.?$/`\\\") # noqa: E501\\n\\n self._hostname = hostname\",\n \"def export_to(self, exporter=None):\\n if not exporter:\\n raise aspecd.exceptions.MissingExporterError(\\\"No exporter provided\\\")\\n exporter.export_from(self)\",\n \"def nfs_export_num(self, nfs_export_num):\\n\\n self._nfs_export_num = nfs_export_num\",\n \"def set_downloader(self, downloader):\\n self._downloader = downloader\",\n \"def __init__(self, *, host_name: str, protocol: typing.Optional[\\\"RedirectProtocol\\\"]=None):\\n self._values = {\\n 'host_name': host_name,\\n }\\n if protocol is not None: self._values[\\\"protocol\\\"] = protocol\",\n \"def host(self) -> str:\\n return self._builder.host\",\n \"def address( self, host=None, port=None ):\\n if host is not None:\\n parts = str( host ).split( ':', 1 )\\n self.host = parts[0]\\n if len(parts) > 1:\\n self.port = int( parts[1] )\\n\\n if port is not None:\\n self.port = int( port )\\n\\n if not self.host or self.port == self.default_port:\\n return self.host\\n\\n return join( (self.host, str(self.port)), ':' )\",\n \"def hostname_label(self, hostname_label):\\n self._hostname_label = hostname_label\",\n \"def set_host_ip(self, host, host_ip):\\n host.setIP(str(host_ip.ip), prefixLen=self.NETPREFIX)\",\n \"def __init__(self, hass, host):\\n self._hass = hass\\n self._host = host\\n self.data = {ATTR_DOWNLOAD: None, ATTR_UPLOAD: None, ATTR_VERSION: None}\",\n \"def host_alias4(self, host_alias4):\\n\\n self._host_alias4 = host_alias4\",\n \"def host_alias1(self, host_alias1):\\n\\n self._host_alias1 = host_alias1\",\n \"def save_on_host(\\n self, host_outputs: Any, writer: SummaryWriter, step: int\\n ) -> None:\\n raise NotImplementedError\",\n \"def hpkp(self, hpkp):\\n\\n self._hpkp = hpkp\",\n \"def set_hostname(self, new_hostname):\\n return self.mycam.devicemgmt.SetHostname(new_hostname)\",\n \"def set_hostname(hostname=None, deploy=False):\\n\\n if not hostname:\\n raise CommandExecutionError(\\\"Hostname option must not be none.\\\")\\n\\n ret = {}\\n\\n query = {\\n \\\"type\\\": \\\"config\\\",\\n \\\"action\\\": \\\"set\\\",\\n \\\"xpath\\\": (\\n \\\"/config/devices/entry[@name='localhost.localdomain']/deviceconfig/system\\\"\\n ),\\n \\\"element\\\": \\\"<hostname>{}</hostname>\\\".format(hostname),\\n }\\n\\n ret.update(__proxy__[\\\"panos.call\\\"](query))\\n\\n if deploy is True:\\n ret.update(commit())\\n\\n return ret\",\n \"def update(self, host, values):\\n body = dict(host=values)\\n return self._update(\\\"/os-hosts/%s\\\" % host, body, response_key='host')\",\n \"def proxy_ntlm_host(self, proxy_ntlm_host):\\n\\n self._proxy_ntlm_host = proxy_ntlm_host\",\n \"async def _parse_hostname(self, output, cb_token) -> None:\\n if not output:\\n self.hostname = \\\"-\\\"\\n return\\n\\n if output[0][\\\"status\\\"] == 0:\\n data = output[1][\\\"data\\\"]\\n try:\\n jout = json.loads(data)\\n self.hostname = jout[\\\"hostname\\\"]\\n except:\\n self.hostname = \\\"-\\\"\",\n \"def set_host(host_index):\\n env.hosts = [public_dns_names[int(host_index)]]\\n env.password = [public_pwds[int(host_index)]]\",\n \"def set(self, host, **kwargs):\\n self.__check_host_args(host, kwargs)\\n\\n for key, values in kwargs.items():\\n if type(values) not in [list, tuple]: # pylint: disable=unidiomatic-typecheck\\n values = [values]\\n\\n lower_key = key.lower()\\n update_idx = [idx for idx, x in enumerate(self.lines_)\\n if x.host == host and x.key.lower() == lower_key]\\n extra_remove = []\\n for idx in update_idx:\\n if values: # values available, update the line\\n value = values.pop()\\n self.lines_[idx].line = self._new_line(self.lines_[idx].key, value)\\n self.lines_[idx].value = value\\n else: # no more values available, remove the line\\n extra_remove.append(idx)\\n\\n for idx in reversed(sorted(extra_remove)):\\n del self.lines_[idx]\\n\\n if values:\\n mapped_key = _remap_key(key)\\n max_idx = max([idx for idx, line in enumerate(self.lines_) if line.host == host])\\n for value in values:\\n self.lines_.insert(max_idx + 1, ConfigLine(line=self._new_line(mapped_key, value),\\n host=host, key=mapped_key,\\n value=value))\",\n \"def getHost(self):\\n return self._host\",\n \"def host_num_in(self, host_num_in):\\n\\n self._host_num_in = host_num_in\",\n \"def hosts_none(self, hosts_none):\\n\\n self._hosts_none = hosts_none\",\n \"def host_num_gt(self, host_num_gt):\\n\\n self._host_num_gt = host_num_gt\",\n \"def esxi_host_count(self, esxi_host_count):\\n\\n self._esxi_host_count = esxi_host_count\",\n \"def get_host(self):\\n return '{}://{}{}'.format(self.protocol, self.host, self.port)\",\n \"def setExportWhat(self, buttonNum):\\n ExportDialog.exportWhat = buttonNum\\n self.initializePage()\",\n \"def set_target(self, host, port):\\r\\n pass\",\n \"def __init__(self, link_dict, target_host, table_output=\\\"Links_Scraped\\\"):\\n self.link_dict = link_dict\\n self.hm = classHostManager.HostManager(target_host=target_host)\\n self.headers = dict()\\n self.proxies = dict()\\n self.key = link_dict['key']\\n self.link = link_dict['link']\\n self.raw_html = b''\\n self.html = ''\\n self.delta = -1\\n self.status = 0\\n self.resp = None\\n\\n self.table_output = table_output\\n\\n self.insert_stmnt = \\\"\\\"\\\"\\n insert or replace info {table}(\\n key,\\n headers,\\n proxies,\\n link,\\n delta,\\n size,\\n status,\\n insert_date\\n ) values (\\n ?--key,\\n ?--headers,\\n ?--proxies,\\n ?--link,\\n ?--delta,\\n ?--size,\\n ?--status,\\n ?--insert_date)\\n \\\"\\\"\\\".format(table=self.table_output)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7138213","0.7138213","0.644298","0.644298","0.644298","0.644298","0.6365714","0.6363546","0.6119689","0.5977553","0.5908788","0.58681583","0.5725987","0.5704862","0.5632454","0.5604846","0.5604846","0.5506752","0.5506752","0.5476766","0.54253507","0.5403806","0.53860843","0.53830934","0.5342106","0.52974904","0.5283787","0.5248919","0.5229912","0.5226388","0.51300967","0.51015407","0.5029246","0.501174","0.48519656","0.48349282","0.48264518","0.48264518","0.47456","0.4743067","0.47223282","0.4712471","0.46922573","0.46714038","0.46665856","0.4655497","0.46545076","0.46313936","0.46291417","0.4609974","0.46079496","0.45958278","0.45958278","0.45769125","0.45769125","0.45769125","0.45769125","0.45769125","0.45769125","0.45769125","0.45666423","0.45655826","0.45628735","0.45561507","0.45555362","0.45376337","0.45266342","0.4507638","0.4507638","0.4496712","0.44965","0.44959965","0.4484007","0.4473397","0.44416615","0.44345233","0.44330484","0.44313878","0.44229332","0.44146076","0.44017205","0.43896824","0.4379398","0.43661392","0.4365749","0.43643197","0.4361924","0.43440026","0.43429154","0.43383238","0.43338412","0.43335348","0.43252286","0.43237913","0.43165055","0.43157786","0.4295328","0.42823392","0.42809394","0.42799136"],"string":"[\n \"0.7138213\",\n \"0.7138213\",\n \"0.644298\",\n \"0.644298\",\n \"0.644298\",\n \"0.644298\",\n \"0.6365714\",\n \"0.6363546\",\n \"0.6119689\",\n \"0.5977553\",\n \"0.5908788\",\n \"0.58681583\",\n \"0.5725987\",\n \"0.5704862\",\n \"0.5632454\",\n \"0.5604846\",\n \"0.5604846\",\n \"0.5506752\",\n \"0.5506752\",\n \"0.5476766\",\n \"0.54253507\",\n \"0.5403806\",\n \"0.53860843\",\n \"0.53830934\",\n \"0.5342106\",\n \"0.52974904\",\n \"0.5283787\",\n \"0.5248919\",\n \"0.5229912\",\n \"0.5226388\",\n \"0.51300967\",\n \"0.51015407\",\n \"0.5029246\",\n \"0.501174\",\n \"0.48519656\",\n \"0.48349282\",\n \"0.48264518\",\n \"0.48264518\",\n \"0.47456\",\n \"0.4743067\",\n \"0.47223282\",\n \"0.4712471\",\n \"0.46922573\",\n \"0.46714038\",\n \"0.46665856\",\n \"0.4655497\",\n \"0.46545076\",\n \"0.46313936\",\n \"0.46291417\",\n \"0.4609974\",\n \"0.46079496\",\n \"0.45958278\",\n \"0.45958278\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45769125\",\n \"0.45666423\",\n \"0.45655826\",\n \"0.45628735\",\n \"0.45561507\",\n \"0.45555362\",\n \"0.45376337\",\n \"0.45266342\",\n \"0.4507638\",\n \"0.4507638\",\n \"0.4496712\",\n \"0.44965\",\n \"0.44959965\",\n \"0.4484007\",\n \"0.4473397\",\n \"0.44416615\",\n \"0.44345233\",\n \"0.44330484\",\n \"0.44313878\",\n \"0.44229332\",\n \"0.44146076\",\n \"0.44017205\",\n \"0.43896824\",\n \"0.4379398\",\n \"0.43661392\",\n \"0.4365749\",\n \"0.43643197\",\n \"0.4361924\",\n \"0.43440026\",\n \"0.43429154\",\n \"0.43383238\",\n \"0.43338412\",\n \"0.43335348\",\n \"0.43252286\",\n \"0.43237913\",\n \"0.43165055\",\n \"0.43157786\",\n \"0.4295328\",\n \"0.42823392\",\n \"0.42809394\",\n \"0.42799136\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8150576"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":10693,"cells":{"query":{"kind":"string","value":"Sets the export_date of this ExportResponseMetadata."},"document":{"kind":"string","value":"def export_date(self, export_date):\n\n self._export_date = export_date"},"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_date(self, date):\n self.data['date'] = date","def set_date(self, date):\n self.date = date\n return","def set_date(self, date):\n self.date = date","def date(self, date):\n\n self._date = date","def date(self, date):\n\n self._date = date","def date(self, date):\n\n self._date = date","def date(self, date):\n\n self._date = date","def date(self, date):\n\n self._date = date","def date(self, date):\n self._date = date","def set_extracte_date(self, extracte_date):\n if extracte_date is not None:\n self.extracte_date = extracte_date","def _set_last_exported_date(self, cr, uid, external_session, date, context=None):\n return True","def snapshot_date(self, snapshot_date):\n\n self._snapshot_date = snapshot_date","def date(self, date):\n if self.local_vars_configuration.client_side_validation and date is None: # noqa: E501\n raise ValueError(\"Invalid value for `date`, must not be `None`\") # noqa: E501\n\n self._date = date","def date(self, date):\n if date is None:\n raise ValueError(\n \"Invalid value for `date`, must not be `None`\"\n ) # noqa: E501\n\n self._date = date","def _date(self, _date):\n\n self.__date = _date","def _date(self, _date):\n\n self.__date = _date","def authorization_date(self, authorization_date):\n\n self._authorization_date = authorization_date","def set_datetime(self, date):\n self.date = date","def mod_date(self, mod_date):\n\n self._mod_date = mod_date","def _date(self, _date: datetime):\n if _date is None:\n raise ValueError(\"Invalid value for `_date`, must not be `None`\") # noqa: E501\n\n self.__date = _date","def announcement_date(self, announcement_date):\n\n self._announcement_date = announcement_date","def expiration_date(self, expiration_date):\n\n self._expiration_date = expiration_date","def set_date(self, date):\n self.date = self.date_to_local(date)\n # ephem deals only in UTC\n self.site.date = ephem.Date(self.date_to_utc(self.date))","def revision_date(self, revision_date):\n\n self._revision_date = revision_date","def set_access_date(self, access_date):\n\t\t\n\t\tif (access_date.__class__ != str or access_date ==\"\") and (access_date.__class__ != time.struct_time or len(access_date) != 9 ):\n\t\t\traise InvalidParameterError(\"access_date\", \"access_date is not in a proper format\")\n\t\ttry:\n\t\t\tif access_date.__class__ == str:\n\t\t\t\ttmp_ad = time.strptime(access_date, '%S %M %H %d %m %Y')\n\t\t\telif access_date.__class__ == time.struct_time:\n\t\t\t\ttmp_ad = access_date\n\t\t\tself.__access_date = datetime(tmp_ad[0], tmp_ad[1], tmp_ad[2], tmp_ad[3], tmp_ad[4], tmp_ad[5])\n\t\texcept:\n\t\t\traise InvalidDate, \"date is not valid access_date is not in a proper format\"","def license_date(self, license_date):\n\n self._license_date = license_date","def date(self, new_date):\n self._date.date = new_date","def completion_date(self, completion_date):\n\n self._completion_date = completion_date","def date(self, date):\n self.value = date.strftime(\"%Y-%m-%d\") if date else \"\"","def set_publishdate_extractor(self, extractor):\r\n if not extractor:\r\n raise ValueError(\"extractor must not be null!\")\r\n self.extract_publishdate = extractor","def date(self, value):\n self.date_value = value","def datefinished(self, datefinished):\n\n self._datefinished = datefinished","def update_date(self, update_date):\n\n self._update_date = update_date","def update_date(self, update_date):\n\n self._update_date = update_date","def date(self, date_):\n # type: (date) -> None\n\n if date_ is not None:\n if not isinstance(date_, date):\n raise TypeError(\"Invalid type for `date`, type has to be `date`\")\n\n self._date = date_","def set_harvest_date(self, date):\n if not date:\n return datetime.utcnow().strftime(\"%Y/%m/%d\")\n return datetime.strptime(date, \"%Y%m%d\").strftime(\"%Y/%m/%d\")","def dep_date(self, dep_date):\n\n self._dep_date = dep_date","def observation_date(self, observation_date):\n\n self._observation_date = observation_date","def set_document_date(self, date):\n self.set_value_into_input_field(self.document_date_text_field_locator, date)","def decommission_date(self, decommission_date):\n\n self._decommission_date = decommission_date","def set_modification_date(self, modification_date):\n\t\t\n\t\tif (modification_date.__class__ != str or modification_date ==\"\") and (modification_date.__class__ != time.struct_time or len(modification_date) != 9 ):\n\t\t\traise InvalidParameterError(\"modification_date\", \"modification_date is not in a proper format\")\n\t\ttry:\n\t\t\tif modification_date.__class__ == str:\n\t\t\t\ttmp_md = time.strptime(modification_date, '%S %M %H %d %m %Y')\n\t\t\telif modification_date.__class__ == time.struct_time:\n\t\t\t\ttmp_md = modification_date\n\t\t\tself.__modification_date = datetime(tmp_md[0], tmp_md[1], tmp_md[2], tmp_md[3], tmp_md[4], tmp_md[5])\t\n\t\texcept:\n\t\t\traise InvalidDate, \"date is not valid modification_date is not in a proper format\"","def set_end_date(self, date):\n pass","def export_host(self, export_host):\n\n self._export_host = export_host","def upload_date(self, upload_date):\n\n self._upload_date = upload_date","def date_finished(self, date_finished):\n self._date_finished = date_finished","def forecast_date(self, forecast_date):\n self._forecast_date = forecast_date.strftime(\"%a %b %d\")","def acquisition_date(self, acquisition_date):\n\n self._acquisition_date = acquisition_date","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def date_modified(self, date_modified):\n\n self._date_modified = date_modified","def payment_date(self, payment_date):\n\n self._payment_date = payment_date","def payment_date(self, payment_date):\n\n self._payment_date = payment_date","def date_modified(self, date_modified):\n \n self._date_modified = date_modified","def disable_date(self, disable_date):\n\n self._disable_date = disable_date","def citation_date(self, citation_date):\n\n self._citation_date = citation_date","def modified_date(self, modified_date):\n\n self._modified_date = modified_date","def modified_date(self, modified_date):\n\n self._modified_date = modified_date","def balance_date(self, balance_date):\n\n self._balance_date = balance_date","def election_date(self, election_date):\n\n self._election_date = election_date","def set_rdate(self, rdate):\n self.__rdate = rdate","def expire_date(self, expire_date):\n\n self._expire_date = expire_date","def set_checkout(self, date):\n if type(date) != dt.datetime:\n raise TypeError('date must be a datetime.datetime object')\n else:\n pass\n self._checkout_date = date","def updated_date(self, updated_date):\n self._updated_date = updated_date","def updated_date(self, updated_date):\n\n self._updated_date = updated_date","def updated_date(self, updated_date):\n\n self._updated_date = updated_date","def SetDateCreated(self, date):\n self.datecreated = str(date)","def update(self, date):\r\n self.date = date","def application_expiry_date(self, application_expiry_date):\n\n self._application_expiry_date = application_expiry_date","def setDateAsString(self, *args):\n return _libsbml.Date_setDateAsString(self, *args)","def set_account_created_date(self, account_created_date):\n self.account_created_date = account_created_date","def selected_date(self, selected_date):\n\n self._selected_date = selected_date","def receipt_date(self, receipt_date):\n\n self._receipt_date = receipt_date","def receipt_date(self, receipt_date):\n\n self._receipt_date = receipt_date","def hide_expiration_date(self, hide_expiration_date):\n\n self._hide_expiration_date = hide_expiration_date","def end_date(self, end_date):\n self._end_date = end_date","def setExportWhat(self, buttonNum):\n ExportDialog.exportWhat = buttonNum\n self.initializePage()","def dates(self, dates):\n\n self._dates = dates","def end_date(self, end_date):\n if end_date is None:\n end_date = datetime.utcnow()\n\n self._end_date = dt_utils.parse_date(end_date)","def set_date(self, date):\n\n newdate = datetime.datetime.strptime(date, \"%Y-%m-%dT%H:%M:%S\")\n self.__get_century(date)\n self.__bus.write_byte_data(self.__rtcaddress,\n self.SECONDS,\n self.__dec_bcd(newdate.second))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.MINUTES,\n self.__dec_bcd(newdate.minute))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.HOURS,\n self.__dec_bcd(newdate.hour))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.DAYOFWEEK,\n self.__dec_bcd(newdate.weekday()))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.DAY,\n self.__dec_bcd(newdate.day))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.MONTH,\n self.__dec_bcd(newdate.month))\n self.__bus.write_byte_data(self.__rtcaddress,\n self.YEAR,\n self.__dec_bcd(newdate.year -\n self.__century))\n return","def datecreated(self, datecreated):\n\n self._datecreated = datecreated","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def end_date(self, end_date):\n\n self._end_date = end_date","def founding_date(self, founding_date: datetime):\n\n self._founding_date = founding_date","def coverage_end_date(self, coverage_end_date):\n\n self._coverage_end_date = coverage_end_date","def coverage_end_date(self, coverage_end_date):\n\n self._coverage_end_date = coverage_end_date","def date_format(self, date_format):\n\n self._date_format = date_format","def model_end_date(self, model_end_date):\n\n self._model_end_date = model_end_date","def set_download_url(self, download_url):\n\n\t\tif download_url is not None and not isinstance(download_url, str):\n\t\t\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: download_url EXPECTED TYPE: str', None, None)\n\t\t\n\t\tself.__download_url = download_url\n\t\tself.__key_modified['download_url'] = 1","def add_annotation_date(self, doc, annotation_date):\n if len(doc.annotations) != 0:\n if not self.annotation_date_set:\n self.annotation_date_set = True\n date = utils.datetime_from_iso_format(annotation_date)\n if date is not None:\n doc.annotations[-1].annotation_date = date\n return True\n else:\n raise SPDXValueError('Annotation::AnnotationDate')\n else:\n raise CardinalityError('Annotation::AnnotationDate')\n else:\n raise OrderError('Annotation::AnnotationDate')","def monthly_day(self, monthly_day):\n\n self._monthly_day = monthly_day"],"string":"[\n \"def set_date(self, date):\\n self.data['date'] = date\",\n \"def set_date(self, date):\\n self.date = date\\n return\",\n \"def set_date(self, date):\\n self.date = date\",\n \"def date(self, date):\\n\\n self._date = date\",\n \"def date(self, date):\\n\\n self._date = date\",\n \"def date(self, date):\\n\\n self._date = date\",\n \"def date(self, date):\\n\\n self._date = date\",\n \"def date(self, date):\\n\\n self._date = date\",\n \"def date(self, date):\\n self._date = date\",\n \"def set_extracte_date(self, extracte_date):\\n if extracte_date is not None:\\n self.extracte_date = extracte_date\",\n \"def _set_last_exported_date(self, cr, uid, external_session, date, context=None):\\n return True\",\n \"def snapshot_date(self, snapshot_date):\\n\\n self._snapshot_date = snapshot_date\",\n \"def date(self, date):\\n if self.local_vars_configuration.client_side_validation and date is None: # noqa: E501\\n raise ValueError(\\\"Invalid value for `date`, must not be `None`\\\") # noqa: E501\\n\\n self._date = date\",\n \"def date(self, date):\\n if date is None:\\n raise ValueError(\\n \\\"Invalid value for `date`, must not be `None`\\\"\\n ) # noqa: E501\\n\\n self._date = date\",\n \"def _date(self, _date):\\n\\n self.__date = _date\",\n \"def _date(self, _date):\\n\\n self.__date = _date\",\n \"def authorization_date(self, authorization_date):\\n\\n self._authorization_date = authorization_date\",\n \"def set_datetime(self, date):\\n self.date = date\",\n \"def mod_date(self, mod_date):\\n\\n self._mod_date = mod_date\",\n \"def _date(self, _date: datetime):\\n if _date is None:\\n raise ValueError(\\\"Invalid value for `_date`, must not be `None`\\\") # noqa: E501\\n\\n self.__date = _date\",\n \"def announcement_date(self, announcement_date):\\n\\n self._announcement_date = announcement_date\",\n \"def expiration_date(self, expiration_date):\\n\\n self._expiration_date = expiration_date\",\n \"def set_date(self, date):\\n self.date = self.date_to_local(date)\\n # ephem deals only in UTC\\n self.site.date = ephem.Date(self.date_to_utc(self.date))\",\n \"def revision_date(self, revision_date):\\n\\n self._revision_date = revision_date\",\n \"def set_access_date(self, access_date):\\n\\t\\t\\n\\t\\tif (access_date.__class__ != str or access_date ==\\\"\\\") and (access_date.__class__ != time.struct_time or len(access_date) != 9 ):\\n\\t\\t\\traise InvalidParameterError(\\\"access_date\\\", \\\"access_date is not in a proper format\\\")\\n\\t\\ttry:\\n\\t\\t\\tif access_date.__class__ == str:\\n\\t\\t\\t\\ttmp_ad = time.strptime(access_date, '%S %M %H %d %m %Y')\\n\\t\\t\\telif access_date.__class__ == time.struct_time:\\n\\t\\t\\t\\ttmp_ad = access_date\\n\\t\\t\\tself.__access_date = datetime(tmp_ad[0], tmp_ad[1], tmp_ad[2], tmp_ad[3], tmp_ad[4], tmp_ad[5])\\n\\t\\texcept:\\n\\t\\t\\traise InvalidDate, \\\"date is not valid access_date is not in a proper format\\\"\",\n \"def license_date(self, license_date):\\n\\n self._license_date = license_date\",\n \"def date(self, new_date):\\n self._date.date = new_date\",\n \"def completion_date(self, completion_date):\\n\\n self._completion_date = completion_date\",\n \"def date(self, date):\\n self.value = date.strftime(\\\"%Y-%m-%d\\\") if date else \\\"\\\"\",\n \"def set_publishdate_extractor(self, extractor):\\r\\n if not extractor:\\r\\n raise ValueError(\\\"extractor must not be null!\\\")\\r\\n self.extract_publishdate = extractor\",\n \"def date(self, value):\\n self.date_value = value\",\n \"def datefinished(self, datefinished):\\n\\n self._datefinished = datefinished\",\n \"def update_date(self, update_date):\\n\\n self._update_date = update_date\",\n \"def update_date(self, update_date):\\n\\n self._update_date = update_date\",\n \"def date(self, date_):\\n # type: (date) -> None\\n\\n if date_ is not None:\\n if not isinstance(date_, date):\\n raise TypeError(\\\"Invalid type for `date`, type has to be `date`\\\")\\n\\n self._date = date_\",\n \"def set_harvest_date(self, date):\\n if not date:\\n return datetime.utcnow().strftime(\\\"%Y/%m/%d\\\")\\n return datetime.strptime(date, \\\"%Y%m%d\\\").strftime(\\\"%Y/%m/%d\\\")\",\n \"def dep_date(self, dep_date):\\n\\n self._dep_date = dep_date\",\n \"def observation_date(self, observation_date):\\n\\n self._observation_date = observation_date\",\n \"def set_document_date(self, date):\\n self.set_value_into_input_field(self.document_date_text_field_locator, date)\",\n \"def decommission_date(self, decommission_date):\\n\\n self._decommission_date = decommission_date\",\n \"def set_modification_date(self, modification_date):\\n\\t\\t\\n\\t\\tif (modification_date.__class__ != str or modification_date ==\\\"\\\") and (modification_date.__class__ != time.struct_time or len(modification_date) != 9 ):\\n\\t\\t\\traise InvalidParameterError(\\\"modification_date\\\", \\\"modification_date is not in a proper format\\\")\\n\\t\\ttry:\\n\\t\\t\\tif modification_date.__class__ == str:\\n\\t\\t\\t\\ttmp_md = time.strptime(modification_date, '%S %M %H %d %m %Y')\\n\\t\\t\\telif modification_date.__class__ == time.struct_time:\\n\\t\\t\\t\\ttmp_md = modification_date\\n\\t\\t\\tself.__modification_date = datetime(tmp_md[0], tmp_md[1], tmp_md[2], tmp_md[3], tmp_md[4], tmp_md[5])\\t\\n\\t\\texcept:\\n\\t\\t\\traise InvalidDate, \\\"date is not valid modification_date is not in a proper format\\\"\",\n \"def set_end_date(self, date):\\n pass\",\n \"def export_host(self, export_host):\\n\\n self._export_host = export_host\",\n \"def upload_date(self, upload_date):\\n\\n self._upload_date = upload_date\",\n \"def date_finished(self, date_finished):\\n self._date_finished = date_finished\",\n \"def forecast_date(self, forecast_date):\\n self._forecast_date = forecast_date.strftime(\\\"%a %b %d\\\")\",\n \"def acquisition_date(self, acquisition_date):\\n\\n self._acquisition_date = acquisition_date\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def date_modified(self, date_modified):\\n\\n self._date_modified = date_modified\",\n \"def payment_date(self, payment_date):\\n\\n self._payment_date = payment_date\",\n \"def payment_date(self, payment_date):\\n\\n self._payment_date = payment_date\",\n \"def date_modified(self, date_modified):\\n \\n self._date_modified = date_modified\",\n \"def disable_date(self, disable_date):\\n\\n self._disable_date = disable_date\",\n \"def citation_date(self, citation_date):\\n\\n self._citation_date = citation_date\",\n \"def modified_date(self, modified_date):\\n\\n self._modified_date = modified_date\",\n \"def modified_date(self, modified_date):\\n\\n self._modified_date = modified_date\",\n \"def balance_date(self, balance_date):\\n\\n self._balance_date = balance_date\",\n \"def election_date(self, election_date):\\n\\n self._election_date = election_date\",\n \"def set_rdate(self, rdate):\\n self.__rdate = rdate\",\n \"def expire_date(self, expire_date):\\n\\n self._expire_date = expire_date\",\n \"def set_checkout(self, date):\\n if type(date) != dt.datetime:\\n raise TypeError('date must be a datetime.datetime object')\\n else:\\n pass\\n self._checkout_date = date\",\n \"def updated_date(self, updated_date):\\n self._updated_date = updated_date\",\n \"def updated_date(self, updated_date):\\n\\n self._updated_date = updated_date\",\n \"def updated_date(self, updated_date):\\n\\n self._updated_date = updated_date\",\n \"def SetDateCreated(self, date):\\n self.datecreated = str(date)\",\n \"def update(self, date):\\r\\n self.date = date\",\n \"def application_expiry_date(self, application_expiry_date):\\n\\n self._application_expiry_date = application_expiry_date\",\n \"def setDateAsString(self, *args):\\n return _libsbml.Date_setDateAsString(self, *args)\",\n \"def set_account_created_date(self, account_created_date):\\n self.account_created_date = account_created_date\",\n \"def selected_date(self, selected_date):\\n\\n self._selected_date = selected_date\",\n \"def receipt_date(self, receipt_date):\\n\\n self._receipt_date = receipt_date\",\n \"def receipt_date(self, receipt_date):\\n\\n self._receipt_date = receipt_date\",\n \"def hide_expiration_date(self, hide_expiration_date):\\n\\n self._hide_expiration_date = hide_expiration_date\",\n \"def end_date(self, end_date):\\n self._end_date = end_date\",\n \"def setExportWhat(self, buttonNum):\\n ExportDialog.exportWhat = buttonNum\\n self.initializePage()\",\n \"def dates(self, dates):\\n\\n self._dates = dates\",\n \"def end_date(self, end_date):\\n if end_date is None:\\n end_date = datetime.utcnow()\\n\\n self._end_date = dt_utils.parse_date(end_date)\",\n \"def set_date(self, date):\\n\\n newdate = datetime.datetime.strptime(date, \\\"%Y-%m-%dT%H:%M:%S\\\")\\n self.__get_century(date)\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.SECONDS,\\n self.__dec_bcd(newdate.second))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.MINUTES,\\n self.__dec_bcd(newdate.minute))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.HOURS,\\n self.__dec_bcd(newdate.hour))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.DAYOFWEEK,\\n self.__dec_bcd(newdate.weekday()))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.DAY,\\n self.__dec_bcd(newdate.day))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.MONTH,\\n self.__dec_bcd(newdate.month))\\n self.__bus.write_byte_data(self.__rtcaddress,\\n self.YEAR,\\n self.__dec_bcd(newdate.year -\\n self.__century))\\n return\",\n \"def datecreated(self, datecreated):\\n\\n self._datecreated = datecreated\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def end_date(self, end_date):\\n\\n self._end_date = end_date\",\n \"def founding_date(self, founding_date: datetime):\\n\\n self._founding_date = founding_date\",\n \"def coverage_end_date(self, coverage_end_date):\\n\\n self._coverage_end_date = coverage_end_date\",\n \"def coverage_end_date(self, coverage_end_date):\\n\\n self._coverage_end_date = coverage_end_date\",\n \"def date_format(self, date_format):\\n\\n self._date_format = date_format\",\n \"def model_end_date(self, model_end_date):\\n\\n self._model_end_date = model_end_date\",\n \"def set_download_url(self, download_url):\\n\\n\\t\\tif download_url is not None and not isinstance(download_url, str):\\n\\t\\t\\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: download_url EXPECTED TYPE: str', None, None)\\n\\t\\t\\n\\t\\tself.__download_url = download_url\\n\\t\\tself.__key_modified['download_url'] = 1\",\n \"def add_annotation_date(self, doc, annotation_date):\\n if len(doc.annotations) != 0:\\n if not self.annotation_date_set:\\n self.annotation_date_set = True\\n date = utils.datetime_from_iso_format(annotation_date)\\n if date is not None:\\n doc.annotations[-1].annotation_date = date\\n return True\\n else:\\n raise SPDXValueError('Annotation::AnnotationDate')\\n else:\\n raise CardinalityError('Annotation::AnnotationDate')\\n else:\\n raise OrderError('Annotation::AnnotationDate')\",\n \"def monthly_day(self, monthly_day):\\n\\n self._monthly_day = monthly_day\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.64057446","0.63387674","0.63318104","0.62219906","0.62219906","0.62219906","0.62219906","0.62219906","0.6208642","0.6150361","0.6148115","0.597754","0.59448314","0.59330714","0.5932477","0.5932477","0.59302837","0.59251916","0.5893984","0.5889508","0.5869775","0.5869477","0.57849216","0.5764885","0.57600737","0.57261586","0.5693605","0.56526333","0.56038797","0.5603519","0.55755305","0.5542273","0.5532922","0.5532922","0.5506798","0.5484878","0.54709685","0.5465905","0.5462367","0.5454034","0.5452039","0.54283524","0.5418019","0.54131603","0.54034954","0.5399778","0.5396933","0.5352738","0.5352738","0.5352738","0.5352738","0.5352738","0.5352738","0.5352738","0.5344227","0.5344227","0.5328359","0.5315445","0.53071886","0.5303033","0.5303033","0.52926564","0.5285332","0.52689016","0.5253707","0.5245113","0.5213911","0.5213253","0.5213253","0.5177571","0.5119861","0.50994295","0.50806534","0.50608015","0.50422025","0.50333756","0.50333756","0.50306094","0.5013336","0.5012429","0.5010544","0.49840027","0.49822313","0.49715987","0.49666157","0.49666157","0.49666157","0.49666157","0.49666157","0.49666157","0.49666157","0.49666157","0.494018","0.49355277","0.49355277","0.49225703","0.49205634","0.49195287","0.4915363","0.49146557"],"string":"[\n \"0.64057446\",\n \"0.63387674\",\n \"0.63318104\",\n \"0.62219906\",\n \"0.62219906\",\n \"0.62219906\",\n \"0.62219906\",\n \"0.62219906\",\n \"0.6208642\",\n \"0.6150361\",\n \"0.6148115\",\n \"0.597754\",\n \"0.59448314\",\n \"0.59330714\",\n \"0.5932477\",\n \"0.5932477\",\n \"0.59302837\",\n \"0.59251916\",\n \"0.5893984\",\n \"0.5889508\",\n \"0.5869775\",\n \"0.5869477\",\n \"0.57849216\",\n \"0.5764885\",\n \"0.57600737\",\n \"0.57261586\",\n \"0.5693605\",\n \"0.56526333\",\n \"0.56038797\",\n \"0.5603519\",\n \"0.55755305\",\n \"0.5542273\",\n \"0.5532922\",\n \"0.5532922\",\n \"0.5506798\",\n \"0.5484878\",\n \"0.54709685\",\n \"0.5465905\",\n \"0.5462367\",\n \"0.5454034\",\n \"0.5452039\",\n \"0.54283524\",\n \"0.5418019\",\n \"0.54131603\",\n \"0.54034954\",\n \"0.5399778\",\n \"0.5396933\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5352738\",\n \"0.5344227\",\n \"0.5344227\",\n \"0.5328359\",\n \"0.5315445\",\n \"0.53071886\",\n \"0.5303033\",\n \"0.5303033\",\n \"0.52926564\",\n \"0.5285332\",\n \"0.52689016\",\n \"0.5253707\",\n \"0.5245113\",\n \"0.5213911\",\n \"0.5213253\",\n \"0.5213253\",\n \"0.5177571\",\n \"0.5119861\",\n \"0.50994295\",\n \"0.50806534\",\n \"0.50608015\",\n \"0.50422025\",\n \"0.50333756\",\n \"0.50333756\",\n \"0.50306094\",\n \"0.5013336\",\n \"0.5012429\",\n \"0.5010544\",\n \"0.49840027\",\n \"0.49822313\",\n \"0.49715987\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.49666157\",\n \"0.494018\",\n \"0.49355277\",\n \"0.49355277\",\n \"0.49225703\",\n \"0.49205634\",\n \"0.49195287\",\n \"0.4915363\",\n \"0.49146557\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8478781"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":10694,"cells":{"query":{"kind":"string","value":"Sets the requested_object_list of this ExportResponseMetadata."},"document":{"kind":"string","value":"def requested_object_list(self, requested_object_list):\n\n self._requested_object_list = requested_object_list"},"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 exported_object_list(self, exported_object_list):\n\n self._exported_object_list = exported_object_list","def set_response_list(self, r_list):\n self.response_list = r_list","def set_objects(self, objects: list):\n self._objects = objects","def set_object_list(self, query, fields, sort, start, limit, is_public_request):\n xform = None\n\n try:\n enable_etag = True\n\n if not is_public_request:\n xform = self.get_object()\n self.data_count = xform.num_of_submissions\n enable_etag = self.data_count < SUBMISSION_RETRIEVAL_THRESHOLD\n\n where, where_params = get_where_clause(query)\n\n if where:\n # pylint: disable=attribute-defined-outside-init\n self.object_list = self.object_list.extra(\n where=where, params=where_params\n )\n\n if (start and limit or limit) and (not sort and not fields):\n start_index = start if start is not None else 0\n end_index = limit if start is None or start == 0 else start + limit\n # pylint: disable=attribute-defined-outside-init\n self.object_list = filter_queryset_xform_meta_perms(\n self.get_object(), self.request.user, self.object_list\n )\n # pylint: disable=attribute-defined-outside-init\n self.object_list = self.object_list[start_index:end_index]\n elif (sort or limit or start or fields) and not is_public_request:\n try:\n query = filter_queryset_xform_meta_perms_sql(\n self.get_object(), self.request.user, query\n )\n # pylint: disable=protected-access\n has_json_fields = sort and ParsedInstance._has_json_fields(\n _get_sort_fields(sort)\n )\n should_query_json_fields = fields or has_json_fields\n\n if self._should_paginate():\n retrieval_threshold = getattr(\n settings, \"SUBMISSION_RETRIEVAL_THRESHOLD\", 10000\n )\n query_param_keys = self.request.query_params\n page = int(\n query_param_keys.get(self.paginator.page_query_param, 1)\n )\n page_size = int(\n query_param_keys.get(\n self.paginator.page_size_query_param,\n retrieval_threshold,\n )\n )\n start = (page - 1) * page_size\n limit = page_size\n\n if sort is None:\n # Paginated data needs to be sorted. We order by\n # id ascending if sort is empty\n sort = '{\"_id\": 1}'\n\n if should_query_json_fields:\n data = query_fields_data(\n xform,\n fields=fields,\n query=query,\n sort=sort,\n start_index=start,\n limit=limit,\n )\n # pylint: disable=attribute-defined-outside-init\n self.object_list = data\n else:\n data = query_data(\n xform,\n query=query,\n sort=sort,\n start_index=start,\n limit=limit,\n json_only=not self.kwargs.get(\"format\") == \"xml\",\n )\n # pylint: disable=attribute-defined-outside-init\n self.object_list = data\n except NoRecordsPermission:\n # pylint: disable=attribute-defined-outside-init\n self.object_list = []\n\n # ETags are Disabled for XForms with Submissions that surpass\n # the configured SUBMISSION_RETRIEVAL_THRESHOLD setting\n if enable_etag:\n sql = params = None\n\n if xform:\n sql, params = get_sql_with_params(\n xform,\n query=query,\n sort=sort,\n start_index=start,\n limit=limit,\n fields=fields,\n )\n\n setattr(\n self,\n \"etag_hash\",\n (get_etag_hash_from_query(sql, params)),\n )\n except ValueError as e:\n raise ParseError(str(e)) from e\n except DataError as e:\n raise ParseError(str(e)) from e","def put_list(self, request, **kwargs):\r\n response = super(BaseCorsResource, self).put_list(request, **kwargs)\r\n return self.add_cors_headers(response, True)","def get_object_list(self, request):\r\n\r\n self._reset_collection()\r\n return self._meta.queryset.clone()","def post_list(self, request, **kwargs):\n response = super(BaseCorsResource, self).post_list(request, **kwargs)\n response['Access-Control-Allow-Origin'] = '*'\n response['Access-Control-Expose-Headers'] = 'Location'\n return response","def set(self, request, _object):\n\n value = request._get_parameter_value(self)\n value.object = _object","def extend(self, object_list):\n self.data['object'].extend(object_list)\n self.data['id'].extend(range(self.start_id, self.start_id+len(object_list)))\n for col in self.cols:\n if col != 'object' and col != 'id':\n self.data[col].extend([None]*(len(self.data[\"id\"] ) - len(self.data[col])))\n self.start_id += len(object_list)\n return self","def view_list(self, view_list):\n\n self._view_list = view_list","def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\n\n self._export_host = None\n self._export_date = None\n self._requested_object_list = None\n self._exported_object_list = None\n self.discriminator = None\n\n if export_host is not None:\n self.export_host = export_host\n if export_date is not None:\n self.export_date = export_date\n if requested_object_list is not None:\n self.requested_object_list = requested_object_list\n if exported_object_list is not None:\n self.exported_object_list = exported_object_list","def resources(self, value):\n self._resource_objects = value","def request_object_update(self, AgentID, SessionID, ID_CacheMissType_list = None):\n\n packet = Message('RequestMultipleObjects',\n Block('AgentData',\n AgentID = AgentID,\n SessionID = SessionID),\n *[Block('ObjectData',\n CacheMissType = ID_CacheMissType[1],\n ID = ID_CacheMissType[0]) for ID_CacheMissType in ID_CacheMissType_list])\n\n # enqueue the message, send as reliable\n self.region.enqueue_message(packet, True)","def origin_list(self, origin_list: List[Origin]):\n\n self._origin_list = origin_list","def post_list(self, request, **kwargs):\r\n #logger.debug(\"post list %s\\n%s\" % (request, kwargs));\r\n response = super(BaseCorsResource, self).post_list(request, **kwargs)\r\n return self.add_cors_headers(response, True)","def fields_in_list(self, fields_in_list):\n\n self._fields_in_list = fields_in_list","def fields_in_list(self, fields_in_list):\n\n self._fields_in_list = fields_in_list","def list(self, request, *args, **kwargs):\n query = self.filter_queryset(self.get_queryset())\n if isinstance(query, ErrorResponse):\n return query\n default_limit = DEFAULT_LIST_LIMIT\n limit, offset, range_errors = self.get_offset_limit_params(default_limit)\n if range_errors:\n return ErrorResponse(data=range_errors)\n\n self.object_list = get_object_list(offset, limit, query)\n\n # Default is to allow empty querysets. This can be altered by setting\n # `.allow_empty = False`, to raise 404 errors on empty querysets.\n if not self.allow_empty and not self.object_list:\n warnings.warn(\n 'The `allow_empty` parameter is due to be deprecated. '\n 'To use `allow_empty=False` style behavior, You should override '\n '`get_queryset()` and explicitly raise a 404 on empty querysets.',\n PendingDeprecationWarning\n )\n class_name = self.__class__.__name__\n error_msg = self.empty_error % {'class_name': class_name}\n raise Http404(error_msg)\n\n # the pagination is not supported, use offset and limit\n serializer = self.get_serializer(self.object_list, many=True)\n return self.generate_list_response(query, self.object_list, serializer, offset, limit)","def setListDoc(self, list):\n if list is None: list__o = None\n else: list__o = list._o\n libxml2mod.xmlSetListDoc(list__o, self._o)","def SetLists(self,IndList,ObjList):\n \n if not len(IndList)==len(ObjList):\n raise ValueError(\"IndList and ObjList must be of the same length\")\n \n if not prod([type(x)==tuple for x in IndList]):\n IndFormatError=1\n elif not prod([len(x)==3 for x in IndList]):\n IndFormatError=1\n \n IndFormatError=0\n \n if IndFormatError:\n raise ValueError(\"IndList must be list of 3-tuples\")\n \n if not prod([shape(x) == self.__shape for x in ObjList])==1:\n print([shape(x) for x in ObjList])\n raise ValueError(\"ObjList must contain arrays of the same shape as the BZO (shape %s)\"%str(self.__shape))\n \n \n self.__IndList=IndList\n self.__ObjList=ObjList\n \n self.__Set_NumList() \n self.__SortLists()","def setOutputs(self, output_list):\n self.output_list = output_list","def resolve_objects(self, object_list: List[Downloadable], show_progress: bool):\n resolve_objects_drs_hostname_from_id(\n object_list,\n self.resolved_compact_drs,\n f\"http://{self.hostname}/mds/aggregate/info\",\n )\n progress_bar = (\n tqdm(desc=f\"Resolving objects\", total=len(object_list))\n if show_progress\n else InvisibleProgress()\n )\n for entry in object_list:\n add_drs_object_info(entry)\n # sugar to allow download objects to self download\n entry._manager = self\n progress_bar.update(1)","def SetImageList(self, imageList):\r\n\r\n self._imageList = imageList","def apply_authorization_limits(self, request, object_list):\n return object_list.filter(user=request.user)","def contact_list(self, contact_list):\n \n self._contact_list = contact_list","def set_target_stocks_list(self, list_of_stocks):\n self.target_stocks = list_of_stocks","def _set_listonly(self, value):\n if not value and self.__listonly:\n self.__listonly = False\n self.clear_preprocessed()","def photoset_list(request, queryset=None, **kwargs):\n if queryset is None:\n queryset = Photoset.objects.all()\n \n if 'queryset' in kwargs:\n del kwargs['queryset']\n \n if 'template_name' not in kwargs:\n kwargs['template_name'] = 'flickrsets/photoset/list.html'\n \n if 'template_object_name' not in kwargs:\n kwargs['template_object_name'] = 'photoset'\n \n if 'paginate_by' not in kwargs:\n kwargs['paginate_by'] = getattr(\n app_settings,\n 'PHOTOSET_LIST_VIEW_PAGINATE_BY')\n \n return list_detail.object_list(request, queryset, **kwargs)","def set_event_list(self):\n self.eventList = self.get_event_list()","def marshal(self, request, _object):\n\n raise NotImplementedError()","def selected_field_list(self, selected_field_list):\n\n self._selected_field_list = selected_field_list","def read_list(self, object_list, bundle):\n\t\tself.is_authenticated(request)\n\t\treturn object_list.filter(pk=bundle.request.user.id)","def setConflictList(self, conflict_list):\n return\n # if conflict_list is None or conflict_list == []:\n # self.resetConflictList()\n # else:\n # self.conflict_list = conflict_list ","def plane_list(self, new_list):\n self.__plane_list = new_list","def set_response_list(cls,response_list):\n if not isinstance(response_list,list):\n raise ValueError('response_list arg must be a list')\n\n # Run through the responses\n for response in response_list:\n if not isinstance(response,(list,dict)):\n raise ValueError('response_list entry must be a list or dict')\n\n if isinstance(response,list):\n if len(response) != 3:\n raise ValueError('response_list entry must have 3 fields')\n\n # Grab each fields\n url = response[0]\n method = 'POST'\n status = response[1]\n type = 'xml'\n message = response[2]\n\n else:\n # response is a dict\n url = response.get('base_url')\n method = response.get('method','POST')\n status = response.get('status')\n type = response.get('type','xml')\n message = response.get('message')\n\n response_list = BonitaMockedServerImpl.get_response_list()\n response_list.add_or_augment_response_list(url,method,status,type,message)","def available_field_list(self, available_field_list):\n\n self._available_field_list = available_field_list","def get_list(self, request, **kwargs):\n # TODO: Uncached for now. Invalidation that works for everyone may be\n # impossible.\n objects = self.obj_get_list(request=request, **self.remove_api_resource_names(kwargs))\n sorted_objects = self.apply_sorting(objects, options=request.GET)\n\n paginator = self._meta.paginator_class(request.GET, sorted_objects, resource_uri=self.get_resource_uri(),\n limit=self._meta.limit, max_limit=self._meta.max_limit, collection_name=self._meta.collection_name)\n to_be_serialized = paginator.page()\n\n # Dehydrate the bundles in preparation for serialization.\n bundles = [self.build_bundle(obj=obj, request=request) for obj in to_be_serialized['objects']]\n to_be_serialized['objects'] = [self.full_dehydrate(bundle) for bundle in bundles]\n to_be_serialized = self.alter_list_data_to_serialize(request, to_be_serialized)\n\n self.add_shit_to_meta(request, to_be_serialized)\n\n return self.create_response(request, to_be_serialized)","def associated_objects(self, associated_objects):\n self._associated_objects = associated_objects","def _list_set_iss(self, iss):\n self.iss = list(iss)","def ole_objects(self, ole_objects):\n\n self.container['ole_objects'] = ole_objects","def populate_list(self):\n self._list.value = self.__get_queryset()\n # force the list to be updated\n self._list.mark_to_update_client()","def setListDoc(self, doc):\n if doc is None: doc__o = None\n else: doc__o = doc._o\n libxml2mod.xmlSetListDoc(self._o, doc__o)","def list(self, list):\n if list is None:\n raise ValueError(\"Invalid value for `list`, must not be `None`\") # noqa: E501\n\n self._list = list","def assert_object_list(self, objects: List[models.Model],\n **kwargs: Any) -> None:\n data = self.get_list(**kwargs)\n ids = [obj[self.pk_field] for obj in data]\n expected = [obj.pk for obj in objects]\n self.assertListEqual(ids, expected)","def update_list(self):\n Asset.update_list(self, uri_keys=('ems_sys', 'list'))","def update_copied_objects_list(object, event):\n request = event.original.REQUEST\n if not ISpecialPasteInProgress.providedBy(request):\n return\n annotations = IAnnotations(object, None)\n if annotations is None:\n # Annotations on this object are not supported. This happens\n # e.g. for SyndicationInformation, ATSimpleStringCriterion,\n # and WorkflowPolicyConfig, so it is quite normal.\n return\n if object is event.object:\n original = event.original\n else:\n # Use the path minus the top level folder, as that may be\n # copy_of_folder.\n path = '/'.join(object.getPhysicalPath()[1:])\n try:\n original = event.original.restrictedTraverse(path)\n except:\n logger.error(\"Could not get original %s from parent %r\", path,\n event.original)\n raise\n annotations[ANNO_KEY] = original.getPhysicalPath()\n logger.debug(\"Annotation set: %r\", '/'.join(original.getPhysicalPath()))","def populate_with_object(self, obj):\n super(ListTile, self).populate_with_object(obj) # check permission\n self.populate_with_uuids([self.get_uuid(obj)])","def setExplicitlyListed(self, value=True):\n return _libsbml.ListOf_setExplicitlyListed(self, value)","def SetObject(self, obj):\n return _gmat_py.EphemManager_SetObject(self, obj)","def append_to_request(self, request_base, request_object):\n\n pass","def __init__(self, **kwargs):\n for f in self.list_fields:\n val = kwargs.pop(f, None)\n if val is not None and isinstance(val, (str, unicode, dict)):\n kwargs[f] = [val]\n elif isinstance(val, list):\n kwargs[f] = val\n super(HasMetadata, self).__init__(**kwargs)","def set_PageToken(self, value):\n super(ListOrdersInputSet, self)._set_input('PageToken', value)","def response_values(self, response_values):\n\n self._response_values = response_values","def handle_list(self, object, name, old, new):\n raise NotImplementedError","def obj_get_list(self, bundle, **kwargs):\n filters = {}\n if hasattr(bundle.request, 'GET'):\n # Grab a mutable copy.\n filters = bundle.request.GET.copy()\n\n # Update with the provided kwargs.\n filters.update(kwargs)\n channel = False\n if 'owner' in filters:\n channel = True\n applicable_filters = self.build_filters(filters=filters)\n\n try:\n objects = self.apply_filters(bundle.request, applicable_filters)\n self.objects_returned = len(objects)\n if len(objects) == 1 and applicable_filters and not channel:\n obj = objects[0]\n obj.views = obj.views + 1\n obj.lastview_date = timezone.now()\n obj.save(update_fields=['views', 'lastview_date'])\n return self.authorized_read_list(objects, bundle)\n except ValueError:\n raise BadRequest(\"Invalid resource lookup data provided (mismatched type).\")","def obj_get_list(self, request=None, **kwargs):\n filters = {}\n if hasattr(request, 'GET'):\n # Grab a mutable copy.\n filters = request.GET.copy()\n\n # Update with the provided kwargs.\n filters.update(kwargs)\n if \"community\" in filters:\n try:\n community = Community.objects.get(\n uuid=uuid_from_uri(filters['community']))\n im = community.image_set.filter(is_active=True)\n wb = community.wordbox_set.filter(is_active=True)\n base_object_list = sorted(chain(im, wb),\n key=attrgetter('created_time'))[::-1]\n return self.apply_authorization_limits(request,\n base_object_list)\n except ValueError:\n raise BadRequest(\"Invalid resource lookup data provided \"\n \"(mismatched type).\")\n else:\n raise BadRequest(\"Invalid filtering parameter\")","def set_all(self, value):\n self.__items = value","def post(self, request, *args, **kwargs):\n return super(AccessibleByListAPIView, self).post(\n request, *args, **kwargs)","def object_attribute_values(self, values):\n if values is not None:\n if not isinstance(values, list):\n raise TypeError('object_attribute_values must be a list')\n \n self._batch_size = len(values)\n \n self._object_attribute_values = values","def AssignImageList(self, imageList):\r\n\r\n self.SetImageList(imageList)","def __init__(\n self,\n *,\n updated: Sequence[KeylistUpdated] = None,\n **kwargs,\n ):\n super(KeylistUpdateResponse, self).__init__(**kwargs)\n self.updated = list(updated) if updated else []","def set_race_events_list(self, race_events_list):\n self.race_events_list = race_events_list","def __set__(self, obj, value):\r\n if self.item_type in (int, long):\r\n item_type = (int, long)\r\n elif self.item_type in (str, unicode):\r\n item_type = (str, unicode)\r\n else:\r\n item_type = self.item_type\r\n if isinstance(value, item_type):\r\n value = [value]\r\n elif value == None: # Override to allow them to set this to \"None\" to remove everything\r\n value = []\r\n return super(ListProperty, self).__set__(obj,value)","def Set(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def set_list_index(self, n=0):\r\n return self._api.set_list_index(n)","def request_data(self, request_data):\n\n self._request_data = request_data","def setSublist(self, sublist):\n if self.cursor:\n self.cursor.sublist = sublist","def add_metadata(self, metdatadata_list):\n self._metadata.append((metdatadata_list, ))","def add_metadata(self, metdatadata_list):\n self._metadata.append((metdatadata_list, ))","def review_requested_by(self, review_requested_by):\n\n self._review_requested_by = review_requested_by","def set_hidden_list(hidden_list, user=None):\n\tif isinstance(hidden_list, str):\n\t\thidden_list = json.loads(hidden_list)\n\n\t# set as hidden\n\tfor module_name in hidden_list:\n\t\tset_hidden(module_name, user, 1)\n\n\t# set as seen\n\tfor module_name in list(set(get_all_icons()) - set(hidden_list)):\n\t\tset_hidden(module_name, user, 0)\n\n\tif user:\n\t\tclear_desktop_icons_cache()\n\telse:\n\t\tfrappe.clear_cache()","def AssignImageList(self, imageList):\r\n\r\n self.SetImageList(imageList)\r\n self._ownsImageListNormal = True","def add_objects(self, objects):\n requests = []\n for obj in objects:\n requests.append({\"action\": \"addObject\", \"body\": obj})\n request = {\"requests\": requests}\n return self.batch(request)","def set_full_stocklist_to_retrieve(self, list_of_stocks):\n self.full_stocklist_to_retrieve = list_of_stocks","def set_all_from_json(self, value:list):\n self.clear()\n for item in value:\n relation_id = item['relation_id']\n members = item['members']\n self[relation_id] = members","def set_related_params(self,request,responsedata):\n pass","def update_multiple_objects_properties(self, object_list):\n\n #if self.settings.LOG_VERBOSE and self.settings.ENABLE_OBJECT_LOGGING: logger.debug(\"Processing multiple object properties updates: %s\" % (len(object_list)))\n\n for object_properties in object_list:\n\n self.update_object_properties(object_properties)","def setfiles(self, filelist):\r\n self._filelist=filelist\r\n self._energy=self.readenergy(filelist)","def fdsid_list(self, fdsid_list):\n\n self._fdsid_list = fdsid_list","def setPathsList(self, pathsList):\n self.clear()\n self.addItems(pathsList)","def set_attachments(self):\n self.response['attachments'] = []","def person_list(self, new_persons_list):\n self._person_list = new_persons_list\n self.__save_persons_from_memory_to_file()","def obj_delete_list(self, request=None, **kwargs):\n self.get_collection(request).remove()","def member_list(self, member_list):\n\n self._member_list = member_list","def serialize_catalogue_metadata(md_queryset: QuerySet) -> list:\n # If no queryset but a single metadata is provided, we do not add everything into a\n is_single_retrieve = not isinstance(md_queryset, Iterable)\n\n if is_single_retrieve:\n ret_val = perform_catalogue_entry_serialization(md_queryset)\n else:\n ret_val = [perform_catalogue_entry_serialization(md) for md in md_queryset]\n\n return ret_val","def build_response(self, data_list):\n raise NotImplementedError(\"build_response method is not implemented.\")","def fake_generic_listing(object_list, object_type):\n\n return {\n 'data': object_list,\n 'has_more': False,\n 'object': 'list',\n 'total_count': len(object_list),\n 'url': '/v1/{}s'.format(object_type),\n }","def set_used_samples(self, used_sample_id_list):\n self._make_index_list(used_sample_id_list)","def list(self,request,*args,**kwargs):\n response=super(ListAPIView,self).list(request,*args,**kwargs)\n #add applied_filters to the response which is set when filter_queryset method is called\n response=self.addAppliedFilters(response)\n #fetch data from the related views\n return self.fetch_related(request,response,*args,**kwargs)","def set_xList(self, *xList):\n assert len(xList) == self.__nx\n self.__x = xList\n self.__xshape = xList[0].shape # Reset the shape of the input.","def set_ResponseFormat(self, value):\n super(ListOrdersInputSet, self)._set_input('ResponseFormat', value)","def _set_scrolls(self, listOfScrolls):\n self._scrolls = listOfScrolls","def obj_get_list(self, request=None, **kwargs):\n filters = {}\n if hasattr(request, 'GET'):\n # Grab a mutable copy.\n filters = request.GET.copy()\n\n # Update with the provided kwargs.\n filters.update(kwargs)\n if \"user\" in filters and \"media\" in filters:\n try:\n image_uuid_list = []\n wordbox_uuid_list = []\n for item in filters['media'].split(','):\n # use kwarg \"resource\" field to be more general rather\n # than take the 2 element\n try:\n if item.split('/')[2] == 'image':\n image_uuid_list.append(uuid_re.findall(item)[0])\n elif item.split('/')[2] == 'wordbox':\n wordbox_uuid_list.append(uuid_re.findall(item)[0])\n except IndexError:\n raise BadRequest(\"Invalid uuid or resource URI.\")\n userprofile = UserProfile.objects.get(\n uuid=uuid_from_uri(filters['user']))\n im = userprofile.image_collection_set.filter(\n is_active=True, uuid__in=image_uuid_list)\n wb = userprofile.wordbox_collection_set.\\\n filter(is_active=True, uuid__in=wordbox_uuid_list)\n base_object_list = sorted(chain(im, wb),\n key=attrgetter('created_time'))[::-1]\n return self.apply_authorization_limits(request,\n base_object_list)\n except ValueError:\n raise BadRequest(\"Invalid resource lookup data provided \"\n \"(mismatched type).\")\n elif \"user\" in filters and len(filters) == 1:\n try:\n userprofile = UserProfile.objects.get(\n uuid=uuid_from_uri(filters['user']))\n im = userprofile.image_collection_set.filter(is_active=True)\n wb = userprofile.wordbox_collection_set.filter(is_active=True)\n base_object_list = sorted(chain(im, wb),\n key=attrgetter('created_time'))[::-1]\n return self.apply_authorization_limits(request,\n base_object_list)\n except ValueError:\n raise BadRequest(\"Invalid resource lookup data provided \"\n \"(mismatched type).\")\n else:\n raise BadRequest(\"Invalid filtering parameter(s)\")","def add_access_list(self, access_list):\n return self.manager.add_access_list(self, access_list)","def setObjectID(self, objectid):\n self._objectid = objectid","def data(self, data: List[InlineResponse2002]):\n\n self._data = data","def object_list_name(self):\n return self.object_name + '_list'","def metadata(self, val: list):\n self._metadata = []\n if val is not None:\n for item in val:\n if isinstance(item, Metadata):\n self._metadata.append(item)","def set_documents(cls, input_list_text: List[str]) -> None:\n cls.documents = input_list_text","def partial_update_objects(self, objects):\n requests = []\n for obj in objects:\n requests.append({\"action\": \"partialUpdateObject\", \"objectID\": obj[\"objectID\"], \"body\": obj})\n request = {\"requests\": requests}\n return self.batch(request)"],"string":"[\n \"def exported_object_list(self, exported_object_list):\\n\\n self._exported_object_list = exported_object_list\",\n \"def set_response_list(self, r_list):\\n self.response_list = r_list\",\n \"def set_objects(self, objects: list):\\n self._objects = objects\",\n \"def set_object_list(self, query, fields, sort, start, limit, is_public_request):\\n xform = None\\n\\n try:\\n enable_etag = True\\n\\n if not is_public_request:\\n xform = self.get_object()\\n self.data_count = xform.num_of_submissions\\n enable_etag = self.data_count < SUBMISSION_RETRIEVAL_THRESHOLD\\n\\n where, where_params = get_where_clause(query)\\n\\n if where:\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = self.object_list.extra(\\n where=where, params=where_params\\n )\\n\\n if (start and limit or limit) and (not sort and not fields):\\n start_index = start if start is not None else 0\\n end_index = limit if start is None or start == 0 else start + limit\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = filter_queryset_xform_meta_perms(\\n self.get_object(), self.request.user, self.object_list\\n )\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = self.object_list[start_index:end_index]\\n elif (sort or limit or start or fields) and not is_public_request:\\n try:\\n query = filter_queryset_xform_meta_perms_sql(\\n self.get_object(), self.request.user, query\\n )\\n # pylint: disable=protected-access\\n has_json_fields = sort and ParsedInstance._has_json_fields(\\n _get_sort_fields(sort)\\n )\\n should_query_json_fields = fields or has_json_fields\\n\\n if self._should_paginate():\\n retrieval_threshold = getattr(\\n settings, \\\"SUBMISSION_RETRIEVAL_THRESHOLD\\\", 10000\\n )\\n query_param_keys = self.request.query_params\\n page = int(\\n query_param_keys.get(self.paginator.page_query_param, 1)\\n )\\n page_size = int(\\n query_param_keys.get(\\n self.paginator.page_size_query_param,\\n retrieval_threshold,\\n )\\n )\\n start = (page - 1) * page_size\\n limit = page_size\\n\\n if sort is None:\\n # Paginated data needs to be sorted. We order by\\n # id ascending if sort is empty\\n sort = '{\\\"_id\\\": 1}'\\n\\n if should_query_json_fields:\\n data = query_fields_data(\\n xform,\\n fields=fields,\\n query=query,\\n sort=sort,\\n start_index=start,\\n limit=limit,\\n )\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = data\\n else:\\n data = query_data(\\n xform,\\n query=query,\\n sort=sort,\\n start_index=start,\\n limit=limit,\\n json_only=not self.kwargs.get(\\\"format\\\") == \\\"xml\\\",\\n )\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = data\\n except NoRecordsPermission:\\n # pylint: disable=attribute-defined-outside-init\\n self.object_list = []\\n\\n # ETags are Disabled for XForms with Submissions that surpass\\n # the configured SUBMISSION_RETRIEVAL_THRESHOLD setting\\n if enable_etag:\\n sql = params = None\\n\\n if xform:\\n sql, params = get_sql_with_params(\\n xform,\\n query=query,\\n sort=sort,\\n start_index=start,\\n limit=limit,\\n fields=fields,\\n )\\n\\n setattr(\\n self,\\n \\\"etag_hash\\\",\\n (get_etag_hash_from_query(sql, params)),\\n )\\n except ValueError as e:\\n raise ParseError(str(e)) from e\\n except DataError as e:\\n raise ParseError(str(e)) from e\",\n \"def put_list(self, request, **kwargs):\\r\\n response = super(BaseCorsResource, self).put_list(request, **kwargs)\\r\\n return self.add_cors_headers(response, True)\",\n \"def get_object_list(self, request):\\r\\n\\r\\n self._reset_collection()\\r\\n return self._meta.queryset.clone()\",\n \"def post_list(self, request, **kwargs):\\n response = super(BaseCorsResource, self).post_list(request, **kwargs)\\n response['Access-Control-Allow-Origin'] = '*'\\n response['Access-Control-Expose-Headers'] = 'Location'\\n return response\",\n \"def set(self, request, _object):\\n\\n value = request._get_parameter_value(self)\\n value.object = _object\",\n \"def extend(self, object_list):\\n self.data['object'].extend(object_list)\\n self.data['id'].extend(range(self.start_id, self.start_id+len(object_list)))\\n for col in self.cols:\\n if col != 'object' and col != 'id':\\n self.data[col].extend([None]*(len(self.data[\\\"id\\\"] ) - len(self.data[col])))\\n self.start_id += len(object_list)\\n return self\",\n \"def view_list(self, view_list):\\n\\n self._view_list = view_list\",\n \"def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\\n\\n self._export_host = None\\n self._export_date = None\\n self._requested_object_list = None\\n self._exported_object_list = None\\n self.discriminator = None\\n\\n if export_host is not None:\\n self.export_host = export_host\\n if export_date is not None:\\n self.export_date = export_date\\n if requested_object_list is not None:\\n self.requested_object_list = requested_object_list\\n if exported_object_list is not None:\\n self.exported_object_list = exported_object_list\",\n \"def resources(self, value):\\n self._resource_objects = value\",\n \"def request_object_update(self, AgentID, SessionID, ID_CacheMissType_list = None):\\n\\n packet = Message('RequestMultipleObjects',\\n Block('AgentData',\\n AgentID = AgentID,\\n SessionID = SessionID),\\n *[Block('ObjectData',\\n CacheMissType = ID_CacheMissType[1],\\n ID = ID_CacheMissType[0]) for ID_CacheMissType in ID_CacheMissType_list])\\n\\n # enqueue the message, send as reliable\\n self.region.enqueue_message(packet, True)\",\n \"def origin_list(self, origin_list: List[Origin]):\\n\\n self._origin_list = origin_list\",\n \"def post_list(self, request, **kwargs):\\r\\n #logger.debug(\\\"post list %s\\\\n%s\\\" % (request, kwargs));\\r\\n response = super(BaseCorsResource, self).post_list(request, **kwargs)\\r\\n return self.add_cors_headers(response, True)\",\n \"def fields_in_list(self, fields_in_list):\\n\\n self._fields_in_list = fields_in_list\",\n \"def fields_in_list(self, fields_in_list):\\n\\n self._fields_in_list = fields_in_list\",\n \"def list(self, request, *args, **kwargs):\\n query = self.filter_queryset(self.get_queryset())\\n if isinstance(query, ErrorResponse):\\n return query\\n default_limit = DEFAULT_LIST_LIMIT\\n limit, offset, range_errors = self.get_offset_limit_params(default_limit)\\n if range_errors:\\n return ErrorResponse(data=range_errors)\\n\\n self.object_list = get_object_list(offset, limit, query)\\n\\n # Default is to allow empty querysets. This can be altered by setting\\n # `.allow_empty = False`, to raise 404 errors on empty querysets.\\n if not self.allow_empty and not self.object_list:\\n warnings.warn(\\n 'The `allow_empty` parameter is due to be deprecated. '\\n 'To use `allow_empty=False` style behavior, You should override '\\n '`get_queryset()` and explicitly raise a 404 on empty querysets.',\\n PendingDeprecationWarning\\n )\\n class_name = self.__class__.__name__\\n error_msg = self.empty_error % {'class_name': class_name}\\n raise Http404(error_msg)\\n\\n # the pagination is not supported, use offset and limit\\n serializer = self.get_serializer(self.object_list, many=True)\\n return self.generate_list_response(query, self.object_list, serializer, offset, limit)\",\n \"def setListDoc(self, list):\\n if list is None: list__o = None\\n else: list__o = list._o\\n libxml2mod.xmlSetListDoc(list__o, self._o)\",\n \"def SetLists(self,IndList,ObjList):\\n \\n if not len(IndList)==len(ObjList):\\n raise ValueError(\\\"IndList and ObjList must be of the same length\\\")\\n \\n if not prod([type(x)==tuple for x in IndList]):\\n IndFormatError=1\\n elif not prod([len(x)==3 for x in IndList]):\\n IndFormatError=1\\n \\n IndFormatError=0\\n \\n if IndFormatError:\\n raise ValueError(\\\"IndList must be list of 3-tuples\\\")\\n \\n if not prod([shape(x) == self.__shape for x in ObjList])==1:\\n print([shape(x) for x in ObjList])\\n raise ValueError(\\\"ObjList must contain arrays of the same shape as the BZO (shape %s)\\\"%str(self.__shape))\\n \\n \\n self.__IndList=IndList\\n self.__ObjList=ObjList\\n \\n self.__Set_NumList() \\n self.__SortLists()\",\n \"def setOutputs(self, output_list):\\n self.output_list = output_list\",\n \"def resolve_objects(self, object_list: List[Downloadable], show_progress: bool):\\n resolve_objects_drs_hostname_from_id(\\n object_list,\\n self.resolved_compact_drs,\\n f\\\"http://{self.hostname}/mds/aggregate/info\\\",\\n )\\n progress_bar = (\\n tqdm(desc=f\\\"Resolving objects\\\", total=len(object_list))\\n if show_progress\\n else InvisibleProgress()\\n )\\n for entry in object_list:\\n add_drs_object_info(entry)\\n # sugar to allow download objects to self download\\n entry._manager = self\\n progress_bar.update(1)\",\n \"def SetImageList(self, imageList):\\r\\n\\r\\n self._imageList = imageList\",\n \"def apply_authorization_limits(self, request, object_list):\\n return object_list.filter(user=request.user)\",\n \"def contact_list(self, contact_list):\\n \\n self._contact_list = contact_list\",\n \"def set_target_stocks_list(self, list_of_stocks):\\n self.target_stocks = list_of_stocks\",\n \"def _set_listonly(self, value):\\n if not value and self.__listonly:\\n self.__listonly = False\\n self.clear_preprocessed()\",\n \"def photoset_list(request, queryset=None, **kwargs):\\n if queryset is None:\\n queryset = Photoset.objects.all()\\n \\n if 'queryset' in kwargs:\\n del kwargs['queryset']\\n \\n if 'template_name' not in kwargs:\\n kwargs['template_name'] = 'flickrsets/photoset/list.html'\\n \\n if 'template_object_name' not in kwargs:\\n kwargs['template_object_name'] = 'photoset'\\n \\n if 'paginate_by' not in kwargs:\\n kwargs['paginate_by'] = getattr(\\n app_settings,\\n 'PHOTOSET_LIST_VIEW_PAGINATE_BY')\\n \\n return list_detail.object_list(request, queryset, **kwargs)\",\n \"def set_event_list(self):\\n self.eventList = self.get_event_list()\",\n \"def marshal(self, request, _object):\\n\\n raise NotImplementedError()\",\n \"def selected_field_list(self, selected_field_list):\\n\\n self._selected_field_list = selected_field_list\",\n \"def read_list(self, object_list, bundle):\\n\\t\\tself.is_authenticated(request)\\n\\t\\treturn object_list.filter(pk=bundle.request.user.id)\",\n \"def setConflictList(self, conflict_list):\\n return\\n # if conflict_list is None or conflict_list == []:\\n # self.resetConflictList()\\n # else:\\n # self.conflict_list = conflict_list \",\n \"def plane_list(self, new_list):\\n self.__plane_list = new_list\",\n \"def set_response_list(cls,response_list):\\n if not isinstance(response_list,list):\\n raise ValueError('response_list arg must be a list')\\n\\n # Run through the responses\\n for response in response_list:\\n if not isinstance(response,(list,dict)):\\n raise ValueError('response_list entry must be a list or dict')\\n\\n if isinstance(response,list):\\n if len(response) != 3:\\n raise ValueError('response_list entry must have 3 fields')\\n\\n # Grab each fields\\n url = response[0]\\n method = 'POST'\\n status = response[1]\\n type = 'xml'\\n message = response[2]\\n\\n else:\\n # response is a dict\\n url = response.get('base_url')\\n method = response.get('method','POST')\\n status = response.get('status')\\n type = response.get('type','xml')\\n message = response.get('message')\\n\\n response_list = BonitaMockedServerImpl.get_response_list()\\n response_list.add_or_augment_response_list(url,method,status,type,message)\",\n \"def available_field_list(self, available_field_list):\\n\\n self._available_field_list = available_field_list\",\n \"def get_list(self, request, **kwargs):\\n # TODO: Uncached for now. Invalidation that works for everyone may be\\n # impossible.\\n objects = self.obj_get_list(request=request, **self.remove_api_resource_names(kwargs))\\n sorted_objects = self.apply_sorting(objects, options=request.GET)\\n\\n paginator = self._meta.paginator_class(request.GET, sorted_objects, resource_uri=self.get_resource_uri(),\\n limit=self._meta.limit, max_limit=self._meta.max_limit, collection_name=self._meta.collection_name)\\n to_be_serialized = paginator.page()\\n\\n # Dehydrate the bundles in preparation for serialization.\\n bundles = [self.build_bundle(obj=obj, request=request) for obj in to_be_serialized['objects']]\\n to_be_serialized['objects'] = [self.full_dehydrate(bundle) for bundle in bundles]\\n to_be_serialized = self.alter_list_data_to_serialize(request, to_be_serialized)\\n\\n self.add_shit_to_meta(request, to_be_serialized)\\n\\n return self.create_response(request, to_be_serialized)\",\n \"def associated_objects(self, associated_objects):\\n self._associated_objects = associated_objects\",\n \"def _list_set_iss(self, iss):\\n self.iss = list(iss)\",\n \"def ole_objects(self, ole_objects):\\n\\n self.container['ole_objects'] = ole_objects\",\n \"def populate_list(self):\\n self._list.value = self.__get_queryset()\\n # force the list to be updated\\n self._list.mark_to_update_client()\",\n \"def setListDoc(self, doc):\\n if doc is None: doc__o = None\\n else: doc__o = doc._o\\n libxml2mod.xmlSetListDoc(self._o, doc__o)\",\n \"def list(self, list):\\n if list is None:\\n raise ValueError(\\\"Invalid value for `list`, must not be `None`\\\") # noqa: E501\\n\\n self._list = list\",\n \"def assert_object_list(self, objects: List[models.Model],\\n **kwargs: Any) -> None:\\n data = self.get_list(**kwargs)\\n ids = [obj[self.pk_field] for obj in data]\\n expected = [obj.pk for obj in objects]\\n self.assertListEqual(ids, expected)\",\n \"def update_list(self):\\n Asset.update_list(self, uri_keys=('ems_sys', 'list'))\",\n \"def update_copied_objects_list(object, event):\\n request = event.original.REQUEST\\n if not ISpecialPasteInProgress.providedBy(request):\\n return\\n annotations = IAnnotations(object, None)\\n if annotations is None:\\n # Annotations on this object are not supported. This happens\\n # e.g. for SyndicationInformation, ATSimpleStringCriterion,\\n # and WorkflowPolicyConfig, so it is quite normal.\\n return\\n if object is event.object:\\n original = event.original\\n else:\\n # Use the path minus the top level folder, as that may be\\n # copy_of_folder.\\n path = '/'.join(object.getPhysicalPath()[1:])\\n try:\\n original = event.original.restrictedTraverse(path)\\n except:\\n logger.error(\\\"Could not get original %s from parent %r\\\", path,\\n event.original)\\n raise\\n annotations[ANNO_KEY] = original.getPhysicalPath()\\n logger.debug(\\\"Annotation set: %r\\\", '/'.join(original.getPhysicalPath()))\",\n \"def populate_with_object(self, obj):\\n super(ListTile, self).populate_with_object(obj) # check permission\\n self.populate_with_uuids([self.get_uuid(obj)])\",\n \"def setExplicitlyListed(self, value=True):\\n return _libsbml.ListOf_setExplicitlyListed(self, value)\",\n \"def SetObject(self, obj):\\n return _gmat_py.EphemManager_SetObject(self, obj)\",\n \"def append_to_request(self, request_base, request_object):\\n\\n pass\",\n \"def __init__(self, **kwargs):\\n for f in self.list_fields:\\n val = kwargs.pop(f, None)\\n if val is not None and isinstance(val, (str, unicode, dict)):\\n kwargs[f] = [val]\\n elif isinstance(val, list):\\n kwargs[f] = val\\n super(HasMetadata, self).__init__(**kwargs)\",\n \"def set_PageToken(self, value):\\n super(ListOrdersInputSet, self)._set_input('PageToken', value)\",\n \"def response_values(self, response_values):\\n\\n self._response_values = response_values\",\n \"def handle_list(self, object, name, old, new):\\n raise NotImplementedError\",\n \"def obj_get_list(self, bundle, **kwargs):\\n filters = {}\\n if hasattr(bundle.request, 'GET'):\\n # Grab a mutable copy.\\n filters = bundle.request.GET.copy()\\n\\n # Update with the provided kwargs.\\n filters.update(kwargs)\\n channel = False\\n if 'owner' in filters:\\n channel = True\\n applicable_filters = self.build_filters(filters=filters)\\n\\n try:\\n objects = self.apply_filters(bundle.request, applicable_filters)\\n self.objects_returned = len(objects)\\n if len(objects) == 1 and applicable_filters and not channel:\\n obj = objects[0]\\n obj.views = obj.views + 1\\n obj.lastview_date = timezone.now()\\n obj.save(update_fields=['views', 'lastview_date'])\\n return self.authorized_read_list(objects, bundle)\\n except ValueError:\\n raise BadRequest(\\\"Invalid resource lookup data provided (mismatched type).\\\")\",\n \"def obj_get_list(self, request=None, **kwargs):\\n filters = {}\\n if hasattr(request, 'GET'):\\n # Grab a mutable copy.\\n filters = request.GET.copy()\\n\\n # Update with the provided kwargs.\\n filters.update(kwargs)\\n if \\\"community\\\" in filters:\\n try:\\n community = Community.objects.get(\\n uuid=uuid_from_uri(filters['community']))\\n im = community.image_set.filter(is_active=True)\\n wb = community.wordbox_set.filter(is_active=True)\\n base_object_list = sorted(chain(im, wb),\\n key=attrgetter('created_time'))[::-1]\\n return self.apply_authorization_limits(request,\\n base_object_list)\\n except ValueError:\\n raise BadRequest(\\\"Invalid resource lookup data provided \\\"\\n \\\"(mismatched type).\\\")\\n else:\\n raise BadRequest(\\\"Invalid filtering parameter\\\")\",\n \"def set_all(self, value):\\n self.__items = value\",\n \"def post(self, request, *args, **kwargs):\\n return super(AccessibleByListAPIView, self).post(\\n request, *args, **kwargs)\",\n \"def object_attribute_values(self, values):\\n if values is not None:\\n if not isinstance(values, list):\\n raise TypeError('object_attribute_values must be a list')\\n \\n self._batch_size = len(values)\\n \\n self._object_attribute_values = values\",\n \"def AssignImageList(self, imageList):\\r\\n\\r\\n self.SetImageList(imageList)\",\n \"def __init__(\\n self,\\n *,\\n updated: Sequence[KeylistUpdated] = None,\\n **kwargs,\\n ):\\n super(KeylistUpdateResponse, self).__init__(**kwargs)\\n self.updated = list(updated) if updated else []\",\n \"def set_race_events_list(self, race_events_list):\\n self.race_events_list = race_events_list\",\n \"def __set__(self, obj, value):\\r\\n if self.item_type in (int, long):\\r\\n item_type = (int, long)\\r\\n elif self.item_type in (str, unicode):\\r\\n item_type = (str, unicode)\\r\\n else:\\r\\n item_type = self.item_type\\r\\n if isinstance(value, item_type):\\r\\n value = [value]\\r\\n elif value == None: # Override to allow them to set this to \\\"None\\\" to remove everything\\r\\n value = []\\r\\n return super(ListProperty, self).__set__(obj,value)\",\n \"def Set(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def set_list_index(self, n=0):\\r\\n return self._api.set_list_index(n)\",\n \"def request_data(self, request_data):\\n\\n self._request_data = request_data\",\n \"def setSublist(self, sublist):\\n if self.cursor:\\n self.cursor.sublist = sublist\",\n \"def add_metadata(self, metdatadata_list):\\n self._metadata.append((metdatadata_list, ))\",\n \"def add_metadata(self, metdatadata_list):\\n self._metadata.append((metdatadata_list, ))\",\n \"def review_requested_by(self, review_requested_by):\\n\\n self._review_requested_by = review_requested_by\",\n \"def set_hidden_list(hidden_list, user=None):\\n\\tif isinstance(hidden_list, str):\\n\\t\\thidden_list = json.loads(hidden_list)\\n\\n\\t# set as hidden\\n\\tfor module_name in hidden_list:\\n\\t\\tset_hidden(module_name, user, 1)\\n\\n\\t# set as seen\\n\\tfor module_name in list(set(get_all_icons()) - set(hidden_list)):\\n\\t\\tset_hidden(module_name, user, 0)\\n\\n\\tif user:\\n\\t\\tclear_desktop_icons_cache()\\n\\telse:\\n\\t\\tfrappe.clear_cache()\",\n \"def AssignImageList(self, imageList):\\r\\n\\r\\n self.SetImageList(imageList)\\r\\n self._ownsImageListNormal = True\",\n \"def add_objects(self, objects):\\n requests = []\\n for obj in objects:\\n requests.append({\\\"action\\\": \\\"addObject\\\", \\\"body\\\": obj})\\n request = {\\\"requests\\\": requests}\\n return self.batch(request)\",\n \"def set_full_stocklist_to_retrieve(self, list_of_stocks):\\n self.full_stocklist_to_retrieve = list_of_stocks\",\n \"def set_all_from_json(self, value:list):\\n self.clear()\\n for item in value:\\n relation_id = item['relation_id']\\n members = item['members']\\n self[relation_id] = members\",\n \"def set_related_params(self,request,responsedata):\\n pass\",\n \"def update_multiple_objects_properties(self, object_list):\\n\\n #if self.settings.LOG_VERBOSE and self.settings.ENABLE_OBJECT_LOGGING: logger.debug(\\\"Processing multiple object properties updates: %s\\\" % (len(object_list)))\\n\\n for object_properties in object_list:\\n\\n self.update_object_properties(object_properties)\",\n \"def setfiles(self, filelist):\\r\\n self._filelist=filelist\\r\\n self._energy=self.readenergy(filelist)\",\n \"def fdsid_list(self, fdsid_list):\\n\\n self._fdsid_list = fdsid_list\",\n \"def setPathsList(self, pathsList):\\n self.clear()\\n self.addItems(pathsList)\",\n \"def set_attachments(self):\\n self.response['attachments'] = []\",\n \"def person_list(self, new_persons_list):\\n self._person_list = new_persons_list\\n self.__save_persons_from_memory_to_file()\",\n \"def obj_delete_list(self, request=None, **kwargs):\\n self.get_collection(request).remove()\",\n \"def member_list(self, member_list):\\n\\n self._member_list = member_list\",\n \"def serialize_catalogue_metadata(md_queryset: QuerySet) -> list:\\n # If no queryset but a single metadata is provided, we do not add everything into a\\n is_single_retrieve = not isinstance(md_queryset, Iterable)\\n\\n if is_single_retrieve:\\n ret_val = perform_catalogue_entry_serialization(md_queryset)\\n else:\\n ret_val = [perform_catalogue_entry_serialization(md) for md in md_queryset]\\n\\n return ret_val\",\n \"def build_response(self, data_list):\\n raise NotImplementedError(\\\"build_response method is not implemented.\\\")\",\n \"def fake_generic_listing(object_list, object_type):\\n\\n return {\\n 'data': object_list,\\n 'has_more': False,\\n 'object': 'list',\\n 'total_count': len(object_list),\\n 'url': '/v1/{}s'.format(object_type),\\n }\",\n \"def set_used_samples(self, used_sample_id_list):\\n self._make_index_list(used_sample_id_list)\",\n \"def list(self,request,*args,**kwargs):\\n response=super(ListAPIView,self).list(request,*args,**kwargs)\\n #add applied_filters to the response which is set when filter_queryset method is called\\n response=self.addAppliedFilters(response)\\n #fetch data from the related views\\n return self.fetch_related(request,response,*args,**kwargs)\",\n \"def set_xList(self, *xList):\\n assert len(xList) == self.__nx\\n self.__x = xList\\n self.__xshape = xList[0].shape # Reset the shape of the input.\",\n \"def set_ResponseFormat(self, value):\\n super(ListOrdersInputSet, self)._set_input('ResponseFormat', value)\",\n \"def _set_scrolls(self, listOfScrolls):\\n self._scrolls = listOfScrolls\",\n \"def obj_get_list(self, request=None, **kwargs):\\n filters = {}\\n if hasattr(request, 'GET'):\\n # Grab a mutable copy.\\n filters = request.GET.copy()\\n\\n # Update with the provided kwargs.\\n filters.update(kwargs)\\n if \\\"user\\\" in filters and \\\"media\\\" in filters:\\n try:\\n image_uuid_list = []\\n wordbox_uuid_list = []\\n for item in filters['media'].split(','):\\n # use kwarg \\\"resource\\\" field to be more general rather\\n # than take the 2 element\\n try:\\n if item.split('/')[2] == 'image':\\n image_uuid_list.append(uuid_re.findall(item)[0])\\n elif item.split('/')[2] == 'wordbox':\\n wordbox_uuid_list.append(uuid_re.findall(item)[0])\\n except IndexError:\\n raise BadRequest(\\\"Invalid uuid or resource URI.\\\")\\n userprofile = UserProfile.objects.get(\\n uuid=uuid_from_uri(filters['user']))\\n im = userprofile.image_collection_set.filter(\\n is_active=True, uuid__in=image_uuid_list)\\n wb = userprofile.wordbox_collection_set.\\\\\\n filter(is_active=True, uuid__in=wordbox_uuid_list)\\n base_object_list = sorted(chain(im, wb),\\n key=attrgetter('created_time'))[::-1]\\n return self.apply_authorization_limits(request,\\n base_object_list)\\n except ValueError:\\n raise BadRequest(\\\"Invalid resource lookup data provided \\\"\\n \\\"(mismatched type).\\\")\\n elif \\\"user\\\" in filters and len(filters) == 1:\\n try:\\n userprofile = UserProfile.objects.get(\\n uuid=uuid_from_uri(filters['user']))\\n im = userprofile.image_collection_set.filter(is_active=True)\\n wb = userprofile.wordbox_collection_set.filter(is_active=True)\\n base_object_list = sorted(chain(im, wb),\\n key=attrgetter('created_time'))[::-1]\\n return self.apply_authorization_limits(request,\\n base_object_list)\\n except ValueError:\\n raise BadRequest(\\\"Invalid resource lookup data provided \\\"\\n \\\"(mismatched type).\\\")\\n else:\\n raise BadRequest(\\\"Invalid filtering parameter(s)\\\")\",\n \"def add_access_list(self, access_list):\\n return self.manager.add_access_list(self, access_list)\",\n \"def setObjectID(self, objectid):\\n self._objectid = objectid\",\n \"def data(self, data: List[InlineResponse2002]):\\n\\n self._data = data\",\n \"def object_list_name(self):\\n return self.object_name + '_list'\",\n \"def metadata(self, val: list):\\n self._metadata = []\\n if val is not None:\\n for item in val:\\n if isinstance(item, Metadata):\\n self._metadata.append(item)\",\n \"def set_documents(cls, input_list_text: List[str]) -> None:\\n cls.documents = input_list_text\",\n \"def partial_update_objects(self, objects):\\n requests = []\\n for obj in objects:\\n requests.append({\\\"action\\\": \\\"partialUpdateObject\\\", \\\"objectID\\\": obj[\\\"objectID\\\"], \\\"body\\\": obj})\\n request = {\\\"requests\\\": requests}\\n return self.batch(request)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65758","0.58558273","0.5800644","0.5349972","0.51523393","0.5088856","0.5084719","0.5048292","0.50420725","0.5036184","0.50234246","0.50130266","0.4954567","0.4948551","0.49092585","0.49018076","0.49018076","0.48524174","0.48476678","0.47991368","0.479118","0.47851488","0.47762388","0.47753882","0.47480747","0.47454834","0.47053242","0.46894065","0.4686309","0.4675035","0.46350613","0.46264467","0.46047285","0.459522","0.45914462","0.45754078","0.45707485","0.45504364","0.45418003","0.45387867","0.45278722","0.45137313","0.45040086","0.44894567","0.44888616","0.44879973","0.44791603","0.44714534","0.44620717","0.44574776","0.4448087","0.4448057","0.44178194","0.44085643","0.4375158","0.43733585","0.43687","0.43681976","0.43547553","0.43496835","0.43398476","0.43343818","0.43277794","0.43073168","0.42953122","0.42916313","0.42911017","0.42900932","0.42900932","0.42879122","0.42874864","0.42858115","0.42842034","0.42809665","0.42681327","0.42669323","0.42522943","0.42522898","0.42520747","0.42505008","0.4241397","0.42346823","0.4230975","0.42296582","0.42239127","0.42206293","0.4212278","0.42050305","0.4200148","0.4197029","0.41917056","0.419078","0.41858545","0.41838524","0.41803333","0.41749114","0.41747454","0.4172275","0.41693807","0.41681108"],"string":"[\n \"0.65758\",\n \"0.58558273\",\n \"0.5800644\",\n \"0.5349972\",\n \"0.51523393\",\n \"0.5088856\",\n \"0.5084719\",\n \"0.5048292\",\n \"0.50420725\",\n \"0.5036184\",\n \"0.50234246\",\n \"0.50130266\",\n \"0.4954567\",\n \"0.4948551\",\n \"0.49092585\",\n \"0.49018076\",\n \"0.49018076\",\n \"0.48524174\",\n \"0.48476678\",\n \"0.47991368\",\n \"0.479118\",\n \"0.47851488\",\n \"0.47762388\",\n \"0.47753882\",\n \"0.47480747\",\n \"0.47454834\",\n \"0.47053242\",\n \"0.46894065\",\n \"0.4686309\",\n \"0.4675035\",\n \"0.46350613\",\n \"0.46264467\",\n \"0.46047285\",\n \"0.459522\",\n \"0.45914462\",\n \"0.45754078\",\n \"0.45707485\",\n \"0.45504364\",\n \"0.45418003\",\n \"0.45387867\",\n \"0.45278722\",\n \"0.45137313\",\n \"0.45040086\",\n \"0.44894567\",\n \"0.44888616\",\n \"0.44879973\",\n \"0.44791603\",\n \"0.44714534\",\n \"0.44620717\",\n \"0.44574776\",\n \"0.4448087\",\n \"0.4448057\",\n \"0.44178194\",\n \"0.44085643\",\n \"0.4375158\",\n \"0.43733585\",\n \"0.43687\",\n \"0.43681976\",\n \"0.43547553\",\n \"0.43496835\",\n \"0.43398476\",\n \"0.43343818\",\n \"0.43277794\",\n \"0.43073168\",\n \"0.42953122\",\n \"0.42916313\",\n \"0.42911017\",\n \"0.42900932\",\n \"0.42900932\",\n \"0.42879122\",\n \"0.42874864\",\n \"0.42858115\",\n \"0.42842034\",\n \"0.42809665\",\n \"0.42681327\",\n \"0.42669323\",\n \"0.42522943\",\n \"0.42522898\",\n \"0.42520747\",\n \"0.42505008\",\n \"0.4241397\",\n \"0.42346823\",\n \"0.4230975\",\n \"0.42296582\",\n \"0.42239127\",\n \"0.42206293\",\n \"0.4212278\",\n \"0.42050305\",\n \"0.4200148\",\n \"0.4197029\",\n \"0.41917056\",\n \"0.419078\",\n \"0.41858545\",\n \"0.41838524\",\n \"0.41803333\",\n \"0.41749114\",\n \"0.41747454\",\n \"0.4172275\",\n \"0.41693807\",\n \"0.41681108\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.843938"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":10695,"cells":{"query":{"kind":"string","value":"Sets the exported_object_list of this ExportResponseMetadata."},"document":{"kind":"string","value":"def exported_object_list(self, exported_object_list):\n\n self._exported_object_list = exported_object_list"},"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 __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\n\n self._export_host = None\n self._export_date = None\n self._requested_object_list = None\n self._exported_object_list = None\n self.discriminator = None\n\n if export_host is not None:\n self.export_host = export_host\n if export_date is not None:\n self.export_date = export_date\n if requested_object_list is not None:\n self.requested_object_list = requested_object_list\n if exported_object_list is not None:\n self.exported_object_list = exported_object_list","def requested_object_list(self, requested_object_list):\n\n self._requested_object_list = requested_object_list","def setOutputs(self, output_list):\n self.output_list = output_list","def export_date(self, export_date):\n\n self._export_date = export_date","def set_response_list(self, r_list):\n self.response_list = r_list","def set_objects(self, objects: list):\n self._objects = objects","def nfs_export(self, nfs_export):\n\n self._nfs_export = nfs_export","def list(self, list):\n if list is None:\n raise ValueError(\"Invalid value for `list`, must not be `None`\") # noqa: E501\n\n self._list = list","def __init__(self, export_tuples=None):\n self._exports = export_tuples if export_tuples else []","def on_get_export(self, req, resp):\n resp.body = json.dumps(self.concord_list, ensure_ascii=False, indent=\"\\t\")","def listExport(self, params):\n\n records = self.list(params)\n\n return self.decodeDataToExport(records, params.get('exportColumns'))","def listExport(self, params):\n\n records = self.list(params)\n\n return self.decodeDataToExport(records, params.get('exportColumns'))","def manage_exportObject(\n self,\n id='',\n download=None,\n RESPONSE=None,\n REQUEST=None\n ):\n if not id:\n # can't use getId() here (breaks on \"old\" exported objects)\n id = self.id\n if getattr(id, '__func__', None) is not None:\n id = id()\n ob = self\n else:\n ob = self._getOb(id)\n\n suffix = 'zexp'\n\n if download:\n with BytesIO() as f:\n ob._p_jar.exportFile(ob._p_oid, f)\n result = f.getvalue()\n\n if RESPONSE is not None:\n RESPONSE.setHeader('Content-type', 'application/data')\n RESPONSE.setHeader(\n 'Content-Disposition',\n make_content_disposition('inline', f'{id}.{suffix}')\n )\n return result\n\n f = os.path.join(CONFIG.clienthome, f'{id}.{suffix}')\n with open(f, 'w+b') as fd:\n ob._p_jar.exportFile(ob._p_oid, fd)\n\n if REQUEST is not None:\n return self.manage_main(\n self, REQUEST,\n manage_tabs_message=f'\"{id}\" successfully exported to \"{f}\"',\n title='Object exported'\n )","def set_hidden_list(hidden_list, user=None):\n\tif isinstance(hidden_list, str):\n\t\thidden_list = json.loads(hidden_list)\n\n\t# set as hidden\n\tfor module_name in hidden_list:\n\t\tset_hidden(module_name, user, 1)\n\n\t# set as seen\n\tfor module_name in list(set(get_all_icons()) - set(hidden_list)):\n\t\tset_hidden(module_name, user, 0)\n\n\tif user:\n\t\tclear_desktop_icons_cache()\n\telse:\n\t\tfrappe.clear_cache()","def export_host(self, export_host):\n\n self._export_host = export_host","def output_groups(self, output_groups: List[str]):\n\n self._output_groups = output_groups","def save_asset_metadata_list(self, asset_metadata_list, user_id, import_only=False):\n # Determine course key to use in bulk operation. Use the first asset assuming that\n # all assets will be for the same course.\n asset_key = asset_metadata_list[0].asset_id\n course_key = asset_key.course_key\n\n with self.bulk_operations(course_key):\n original_structure = self._lookup_course(course_key).structure\n index_entry = self._get_index_if_valid(course_key)\n new_structure = self.version_structure(course_key, original_structure, user_id)\n course_assets = new_structure.setdefault('assets', {})\n\n assets_by_type = self._save_assets_by_type(\n course_key, asset_metadata_list, course_assets, user_id, import_only\n )\n\n for asset_type, assets in assets_by_type.items():\n new_structure['assets'][asset_type] = list(assets)\n\n # update index if appropriate and structures\n self.update_structure(course_key, new_structure)\n\n if index_entry is not None:\n # update the index entry if appropriate\n self._update_head(course_key, index_entry, asset_key.branch, new_structure['_id'])","def download(\n self,\n object_list: List[Downloadable],\n save_directory: str = \".\",\n show_progress: bool = False,\n unpack_packages: bool = True,\n delete_unpacked_packages: bool = False,\n ) -> Dict[str, Any]:\n\n self.cache_hosts_wts_tokens(object_list)\n output_dir = Path(save_directory)\n\n completed = {\n entry.object_id: DownloadStatus(filename=entry.file_name)\n for entry in object_list\n }\n\n for entry in object_list:\n # handle bundles first\n if entry.object_type is DRSObjectType.bundle:\n # append the filename to the directory path and\n child_dir = Path(save_directory, entry.file_name)\n # call download with the children object list\n child_status = self.download(\n entry.children,\n child_dir,\n show_progress,\n unpack_packages,\n delete_unpacked_packages,\n )\n # when complete, append the return status\n completed[entry.object_id] = child_status\n continue\n\n if entry.hostname is None:\n logger.critical(\n f\"{entry.hostname} was not resolved, skipping {entry.object_id}.\"\n f\"Skipping {entry.file_name}\"\n )\n completed[entry.object_id].status = \"error (resolving DRS host)\"\n continue\n\n # check to see if we have tokens\n if entry.hostname not in self.known_hosts:\n logger.critical(\n f\"{entry.hostname} is not present in this commons remote user access.\"\n f\"Skipping {entry.file_name}\"\n )\n completed[entry.object_id].status = \"error (resolving DRS host)\"\n continue\n if self.known_hosts[entry.hostname].available is False:\n logger.critical(\n f\"Was unable to get user authorization from {entry.hostname}. Skipping {entry.file_name}\"\n )\n completed[entry.object_id].status = \"error (no auth)\"\n continue\n\n drs_hostname = entry.hostname\n access_token = self.get_fresh_token(drs_hostname)\n\n if access_token is None:\n logger.critical(\n f\"No access token defined for {entry.object_id}. Skipping\"\n )\n completed[entry.object_id].status = \"error (no access token)\"\n continue\n # TODO refine the selection of access_method\n if len(entry.access_methods) == 0:\n logger.critical(\n f\"No access methods defined for {entry.object_id}. Skipping\"\n )\n completed[entry.object_id].status = \"error (no access methods)\"\n continue\n access_method = entry.access_methods[0][\"access_id\"]\n\n download_url = get_download_url_using_drs(\n drs_hostname,\n entry.object_id,\n access_method,\n access_token,\n )\n\n if download_url is None:\n completed[entry.object_id].status = \"error\"\n continue\n\n completed[entry.object_id].start_time = datetime.now(timezone.utc)\n filepath = output_dir.joinpath(entry.file_name)\n res = download_file_from_url(\n url=download_url, filename=filepath, show_progress=show_progress\n )\n\n # check if the file is a package; if so, unpack it in place\n ext = os.path.splitext(entry.file_name)[-1]\n if unpack_packages and ext in PACKAGE_EXTENSIONS:\n try:\n mds_entry = self.metadata.get(entry.object_id)\n except Exception:\n mds_entry = {} # no MDS or object not in MDS\n logger.debug(\n f\"{entry.file_name} is not a package and will not be expanded\"\n )\n\n # if the metadata type is \"package\", then unpack\n if mds_entry.get(\"type\") == \"package\":\n try:\n unpackage_object(filepath)\n except Exception as e:\n logger.critical(\n f\"{entry.file_name} had an issue while being unpackaged: {e}\"\n )\n res = False\n\n if delete_unpacked_packages:\n filepath.unlink()\n if res:\n completed[entry.object_id].status = \"downloaded\"\n logger.debug(\n f\"object {entry.object_id} has been successfully downloaded.\"\n )\n else:\n completed[entry.object_id].status = \"error\"\n logger.debug(f\"object {entry.object_id} has failed to be downloaded.\")\n completed[entry.object_id].end_time = datetime.now(timezone.utc)\n\n return completed","def setListDoc(self, list):\n if list is None: list__o = None\n else: list__o = list._o\n libxml2mod.xmlSetListDoc(list__o, self._o)","def plane_list(self, new_list):\n self.__plane_list = new_list","def export(self, value):\n \n self._export = bool(value)","def SetImageList(self, imageList):\r\n\r\n self._imageList = imageList","def import_(self, exported, update=False):\n for path in exported:\n kv = exported[path]\n fn = self.update if update else self.write\n fn(path, **kv)","def fields_in_list(self, fields_in_list):\n\n self._fields_in_list = fields_in_list","def fields_in_list(self, fields_in_list):\n\n self._fields_in_list = fields_in_list","def exportList(self, list_id):\n params = {'LIST_ID' : list_id,\n 'EXPORT_TYPE' : 'ALL',\n 'EXPORT_FORMAT': 'CSV',\n 'FILE_ENCODING': 'utf-8'}\n xrequest = xml_str(self.buildRequestEtree('ExportList', params))\n xresults = self.request(xrequest)\n xpath = '/Envelope/Body/RESULT/FILE_PATH'\n return xresults.xpath(xpath)[0].text","def resolve_objects(self, object_list: List[Downloadable], show_progress: bool):\n resolve_objects_drs_hostname_from_id(\n object_list,\n self.resolved_compact_drs,\n f\"http://{self.hostname}/mds/aggregate/info\",\n )\n progress_bar = (\n tqdm(desc=f\"Resolving objects\", total=len(object_list))\n if show_progress\n else InvisibleProgress()\n )\n for entry in object_list:\n add_drs_object_info(entry)\n # sugar to allow download objects to self download\n entry._manager = self\n progress_bar.update(1)","def set_blists(self, blists):\n self.blists = blists[:]","def setDownload(self, filename, data, response, bytes):\n #print data\n #serializedData=NSPropertyListSerialization.dataFromPropertyList_format_errorDescription_(data, NSPropertyListXMLFormat_v1_0, None)\n #print serializedData\n defaults=NSUserDefaults.standardUserDefaults()\n downloads=defaults.objectForKey_('downloads')\n downloads = [package for package in downloads if package[0]!=filename]\n downloads.append((filename, data, NSArchiver.archivedDataWithRootObject_(response), bytes))\n defaults.removeObjectForKey_('downloads')\n defaults.setObject_forKey_(downloads, 'downloads')","def view_list(self, view_list):\n\n self._view_list = view_list","def save_to_file(cls, list_objs):\n the_list = []\n if list_objs is not None:\n for stuff in list_objs:\n new_stuff = stuff.to_dictionary()\n the_list.append(new_stuff)\n the_list = Base.to_json_string(the_list)\n with open(\"{}.json\".format(cls.__name__), mode='w') as f:\n f.write(str(the_list))","def dnc_lists(self, dnc_lists):\n \n self._dnc_lists = dnc_lists","def save_to_file_csv(cls, list_objs):\n l = []\n if list_objs is not None:\n for item in list_objs:\n l.append(item.to_dictionary())\n with open(\"%s.csv\" % cls.__name__, mode='w') as f:\n f.write(Base.to_json_string(l))","def set_event_list(self):\n self.eventList = self.get_event_list()","def _set_data_to_export(self, dict_results):\n\n self._data_to_export = dict_results","def SetLists(self,IndList,ObjList):\n \n if not len(IndList)==len(ObjList):\n raise ValueError(\"IndList and ObjList must be of the same length\")\n \n if not prod([type(x)==tuple for x in IndList]):\n IndFormatError=1\n elif not prod([len(x)==3 for x in IndList]):\n IndFormatError=1\n \n IndFormatError=0\n \n if IndFormatError:\n raise ValueError(\"IndList must be list of 3-tuples\")\n \n if not prod([shape(x) == self.__shape for x in ObjList])==1:\n print([shape(x) for x in ObjList])\n raise ValueError(\"ObjList must contain arrays of the same shape as the BZO (shape %s)\"%str(self.__shape))\n \n \n self.__IndList=IndList\n self.__ObjList=ObjList\n \n self.__Set_NumList() \n self.__SortLists()","def portal_outboxes(self, portal_outboxes):\n\n self._portal_outboxes = portal_outboxes","def update_list(self):\n Asset.update_list(self, uri_keys=('ems_sys', 'list'))","def resources(self, value):\n self._resource_objects = value","def get_exports(self, obj):\n formats = [format for format in obj.formats.all()]\n serializer = ExportFormatSerializer(formats, many=True, context={'request': self.context['request']})\n return serializer.data","def set_offline_services(self, hOfflineServicesList):\n\t\tcall_sdk_function('PrlVmCfg_SetOfflineServices', self.handle, conv_handle_arg(hOfflineServicesList))","def nfs_exports_some(self, nfs_exports_some):\n\n self._nfs_exports_some = nfs_exports_some","def set_response_list(cls,response_list):\n if not isinstance(response_list,list):\n raise ValueError('response_list arg must be a list')\n\n # Run through the responses\n for response in response_list:\n if not isinstance(response,(list,dict)):\n raise ValueError('response_list entry must be a list or dict')\n\n if isinstance(response,list):\n if len(response) != 3:\n raise ValueError('response_list entry must have 3 fields')\n\n # Grab each fields\n url = response[0]\n method = 'POST'\n status = response[1]\n type = 'xml'\n message = response[2]\n\n else:\n # response is a dict\n url = response.get('base_url')\n method = response.get('method','POST')\n status = response.get('status')\n type = response.get('type','xml')\n message = response.get('message')\n\n response_list = BonitaMockedServerImpl.get_response_list()\n response_list.add_or_augment_response_list(url,method,status,type,message)","def write_cache_file_list(self, file_list=None):\n if file_list:\n self.add_filelist_to_cache(file_list)\n cache_list = []\n for finfo in self.cache_file_list_dict.values():\n cache_list.append(finfo.output_cache_tuple())\n return self.write_pickle_object_to_file(tuple(cache_list))","def activities_list(self, new_activities_list):\n self._activities_list = new_activities_list\n self.__save_activities_from_memory_to_file()","def _set_last_exported_date(self, cr, uid, external_session, date, context=None):\n return True","def SetExportAttrs(self, param, attrs):\n parent, unused_name = self.FindExport(param)\n if not hasattr(parent.obj, 'SetAttributes'):\n return False\n parent.obj.SetAttributes(attrs)\n return True","def update_list(self):\n\t\tAsset.update_list(self, uri_keys=('airport', 'list'), uri_args=self._ems_id, colsort=False)","def extend(self, object_list):\n self.data['object'].extend(object_list)\n self.data['id'].extend(range(self.start_id, self.start_id+len(object_list)))\n for col in self.cols:\n if col != 'object' and col != 'id':\n self.data[col].extend([None]*(len(self.data[\"id\"] ) - len(self.data[col])))\n self.start_id += len(object_list)\n return self","def response_values(self, response_values):\n\n self._response_values = response_values","def ole_objects(self, ole_objects):\n\n self.container['ole_objects'] = ole_objects","def set_all(self, value):\n self.__items = value","def _set_listonly(self, value):\n if not value and self.__listonly:\n self.__listonly = False\n self.clear_preprocessed()","def setSublist(self, sublist):\n if self.cursor:\n self.cursor.sublist = sublist","def serialize(self, writer: serialization.BinaryWriter) -> None:\n writer.write_serializable_list(self.headers)","def add_metadata(self, metdatadata_list):\n self._metadata.append((metdatadata_list, ))","def add_metadata(self, metdatadata_list):\n self._metadata.append((metdatadata_list, ))","def selected_field_list(self, selected_field_list):\n\n self._selected_field_list = selected_field_list","def set_race_events_list(self, race_events_list):\n self.race_events_list = race_events_list","def security_list_ids(self, security_list_ids):\n self._security_list_ids = security_list_ids","def export(self):\n \n return self._export","def export(self, export_args: Dict) -> None:\n\n dataset2exporter = {\n 'era5': ERA5Exporter,\n 'vhi': VHIExporter,\n 'era5POS': ERA5ExporterPOS,\n }\n\n for dataset, variables in export_args.items():\n\n # check the format is as we expected\n assert dataset in dataset2exporter, \\\n f'{dataset} is not supported! Supported datasets are {dataset2exporter.keys()}'\n\n assert type(variables) is list, \\\n f'Expected {dataset} values to be a list. Got {type(variables)} instead'\n\n exporter = dataset2exporter[dataset](self.data)\n\n for variable in variables:\n _ = exporter.export(**variable) # type: ignore","def setListDoc(self, doc):\n if doc is None: doc__o = None\n else: doc__o = doc._o\n libxml2mod.xmlSetListDoc(self._o, doc__o)","def save_to_file(cls, list_objs):\n l = []\n if list_objs is not None:\n for item in list_objs:\n l.append(item.to_dictionary())\n with open(\"%s.json\" % cls.__name__, mode='w') as f:\n f.write(Base.to_json_string(l))","def nfs_export_num(self, nfs_export_num):\n\n self._nfs_export_num = nfs_export_num","def set_label_list(self, label_lists):\n\n if isinstance(label_lists, annotations.LabelList):\n label_lists = [label_lists]\n\n for label_list in label_lists:\n if label_list.idx is None:\n label_list.idx = 'default'\n\n label_list.utterance = self\n self.label_lists[label_list.idx] = label_list","def _list_object(hostname, auth, object_id: str) -> bool:\n try:\n auth.get_access_token()\n except Gen3AuthError:\n logger.critical(f\"Unable to authenticate your credentials with {hostname}\")\n return False\n except requests.exceptions.RequestException as ex:\n logger.critical(\n f\"Unable to authenticate your credentials with {hostname}: {ex}\"\n )\n return False\n\n object_list = [Downloadable(object_id=object_id)]\n DownloadManager(\n hostname=hostname, auth=auth, download_list=object_list, show_progress=False\n )\n\n for x in object_list:\n print(x.pprint())\n\n return True","def fdsid_list(self, fdsid_list):\n\n self._fdsid_list = fdsid_list","def export_to(self, exporter=None):\n if not exporter:\n raise aspecd.exceptions.MissingExporterError(\"No exporter provided\")\n exporter.export_from(self)","def save_to_file(cls, list_objs):\n filename = cls.__name__ + \".json\"\n with open(filename, \"w\") as f:\n if list_objs is None:\n f.write(\"[]\")\n else:\n d = [x.to_dictionary() for x in list_objs]\n f.write(Base.to_json_string(d))","def _trackItemsToExport(self, exportItems):\n trackItems = []\n if exportItems[0].trackItem():\n trackItems = [ item.trackItem() for item in exportItems if isinstance(item.trackItem(), hiero.core.TrackItem) and not item.ignore() ]\n else:\n sequences = [ item.sequence() for item in exportItems ]\n for sequence in sequences:\n for track in self._tracksToExport(sequence):\n trackItems.extend( [ item for item in track if (item.isMediaPresent() or not self.skipOffline()) ] )\n\n return trackItems","def available_field_list(self, available_field_list):\n\n self._available_field_list = available_field_list","def save_to_file(cls, list_objs):\n filename = cls.__name__ + \".json\"\n new_list = []\n with open(filename, \"w\") as fp:\n if list_objs is None:\n fp.write(\"[]\")\n else:\n for objs in list_objs:\n new_list.append(cls.to_dictionary(objs))\n fp.write(cls.to_json_string(new_list))","def set_attachments(self):\n self.response['attachments'] = []","def AssignImageList(self, imageList):\r\n\r\n self.SetImageList(imageList)","def save_to_file(cls, list_objs):\n li = []\n with open(cls.__name__ + \".json\", mode=\"w\") as fl:\n if list_objs is None:\n fl.write(Base.to_json_string(list_objs))\n return\n for i in list_objs:\n li.append(i.to_dictionary())\n fl.write(Base.to_json_string(li))","def save_to_file_csv(cls, list_objs):\n list_dictionaries = []\n if list_objs is None or list_objs == []:\n string_dictionary = \"[]\"\n else:\n for _obj_dict in list_objs:\n list_dictionaries.append(_obj_dict.to_dictionary())\n string_dictionary = Base.to_json_string(list_dictionaries)\n with open(cls.__name__ + \".csv\", \"w\") as _file:\n _file.write(string_dictionary)\n _file.close()","def expose_headers(self, expose_headers):\n\n self._expose_headers = expose_headers","def exposed_services(self, exposed_services):\n\n self._exposed_services = exposed_services","def set_many(self, value: bool) -> None:\n self.__sql_many_state = value","def set_PageToken(self, value):\n super(ListOrdersInputSet, self)._set_input('PageToken', value)","def setDetectLists(self, value):\n return self._set(detectLists=value)","def set_target_stocks_list(self, list_of_stocks):\n self.target_stocks = list_of_stocks","def origin_list(self, origin_list: List[Origin]):\n\n self._origin_list = origin_list","def download_queryset(self, queryset, export_format):\n\n dataset = LocationResource().export(queryset=queryset)\n filedata = dataset.export(export_format)\n filename = f\"InvenTree_Locations.{export_format}\"\n\n return DownloadFile(filedata, filename)","def save_to_file(cls, list_objs):\n my_list = []\n if list_objs or list_objs is not None:\n my_list = [obj.to_dictionary() for obj in list_objs]\n with open(cls.__name__ + '.json', 'w+') as f:\n f.write(cls.to_json_string(my_list))","def save_to_file(cls, list_objs):\n if list_objs is not None:\n list_objs = [obj.to_dictionary() for obj in list_objs]\n with open(\"{}.json\".format(cls.__name__), \"w\", encoding=\"utf-8\") as f:\n f.write(cls.to_json_string(list_objs))","def list_return_field_id(self, list_return_field_id):\n\n self._list_return_field_id = list_return_field_id","def data(self, data: List[InlineResponse2002]):\n\n self._data = data","def AssignImageList(self, imageList):\r\n\r\n self.SetImageList(imageList)\r\n self._ownsImageListNormal = True","def create_object_list(manifest) -> List[\"Downloadable\"]:\n results = []\n for entry in manifest:\n results.append(\n Downloadable(\n object_id=entry.object_id,\n hostname=remove_trailing_whitespace_and_slashes_in_url(\n entry.commons_url\n ),\n )\n )\n return results","def member_list(self, member_list):\n\n self._member_list = member_list","def nfs_exports_every(self, nfs_exports_every):\n\n self._nfs_exports_every = nfs_exports_every","def downloads(self, downloads: str):\n\n self._downloads = downloads","def setPathsList(self, pathsList):\n self.clear()\n self.addItems(pathsList)","def save_to_file(cls, list_objs):\n file = cls.__name__ + '.json'\n with open(file, 'w') as json_file:\n if list_objs is None:\n json_file.write('[]')\n else:\n dic = [obj.to_dictionary() for obj in list_objs]\n json_file.write(Base.to_json_string(dic))","def metadata(self, val: list):\n self._metadata = []\n if val is not None:\n for item in val:\n if isinstance(item, Metadata):\n self._metadata.append(item)","def export_part_list(self, filetype='xlsx'):\n if filetype == 'csv':\n enum = 48649\n else:\n enum = 48642\n path = self.export_dir.joinpath(self.partcode).joinpath('part_list.xlsx')\n self.doc.Sheets(1).PartsLists(1).Export(str(path), enum)","def save_to_file(cls, list_objs):\n\n with open(cls.__name__ + \".json\", 'w') as f:\n l = []\n if list_objs is None or len(list_objs) <= 0:\n f.write(Base.to_json_string(l))\n\n else:\n for obj in list_objs:\n l.append(cls.to_dictionary(obj))\n f.write(Base.to_json_string(l))","def set_animated(self, value):\n for artist in self.artists:\n artist.set_animated(value)"],"string":"[\n \"def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\\n\\n self._export_host = None\\n self._export_date = None\\n self._requested_object_list = None\\n self._exported_object_list = None\\n self.discriminator = None\\n\\n if export_host is not None:\\n self.export_host = export_host\\n if export_date is not None:\\n self.export_date = export_date\\n if requested_object_list is not None:\\n self.requested_object_list = requested_object_list\\n if exported_object_list is not None:\\n self.exported_object_list = exported_object_list\",\n \"def requested_object_list(self, requested_object_list):\\n\\n self._requested_object_list = requested_object_list\",\n \"def setOutputs(self, output_list):\\n self.output_list = output_list\",\n \"def export_date(self, export_date):\\n\\n self._export_date = export_date\",\n \"def set_response_list(self, r_list):\\n self.response_list = r_list\",\n \"def set_objects(self, objects: list):\\n self._objects = objects\",\n \"def nfs_export(self, nfs_export):\\n\\n self._nfs_export = nfs_export\",\n \"def list(self, list):\\n if list is None:\\n raise ValueError(\\\"Invalid value for `list`, must not be `None`\\\") # noqa: E501\\n\\n self._list = list\",\n \"def __init__(self, export_tuples=None):\\n self._exports = export_tuples if export_tuples else []\",\n \"def on_get_export(self, req, resp):\\n resp.body = json.dumps(self.concord_list, ensure_ascii=False, indent=\\\"\\\\t\\\")\",\n \"def listExport(self, params):\\n\\n records = self.list(params)\\n\\n return self.decodeDataToExport(records, params.get('exportColumns'))\",\n \"def listExport(self, params):\\n\\n records = self.list(params)\\n\\n return self.decodeDataToExport(records, params.get('exportColumns'))\",\n \"def manage_exportObject(\\n self,\\n id='',\\n download=None,\\n RESPONSE=None,\\n REQUEST=None\\n ):\\n if not id:\\n # can't use getId() here (breaks on \\\"old\\\" exported objects)\\n id = self.id\\n if getattr(id, '__func__', None) is not None:\\n id = id()\\n ob = self\\n else:\\n ob = self._getOb(id)\\n\\n suffix = 'zexp'\\n\\n if download:\\n with BytesIO() as f:\\n ob._p_jar.exportFile(ob._p_oid, f)\\n result = f.getvalue()\\n\\n if RESPONSE is not None:\\n RESPONSE.setHeader('Content-type', 'application/data')\\n RESPONSE.setHeader(\\n 'Content-Disposition',\\n make_content_disposition('inline', f'{id}.{suffix}')\\n )\\n return result\\n\\n f = os.path.join(CONFIG.clienthome, f'{id}.{suffix}')\\n with open(f, 'w+b') as fd:\\n ob._p_jar.exportFile(ob._p_oid, fd)\\n\\n if REQUEST is not None:\\n return self.manage_main(\\n self, REQUEST,\\n manage_tabs_message=f'\\\"{id}\\\" successfully exported to \\\"{f}\\\"',\\n title='Object exported'\\n )\",\n \"def set_hidden_list(hidden_list, user=None):\\n\\tif isinstance(hidden_list, str):\\n\\t\\thidden_list = json.loads(hidden_list)\\n\\n\\t# set as hidden\\n\\tfor module_name in hidden_list:\\n\\t\\tset_hidden(module_name, user, 1)\\n\\n\\t# set as seen\\n\\tfor module_name in list(set(get_all_icons()) - set(hidden_list)):\\n\\t\\tset_hidden(module_name, user, 0)\\n\\n\\tif user:\\n\\t\\tclear_desktop_icons_cache()\\n\\telse:\\n\\t\\tfrappe.clear_cache()\",\n \"def export_host(self, export_host):\\n\\n self._export_host = export_host\",\n \"def output_groups(self, output_groups: List[str]):\\n\\n self._output_groups = output_groups\",\n \"def save_asset_metadata_list(self, asset_metadata_list, user_id, import_only=False):\\n # Determine course key to use in bulk operation. Use the first asset assuming that\\n # all assets will be for the same course.\\n asset_key = asset_metadata_list[0].asset_id\\n course_key = asset_key.course_key\\n\\n with self.bulk_operations(course_key):\\n original_structure = self._lookup_course(course_key).structure\\n index_entry = self._get_index_if_valid(course_key)\\n new_structure = self.version_structure(course_key, original_structure, user_id)\\n course_assets = new_structure.setdefault('assets', {})\\n\\n assets_by_type = self._save_assets_by_type(\\n course_key, asset_metadata_list, course_assets, user_id, import_only\\n )\\n\\n for asset_type, assets in assets_by_type.items():\\n new_structure['assets'][asset_type] = list(assets)\\n\\n # update index if appropriate and structures\\n self.update_structure(course_key, new_structure)\\n\\n if index_entry is not None:\\n # update the index entry if appropriate\\n self._update_head(course_key, index_entry, asset_key.branch, new_structure['_id'])\",\n \"def download(\\n self,\\n object_list: List[Downloadable],\\n save_directory: str = \\\".\\\",\\n show_progress: bool = False,\\n unpack_packages: bool = True,\\n delete_unpacked_packages: bool = False,\\n ) -> Dict[str, Any]:\\n\\n self.cache_hosts_wts_tokens(object_list)\\n output_dir = Path(save_directory)\\n\\n completed = {\\n entry.object_id: DownloadStatus(filename=entry.file_name)\\n for entry in object_list\\n }\\n\\n for entry in object_list:\\n # handle bundles first\\n if entry.object_type is DRSObjectType.bundle:\\n # append the filename to the directory path and\\n child_dir = Path(save_directory, entry.file_name)\\n # call download with the children object list\\n child_status = self.download(\\n entry.children,\\n child_dir,\\n show_progress,\\n unpack_packages,\\n delete_unpacked_packages,\\n )\\n # when complete, append the return status\\n completed[entry.object_id] = child_status\\n continue\\n\\n if entry.hostname is None:\\n logger.critical(\\n f\\\"{entry.hostname} was not resolved, skipping {entry.object_id}.\\\"\\n f\\\"Skipping {entry.file_name}\\\"\\n )\\n completed[entry.object_id].status = \\\"error (resolving DRS host)\\\"\\n continue\\n\\n # check to see if we have tokens\\n if entry.hostname not in self.known_hosts:\\n logger.critical(\\n f\\\"{entry.hostname} is not present in this commons remote user access.\\\"\\n f\\\"Skipping {entry.file_name}\\\"\\n )\\n completed[entry.object_id].status = \\\"error (resolving DRS host)\\\"\\n continue\\n if self.known_hosts[entry.hostname].available is False:\\n logger.critical(\\n f\\\"Was unable to get user authorization from {entry.hostname}. Skipping {entry.file_name}\\\"\\n )\\n completed[entry.object_id].status = \\\"error (no auth)\\\"\\n continue\\n\\n drs_hostname = entry.hostname\\n access_token = self.get_fresh_token(drs_hostname)\\n\\n if access_token is None:\\n logger.critical(\\n f\\\"No access token defined for {entry.object_id}. Skipping\\\"\\n )\\n completed[entry.object_id].status = \\\"error (no access token)\\\"\\n continue\\n # TODO refine the selection of access_method\\n if len(entry.access_methods) == 0:\\n logger.critical(\\n f\\\"No access methods defined for {entry.object_id}. Skipping\\\"\\n )\\n completed[entry.object_id].status = \\\"error (no access methods)\\\"\\n continue\\n access_method = entry.access_methods[0][\\\"access_id\\\"]\\n\\n download_url = get_download_url_using_drs(\\n drs_hostname,\\n entry.object_id,\\n access_method,\\n access_token,\\n )\\n\\n if download_url is None:\\n completed[entry.object_id].status = \\\"error\\\"\\n continue\\n\\n completed[entry.object_id].start_time = datetime.now(timezone.utc)\\n filepath = output_dir.joinpath(entry.file_name)\\n res = download_file_from_url(\\n url=download_url, filename=filepath, show_progress=show_progress\\n )\\n\\n # check if the file is a package; if so, unpack it in place\\n ext = os.path.splitext(entry.file_name)[-1]\\n if unpack_packages and ext in PACKAGE_EXTENSIONS:\\n try:\\n mds_entry = self.metadata.get(entry.object_id)\\n except Exception:\\n mds_entry = {} # no MDS or object not in MDS\\n logger.debug(\\n f\\\"{entry.file_name} is not a package and will not be expanded\\\"\\n )\\n\\n # if the metadata type is \\\"package\\\", then unpack\\n if mds_entry.get(\\\"type\\\") == \\\"package\\\":\\n try:\\n unpackage_object(filepath)\\n except Exception as e:\\n logger.critical(\\n f\\\"{entry.file_name} had an issue while being unpackaged: {e}\\\"\\n )\\n res = False\\n\\n if delete_unpacked_packages:\\n filepath.unlink()\\n if res:\\n completed[entry.object_id].status = \\\"downloaded\\\"\\n logger.debug(\\n f\\\"object {entry.object_id} has been successfully downloaded.\\\"\\n )\\n else:\\n completed[entry.object_id].status = \\\"error\\\"\\n logger.debug(f\\\"object {entry.object_id} has failed to be downloaded.\\\")\\n completed[entry.object_id].end_time = datetime.now(timezone.utc)\\n\\n return completed\",\n \"def setListDoc(self, list):\\n if list is None: list__o = None\\n else: list__o = list._o\\n libxml2mod.xmlSetListDoc(list__o, self._o)\",\n \"def plane_list(self, new_list):\\n self.__plane_list = new_list\",\n \"def export(self, value):\\n \\n self._export = bool(value)\",\n \"def SetImageList(self, imageList):\\r\\n\\r\\n self._imageList = imageList\",\n \"def import_(self, exported, update=False):\\n for path in exported:\\n kv = exported[path]\\n fn = self.update if update else self.write\\n fn(path, **kv)\",\n \"def fields_in_list(self, fields_in_list):\\n\\n self._fields_in_list = fields_in_list\",\n \"def fields_in_list(self, fields_in_list):\\n\\n self._fields_in_list = fields_in_list\",\n \"def exportList(self, list_id):\\n params = {'LIST_ID' : list_id,\\n 'EXPORT_TYPE' : 'ALL',\\n 'EXPORT_FORMAT': 'CSV',\\n 'FILE_ENCODING': 'utf-8'}\\n xrequest = xml_str(self.buildRequestEtree('ExportList', params))\\n xresults = self.request(xrequest)\\n xpath = '/Envelope/Body/RESULT/FILE_PATH'\\n return xresults.xpath(xpath)[0].text\",\n \"def resolve_objects(self, object_list: List[Downloadable], show_progress: bool):\\n resolve_objects_drs_hostname_from_id(\\n object_list,\\n self.resolved_compact_drs,\\n f\\\"http://{self.hostname}/mds/aggregate/info\\\",\\n )\\n progress_bar = (\\n tqdm(desc=f\\\"Resolving objects\\\", total=len(object_list))\\n if show_progress\\n else InvisibleProgress()\\n )\\n for entry in object_list:\\n add_drs_object_info(entry)\\n # sugar to allow download objects to self download\\n entry._manager = self\\n progress_bar.update(1)\",\n \"def set_blists(self, blists):\\n self.blists = blists[:]\",\n \"def setDownload(self, filename, data, response, bytes):\\n #print data\\n #serializedData=NSPropertyListSerialization.dataFromPropertyList_format_errorDescription_(data, NSPropertyListXMLFormat_v1_0, None)\\n #print serializedData\\n defaults=NSUserDefaults.standardUserDefaults()\\n downloads=defaults.objectForKey_('downloads')\\n downloads = [package for package in downloads if package[0]!=filename]\\n downloads.append((filename, data, NSArchiver.archivedDataWithRootObject_(response), bytes))\\n defaults.removeObjectForKey_('downloads')\\n defaults.setObject_forKey_(downloads, 'downloads')\",\n \"def view_list(self, view_list):\\n\\n self._view_list = view_list\",\n \"def save_to_file(cls, list_objs):\\n the_list = []\\n if list_objs is not None:\\n for stuff in list_objs:\\n new_stuff = stuff.to_dictionary()\\n the_list.append(new_stuff)\\n the_list = Base.to_json_string(the_list)\\n with open(\\\"{}.json\\\".format(cls.__name__), mode='w') as f:\\n f.write(str(the_list))\",\n \"def dnc_lists(self, dnc_lists):\\n \\n self._dnc_lists = dnc_lists\",\n \"def save_to_file_csv(cls, list_objs):\\n l = []\\n if list_objs is not None:\\n for item in list_objs:\\n l.append(item.to_dictionary())\\n with open(\\\"%s.csv\\\" % cls.__name__, mode='w') as f:\\n f.write(Base.to_json_string(l))\",\n \"def set_event_list(self):\\n self.eventList = self.get_event_list()\",\n \"def _set_data_to_export(self, dict_results):\\n\\n self._data_to_export = dict_results\",\n \"def SetLists(self,IndList,ObjList):\\n \\n if not len(IndList)==len(ObjList):\\n raise ValueError(\\\"IndList and ObjList must be of the same length\\\")\\n \\n if not prod([type(x)==tuple for x in IndList]):\\n IndFormatError=1\\n elif not prod([len(x)==3 for x in IndList]):\\n IndFormatError=1\\n \\n IndFormatError=0\\n \\n if IndFormatError:\\n raise ValueError(\\\"IndList must be list of 3-tuples\\\")\\n \\n if not prod([shape(x) == self.__shape for x in ObjList])==1:\\n print([shape(x) for x in ObjList])\\n raise ValueError(\\\"ObjList must contain arrays of the same shape as the BZO (shape %s)\\\"%str(self.__shape))\\n \\n \\n self.__IndList=IndList\\n self.__ObjList=ObjList\\n \\n self.__Set_NumList() \\n self.__SortLists()\",\n \"def portal_outboxes(self, portal_outboxes):\\n\\n self._portal_outboxes = portal_outboxes\",\n \"def update_list(self):\\n Asset.update_list(self, uri_keys=('ems_sys', 'list'))\",\n \"def resources(self, value):\\n self._resource_objects = value\",\n \"def get_exports(self, obj):\\n formats = [format for format in obj.formats.all()]\\n serializer = ExportFormatSerializer(formats, many=True, context={'request': self.context['request']})\\n return serializer.data\",\n \"def set_offline_services(self, hOfflineServicesList):\\n\\t\\tcall_sdk_function('PrlVmCfg_SetOfflineServices', self.handle, conv_handle_arg(hOfflineServicesList))\",\n \"def nfs_exports_some(self, nfs_exports_some):\\n\\n self._nfs_exports_some = nfs_exports_some\",\n \"def set_response_list(cls,response_list):\\n if not isinstance(response_list,list):\\n raise ValueError('response_list arg must be a list')\\n\\n # Run through the responses\\n for response in response_list:\\n if not isinstance(response,(list,dict)):\\n raise ValueError('response_list entry must be a list or dict')\\n\\n if isinstance(response,list):\\n if len(response) != 3:\\n raise ValueError('response_list entry must have 3 fields')\\n\\n # Grab each fields\\n url = response[0]\\n method = 'POST'\\n status = response[1]\\n type = 'xml'\\n message = response[2]\\n\\n else:\\n # response is a dict\\n url = response.get('base_url')\\n method = response.get('method','POST')\\n status = response.get('status')\\n type = response.get('type','xml')\\n message = response.get('message')\\n\\n response_list = BonitaMockedServerImpl.get_response_list()\\n response_list.add_or_augment_response_list(url,method,status,type,message)\",\n \"def write_cache_file_list(self, file_list=None):\\n if file_list:\\n self.add_filelist_to_cache(file_list)\\n cache_list = []\\n for finfo in self.cache_file_list_dict.values():\\n cache_list.append(finfo.output_cache_tuple())\\n return self.write_pickle_object_to_file(tuple(cache_list))\",\n \"def activities_list(self, new_activities_list):\\n self._activities_list = new_activities_list\\n self.__save_activities_from_memory_to_file()\",\n \"def _set_last_exported_date(self, cr, uid, external_session, date, context=None):\\n return True\",\n \"def SetExportAttrs(self, param, attrs):\\n parent, unused_name = self.FindExport(param)\\n if not hasattr(parent.obj, 'SetAttributes'):\\n return False\\n parent.obj.SetAttributes(attrs)\\n return True\",\n \"def update_list(self):\\n\\t\\tAsset.update_list(self, uri_keys=('airport', 'list'), uri_args=self._ems_id, colsort=False)\",\n \"def extend(self, object_list):\\n self.data['object'].extend(object_list)\\n self.data['id'].extend(range(self.start_id, self.start_id+len(object_list)))\\n for col in self.cols:\\n if col != 'object' and col != 'id':\\n self.data[col].extend([None]*(len(self.data[\\\"id\\\"] ) - len(self.data[col])))\\n self.start_id += len(object_list)\\n return self\",\n \"def response_values(self, response_values):\\n\\n self._response_values = response_values\",\n \"def ole_objects(self, ole_objects):\\n\\n self.container['ole_objects'] = ole_objects\",\n \"def set_all(self, value):\\n self.__items = value\",\n \"def _set_listonly(self, value):\\n if not value and self.__listonly:\\n self.__listonly = False\\n self.clear_preprocessed()\",\n \"def setSublist(self, sublist):\\n if self.cursor:\\n self.cursor.sublist = sublist\",\n \"def serialize(self, writer: serialization.BinaryWriter) -> None:\\n writer.write_serializable_list(self.headers)\",\n \"def add_metadata(self, metdatadata_list):\\n self._metadata.append((metdatadata_list, ))\",\n \"def add_metadata(self, metdatadata_list):\\n self._metadata.append((metdatadata_list, ))\",\n \"def selected_field_list(self, selected_field_list):\\n\\n self._selected_field_list = selected_field_list\",\n \"def set_race_events_list(self, race_events_list):\\n self.race_events_list = race_events_list\",\n \"def security_list_ids(self, security_list_ids):\\n self._security_list_ids = security_list_ids\",\n \"def export(self):\\n \\n return self._export\",\n \"def export(self, export_args: Dict) -> None:\\n\\n dataset2exporter = {\\n 'era5': ERA5Exporter,\\n 'vhi': VHIExporter,\\n 'era5POS': ERA5ExporterPOS,\\n }\\n\\n for dataset, variables in export_args.items():\\n\\n # check the format is as we expected\\n assert dataset in dataset2exporter, \\\\\\n f'{dataset} is not supported! Supported datasets are {dataset2exporter.keys()}'\\n\\n assert type(variables) is list, \\\\\\n f'Expected {dataset} values to be a list. Got {type(variables)} instead'\\n\\n exporter = dataset2exporter[dataset](self.data)\\n\\n for variable in variables:\\n _ = exporter.export(**variable) # type: ignore\",\n \"def setListDoc(self, doc):\\n if doc is None: doc__o = None\\n else: doc__o = doc._o\\n libxml2mod.xmlSetListDoc(self._o, doc__o)\",\n \"def save_to_file(cls, list_objs):\\n l = []\\n if list_objs is not None:\\n for item in list_objs:\\n l.append(item.to_dictionary())\\n with open(\\\"%s.json\\\" % cls.__name__, mode='w') as f:\\n f.write(Base.to_json_string(l))\",\n \"def nfs_export_num(self, nfs_export_num):\\n\\n self._nfs_export_num = nfs_export_num\",\n \"def set_label_list(self, label_lists):\\n\\n if isinstance(label_lists, annotations.LabelList):\\n label_lists = [label_lists]\\n\\n for label_list in label_lists:\\n if label_list.idx is None:\\n label_list.idx = 'default'\\n\\n label_list.utterance = self\\n self.label_lists[label_list.idx] = label_list\",\n \"def _list_object(hostname, auth, object_id: str) -> bool:\\n try:\\n auth.get_access_token()\\n except Gen3AuthError:\\n logger.critical(f\\\"Unable to authenticate your credentials with {hostname}\\\")\\n return False\\n except requests.exceptions.RequestException as ex:\\n logger.critical(\\n f\\\"Unable to authenticate your credentials with {hostname}: {ex}\\\"\\n )\\n return False\\n\\n object_list = [Downloadable(object_id=object_id)]\\n DownloadManager(\\n hostname=hostname, auth=auth, download_list=object_list, show_progress=False\\n )\\n\\n for x in object_list:\\n print(x.pprint())\\n\\n return True\",\n \"def fdsid_list(self, fdsid_list):\\n\\n self._fdsid_list = fdsid_list\",\n \"def export_to(self, exporter=None):\\n if not exporter:\\n raise aspecd.exceptions.MissingExporterError(\\\"No exporter provided\\\")\\n exporter.export_from(self)\",\n \"def save_to_file(cls, list_objs):\\n filename = cls.__name__ + \\\".json\\\"\\n with open(filename, \\\"w\\\") as f:\\n if list_objs is None:\\n f.write(\\\"[]\\\")\\n else:\\n d = [x.to_dictionary() for x in list_objs]\\n f.write(Base.to_json_string(d))\",\n \"def _trackItemsToExport(self, exportItems):\\n trackItems = []\\n if exportItems[0].trackItem():\\n trackItems = [ item.trackItem() for item in exportItems if isinstance(item.trackItem(), hiero.core.TrackItem) and not item.ignore() ]\\n else:\\n sequences = [ item.sequence() for item in exportItems ]\\n for sequence in sequences:\\n for track in self._tracksToExport(sequence):\\n trackItems.extend( [ item for item in track if (item.isMediaPresent() or not self.skipOffline()) ] )\\n\\n return trackItems\",\n \"def available_field_list(self, available_field_list):\\n\\n self._available_field_list = available_field_list\",\n \"def save_to_file(cls, list_objs):\\n filename = cls.__name__ + \\\".json\\\"\\n new_list = []\\n with open(filename, \\\"w\\\") as fp:\\n if list_objs is None:\\n fp.write(\\\"[]\\\")\\n else:\\n for objs in list_objs:\\n new_list.append(cls.to_dictionary(objs))\\n fp.write(cls.to_json_string(new_list))\",\n \"def set_attachments(self):\\n self.response['attachments'] = []\",\n \"def AssignImageList(self, imageList):\\r\\n\\r\\n self.SetImageList(imageList)\",\n \"def save_to_file(cls, list_objs):\\n li = []\\n with open(cls.__name__ + \\\".json\\\", mode=\\\"w\\\") as fl:\\n if list_objs is None:\\n fl.write(Base.to_json_string(list_objs))\\n return\\n for i in list_objs:\\n li.append(i.to_dictionary())\\n fl.write(Base.to_json_string(li))\",\n \"def save_to_file_csv(cls, list_objs):\\n list_dictionaries = []\\n if list_objs is None or list_objs == []:\\n string_dictionary = \\\"[]\\\"\\n else:\\n for _obj_dict in list_objs:\\n list_dictionaries.append(_obj_dict.to_dictionary())\\n string_dictionary = Base.to_json_string(list_dictionaries)\\n with open(cls.__name__ + \\\".csv\\\", \\\"w\\\") as _file:\\n _file.write(string_dictionary)\\n _file.close()\",\n \"def expose_headers(self, expose_headers):\\n\\n self._expose_headers = expose_headers\",\n \"def exposed_services(self, exposed_services):\\n\\n self._exposed_services = exposed_services\",\n \"def set_many(self, value: bool) -> None:\\n self.__sql_many_state = value\",\n \"def set_PageToken(self, value):\\n super(ListOrdersInputSet, self)._set_input('PageToken', value)\",\n \"def setDetectLists(self, value):\\n return self._set(detectLists=value)\",\n \"def set_target_stocks_list(self, list_of_stocks):\\n self.target_stocks = list_of_stocks\",\n \"def origin_list(self, origin_list: List[Origin]):\\n\\n self._origin_list = origin_list\",\n \"def download_queryset(self, queryset, export_format):\\n\\n dataset = LocationResource().export(queryset=queryset)\\n filedata = dataset.export(export_format)\\n filename = f\\\"InvenTree_Locations.{export_format}\\\"\\n\\n return DownloadFile(filedata, filename)\",\n \"def save_to_file(cls, list_objs):\\n my_list = []\\n if list_objs or list_objs is not None:\\n my_list = [obj.to_dictionary() for obj in list_objs]\\n with open(cls.__name__ + '.json', 'w+') as f:\\n f.write(cls.to_json_string(my_list))\",\n \"def save_to_file(cls, list_objs):\\n if list_objs is not None:\\n list_objs = [obj.to_dictionary() for obj in list_objs]\\n with open(\\\"{}.json\\\".format(cls.__name__), \\\"w\\\", encoding=\\\"utf-8\\\") as f:\\n f.write(cls.to_json_string(list_objs))\",\n \"def list_return_field_id(self, list_return_field_id):\\n\\n self._list_return_field_id = list_return_field_id\",\n \"def data(self, data: List[InlineResponse2002]):\\n\\n self._data = data\",\n \"def AssignImageList(self, imageList):\\r\\n\\r\\n self.SetImageList(imageList)\\r\\n self._ownsImageListNormal = True\",\n \"def create_object_list(manifest) -> List[\\\"Downloadable\\\"]:\\n results = []\\n for entry in manifest:\\n results.append(\\n Downloadable(\\n object_id=entry.object_id,\\n hostname=remove_trailing_whitespace_and_slashes_in_url(\\n entry.commons_url\\n ),\\n )\\n )\\n return results\",\n \"def member_list(self, member_list):\\n\\n self._member_list = member_list\",\n \"def nfs_exports_every(self, nfs_exports_every):\\n\\n self._nfs_exports_every = nfs_exports_every\",\n \"def downloads(self, downloads: str):\\n\\n self._downloads = downloads\",\n \"def setPathsList(self, pathsList):\\n self.clear()\\n self.addItems(pathsList)\",\n \"def save_to_file(cls, list_objs):\\n file = cls.__name__ + '.json'\\n with open(file, 'w') as json_file:\\n if list_objs is None:\\n json_file.write('[]')\\n else:\\n dic = [obj.to_dictionary() for obj in list_objs]\\n json_file.write(Base.to_json_string(dic))\",\n \"def metadata(self, val: list):\\n self._metadata = []\\n if val is not None:\\n for item in val:\\n if isinstance(item, Metadata):\\n self._metadata.append(item)\",\n \"def export_part_list(self, filetype='xlsx'):\\n if filetype == 'csv':\\n enum = 48649\\n else:\\n enum = 48642\\n path = self.export_dir.joinpath(self.partcode).joinpath('part_list.xlsx')\\n self.doc.Sheets(1).PartsLists(1).Export(str(path), enum)\",\n \"def save_to_file(cls, list_objs):\\n\\n with open(cls.__name__ + \\\".json\\\", 'w') as f:\\n l = []\\n if list_objs is None or len(list_objs) <= 0:\\n f.write(Base.to_json_string(l))\\n\\n else:\\n for obj in list_objs:\\n l.append(cls.to_dictionary(obj))\\n f.write(Base.to_json_string(l))\",\n \"def set_animated(self, value):\\n for artist in self.artists:\\n artist.set_animated(value)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.57387066","0.572405","0.5720836","0.50837755","0.5052673","0.4954005","0.49233595","0.48638776","0.48131937","0.47819278","0.47225076","0.47225076","0.47171348","0.46870238","0.46680313","0.46198332","0.46057516","0.45436734","0.45278898","0.45272794","0.45091638","0.4498648","0.44917497","0.44813567","0.44813567","0.44757375","0.4452348","0.44139603","0.44012398","0.43921265","0.43755835","0.4374591","0.43413812","0.4336688","0.43364543","0.43318608","0.43289664","0.43257892","0.4324829","0.4315585","0.42979312","0.42840314","0.42818332","0.42777264","0.4256807","0.42539704","0.42359465","0.42284226","0.42280838","0.4225672","0.42251217","0.4218363","0.4210341","0.4196404","0.41877657","0.4186915","0.4186915","0.41847068","0.41776064","0.41771436","0.41763","0.4176141","0.41686395","0.41662315","0.41647917","0.41598564","0.4159822","0.41527182","0.4149815","0.41489634","0.41464564","0.4144607","0.4136806","0.41268298","0.41267598","0.41181475","0.41168794","0.40995944","0.40943956","0.40902227","0.408869","0.4082068","0.40791428","0.40748912","0.40643615","0.40622377","0.40615425","0.40605098","0.40549242","0.40541455","0.40493777","0.40482876","0.40444094","0.40386295","0.40346986","0.40326345","0.4029807","0.40225112","0.40169486","0.40107915"],"string":"[\n \"0.57387066\",\n \"0.572405\",\n \"0.5720836\",\n \"0.50837755\",\n \"0.5052673\",\n \"0.4954005\",\n \"0.49233595\",\n \"0.48638776\",\n \"0.48131937\",\n \"0.47819278\",\n \"0.47225076\",\n \"0.47225076\",\n \"0.47171348\",\n \"0.46870238\",\n \"0.46680313\",\n \"0.46198332\",\n \"0.46057516\",\n \"0.45436734\",\n \"0.45278898\",\n \"0.45272794\",\n \"0.45091638\",\n \"0.4498648\",\n \"0.44917497\",\n \"0.44813567\",\n \"0.44813567\",\n \"0.44757375\",\n \"0.4452348\",\n \"0.44139603\",\n \"0.44012398\",\n \"0.43921265\",\n \"0.43755835\",\n \"0.4374591\",\n \"0.43413812\",\n \"0.4336688\",\n \"0.43364543\",\n \"0.43318608\",\n \"0.43289664\",\n \"0.43257892\",\n \"0.4324829\",\n \"0.4315585\",\n \"0.42979312\",\n \"0.42840314\",\n \"0.42818332\",\n \"0.42777264\",\n \"0.4256807\",\n \"0.42539704\",\n \"0.42359465\",\n \"0.42284226\",\n \"0.42280838\",\n \"0.4225672\",\n \"0.42251217\",\n \"0.4218363\",\n \"0.4210341\",\n \"0.4196404\",\n \"0.41877657\",\n \"0.4186915\",\n \"0.4186915\",\n \"0.41847068\",\n \"0.41776064\",\n \"0.41771436\",\n \"0.41763\",\n \"0.4176141\",\n \"0.41686395\",\n \"0.41662315\",\n \"0.41647917\",\n \"0.41598564\",\n \"0.4159822\",\n \"0.41527182\",\n \"0.4149815\",\n \"0.41489634\",\n \"0.41464564\",\n \"0.4144607\",\n \"0.4136806\",\n \"0.41268298\",\n \"0.41267598\",\n \"0.41181475\",\n \"0.41168794\",\n \"0.40995944\",\n \"0.40943956\",\n \"0.40902227\",\n \"0.408869\",\n \"0.4082068\",\n \"0.40791428\",\n \"0.40748912\",\n \"0.40643615\",\n \"0.40622377\",\n \"0.40615425\",\n \"0.40605098\",\n \"0.40549242\",\n \"0.40541455\",\n \"0.40493777\",\n \"0.40482876\",\n \"0.40444094\",\n \"0.40386295\",\n \"0.40346986\",\n \"0.40326345\",\n \"0.4029807\",\n \"0.40225112\",\n \"0.40169486\",\n \"0.40107915\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8515711"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":10696,"cells":{"query":{"kind":"string","value":"Returns the model properties as a dict"},"document":{"kind":"string","value":"def to_dict(self):\n result = {}\n\n for attr, _ in six.iteritems(self.swagger_types):\n value = getattr(self, attr)\n if isinstance(value, list):\n result[attr] = list(map(\n lambda x: x.to_dict() if hasattr(x, \"to_dict\") else x,\n value\n ))\n elif hasattr(value, \"to_dict\"):\n result[attr] = value.to_dict()\n elif isinstance(value, dict):\n result[attr] = dict(map(\n lambda item: (item[0], item[1].to_dict())\n if hasattr(item[1], \"to_dict\") else item,\n value.items()\n ))\n else:\n result[attr] = value\n if issubclass(ExportResponseMetadata, dict):\n for key, value in self.items():\n result[key] = value\n\n return result"},"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 to_dict(self):\n return self.properties","def to_dict(self):\n return self.properties","def get_properties(self):\n return self.properties","def asdict(self):\n return self._prop_dict","def json(self):\n rv = {\n prop: getattr(self, prop)\n for prop in self.__properties__\n if prop in vars(self)\n }\n rv.update(self._props)\n return rv","def get_properties(self):\n return self.properties","def get_properties():","def getProperties():","def properties(self):\r\n if self._properties is None:\r\n res = self._con.get(self._url, {'f':'json'})\r\n self._properties = PropertyMap(res)\r\n return self._properties","def properties(self):\r\n if self._properties is None:\r\n res = self._con.get(self._url, {'f':'json'})\r\n self._properties = PropertyMap(res)\r\n return self._properties","def getProperties(self):\n return self.properties","def __properties__(self) -> dict:\r\n parameters = [\r\n d for d in dir(self) if (d[0] != \"_\") and (d.count(\"set\") == 0)\r\n and (d.count(\"_c\") == 0) and (d.count(\"_f\") == 0)\r\n ]\r\n\r\n return self.__as_json__(parameters)","def json_properties(self):\n attributes = []\n all = vars(self)\n for var in all:\n if var[:1] != '_':\n attributes.append(var)\n if isinstance(self, db.Model):\n properties = self.properties().keys()\n for property in properties:\n if property[:1] != '_':\n attributes.append(property)\n return attributes","def properties(self) -> Any:\n return pulumi.get(self, \"properties\")","def _properties(self) -> dict[str, dict[str, str]]:\n schema = self.schema(by_alias=False)\n if schema.get('properties') is not None:\n return schema.get('properties', {})\n return schema.get('definitions', {}).get(self.__class__.__name__, {}).get('properties', {})","def get_model_properties(self):\n properties = {}\n\n filename = self._get_data_filename(\"modelargs.json\")\n with open(filename, \"r\") as f:\n results = json.loads(f.read())\n properties[\"image_size\"] = results.get(\"image_size\")\n properties[\"num_classes\"] = results.get(\"num_classes\")\n properties[\"model\"] = results.get(\"model\")\n properties[\"name\"] = results.get(\"name\")\n properties[\"filter_size\"] = results.get(\"filter_size\", 3)\n properties[\"increase_factor\"] = results.get(\"increase_factor\", 0)\n self.model = properties[\"name\"] # regardless of the name of the folder, this will get the proper model name (i.e. <modelname>.cntk)\n\n # optional property\n properties[\"trainer\"] = results.get(\"trainer\", \"CNTK 2.2\")\n\n self._ensure_model_file()\n properties[\"size_mb\"] = round(os.path.getsize(self.model_file) / (1000 * 1000))\n\n return properties","def as_dict(self):\n result = {}\n for attr in self.__attr:\n result[attr] = getattr(self, attr)\n return result","def to_dict_model(self) -> dict:\n return dict((key, getattr(self, key)) for key in self.__mapper__.c.keys())","def get_properties():\n properties = dict()\n properties['size'] = list()\n properties['color'] = list()\n properties['quality'] = list()\n u = models.Size.query.all()\n for i in u:\n properties['size'].append(i.size_name)\n u = models.Color.query.all()\n for i in u:\n properties['color'].append(i.color_name)\n u = models.Quality.query.all()\n for i in u:\n properties['quality'].append(i.quality_name)\n return make_response(jsonify(properties))","def get_modelDict(self):\n return self.__modelDict","def attributes(self):\n return dict(self.__attributes)","def properties(self):\n return self._properties","def properties(self):\n return self._properties","def to_dict(self):\n result = {}\n for p in self.json_properties():\n value = getattr(self, p)\n if isinstance(value, datetime.datetime):\n value = value.strftime('%s%f')[:-3]\n result[Jsonifiable.transform_to_camelcase(p)] = value\n return result","def properties(self):\n return self._props","def properties(self):\n pass","def to_dict(self):\n d = {}\n for attr in self.__class__.attributes:\n d[attr] = getattr(self, attr)\n return d","def properties_get(self):\n return self._get('properties')","def _collect_properties(self):\n properties = {\n 'userid': self.user_id,\n 'title': self.get_fullname()\n }\n if not self.ogds_user:\n return properties\n\n for attribute_name in self.ogds_user_attributes:\n value = getattr(self.ogds_user, attribute_name)\n properties[attribute_name] = value\n return properties","def getPropertyDict(self):\n \n d = self.getChild('__properties')\n if d:\n return d.getDict()\n else:\n return {}","def get_attributes(self):\n return dict(self.attributes) # return the attributes","def get_attributes(self):\n return dict(self.attributes) # return the attributes","def get_attributes(self):\n return dict(self.attributes) # return the attributes","def to_dict(self, include=None):\n _MODEL = type(self)\n repr_dict = {}\n if include is None:\n include = []\n for name, prop in _MODEL._properties.iteritems():\n if hasattr(prop, 'public') and getattr(prop, 'public', False):\n include.append(name)\n\n for name in include:\n # check if this property is even allowed to be public\n # or has a value set\n if not hasattr(self, name):\n continue\n\n value = getattr(self, name)\n if type(getattr(_MODEL, name)) == ndb.StructuredProperty:\n if isinstance(value, list):\n items = []\n for item in value:\n items.append(item.to_dict(include=None))\n repr_dict[name] = items\n else:\n repr_dict[name] = value.to_dict(include=None)\n elif isinstance(value, date):\n repr_dict[name] = value.isoformat()\n elif isinstance(value, ndb.Key):\n repr_dict[name] = value.urlsafe()\n else:\n repr_dict[name] = value\n\n if self._key:\n repr_dict['key'] = self.get_key_urlsafe()\n return repr_dict","def to_dict(self):\n properties = {}\n for k in self.__dict__:\n if k == 'POSSIBLE_METHODS':\n continue\n if k == 'keysamplers':\n properties[k] = [i.to_dict() for i in self.__dict__[k] if hasattr(i,'to_dict')]\n elif k in {'pooler'}:\n properties[k] = self.__dict__[k].to_dict()\n else:\n properties[k] = deepcopy(self.__dict__[k])\n return properties","def get_all_properties(cls):\n return ['key', 'id'] + _.keys(cls._properties)","def get_properties(self):\n return self.name, self.author, self.description, self.fmu_type, self.version, self.guid, self.tool, self.numStates","def properties(self):\n\n return self._properties","def ToDict(self):\n atributes_dictionary = {}\n for key, value in self.__dict__.iteritems():\n atributes_dictionary[key] = value\n return atributes_dictionary","def properties(self):","def properties(self):","def properties(self):","def modelPropertiesDictionary(sql_row_list):\n \n properties_dictionary = \\\n {\n \"id\": sql_row_list[0],\n \"name\": sql_row_list[1],\n \"last_deploy_timestamp\": sql_row_list[2],\n \"active_version\": sql_row_list[3],\n \"build_id\": sql_row_list[4]\n };\n\n return properties_dictionary;","def as_dict(self):\n data = dict()\n for name in self.fields:\n val = getattr(self, name)\n if isinstance(val, Model):\n val = val.as_dict()\n elif isinstance(val, list) and val and isinstance(val[0], Model):\n val = [sub.as_dict() for sub in val]\n data[name] = val\n return data","def to_dict(self):\n if self._dict is not None:\n return self._dict\n\n result = {}\n for key in self.ATTRIBUTES:\n value = getattr(self, key)\n if value:\n result[key] = value\n self._dict = result\n return result","def properties(self) -> Optional[Mapping[str, str]]:\n return pulumi.get(self, \"properties\")","def properties(self) -> Optional[Mapping[str, str]]:\n return pulumi.get(self, \"properties\")","def to_dict(self):\n _dict = {}\n for f in self._meta.fields:\n if f.name == 'created':\n _dict[f.name] = str(f.value_from_object(self))\n else:\n _dict[f.name] = f.value_from_object(self)\n\n return _dict","def to_dict(self):\r\n return self.__dict__","def properties(self):\n return None","def properties(self):\n return None","def to_dict(self):\n return attr.asdict(self)","def as_dict(self):\n return self.__dict__","def _get_model_state(self) -> dict:\n return dict(model=self.model, kwargs=self._model_kwargs)","def dictify(self):\n return {\n \"name\" : self.name,\n \"lastname\" : self.lastname,\n \"phone\" : self.phone,\n \"email\" : self.email\n }","def to_dict(self):\n return {\n \"id\": self.id,\n \"name\": self.name,\n # \"created_by\": self.created_by,\n # \"created_on\": self.created_on,\n # \"modified_by\": self.modified_by,\n # \"modified_on\": self.modified_on\n }","def properties(self):\r\n return resources.Properties(self)","def attributes(self):\n params = self.model.param_array\n return {'parameters': params}","def properties(self, pk):\n return JsonResponse(self._get_properties(pk))","def to_dict(self):\n return vars(self)","def to_dict(self):\n\n # Check if is the right instance.\n if isinstance(self, db.Model):\n # construct a dictionary from column names and values.\n dict_representation = {c.name: getattr(self, c.name) for c in self.__table__.columns}\n return dict_representation\n else:\n raise AttributeError(type(self).__name__ + \" is not instance of \" + db.Model.__name__)","def bson_properties(self):\n return []","def to_dict(self):\n return {\n \"id\": self.id,\n \"name\": self.name\n }","def get_dict(self):\n return","def to_dict(self):\n return to_dict(self.__dict__)","def to_json(self):\n properties = self.to_dict()\n if isinstance(self, db.Model):\n properties['id'] = unicode(self.key().id())\n return json.dumps(properties)","def to_dict(self):","def to_dict(self):\n return self.__dict__","def to_dict(self):\n return self.__dict__","def to_dict(self):\n return self.__dict__","def to_dict(self):\n return self.__dict__","def to_dict(self):\n return self.__dict__","def to_dict(self):\n return self.__dict__","def get_attributes(self) -> Dict[str, str]:\n pass","def config(self) -> ModelConfigDict:\n return self.config_obj.to_dict()","def properties(self):\n return self.properties_with_uid[1:]","def to_dict(self):\n properties = {}\n for k in self.__dict__:\n if k in {'idsSoFar'}:\n continue\n else:\n properties[k] = deepcopy(self.__dict__[k])\n return properties","def to_dict(self):\n properties = {}\n for k in self.__dict__:\n if k in {'idsSoFar'}:\n continue\n else:\n properties[k] = deepcopy(self.__dict__[k])\n return properties","def to_dict(self):\n properties = {}\n for k in self.__dict__:\n if k in {'idsSoFar'}:\n continue\n else:\n properties[k] = deepcopy(self.__dict__[k])\n return properties","def serialise(self):\n return {\n 'id': self.id,\n 'category_id': self.category_id,\n 'name': self.name,\n 'description': self.description,\n 'quantity': self.quantity,\n 'price': self.price,\n 'user_id': self.user_id\n }","def getPropertiesAll():","def get_all_properties(self) -> dict:\n return self._request(\n \"post\",\n URL,\n json=attr.asdict(\n Body(\"getAllProperties\", API_VERSION),\n filter=attr.filters.exclude(attr.fields(Body).params),\n ),\n )","def model_info(self):\n if not self._model_info:\n self._load_model_info()\n try:\n data = json.loads(self._model_info)\n except (TypeError, ValueError):\n data = {}\n return data","def to_dict(self):\n return {\n 'name': self.get_name(),\n 'description': self.get_description()\n }","def serialize(self):\n return {\n 'id' : self.id,\n 'name' : self.name,\n }","def serialize(self):\n return {\n 'id' : self.id,\n 'name' : self.name,\n }","def as_dict(self):\n return self.__dict__","def to_dict(self):\r\n\r\n return {\r\n 'product_id': self.product_id,\r\n 'product_name': self.product_name\r\n }","def serialize(self):\n return {\n 'name' : self.name,\n 'id' : self.id,\n }","def asdict(self):\n return attr.asdict(self)","def to_dict(self) -> dict:","def getDict(self):\n res = {}\n for attr, value in self.__dict__.iteritems():\n if type(attr) is IntType or type(attr) is StringType or type(attr) is LongType or type(attr) is UnicodeType:\n res[attr] = value\n elif isinstance(attr, datetime.datetime):\n res[attr] = value.isoformat('-')\n \n return res","def attributes(self):\n return self.__dict.keys()","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def dict(self):\n return self.__dict__","def as_dict(self):\n return {c.key: getattr(self, c.key)\n for c in inspect(self).mapper.column_attrs}"],"string":"[\n \"def to_dict(self):\\n return self.properties\",\n \"def to_dict(self):\\n return self.properties\",\n \"def get_properties(self):\\n return self.properties\",\n \"def asdict(self):\\n return self._prop_dict\",\n \"def json(self):\\n rv = {\\n prop: getattr(self, prop)\\n for prop in self.__properties__\\n if prop in vars(self)\\n }\\n rv.update(self._props)\\n return rv\",\n \"def get_properties(self):\\n return self.properties\",\n \"def get_properties():\",\n \"def getProperties():\",\n \"def properties(self):\\r\\n if self._properties is None:\\r\\n res = self._con.get(self._url, {'f':'json'})\\r\\n self._properties = PropertyMap(res)\\r\\n return self._properties\",\n \"def properties(self):\\r\\n if self._properties is None:\\r\\n res = self._con.get(self._url, {'f':'json'})\\r\\n self._properties = PropertyMap(res)\\r\\n return self._properties\",\n \"def getProperties(self):\\n return self.properties\",\n \"def __properties__(self) -> dict:\\r\\n parameters = [\\r\\n d for d in dir(self) if (d[0] != \\\"_\\\") and (d.count(\\\"set\\\") == 0)\\r\\n and (d.count(\\\"_c\\\") == 0) and (d.count(\\\"_f\\\") == 0)\\r\\n ]\\r\\n\\r\\n return self.__as_json__(parameters)\",\n \"def json_properties(self):\\n attributes = []\\n all = vars(self)\\n for var in all:\\n if var[:1] != '_':\\n attributes.append(var)\\n if isinstance(self, db.Model):\\n properties = self.properties().keys()\\n for property in properties:\\n if property[:1] != '_':\\n attributes.append(property)\\n return attributes\",\n \"def properties(self) -> Any:\\n return pulumi.get(self, \\\"properties\\\")\",\n \"def _properties(self) -> dict[str, dict[str, str]]:\\n schema = self.schema(by_alias=False)\\n if schema.get('properties') is not None:\\n return schema.get('properties', {})\\n return schema.get('definitions', {}).get(self.__class__.__name__, {}).get('properties', {})\",\n \"def get_model_properties(self):\\n properties = {}\\n\\n filename = self._get_data_filename(\\\"modelargs.json\\\")\\n with open(filename, \\\"r\\\") as f:\\n results = json.loads(f.read())\\n properties[\\\"image_size\\\"] = results.get(\\\"image_size\\\")\\n properties[\\\"num_classes\\\"] = results.get(\\\"num_classes\\\")\\n properties[\\\"model\\\"] = results.get(\\\"model\\\")\\n properties[\\\"name\\\"] = results.get(\\\"name\\\")\\n properties[\\\"filter_size\\\"] = results.get(\\\"filter_size\\\", 3)\\n properties[\\\"increase_factor\\\"] = results.get(\\\"increase_factor\\\", 0)\\n self.model = properties[\\\"name\\\"] # regardless of the name of the folder, this will get the proper model name (i.e. <modelname>.cntk)\\n\\n # optional property\\n properties[\\\"trainer\\\"] = results.get(\\\"trainer\\\", \\\"CNTK 2.2\\\")\\n\\n self._ensure_model_file()\\n properties[\\\"size_mb\\\"] = round(os.path.getsize(self.model_file) / (1000 * 1000))\\n\\n return properties\",\n \"def as_dict(self):\\n result = {}\\n for attr in self.__attr:\\n result[attr] = getattr(self, attr)\\n return result\",\n \"def to_dict_model(self) -> dict:\\n return dict((key, getattr(self, key)) for key in self.__mapper__.c.keys())\",\n \"def get_properties():\\n properties = dict()\\n properties['size'] = list()\\n properties['color'] = list()\\n properties['quality'] = list()\\n u = models.Size.query.all()\\n for i in u:\\n properties['size'].append(i.size_name)\\n u = models.Color.query.all()\\n for i in u:\\n properties['color'].append(i.color_name)\\n u = models.Quality.query.all()\\n for i in u:\\n properties['quality'].append(i.quality_name)\\n return make_response(jsonify(properties))\",\n \"def get_modelDict(self):\\n return self.__modelDict\",\n \"def attributes(self):\\n return dict(self.__attributes)\",\n \"def properties(self):\\n return self._properties\",\n \"def properties(self):\\n return self._properties\",\n \"def to_dict(self):\\n result = {}\\n for p in self.json_properties():\\n value = getattr(self, p)\\n if isinstance(value, datetime.datetime):\\n value = value.strftime('%s%f')[:-3]\\n result[Jsonifiable.transform_to_camelcase(p)] = value\\n return result\",\n \"def properties(self):\\n return self._props\",\n \"def properties(self):\\n pass\",\n \"def to_dict(self):\\n d = {}\\n for attr in self.__class__.attributes:\\n d[attr] = getattr(self, attr)\\n return d\",\n \"def properties_get(self):\\n return self._get('properties')\",\n \"def _collect_properties(self):\\n properties = {\\n 'userid': self.user_id,\\n 'title': self.get_fullname()\\n }\\n if not self.ogds_user:\\n return properties\\n\\n for attribute_name in self.ogds_user_attributes:\\n value = getattr(self.ogds_user, attribute_name)\\n properties[attribute_name] = value\\n return properties\",\n \"def getPropertyDict(self):\\n \\n d = self.getChild('__properties')\\n if d:\\n return d.getDict()\\n else:\\n return {}\",\n \"def get_attributes(self):\\n return dict(self.attributes) # return the attributes\",\n \"def get_attributes(self):\\n return dict(self.attributes) # return the attributes\",\n \"def get_attributes(self):\\n return dict(self.attributes) # return the attributes\",\n \"def to_dict(self, include=None):\\n _MODEL = type(self)\\n repr_dict = {}\\n if include is None:\\n include = []\\n for name, prop in _MODEL._properties.iteritems():\\n if hasattr(prop, 'public') and getattr(prop, 'public', False):\\n include.append(name)\\n\\n for name in include:\\n # check if this property is even allowed to be public\\n # or has a value set\\n if not hasattr(self, name):\\n continue\\n\\n value = getattr(self, name)\\n if type(getattr(_MODEL, name)) == ndb.StructuredProperty:\\n if isinstance(value, list):\\n items = []\\n for item in value:\\n items.append(item.to_dict(include=None))\\n repr_dict[name] = items\\n else:\\n repr_dict[name] = value.to_dict(include=None)\\n elif isinstance(value, date):\\n repr_dict[name] = value.isoformat()\\n elif isinstance(value, ndb.Key):\\n repr_dict[name] = value.urlsafe()\\n else:\\n repr_dict[name] = value\\n\\n if self._key:\\n repr_dict['key'] = self.get_key_urlsafe()\\n return repr_dict\",\n \"def to_dict(self):\\n properties = {}\\n for k in self.__dict__:\\n if k == 'POSSIBLE_METHODS':\\n continue\\n if k == 'keysamplers':\\n properties[k] = [i.to_dict() for i in self.__dict__[k] if hasattr(i,'to_dict')]\\n elif k in {'pooler'}:\\n properties[k] = self.__dict__[k].to_dict()\\n else:\\n properties[k] = deepcopy(self.__dict__[k])\\n return properties\",\n \"def get_all_properties(cls):\\n return ['key', 'id'] + _.keys(cls._properties)\",\n \"def get_properties(self):\\n return self.name, self.author, self.description, self.fmu_type, self.version, self.guid, self.tool, self.numStates\",\n \"def properties(self):\\n\\n return self._properties\",\n \"def ToDict(self):\\n atributes_dictionary = {}\\n for key, value in self.__dict__.iteritems():\\n atributes_dictionary[key] = value\\n return atributes_dictionary\",\n \"def properties(self):\",\n \"def properties(self):\",\n \"def properties(self):\",\n \"def modelPropertiesDictionary(sql_row_list):\\n \\n properties_dictionary = \\\\\\n {\\n \\\"id\\\": sql_row_list[0],\\n \\\"name\\\": sql_row_list[1],\\n \\\"last_deploy_timestamp\\\": sql_row_list[2],\\n \\\"active_version\\\": sql_row_list[3],\\n \\\"build_id\\\": sql_row_list[4]\\n };\\n\\n return properties_dictionary;\",\n \"def as_dict(self):\\n data = dict()\\n for name in self.fields:\\n val = getattr(self, name)\\n if isinstance(val, Model):\\n val = val.as_dict()\\n elif isinstance(val, list) and val and isinstance(val[0], Model):\\n val = [sub.as_dict() for sub in val]\\n data[name] = val\\n return data\",\n \"def to_dict(self):\\n if self._dict is not None:\\n return self._dict\\n\\n result = {}\\n for key in self.ATTRIBUTES:\\n value = getattr(self, key)\\n if value:\\n result[key] = value\\n self._dict = result\\n return result\",\n \"def properties(self) -> Optional[Mapping[str, str]]:\\n return pulumi.get(self, \\\"properties\\\")\",\n \"def properties(self) -> Optional[Mapping[str, str]]:\\n return pulumi.get(self, \\\"properties\\\")\",\n \"def to_dict(self):\\n _dict = {}\\n for f in self._meta.fields:\\n if f.name == 'created':\\n _dict[f.name] = str(f.value_from_object(self))\\n else:\\n _dict[f.name] = f.value_from_object(self)\\n\\n return _dict\",\n \"def to_dict(self):\\r\\n return self.__dict__\",\n \"def properties(self):\\n return None\",\n \"def properties(self):\\n return None\",\n \"def to_dict(self):\\n return attr.asdict(self)\",\n \"def as_dict(self):\\n return self.__dict__\",\n \"def _get_model_state(self) -> dict:\\n return dict(model=self.model, kwargs=self._model_kwargs)\",\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 to_dict(self):\\n return {\\n \\\"id\\\": self.id,\\n \\\"name\\\": self.name,\\n # \\\"created_by\\\": self.created_by,\\n # \\\"created_on\\\": self.created_on,\\n # \\\"modified_by\\\": self.modified_by,\\n # \\\"modified_on\\\": self.modified_on\\n }\",\n \"def properties(self):\\r\\n return resources.Properties(self)\",\n \"def attributes(self):\\n params = self.model.param_array\\n return {'parameters': params}\",\n \"def properties(self, pk):\\n return JsonResponse(self._get_properties(pk))\",\n \"def to_dict(self):\\n return vars(self)\",\n \"def to_dict(self):\\n\\n # Check if is the right instance.\\n if isinstance(self, db.Model):\\n # construct a dictionary from column names and values.\\n dict_representation = {c.name: getattr(self, c.name) for c in self.__table__.columns}\\n return dict_representation\\n else:\\n raise AttributeError(type(self).__name__ + \\\" is not instance of \\\" + db.Model.__name__)\",\n \"def bson_properties(self):\\n return []\",\n \"def to_dict(self):\\n return {\\n \\\"id\\\": self.id,\\n \\\"name\\\": self.name\\n }\",\n \"def get_dict(self):\\n return\",\n \"def to_dict(self):\\n return to_dict(self.__dict__)\",\n \"def to_json(self):\\n properties = self.to_dict()\\n if isinstance(self, db.Model):\\n properties['id'] = unicode(self.key().id())\\n return json.dumps(properties)\",\n \"def to_dict(self):\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\n return self.__dict__\",\n \"def get_attributes(self) -> Dict[str, str]:\\n pass\",\n \"def config(self) -> ModelConfigDict:\\n return self.config_obj.to_dict()\",\n \"def properties(self):\\n return self.properties_with_uid[1:]\",\n \"def to_dict(self):\\n properties = {}\\n for k in self.__dict__:\\n if k in {'idsSoFar'}:\\n continue\\n else:\\n properties[k] = deepcopy(self.__dict__[k])\\n return properties\",\n \"def to_dict(self):\\n properties = {}\\n for k in self.__dict__:\\n if k in {'idsSoFar'}:\\n continue\\n else:\\n properties[k] = deepcopy(self.__dict__[k])\\n return properties\",\n \"def to_dict(self):\\n properties = {}\\n for k in self.__dict__:\\n if k in {'idsSoFar'}:\\n continue\\n else:\\n properties[k] = deepcopy(self.__dict__[k])\\n return properties\",\n \"def serialise(self):\\n return {\\n 'id': self.id,\\n 'category_id': self.category_id,\\n 'name': self.name,\\n 'description': self.description,\\n 'quantity': self.quantity,\\n 'price': self.price,\\n 'user_id': self.user_id\\n }\",\n \"def getPropertiesAll():\",\n \"def get_all_properties(self) -> dict:\\n return self._request(\\n \\\"post\\\",\\n URL,\\n json=attr.asdict(\\n Body(\\\"getAllProperties\\\", API_VERSION),\\n filter=attr.filters.exclude(attr.fields(Body).params),\\n ),\\n )\",\n \"def model_info(self):\\n if not self._model_info:\\n self._load_model_info()\\n try:\\n data = json.loads(self._model_info)\\n except (TypeError, ValueError):\\n data = {}\\n return data\",\n \"def to_dict(self):\\n return {\\n 'name': self.get_name(),\\n 'description': self.get_description()\\n }\",\n \"def serialize(self):\\n return {\\n 'id' : self.id,\\n 'name' : self.name,\\n }\",\n \"def serialize(self):\\n return {\\n 'id' : self.id,\\n 'name' : self.name,\\n }\",\n \"def as_dict(self):\\n return self.__dict__\",\n \"def to_dict(self):\\r\\n\\r\\n return {\\r\\n 'product_id': self.product_id,\\r\\n 'product_name': self.product_name\\r\\n }\",\n \"def serialize(self):\\n return {\\n 'name' : self.name,\\n 'id' : self.id,\\n }\",\n \"def asdict(self):\\n return attr.asdict(self)\",\n \"def to_dict(self) -> dict:\",\n \"def getDict(self):\\n res = {}\\n for attr, value in self.__dict__.iteritems():\\n if type(attr) is IntType or type(attr) is StringType or type(attr) is LongType or type(attr) is UnicodeType:\\n res[attr] = value\\n elif isinstance(attr, datetime.datetime):\\n res[attr] = value.isoformat('-')\\n \\n return res\",\n \"def attributes(self):\\n return self.__dict.keys()\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def dict(self):\\n return self.__dict__\",\n \"def as_dict(self):\\n return {c.key: getattr(self, c.key)\\n for c in inspect(self).mapper.column_attrs}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7751993","0.7751993","0.73391134","0.7334895","0.7297356","0.727818","0.7159078","0.71578115","0.71494967","0.71494967","0.71283495","0.71275014","0.7122587","0.71079814","0.7060394","0.7043251","0.7034103","0.70233124","0.69635814","0.69586295","0.690053","0.6881568","0.6881568","0.6857664","0.68415916","0.68122137","0.680096","0.67914945","0.6757063","0.6753585","0.6741746","0.6741746","0.6741746","0.6735291","0.67126125","0.6697801","0.6695801","0.6689893","0.6680752","0.66802895","0.66802895","0.66802895","0.66547817","0.66495687","0.6633999","0.6619567","0.6619567","0.66156983","0.66049474","0.6590706","0.6590706","0.6590206","0.6587873","0.65861845","0.65822417","0.65794736","0.65792733","0.657747","0.6571183","0.65662557","0.65637356","0.6539919","0.65396816","0.65283066","0.65252614","0.6513477","0.65098846","0.65077883","0.65077883","0.65077883","0.65077883","0.65077883","0.65077883","0.6507418","0.6505772","0.65015876","0.64951885","0.64951885","0.64951885","0.64857763","0.6474329","0.6469453","0.64684683","0.6453606","0.6453024","0.6453024","0.6430734","0.6429058","0.6426903","0.64215595","0.64201874","0.6417152","0.6414739","0.6411571","0.6411571","0.6411571","0.6411571","0.6411571","0.6411571","0.6411571","0.64035517"],"string":"[\n \"0.7751993\",\n \"0.7751993\",\n \"0.73391134\",\n \"0.7334895\",\n \"0.7297356\",\n \"0.727818\",\n \"0.7159078\",\n \"0.71578115\",\n \"0.71494967\",\n \"0.71494967\",\n \"0.71283495\",\n \"0.71275014\",\n \"0.7122587\",\n \"0.71079814\",\n \"0.7060394\",\n \"0.7043251\",\n \"0.7034103\",\n \"0.70233124\",\n \"0.69635814\",\n \"0.69586295\",\n \"0.690053\",\n \"0.6881568\",\n \"0.6881568\",\n \"0.6857664\",\n \"0.68415916\",\n \"0.68122137\",\n \"0.680096\",\n \"0.67914945\",\n \"0.6757063\",\n \"0.6753585\",\n \"0.6741746\",\n \"0.6741746\",\n \"0.6741746\",\n \"0.6735291\",\n \"0.67126125\",\n \"0.6697801\",\n \"0.6695801\",\n \"0.6689893\",\n \"0.6680752\",\n \"0.66802895\",\n \"0.66802895\",\n \"0.66802895\",\n \"0.66547817\",\n \"0.66495687\",\n \"0.6633999\",\n \"0.6619567\",\n \"0.6619567\",\n \"0.66156983\",\n \"0.66049474\",\n \"0.6590706\",\n \"0.6590706\",\n \"0.6590206\",\n \"0.6587873\",\n \"0.65861845\",\n \"0.65822417\",\n \"0.65794736\",\n \"0.65792733\",\n \"0.657747\",\n \"0.6571183\",\n \"0.65662557\",\n \"0.65637356\",\n \"0.6539919\",\n \"0.65396816\",\n \"0.65283066\",\n \"0.65252614\",\n \"0.6513477\",\n \"0.65098846\",\n \"0.65077883\",\n \"0.65077883\",\n \"0.65077883\",\n \"0.65077883\",\n \"0.65077883\",\n \"0.65077883\",\n \"0.6507418\",\n \"0.6505772\",\n \"0.65015876\",\n \"0.64951885\",\n \"0.64951885\",\n \"0.64951885\",\n \"0.64857763\",\n \"0.6474329\",\n \"0.6469453\",\n \"0.64684683\",\n \"0.6453606\",\n \"0.6453024\",\n \"0.6453024\",\n \"0.6430734\",\n \"0.6429058\",\n \"0.6426903\",\n \"0.64215595\",\n \"0.64201874\",\n \"0.6417152\",\n \"0.6414739\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.6411571\",\n \"0.64035517\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":10697,"cells":{"query":{"kind":"string","value":"Returns the string representation of the model"},"document":{"kind":"string","value":"def to_str(self):\n return pprint.pformat(self.to_dict())"},"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 __str__(self):\n return super().__str__() + self.model.__str__()","def __str__(self) -> str:\n # noinspection PyUnresolvedReferences\n opts = self._meta\n if self.name_field:\n result = str(opts.get_field(self.name_field).value_from_object(self))\n else:\n model_fields = get_model_fields(\n opts.model,\n foreign=False,\n m2m=False,\n exclude=self.exclude_from_str\n )\n # TODO: replace the above with the below to remove the get_model_fields call:\n # model_fields = [\n # f for f in opts.get_fields()\n # if f.concrete\n # and not (f.primary_key or f.is_relation or f.name in self.exclude_from_str)\n # ]\n result = \" \".join(\n [\n str(fld.value_from_object(self))\n for fld in model_fields\n if fld.value_from_object(self)\n ]\n )\n return result.strip() or super().__str__()","def __str__(self):\n return '%s%s' % (self.name, ' - %s' % self.model if self.model else '')","def __str__(self):\n model = self._meta.verbose_name.title()\n return f\"{model:s}: {self.name:s}\"","def __str__(self):\n model = self._meta.verbose_name.title()\n return f\"{model:s}: {self.name:s}\"","def __repr__(self):\n\n mod = f\"{self.__class__.__name__} Model\"\n try:\n mod += f': {self.filename}'\n except AttributeError:\n pass\n s = [mod]\n for name, v in self.metadata.items():\n s += [f\"{name:16} : {v}\"]\n return '\\n'.join(s)","def __str__(self):\n \n res = ['>>> Model %(model_name)s <<<']\n res.append('')\n res.append('Independent parameters:')\n res.append('-----------------------')\n res.append('')","def __str__(self):\n return \"DataModel(name={},attributes={},description={})\".format(\n self.name, {a.name: str(a) for a in self.attributes}, self.description\n )","def model_info(self) -> str:\n return self._model_info(self.model).decode(\"utf-8\")","def __str__(self):\n return str(self.serialize())","def __str__ (self) :\n\n return self.as_string()","def __str__(self):\n\n return self.toString()","def __str__(self):\n msg = [\n f'{self.model=}',\n f'{self.field=}',\n f'{self.fxx=}',\n f'{self.date=}',\n f'{self.priority=}',\n ]\n return '\\n'.join(msg)","def __str__(self):\n model = self._meta.verbose_name.title()\n title = self.extended_object.get_title()\n return f\"{model:s}: {title:s}\"","def __repr__(self):\n return grid_search_to_str(self.model)","def __str__(self):\n return self.toString()","def __str__(self):\n return str(self.__dict__)","def __str__(self):\n return str(self.__dict__)","def to_representation(self) -> str:\n raise NotImplementedError()","def __str__(self):\n return str(self.obj)","def __str__(self):\n return self.make_flat()","def dump_model(self):","def __str__(self):\n return str(self.__dict__['_obj'])","def __str__(self) -> str:\n model_str = [\"\\nModel info:\\n\", \" Unimodal encoder:\\n\"]\n\n for modality in range(self.num_modalities):\n model_str.append(f\" ({modality + 1}) {self.unimodal_encoder[modality]}\")\n\n model_str.append(\"\\n\\n Unimodal decoder:\\n\")\n for modality in range(self.num_modalities):\n model_str.append(f\" ({modality + 1}) {self.unimodal_decoder[modality]}\")\n\n if self.multimodal_decoder is not None:\n model_str.append(\"\\n\\n Multimodal decoder:\\n\")\n model_str.append(f\" {self.multimodal_decoder}\")\n\n return \"\".join(model_str)","def __repr__(self):\n s = 'text model name: ' + self.name + '\\n'\n s += ' number of words: ' + str(len(self.words)) + '\\n'\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\n'\n s += ' number of stems: ' + str(len(self.stems)) + '\\n'\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths)) + '\\n'\n s += ' most common words: ' + str(self.common_word) + '\\n'\n\n return s","def to_string(self):\r\n return self.__str__()","def __repr__(self):\n return '<ModelSignature(model_name=%r)>' % self.model_name","def __repr__(self):\n return '<ModelSignature(model_name=%r)>' % self.model_name","def __str__(self):\n return str(self.get_data())","def __str__(self):\n return f\"model {self._name}\"","def __str__(self):\n\n return self.raw_field","def __repr__(self):\n \n s = 'text model name: ' + self.name + '\\n' \n s += ' number of words: ' + str(len(self.words)) + '\\n'\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\n'\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths)) + '\\n'\n s += ' number of word stems: ' + str(len(self.stems)) + '\\n'\n s += ' number of commas counts: ' + str(len(self.commas_per_sentence)) + '\\n'\n return s","def serialize(self):\n\n\t\treturn str(self)","def __str__(self):\n return self.get_str()","def serialize(self):\n\n return str(self)","def __str__(self) -> str:\n if self.name_field:\n return str(getattr(self, self.name_field))\n # noinspection PyUnresolvedReferences\n data = [\n # Collect the string representations of related objects.\n # getattr(self, fk_field.attname) and\n # fk_field.value_from_object(self) would only return the primary\n # key of the related object.\n str(getattr(self, fk_field.name))\n for fk_field in get_model_fields(\n self._meta.model, base=False, foreign=True, m2m=False\n )\n if not fk_field.null\n ]\n if len(data) < 2:\n # Cannot build a more meaningful representation than the default.\n return super().__str__()\n else:\n template = \"{}\" + \" ({})\" * (len(data) - 1)\n return template.format(*data)","def __str__(self):\n return self.s","def __str__(self):\n return self.__repr__()","def __str__(self):\n return self.__repr__()","def __str__(self):\n return self.__repr__()","def __str__(self):\n return self.__repr__()","def __str__(self):\n return self.__repr__()","def __repr__(self):\n\n # info string\n info = self.model.__repr__()\n info += \"\\n=========================\\n\"\n info += f\"Train data length:\\t\\t{ len(self.train_dataset) }\\n\"\n info += f\"Eval sata length:\\t\\t{ len(self.eval_dataset) }\\n\"\n info += f\"Optimizer:\\t\\t\\t\\t{ str(self.optimizer).split('(')[0] }\\n\"\n info += f\"Criterion:\\t\\t\\t\\t{ str(self.criterion).split('(')[0] }\\n\"\n info += f\"Training Environment:\\t{ self.device.type }\\n\"\n info += f\"Show information:\\t\\t{ 'True' if self.info else 'False' }\\n\"\n info += \"=========================\\n\"\n\n return info","def __repr__(self):\n s = 'text model name: ' + self.name + '\\n'\n s += ' number of words: ' + str(len(self.words)) + '\\n'\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\n'\n s += ' number of stems: ' + str(len(self.stems)) + '\\n'\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths))\\\n + '\\n'\n s += ' number of punctuation types: ' + str(len(self.punctuation))\n return s","def dumps(self, indent=0):\n outstr = \" \"*indent + \"MewloDbModel object '{0}' attribute values:\\n\".format(self.__class__.__name__)\n public_props = (name for name in dir(object) if not name.startswith('_'))\n for name in public_props:\n outstr += \" \"*indent + \"{0}: {1}\\n\".format(name, str(getattr(self,name)))\n return outstr","def __str__(self):\n model = self._meta.verbose_name.title()\n title = self.title or str(_(\"Empty title\"))\n\n return f\"{model:s}: {title:s}\"","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()","def __repr__(self):\n return self.to_str()"],"string":"[\n \"def __str__(self):\\n return super().__str__() + self.model.__str__()\",\n \"def __str__(self) -> str:\\n # noinspection PyUnresolvedReferences\\n opts = self._meta\\n if self.name_field:\\n result = str(opts.get_field(self.name_field).value_from_object(self))\\n else:\\n model_fields = get_model_fields(\\n opts.model,\\n foreign=False,\\n m2m=False,\\n exclude=self.exclude_from_str\\n )\\n # TODO: replace the above with the below to remove the get_model_fields call:\\n # model_fields = [\\n # f for f in opts.get_fields()\\n # if f.concrete\\n # and not (f.primary_key or f.is_relation or f.name in self.exclude_from_str)\\n # ]\\n result = \\\" \\\".join(\\n [\\n str(fld.value_from_object(self))\\n for fld in model_fields\\n if fld.value_from_object(self)\\n ]\\n )\\n return result.strip() or super().__str__()\",\n \"def __str__(self):\\n return '%s%s' % (self.name, ' - %s' % self.model if self.model else '')\",\n \"def __str__(self):\\n model = self._meta.verbose_name.title()\\n return f\\\"{model:s}: {self.name:s}\\\"\",\n \"def __str__(self):\\n model = self._meta.verbose_name.title()\\n return f\\\"{model:s}: {self.name:s}\\\"\",\n \"def __repr__(self):\\n\\n mod = f\\\"{self.__class__.__name__} Model\\\"\\n try:\\n mod += f': {self.filename}'\\n except AttributeError:\\n pass\\n s = [mod]\\n for name, v in self.metadata.items():\\n s += [f\\\"{name:16} : {v}\\\"]\\n return '\\\\n'.join(s)\",\n \"def __str__(self):\\n \\n res = ['>>> Model %(model_name)s <<<']\\n res.append('')\\n res.append('Independent parameters:')\\n res.append('-----------------------')\\n res.append('')\",\n \"def __str__(self):\\n return \\\"DataModel(name={},attributes={},description={})\\\".format(\\n self.name, {a.name: str(a) for a in self.attributes}, self.description\\n )\",\n \"def model_info(self) -> str:\\n return self._model_info(self.model).decode(\\\"utf-8\\\")\",\n \"def __str__(self):\\n return str(self.serialize())\",\n \"def __str__ (self) :\\n\\n return self.as_string()\",\n \"def __str__(self):\\n\\n return self.toString()\",\n \"def __str__(self):\\n msg = [\\n f'{self.model=}',\\n f'{self.field=}',\\n f'{self.fxx=}',\\n f'{self.date=}',\\n f'{self.priority=}',\\n ]\\n return '\\\\n'.join(msg)\",\n \"def __str__(self):\\n model = self._meta.verbose_name.title()\\n title = self.extended_object.get_title()\\n return f\\\"{model:s}: {title:s}\\\"\",\n \"def __repr__(self):\\n return grid_search_to_str(self.model)\",\n \"def __str__(self):\\n return self.toString()\",\n \"def __str__(self):\\n return str(self.__dict__)\",\n \"def __str__(self):\\n return str(self.__dict__)\",\n \"def to_representation(self) -> str:\\n raise NotImplementedError()\",\n \"def __str__(self):\\n return str(self.obj)\",\n \"def __str__(self):\\n return self.make_flat()\",\n \"def dump_model(self):\",\n \"def __str__(self):\\n return str(self.__dict__['_obj'])\",\n \"def __str__(self) -> str:\\n model_str = [\\\"\\\\nModel info:\\\\n\\\", \\\" Unimodal encoder:\\\\n\\\"]\\n\\n for modality in range(self.num_modalities):\\n model_str.append(f\\\" ({modality + 1}) {self.unimodal_encoder[modality]}\\\")\\n\\n model_str.append(\\\"\\\\n\\\\n Unimodal decoder:\\\\n\\\")\\n for modality in range(self.num_modalities):\\n model_str.append(f\\\" ({modality + 1}) {self.unimodal_decoder[modality]}\\\")\\n\\n if self.multimodal_decoder is not None:\\n model_str.append(\\\"\\\\n\\\\n Multimodal decoder:\\\\n\\\")\\n model_str.append(f\\\" {self.multimodal_decoder}\\\")\\n\\n return \\\"\\\".join(model_str)\",\n \"def __repr__(self):\\n s = 'text model name: ' + self.name + '\\\\n'\\n s += ' number of words: ' + str(len(self.words)) + '\\\\n'\\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\\\n'\\n s += ' number of stems: ' + str(len(self.stems)) + '\\\\n'\\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths)) + '\\\\n'\\n s += ' most common words: ' + str(self.common_word) + '\\\\n'\\n\\n return s\",\n \"def to_string(self):\\r\\n return self.__str__()\",\n \"def __repr__(self):\\n return '<ModelSignature(model_name=%r)>' % self.model_name\",\n \"def __repr__(self):\\n return '<ModelSignature(model_name=%r)>' % self.model_name\",\n \"def __str__(self):\\n return str(self.get_data())\",\n \"def __str__(self):\\n return f\\\"model {self._name}\\\"\",\n \"def __str__(self):\\n\\n return self.raw_field\",\n \"def __repr__(self):\\n \\n s = 'text model name: ' + self.name + '\\\\n' \\n s += ' number of words: ' + str(len(self.words)) + '\\\\n'\\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\\\n'\\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths)) + '\\\\n'\\n s += ' number of word stems: ' + str(len(self.stems)) + '\\\\n'\\n s += ' number of commas counts: ' + str(len(self.commas_per_sentence)) + '\\\\n'\\n return s\",\n \"def serialize(self):\\n\\n\\t\\treturn str(self)\",\n \"def __str__(self):\\n return self.get_str()\",\n \"def serialize(self):\\n\\n return str(self)\",\n \"def __str__(self) -> str:\\n if self.name_field:\\n return str(getattr(self, self.name_field))\\n # noinspection PyUnresolvedReferences\\n data = [\\n # Collect the string representations of related objects.\\n # getattr(self, fk_field.attname) and\\n # fk_field.value_from_object(self) would only return the primary\\n # key of the related object.\\n str(getattr(self, fk_field.name))\\n for fk_field in get_model_fields(\\n self._meta.model, base=False, foreign=True, m2m=False\\n )\\n if not fk_field.null\\n ]\\n if len(data) < 2:\\n # Cannot build a more meaningful representation than the default.\\n return super().__str__()\\n else:\\n template = \\\"{}\\\" + \\\" ({})\\\" * (len(data) - 1)\\n return template.format(*data)\",\n \"def __str__(self):\\n return self.s\",\n \"def __str__(self):\\n return self.__repr__()\",\n \"def __str__(self):\\n return self.__repr__()\",\n \"def __str__(self):\\n return self.__repr__()\",\n \"def __str__(self):\\n return self.__repr__()\",\n \"def __str__(self):\\n return self.__repr__()\",\n \"def __repr__(self):\\n\\n # info string\\n info = self.model.__repr__()\\n info += \\\"\\\\n=========================\\\\n\\\"\\n info += f\\\"Train data length:\\\\t\\\\t{ len(self.train_dataset) }\\\\n\\\"\\n info += f\\\"Eval sata length:\\\\t\\\\t{ len(self.eval_dataset) }\\\\n\\\"\\n info += f\\\"Optimizer:\\\\t\\\\t\\\\t\\\\t{ str(self.optimizer).split('(')[0] }\\\\n\\\"\\n info += f\\\"Criterion:\\\\t\\\\t\\\\t\\\\t{ str(self.criterion).split('(')[0] }\\\\n\\\"\\n info += f\\\"Training Environment:\\\\t{ self.device.type }\\\\n\\\"\\n info += f\\\"Show information:\\\\t\\\\t{ 'True' if self.info else 'False' }\\\\n\\\"\\n info += \\\"=========================\\\\n\\\"\\n\\n return info\",\n \"def __repr__(self):\\n s = 'text model name: ' + self.name + '\\\\n'\\n s += ' number of words: ' + str(len(self.words)) + '\\\\n'\\n s += ' number of word lengths: ' + str(len(self.word_lengths)) + '\\\\n'\\n s += ' number of stems: ' + str(len(self.stems)) + '\\\\n'\\n s += ' number of sentence lengths: ' + str(len(self.sentence_lengths))\\\\\\n + '\\\\n'\\n s += ' number of punctuation types: ' + str(len(self.punctuation))\\n return s\",\n \"def dumps(self, indent=0):\\n outstr = \\\" \\\"*indent + \\\"MewloDbModel object '{0}' attribute values:\\\\n\\\".format(self.__class__.__name__)\\n public_props = (name for name in dir(object) if not name.startswith('_'))\\n for name in public_props:\\n outstr += \\\" \\\"*indent + \\\"{0}: {1}\\\\n\\\".format(name, str(getattr(self,name)))\\n return outstr\",\n \"def __str__(self):\\n model = self._meta.verbose_name.title()\\n title = self.title or str(_(\\\"Empty title\\\"))\\n\\n return f\\\"{model:s}: {title:s}\\\"\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\",\n \"def __repr__(self):\\n return self.to_str()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.85856134","0.7814518","0.77898884","0.7751367","0.7751367","0.7712228","0.76981676","0.76700574","0.7651133","0.7597206","0.75800353","0.7568254","0.7538184","0.75228703","0.7515832","0.7498764","0.74850684","0.74850684","0.7467648","0.74488163","0.7442643","0.74416703","0.7433768","0.7411771","0.7405439","0.7379557","0.7361716","0.7361716","0.732774","0.7325511","0.732528","0.73097324","0.73078936","0.73001266","0.7296789","0.7292791","0.7289445","0.7287187","0.7287187","0.7287187","0.7287187","0.7287187","0.7279803","0.7261615","0.7250399","0.7244789","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068","0.7223068"],"string":"[\n \"0.85856134\",\n \"0.7814518\",\n \"0.77898884\",\n \"0.7751367\",\n \"0.7751367\",\n \"0.7712228\",\n \"0.76981676\",\n \"0.76700574\",\n \"0.7651133\",\n \"0.7597206\",\n \"0.75800353\",\n \"0.7568254\",\n \"0.7538184\",\n \"0.75228703\",\n \"0.7515832\",\n \"0.7498764\",\n \"0.74850684\",\n \"0.74850684\",\n \"0.7467648\",\n \"0.74488163\",\n \"0.7442643\",\n \"0.74416703\",\n \"0.7433768\",\n \"0.7411771\",\n \"0.7405439\",\n \"0.7379557\",\n \"0.7361716\",\n \"0.7361716\",\n \"0.732774\",\n \"0.7325511\",\n \"0.732528\",\n \"0.73097324\",\n \"0.73078936\",\n \"0.73001266\",\n \"0.7296789\",\n \"0.7292791\",\n \"0.7289445\",\n \"0.7287187\",\n \"0.7287187\",\n \"0.7287187\",\n \"0.7287187\",\n \"0.7287187\",\n \"0.7279803\",\n \"0.7261615\",\n \"0.7250399\",\n \"0.7244789\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\",\n \"0.7223068\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":10698,"cells":{"query":{"kind":"string","value":"For `print` and `pprint`"},"document":{"kind":"string","value":"def __repr__(self):\n return self.to_str()"},"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 pprint(*args, **kwargs):\n if PRINTING:\n print(*args, **kwargs)","def print_out():\n pass","def custom_print(*objects):\n print(*objects, sep=OFS, end=ORS)","def _print(self, *args):\n return _ida_hexrays.vd_printer_t__print(self, *args)","def _printable(self):\n pass","def _print_custom(self):\n pass","def pypprint(*args, **kwargs): # type: ignore\n from typing import Iterable\n\n if len(args) != 1:\n print(*args, **kwargs)\n return\n x = args[0]\n if isinstance(x, dict):\n for k, v in x.items():\n print(f\"{k}:\", v, **kwargs)\n elif isinstance(x, Iterable) and not isinstance(x, str):\n for i in x:\n print(i, **kwargs)\n else:\n print(x, **kwargs)","def pprint(self):\n # just here for defining the interface; work is done in subclasses\n pass","def print(*args, **kwargs):\n with P_LOCK:\n __builtins__.print(*args, **kwargs)","def print(self):\n # Your implementation here","def p(value):\n pp.pprint(value)","def static_print(*args, __p=print, **kwargs):\n __p(*args, **kwargs)","def print(self, *args, **kwargs):\n print(*args, **kwargs)","def pprint(self):\n print(self.pprint_str())","def pprint(obj):\n for argname in sorted([x for x in dir(obj) if not x.startswith('__')]):\n # Skip callables\n if hasattr(getattr(obj, argname), '__call__'):\n continue\n print(\"{} : {}\".format(argname, getattr(obj, argname)))","def print_(self, s: str) -> None:","def my_pprint(obj, intend = 0):\n if isinstance(obj, dict):\n for key, value in obj.items():\n print(intend*\" \"+str(key)+\" : \")\n my_pprint(value, intend = intend + 4)\n print()\n elif isinstance(obj, list):\n for value in obj:\n my_pprint(value, intend = intend + 4)\n print()\n elif isinstance(obj, bytes):\n print(\"<binary data>\")\n \n else:\n try:\n print(intend*\" \"+str(obj))\n except UnicodeDecodeError:\n print(intend*\" \"\"<?>\")","def test_print(chikin):\n chikin.print()","def _print(self, text):\n\t\tif self.verbose:\n\t\t\tprint text","def out(*args):\r\n print(*args)","def __pprint(object, stream=None, indent=1, width=80, depth=None):\n printer = PrettyPrinterExt(\n stream=stream, indent=indent, width=width, depth=depth)\n printer.pprint(object)","def DumpPprint(data):\n #NOTE(g): Import is done here, instead of the top of the file, to not require this module if it is not used\n import pprint\n \n text = pprint.pformat(data)\n \n return text","def repl_print_statements():\n pass","def test_03_pass_print(self):\n print('Hello World!')","def p(self):\n self.printstdout = True","def print(*args, **kwargs):\n new_args = []\n for arg in args:\n if builtins.isinstance(arg, models.Point):\n new_args.append(\"({0}, {1})\".format(arg.x, arg.y))\n else:\n new_args.append(arg)\n\n builtins.print(*new_args, **kwargs)","def real_print(*args, **kwargs):\n\n kwargs.setdefault('file', real_stdout)\n _python_print_function(*args, **kwargs)","def to_print_out(self):\n self.error_throw('output')\n\n if self.rank_method == methods_of_ranking[3]: #'diversified_ranking'\n self.output_div('print')\n else:\n self.output('print')","def debug_print(debug_data):\n if DEBUG_MODE == \"true\":\n pp.pprint(debug_data)","def print(self):\r\n self.print_avec_separateur()","def pprint(self):\r\n for i in self.items():\r\n print '%s => %r'%i","def pprint(self, parameter_s=''):\n ptformatter = self.shell.display_formatter.formatters['text/plain']\n ptformatter.pprint = bool(1 - ptformatter.pprint)\n print('Pretty printing has been turned',\n ['OFF','ON'][ptformatter.pprint])","def print(self):\n print(self.pretty_str())","def test_print4(self):\n writer = StringIO()\n collatz_print(writer, 1, 1, 1)\n self.assertEqual(writer.getvalue(), \"1 1 1\\n\")","def eprint(*args, **kwargs):\n\tprint(*args, file=sys.stderr, **kwargs)","def _print(self, *args, **kwargs) -> None:\n # Only print in verbose mode\n if self._verbose:\n arglist = list(args)\n arglist[0] = f\"[buddy-{self._experiment_name}] {args[0]}\"\n print(*arglist, **kwargs)","def use_pypprint_for_implicit_print(self) -> None:\n if self.implicit_print is not None:\n self.implicit_print.func.id = \"pypprint\" # type: ignore\n # Make sure we import it later\n self.undefined.add(\"pypprint\")","def test_print(self):\n writer = StringIO()\n collatz_print(writer, 1, 10, 20)\n self.assertEqual(writer.getvalue(), \"1 10 20\\n\")","def pprint(self):\n return pformat(repr(self))","def printer(message):\n if VERBOSITY:\n pprint(message)","def rec_print(p):\n if len(p) == 0:\n return\n t = p.pop(0)\n print t\n rec_print(p)","def pformat(object):\r\n return PrettyPrinter().pformat(object)","def printc(*a, **kw):\n print(*a, **kw)","def pr(x):\n Card.print_pretty_cards(x)","def debug_print(self, *content):\n if self.debug:\n print(*content)","def pprint(object, stream=None):\r\n printer = PrettyPrinter(stream=stream)\r\n printer.pprint(object)","def safe_print(*objs, errors=\"replace\"):\n\tprint(*(to_stdout(str(o), errors) for o in objs))","def magic_Pprint(self, parameter_s=''):\n \n self.shell.outputcache.Pprint = 1 - self.shell.outputcache.Pprint\n print 'Pretty printing has been turned', \\\n ['OFF','ON'][self.shell.outputcache.Pprint]","def print_output(tree):\n print_value(tree)\n print_tree(tree)","def _Print(self, t):\n self.RaiseError(t, \"Print not supported\")","def vprint(*args, **kwargs ):\n\n forceprint = False\n for key in kwargs:\n if key == \"forceprint\":\n forceprint =kwargs[key]\n \n line = ''\n if debug or forceprint : \n for arg in args:\n line += str(arg) +\" \"\n log = open(exepath + 'pyframe.log', 'a') \n log.write(line + \"\\n\")\n log.close() \n print line","def eprint(*pargs, **kargs):\n print('\\u001b[31m', end='', file=sys.stderr)\n print(*pargs, file=sys.stderr, **kargs)\n print('\\u001b[0m', end='', file=sys.stderr)","def printer(obj, ident=''):\n import inspect\n print ident + obj.__class__.__name__.upper()\n ident += ' '\n lists = []\n for name in dir(obj):\n elem = getattr(obj, name)\n if isinstance(elem, list) and name != u'decoded_content':\n lists.append(elem)\n elif not inspect.ismethod(elem):\n if not name.startswith('__'):\n if name == u'data' and elem:\n print ident + u'data = '\n printer(elem, ident + ' ')\n else:\n print ident + u'%s\\t= %s' % (name, getattr(obj, name))\n for l in lists:\n for i in l:\n printer(i, ident + ' ')","def printer(obj, ident=''):\n import inspect\n print ident + obj.__class__.__name__.upper()\n ident += ' '\n lists = []\n for name in dir(obj):\n elem = getattr(obj, name)\n if isinstance(elem, list) and name != u'decoded_content':\n lists.append(elem)\n elif not inspect.ismethod(elem):\n if not name.startswith('__'):\n if name == u'data' and elem:\n print ident + u'data = '\n printer(elem, ident + ' ')\n else:\n print ident + u'%s\\t= %s' % (name, getattr(obj, name))\n for l in lists:\n for i in l:\n printer(i, ident + ' ')","def _print(self, *args):\n return _ida_hexrays.qstring_printer_t__print(self, *args)","def pprint(self):\n def pprintStr(node):\n s = \"(\" + str(node.value) \n for action in node.children:\n s = s + \", \" + pprintStr(node.children[action])\n s = s + \")\"\n return s\n\n print pprintStr(self)","def hook_print():\n sys.stdout = PrintHook()","def cmdPrint( self, *args):\n return self.cmd( *args, **{ 'verbose': True } )","def print_list(self):\r\n pass","def debugprint(obj, depth=-1, print_type=False,\r\n file=None, ids='CHAR', stop_on_name=False):\r\n if file == 'str':\r\n _file = StringIO()\r\n elif file is None:\r\n _file = sys.stdout\r\n else:\r\n _file = file\r\n done = dict()\r\n results_to_print = []\r\n order = []\r\n if isinstance(obj, gof.Variable):\r\n results_to_print.append(obj)\r\n elif isinstance(obj, gof.Apply):\r\n results_to_print.extend(obj.outputs)\r\n elif isinstance(obj, Function):\r\n results_to_print.extend(obj.maker.fgraph.outputs)\r\n order = obj.maker.fgraph.toposort()\r\n elif isinstance(obj, (list, tuple)):\r\n results_to_print.extend(obj)\r\n elif isinstance(obj, gof.FunctionGraph):\r\n results_to_print.extend(obj.outputs)\r\n order = obj.toposort()\r\n elif isinstance(obj, (int, long, float, numpy.ndarray)):\r\n print obj\r\n else:\r\n raise TypeError(\"debugprint cannot print an object of this type\", obj)\r\n for r in results_to_print:\r\n debugmode.debugprint(r, depth=depth, done=done, print_type=print_type,\r\n file=_file, order=order, ids=ids,\r\n stop_on_name=stop_on_name)\r\n if file is _file:\r\n return file\r\n elif file == 'str':\r\n return _file.getvalue()\r\n else:\r\n _file.flush()","def _get_print_fn(file=sys.stdout):\n def _print_fn(op, xin,):\n for attr in op.attrs:\n temp = getattr(xin, attr)\n if callable(temp):\n pmsg = temp()\n else:\n pmsg = temp\n print(op.message, attr, '=', pmsg, file=file)\n return _print_fn","def test_print1(self):\n writer = StringIO()\n collatz_print(writer, 100, 200, 125)\n self.assertEqual(writer.getvalue(), \"100 200 125\\n\")","def printOutput(self):\n pass","def _print(self, *args):\n return _ida_hexrays.cnumber_t__print(self, *args)","def setPrint():\n (e,d,sr,sw) = codecs.lookup('utf-8')\n unicode_to_utf8 = sw(sys.stdout)\n sys.stdout = unicode_to_utf8","def pr(string, verbose):\n if(verbose):\n print(string)","def print(*args, sep=\" \"):\n pass","def printv(self, *arg):\n if self.verbose:\n print(*arg)","def print(self):\n\n print(self)","def _p(self, *args, level=2, **kwargs):\n if self._verbosity >= level:\n print(*args, **kwargs)","def test_print2(self):\n writer = StringIO()\n collatz_print(writer, 201, 210, 89)\n self.assertEqual(writer.getvalue(), \"201 210 89\\n\")","def print_pointers(self):\n\n ### FILL IN ###","def foo_printer(self):\n print(\"\\nHi I'm {}\".format(self.foo))","def printed(method):\n\t\tdef wrapper(cls, *args):\n\t\t\tif cls.verbose:\n\t\t\t\treturn method(cls, *args)\n\t\treturn wrapper","def print_me(self, tabs=0, tab=' '):\n pre = tab*tabs\n print(pre+'Producer:')\n print(pre+' produces:', self._produces)\n print(pre+' consumes:', self._consumes)\n print(pre+' transfer:', self._transfer)\n print(pre+' capacity:', self._capacity)","def _print(cls, quad):\n\t\tprint(\"\\nLIGHT OUTPUT:\\n<<<<{}>>>>\".format(ast.literal_eval(str(cls.get_address_value(quad.result)))))\n\t\tprint(\"END\")\n\n\t\tvar = cls.get_address_value(quad.result)\n\t\tif isinstance(var, collections.Iterable):\n\t\t\tprint(\"DEEP COPY\")\n\t\t\tcls.print_queue.enqueue(copy.deepcopy(var))\n\t\telse:\n\t\t\tcls.print_queue.enqueue(var)","def printout(*args, **kwargs):\n console_print(sys.stdout, *args, **kwargs)","def pprint(x):\n if is_theano_object(x):\n return _gettheano().printing.pprint(x)\n else:\n return str(x)","def PrettyPrint(self):\r\n print(self.data)\r\n return","def print(self):\n self.print_avec_separateur(\" \")","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def eprint(*args, **kwargs):\n print(*args, file=sys.stderr, **kwargs)","def pprint_helper(self, angle, indent):\n # just here for defining the interface; work is done in subclasses\n pass","def _pprint(params, offset=0, printer=repr):\n # Do a multi-line justified repr:\n param_names = [p for p in params.keys() if p is not \"cost\"]\n param_names.sort()\n\n params_list = list()\n this_line_length = offset\n line_sep = ',\\n' + (1 + offset // 2) * ' '\n for i, name in enumerate(param_names):\n value = params[name]\n if isinstance(value, float):\n this_repr = '%s=%s' % (name, str(value))\n else:\n this_repr = '%s=%s' % (name, printer(value))\n if len(this_repr) > 500:\n this_repr = this_repr[:300] + '...' + this_repr[-100:]\n if i > 0:\n if (this_line_length + len(this_repr) >= 75 or '\\n' in this_repr):\n params_list.append(line_sep)\n this_line_length = len(line_sep)\n else:\n params_list.append(', ')\n this_line_length += 2\n params_list.append(this_repr)\n this_line_length += len(this_repr)\n # options = np.get_printoptions()\n # np.set_printoptions(**options)\n lines = ''.join(params_list)\n # Strip trailing space to avoid nightmare in doctests\n lines = '\\n'.join(l.rstrip(' ') for l in lines.split('\\n'))\n return lines","def init_printing(pretty_print=True, order=None, use_unicode=None):\n if pretty_print:\n stringify_func = lambda arg: pretty(arg, order=order, use_unicode=use_unicode)\n else:\n stringify_func = sstrrepr\n\n try:\n import IPython\n\n ip = IPython.ipapi.get()\n\n if ip is not None:\n def result_display(self, arg):\n \"\"\"IPython's pretty-printer display hook.\n\n This function was adapted from:\n\n ipython/IPython/hooks.py:155\n\n \"\"\"\n if self.rc.pprint:\n out = stringify_func(arg)\n\n if '\\n' in out:\n print\n\n print out\n else:\n print repr(arg)\n\n ip.set_hook('result_display', result_display)\n return\n except ImportError:\n pass\n\n import __builtin__, sys\n\n def displayhook(arg):\n \"\"\"Python's pretty-printer display hook.\n\n This function was adapted from:\n\n http://www.python.org/dev/peps/pep-0217/\n\n \"\"\"\n if arg is not None:\n __builtin__._ = None\n print stringify_func(arg)\n __builtin__._ = arg\n\n sys.displayhook = displayhook","def print_verbose(self) -> None:\n print(self)\n if self.meta is not None:\n print(self.meta.__repr__())","def _print(self, *args):\n return _ida_hexrays.cinsn_t__print(self, *args)","def my_print(self):\n if self.__size == 0:\n print(\"\")\n return\n [print(\"\") for x in range(0, self.__position[1])]\n for i in range(0, self.__size):\n [print(\" \", end=\"\") for i in range(0, self.__position[0])]\n [print(\"#\", end=\"\") for j in range(0, self.__size)]\n print(\"\")","def sequential_print_statements():\n pass","def print_post():\n print('| | |'),","def print_(*args, **kwargs):\r\n fp = kwargs.pop(\"file\", sys.stdout)\r\n if fp is None:\r\n return\r\n def write(data):\r\n if not isinstance(data, basestring):\r\n data = str(data)\r\n fp.write(data)\r\n want_unicode = False\r\n sep = kwargs.pop(\"sep\", None)\r\n if sep is not None:\r\n if isinstance(sep, unicode):\r\n want_unicode = True\r\n elif not isinstance(sep, str):\r\n raise TypeError(\"sep must be None or a string\")\r\n end = kwargs.pop(\"end\", None)\r\n if end is not None:\r\n if isinstance(end, unicode):\r\n want_unicode = True\r\n elif not isinstance(end, str):\r\n raise TypeError(\"end must be None or a string\")\r\n if kwargs:\r\n raise TypeError(\"invalid keyword arguments to print()\")\r\n if not want_unicode:\r\n for arg in args:\r\n if isinstance(arg, unicode):\r\n want_unicode = True\r\n break\r\n if want_unicode:\r\n newline = unicode(\"\\n\")\r\n space = unicode(\" \")\r\n else:\r\n newline = \"\\n\"\r\n space = \" \"\r\n if sep is None:\r\n sep = space\r\n if end is None:\r\n end = newline\r\n for i, arg in enumerate(args):\r\n if i:\r\n write(sep)\r\n write(arg)\r\n write(end)","def print_(*args, **kwargs):\r\n fp = kwargs.pop(\"file\", sys.stdout)\r\n if fp is None:\r\n return\r\n def write(data):\r\n if not isinstance(data, basestring):\r\n data = str(data)\r\n fp.write(data)\r\n want_unicode = False\r\n sep = kwargs.pop(\"sep\", None)\r\n if sep is not None:\r\n if isinstance(sep, unicode):\r\n want_unicode = True\r\n elif not isinstance(sep, str):\r\n raise TypeError(\"sep must be None or a string\")\r\n end = kwargs.pop(\"end\", None)\r\n if end is not None:\r\n if isinstance(end, unicode):\r\n want_unicode = True\r\n elif not isinstance(end, str):\r\n raise TypeError(\"end must be None or a string\")\r\n if kwargs:\r\n raise TypeError(\"invalid keyword arguments to print()\")\r\n if not want_unicode:\r\n for arg in args:\r\n if isinstance(arg, unicode):\r\n want_unicode = True\r\n break\r\n if want_unicode:\r\n newline = unicode(\"\\n\")\r\n space = unicode(\" \")\r\n else:\r\n newline = \"\\n\"\r\n space = \" \"\r\n if sep is None:\r\n sep = space\r\n if end is None:\r\n end = newline\r\n for i, arg in enumerate(args):\r\n if i:\r\n write(sep)\r\n write(arg)\r\n write(end)","def debugprint(r, prefix='', depth=-1, done=None, print_type=False,\r\n file=sys.stdout, print_destroy_map=False,\r\n print_view_map=False, order=None, ids='CHAR',\r\n stop_on_name=False, prefix_child=None):\r\n if depth == 0:\r\n return\r\n\r\n if order is None:\r\n order = []\r\n\r\n if done is None:\r\n done = dict()\r\n\r\n if print_type:\r\n type_str = ' <%s>' % r.type\r\n else:\r\n type_str = ''\r\n\r\n if prefix_child is None:\r\n prefix_child = prefix\r\n\r\n def get_id_str(obj):\r\n if obj in done:\r\n id_str = done[obj]\r\n elif ids == \"id\":\r\n id_str = \"[@%s]\" % str(id(r))\r\n elif ids == \"int\":\r\n id_str = \"[@%s]\" % str(len(done))\r\n elif ids == \"CHAR\":\r\n id_str = \"[@%s]\" % char_from_number(len(done))\r\n elif ids == \"\":\r\n id_str = \"\"\r\n done[obj] = id_str\r\n return id_str\r\n\r\n if hasattr(r.owner, 'op'):\r\n # this variable is the output of computation,\r\n # so just print out the apply\r\n a = r.owner\r\n\r\n r_name = getattr(r, 'name', '')\r\n # normally if the name isn't set, it'll be None, so\r\n # r_name is None here\r\n if r_name is None:\r\n r_name = ''\r\n\r\n if print_destroy_map:\r\n destroy_map_str = str(getattr(r.owner.op, 'destroy_map', ''))\r\n else:\r\n destroy_map_str = ''\r\n\r\n if print_view_map:\r\n view_map_str = str(getattr(r.owner.op, 'view_map', ''))\r\n else:\r\n view_map_str = ''\r\n if destroy_map_str and destroy_map_str != '{}':\r\n destroy_map_str = 'd=' + destroy_map_str\r\n if view_map_str and view_map_str != '{}':\r\n view_map_str = 'v=' + view_map_str\r\n\r\n o = ''\r\n if order:\r\n o = str(order.index(r.owner))\r\n already_printed = a in done # get_id_str put it in the dict\r\n id_str = get_id_str(a)\r\n\r\n if len(a.outputs) == 1:\r\n print >> file, '%s%s %s%s \\'%s\\' %s %s %s' % (prefix, a.op,\r\n id_str,\r\n type_str, r_name,\r\n destroy_map_str,\r\n view_map_str,\r\n o)\r\n else:\r\n print >> file, '%s%s.%i %s%s \\'%s\\' %s %s %s' % (prefix, a.op,\r\n a.outputs.index(r),\r\n id_str, type_str,\r\n r_name,\r\n destroy_map_str,\r\n view_map_str,\r\n o)\r\n if not already_printed:\r\n if (not stop_on_name or\r\n not (hasattr(r, 'name') and r.name is not None)):\r\n new_prefix = prefix_child + ' |'\r\n new_prefix_child = prefix_child + ' |'\r\n for idx, i in enumerate(a.inputs):\r\n if idx == len(a.inputs) - 1:\r\n new_prefix_child = prefix_child + ' '\r\n\r\n debugprint(i, new_prefix, depth=depth - 1, done=done,\r\n print_type=print_type, file=file, order=order,\r\n ids=ids, stop_on_name=stop_on_name,\r\n prefix_child=new_prefix_child)\r\n else:\r\n #this is an input variable\r\n id_str = get_id_str(r)\r\n print >> file, '%s%s %s%s' % (prefix, r, id_str, type_str)\r\n\r\n return file","def bpprint(self, out=None):\n if out is None:\n out = sys.stdout\n print(self.bpformat(), file=out)","def vprint(expr, **settings):\n\n outstr = vsprint(expr, **settings)\n\n import builtins\n if (outstr != 'None'):\n builtins._ = outstr\n print(outstr)","def _pprint(params, offset=0, printer=repr):\n # Do a multi-line justified repr:\n options = numpy.get_printoptions()\n numpy.set_printoptions(precision=5, threshold=64, edgeitems=2)\n params_list = list()\n this_line_length = offset\n line_sep = ',\\n' + (1 + offset // 2) * ' '\n for i, (k, v) in enumerate(sorted(params.items())):\n if isinstance(v, float):\n # use str for representing floating point numbers\n # this way we get consistent representation across\n # architectures and versions.\n this_repr = '%s=%s' % (k, str(v))\n else:\n # use repr of the rest\n this_repr = '%s=%s' % (k, printer(v))\n if len(this_repr) > 500:\n this_repr = this_repr[:300] + '...' + this_repr[-100:]\n if i > 0:\n if this_line_length + len(this_repr) >= 75 or '\\n' in this_repr:\n params_list.append(line_sep)\n this_line_length = len(line_sep)\n else:\n params_list.append(', ')\n this_line_length += 2\n params_list.append(this_repr)\n this_line_length += len(this_repr)\n\n numpy.set_printoptions(**options)\n lines = ''.join(params_list)\n # Strip trailing space to avoid nightmare in doctests\n lines = '\\n'.join(l.rstrip(' ') for l in lines.split('\\n'))\n return lines","def print_(*args, **kwargs):\n fp = kwargs.pop(\"file\", sys.stdout)\n if fp is None:\n return\n\n def write(data):\n if not isinstance(data, basestring):\n data = str(data)\n fp.write(data)\n want_unicode = False\n sep = kwargs.pop(\"sep\", None)\n if sep is not None:\n if isinstance(sep, unicode):\n want_unicode = True\n elif not isinstance(sep, str):\n raise TypeError(\"sep must be None or a string\")\n end = kwargs.pop(\"end\", None)\n if end is not None:\n if isinstance(end, unicode):\n want_unicode = True\n elif not isinstance(end, str):\n raise TypeError(\"end must be None or a string\")\n if kwargs:\n raise TypeError(\"invalid keyword arguments to print()\")\n if not want_unicode:\n for arg in args:\n if isinstance(arg, unicode):\n want_unicode = True\n break\n if want_unicode:\n newline = unicode(\"\\n\")\n space = unicode(\" \")\n else:\n newline = \"\\n\"\n space = \" \"\n if sep is None:\n sep = space\n if end is None:\n end = newline\n for i, arg in enumerate(args):\n if i:\n write(sep)\n write(arg)\n write(end)"],"string":"[\n \"def pprint(*args, **kwargs):\\n if PRINTING:\\n print(*args, **kwargs)\",\n \"def print_out():\\n pass\",\n \"def custom_print(*objects):\\n print(*objects, sep=OFS, end=ORS)\",\n \"def _print(self, *args):\\n return _ida_hexrays.vd_printer_t__print(self, *args)\",\n \"def _printable(self):\\n pass\",\n \"def _print_custom(self):\\n pass\",\n \"def pypprint(*args, **kwargs): # type: ignore\\n from typing import Iterable\\n\\n if len(args) != 1:\\n print(*args, **kwargs)\\n return\\n x = args[0]\\n if isinstance(x, dict):\\n for k, v in x.items():\\n print(f\\\"{k}:\\\", v, **kwargs)\\n elif isinstance(x, Iterable) and not isinstance(x, str):\\n for i in x:\\n print(i, **kwargs)\\n else:\\n print(x, **kwargs)\",\n \"def pprint(self):\\n # just here for defining the interface; work is done in subclasses\\n pass\",\n \"def print(*args, **kwargs):\\n with P_LOCK:\\n __builtins__.print(*args, **kwargs)\",\n \"def print(self):\\n # Your implementation here\",\n \"def p(value):\\n pp.pprint(value)\",\n \"def static_print(*args, __p=print, **kwargs):\\n __p(*args, **kwargs)\",\n \"def print(self, *args, **kwargs):\\n print(*args, **kwargs)\",\n \"def pprint(self):\\n print(self.pprint_str())\",\n \"def pprint(obj):\\n for argname in sorted([x for x in dir(obj) if not x.startswith('__')]):\\n # Skip callables\\n if hasattr(getattr(obj, argname), '__call__'):\\n continue\\n print(\\\"{} : {}\\\".format(argname, getattr(obj, argname)))\",\n \"def print_(self, s: str) -> None:\",\n \"def my_pprint(obj, intend = 0):\\n if isinstance(obj, dict):\\n for key, value in obj.items():\\n print(intend*\\\" \\\"+str(key)+\\\" : \\\")\\n my_pprint(value, intend = intend + 4)\\n print()\\n elif isinstance(obj, list):\\n for value in obj:\\n my_pprint(value, intend = intend + 4)\\n print()\\n elif isinstance(obj, bytes):\\n print(\\\"<binary data>\\\")\\n \\n else:\\n try:\\n print(intend*\\\" \\\"+str(obj))\\n except UnicodeDecodeError:\\n print(intend*\\\" \\\"\\\"<?>\\\")\",\n \"def test_print(chikin):\\n chikin.print()\",\n \"def _print(self, text):\\n\\t\\tif self.verbose:\\n\\t\\t\\tprint text\",\n \"def out(*args):\\r\\n print(*args)\",\n \"def __pprint(object, stream=None, indent=1, width=80, depth=None):\\n printer = PrettyPrinterExt(\\n stream=stream, indent=indent, width=width, depth=depth)\\n printer.pprint(object)\",\n \"def DumpPprint(data):\\n #NOTE(g): Import is done here, instead of the top of the file, to not require this module if it is not used\\n import pprint\\n \\n text = pprint.pformat(data)\\n \\n return text\",\n \"def repl_print_statements():\\n pass\",\n \"def test_03_pass_print(self):\\n print('Hello World!')\",\n \"def p(self):\\n self.printstdout = True\",\n \"def print(*args, **kwargs):\\n new_args = []\\n for arg in args:\\n if builtins.isinstance(arg, models.Point):\\n new_args.append(\\\"({0}, {1})\\\".format(arg.x, arg.y))\\n else:\\n new_args.append(arg)\\n\\n builtins.print(*new_args, **kwargs)\",\n \"def real_print(*args, **kwargs):\\n\\n kwargs.setdefault('file', real_stdout)\\n _python_print_function(*args, **kwargs)\",\n \"def to_print_out(self):\\n self.error_throw('output')\\n\\n if self.rank_method == methods_of_ranking[3]: #'diversified_ranking'\\n self.output_div('print')\\n else:\\n self.output('print')\",\n \"def debug_print(debug_data):\\n if DEBUG_MODE == \\\"true\\\":\\n pp.pprint(debug_data)\",\n \"def print(self):\\r\\n self.print_avec_separateur()\",\n \"def pprint(self):\\r\\n for i in self.items():\\r\\n print '%s => %r'%i\",\n \"def pprint(self, parameter_s=''):\\n ptformatter = self.shell.display_formatter.formatters['text/plain']\\n ptformatter.pprint = bool(1 - ptformatter.pprint)\\n print('Pretty printing has been turned',\\n ['OFF','ON'][ptformatter.pprint])\",\n \"def print(self):\\n print(self.pretty_str())\",\n \"def test_print4(self):\\n writer = StringIO()\\n collatz_print(writer, 1, 1, 1)\\n self.assertEqual(writer.getvalue(), \\\"1 1 1\\\\n\\\")\",\n \"def eprint(*args, **kwargs):\\n\\tprint(*args, file=sys.stderr, **kwargs)\",\n \"def _print(self, *args, **kwargs) -> None:\\n # Only print in verbose mode\\n if self._verbose:\\n arglist = list(args)\\n arglist[0] = f\\\"[buddy-{self._experiment_name}] {args[0]}\\\"\\n print(*arglist, **kwargs)\",\n \"def use_pypprint_for_implicit_print(self) -> None:\\n if self.implicit_print is not None:\\n self.implicit_print.func.id = \\\"pypprint\\\" # type: ignore\\n # Make sure we import it later\\n self.undefined.add(\\\"pypprint\\\")\",\n \"def test_print(self):\\n writer = StringIO()\\n collatz_print(writer, 1, 10, 20)\\n self.assertEqual(writer.getvalue(), \\\"1 10 20\\\\n\\\")\",\n \"def pprint(self):\\n return pformat(repr(self))\",\n \"def printer(message):\\n if VERBOSITY:\\n pprint(message)\",\n \"def rec_print(p):\\n if len(p) == 0:\\n return\\n t = p.pop(0)\\n print t\\n rec_print(p)\",\n \"def pformat(object):\\r\\n return PrettyPrinter().pformat(object)\",\n \"def printc(*a, **kw):\\n print(*a, **kw)\",\n \"def pr(x):\\n Card.print_pretty_cards(x)\",\n \"def debug_print(self, *content):\\n if self.debug:\\n print(*content)\",\n \"def pprint(object, stream=None):\\r\\n printer = PrettyPrinter(stream=stream)\\r\\n printer.pprint(object)\",\n \"def safe_print(*objs, errors=\\\"replace\\\"):\\n\\tprint(*(to_stdout(str(o), errors) for o in objs))\",\n \"def magic_Pprint(self, parameter_s=''):\\n \\n self.shell.outputcache.Pprint = 1 - self.shell.outputcache.Pprint\\n print 'Pretty printing has been turned', \\\\\\n ['OFF','ON'][self.shell.outputcache.Pprint]\",\n \"def print_output(tree):\\n print_value(tree)\\n print_tree(tree)\",\n \"def _Print(self, t):\\n self.RaiseError(t, \\\"Print not supported\\\")\",\n \"def vprint(*args, **kwargs ):\\n\\n forceprint = False\\n for key in kwargs:\\n if key == \\\"forceprint\\\":\\n forceprint =kwargs[key]\\n \\n line = ''\\n if debug or forceprint : \\n for arg in args:\\n line += str(arg) +\\\" \\\"\\n log = open(exepath + 'pyframe.log', 'a') \\n log.write(line + \\\"\\\\n\\\")\\n log.close() \\n print line\",\n \"def eprint(*pargs, **kargs):\\n print('\\\\u001b[31m', end='', file=sys.stderr)\\n print(*pargs, file=sys.stderr, **kargs)\\n print('\\\\u001b[0m', end='', file=sys.stderr)\",\n \"def printer(obj, ident=''):\\n import inspect\\n print ident + obj.__class__.__name__.upper()\\n ident += ' '\\n lists = []\\n for name in dir(obj):\\n elem = getattr(obj, name)\\n if isinstance(elem, list) and name != u'decoded_content':\\n lists.append(elem)\\n elif not inspect.ismethod(elem):\\n if not name.startswith('__'):\\n if name == u'data' and elem:\\n print ident + u'data = '\\n printer(elem, ident + ' ')\\n else:\\n print ident + u'%s\\\\t= %s' % (name, getattr(obj, name))\\n for l in lists:\\n for i in l:\\n printer(i, ident + ' ')\",\n \"def printer(obj, ident=''):\\n import inspect\\n print ident + obj.__class__.__name__.upper()\\n ident += ' '\\n lists = []\\n for name in dir(obj):\\n elem = getattr(obj, name)\\n if isinstance(elem, list) and name != u'decoded_content':\\n lists.append(elem)\\n elif not inspect.ismethod(elem):\\n if not name.startswith('__'):\\n if name == u'data' and elem:\\n print ident + u'data = '\\n printer(elem, ident + ' ')\\n else:\\n print ident + u'%s\\\\t= %s' % (name, getattr(obj, name))\\n for l in lists:\\n for i in l:\\n printer(i, ident + ' ')\",\n \"def _print(self, *args):\\n return _ida_hexrays.qstring_printer_t__print(self, *args)\",\n \"def pprint(self):\\n def pprintStr(node):\\n s = \\\"(\\\" + str(node.value) \\n for action in node.children:\\n s = s + \\\", \\\" + pprintStr(node.children[action])\\n s = s + \\\")\\\"\\n return s\\n\\n print pprintStr(self)\",\n \"def hook_print():\\n sys.stdout = PrintHook()\",\n \"def cmdPrint( self, *args):\\n return self.cmd( *args, **{ 'verbose': True } )\",\n \"def print_list(self):\\r\\n pass\",\n \"def debugprint(obj, depth=-1, print_type=False,\\r\\n file=None, ids='CHAR', stop_on_name=False):\\r\\n if file == 'str':\\r\\n _file = StringIO()\\r\\n elif file is None:\\r\\n _file = sys.stdout\\r\\n else:\\r\\n _file = file\\r\\n done = dict()\\r\\n results_to_print = []\\r\\n order = []\\r\\n if isinstance(obj, gof.Variable):\\r\\n results_to_print.append(obj)\\r\\n elif isinstance(obj, gof.Apply):\\r\\n results_to_print.extend(obj.outputs)\\r\\n elif isinstance(obj, Function):\\r\\n results_to_print.extend(obj.maker.fgraph.outputs)\\r\\n order = obj.maker.fgraph.toposort()\\r\\n elif isinstance(obj, (list, tuple)):\\r\\n results_to_print.extend(obj)\\r\\n elif isinstance(obj, gof.FunctionGraph):\\r\\n results_to_print.extend(obj.outputs)\\r\\n order = obj.toposort()\\r\\n elif isinstance(obj, (int, long, float, numpy.ndarray)):\\r\\n print obj\\r\\n else:\\r\\n raise TypeError(\\\"debugprint cannot print an object of this type\\\", obj)\\r\\n for r in results_to_print:\\r\\n debugmode.debugprint(r, depth=depth, done=done, print_type=print_type,\\r\\n file=_file, order=order, ids=ids,\\r\\n stop_on_name=stop_on_name)\\r\\n if file is _file:\\r\\n return file\\r\\n elif file == 'str':\\r\\n return _file.getvalue()\\r\\n else:\\r\\n _file.flush()\",\n \"def _get_print_fn(file=sys.stdout):\\n def _print_fn(op, xin,):\\n for attr in op.attrs:\\n temp = getattr(xin, attr)\\n if callable(temp):\\n pmsg = temp()\\n else:\\n pmsg = temp\\n print(op.message, attr, '=', pmsg, file=file)\\n return _print_fn\",\n \"def test_print1(self):\\n writer = StringIO()\\n collatz_print(writer, 100, 200, 125)\\n self.assertEqual(writer.getvalue(), \\\"100 200 125\\\\n\\\")\",\n \"def printOutput(self):\\n pass\",\n \"def _print(self, *args):\\n return _ida_hexrays.cnumber_t__print(self, *args)\",\n \"def setPrint():\\n (e,d,sr,sw) = codecs.lookup('utf-8')\\n unicode_to_utf8 = sw(sys.stdout)\\n sys.stdout = unicode_to_utf8\",\n \"def pr(string, verbose):\\n if(verbose):\\n print(string)\",\n \"def print(*args, sep=\\\" \\\"):\\n pass\",\n \"def printv(self, *arg):\\n if self.verbose:\\n print(*arg)\",\n \"def print(self):\\n\\n print(self)\",\n \"def _p(self, *args, level=2, **kwargs):\\n if self._verbosity >= level:\\n print(*args, **kwargs)\",\n \"def test_print2(self):\\n writer = StringIO()\\n collatz_print(writer, 201, 210, 89)\\n self.assertEqual(writer.getvalue(), \\\"201 210 89\\\\n\\\")\",\n \"def print_pointers(self):\\n\\n ### FILL IN ###\",\n \"def foo_printer(self):\\n print(\\\"\\\\nHi I'm {}\\\".format(self.foo))\",\n \"def printed(method):\\n\\t\\tdef wrapper(cls, *args):\\n\\t\\t\\tif cls.verbose:\\n\\t\\t\\t\\treturn method(cls, *args)\\n\\t\\treturn wrapper\",\n \"def print_me(self, tabs=0, tab=' '):\\n pre = tab*tabs\\n print(pre+'Producer:')\\n print(pre+' produces:', self._produces)\\n print(pre+' consumes:', self._consumes)\\n print(pre+' transfer:', self._transfer)\\n print(pre+' capacity:', self._capacity)\",\n \"def _print(cls, quad):\\n\\t\\tprint(\\\"\\\\nLIGHT OUTPUT:\\\\n<<<<{}>>>>\\\".format(ast.literal_eval(str(cls.get_address_value(quad.result)))))\\n\\t\\tprint(\\\"END\\\")\\n\\n\\t\\tvar = cls.get_address_value(quad.result)\\n\\t\\tif isinstance(var, collections.Iterable):\\n\\t\\t\\tprint(\\\"DEEP COPY\\\")\\n\\t\\t\\tcls.print_queue.enqueue(copy.deepcopy(var))\\n\\t\\telse:\\n\\t\\t\\tcls.print_queue.enqueue(var)\",\n \"def printout(*args, **kwargs):\\n console_print(sys.stdout, *args, **kwargs)\",\n \"def pprint(x):\\n if is_theano_object(x):\\n return _gettheano().printing.pprint(x)\\n else:\\n return str(x)\",\n \"def PrettyPrint(self):\\r\\n print(self.data)\\r\\n return\",\n \"def print(self):\\n self.print_avec_separateur(\\\" \\\")\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def eprint(*args, **kwargs):\\n print(*args, file=sys.stderr, **kwargs)\",\n \"def pprint_helper(self, angle, indent):\\n # just here for defining the interface; work is done in subclasses\\n pass\",\n \"def _pprint(params, offset=0, printer=repr):\\n # Do a multi-line justified repr:\\n param_names = [p for p in params.keys() if p is not \\\"cost\\\"]\\n param_names.sort()\\n\\n params_list = list()\\n this_line_length = offset\\n line_sep = ',\\\\n' + (1 + offset // 2) * ' '\\n for i, name in enumerate(param_names):\\n value = params[name]\\n if isinstance(value, float):\\n this_repr = '%s=%s' % (name, str(value))\\n else:\\n this_repr = '%s=%s' % (name, printer(value))\\n if len(this_repr) > 500:\\n this_repr = this_repr[:300] + '...' + this_repr[-100:]\\n if i > 0:\\n if (this_line_length + len(this_repr) >= 75 or '\\\\n' in this_repr):\\n params_list.append(line_sep)\\n this_line_length = len(line_sep)\\n else:\\n params_list.append(', ')\\n this_line_length += 2\\n params_list.append(this_repr)\\n this_line_length += len(this_repr)\\n # options = np.get_printoptions()\\n # np.set_printoptions(**options)\\n lines = ''.join(params_list)\\n # Strip trailing space to avoid nightmare in doctests\\n lines = '\\\\n'.join(l.rstrip(' ') for l in lines.split('\\\\n'))\\n return lines\",\n \"def init_printing(pretty_print=True, order=None, use_unicode=None):\\n if pretty_print:\\n stringify_func = lambda arg: pretty(arg, order=order, use_unicode=use_unicode)\\n else:\\n stringify_func = sstrrepr\\n\\n try:\\n import IPython\\n\\n ip = IPython.ipapi.get()\\n\\n if ip is not None:\\n def result_display(self, arg):\\n \\\"\\\"\\\"IPython's pretty-printer display hook.\\n\\n This function was adapted from:\\n\\n ipython/IPython/hooks.py:155\\n\\n \\\"\\\"\\\"\\n if self.rc.pprint:\\n out = stringify_func(arg)\\n\\n if '\\\\n' in out:\\n print\\n\\n print out\\n else:\\n print repr(arg)\\n\\n ip.set_hook('result_display', result_display)\\n return\\n except ImportError:\\n pass\\n\\n import __builtin__, sys\\n\\n def displayhook(arg):\\n \\\"\\\"\\\"Python's pretty-printer display hook.\\n\\n This function was adapted from:\\n\\n http://www.python.org/dev/peps/pep-0217/\\n\\n \\\"\\\"\\\"\\n if arg is not None:\\n __builtin__._ = None\\n print stringify_func(arg)\\n __builtin__._ = arg\\n\\n sys.displayhook = displayhook\",\n \"def print_verbose(self) -> None:\\n print(self)\\n if self.meta is not None:\\n print(self.meta.__repr__())\",\n \"def _print(self, *args):\\n return _ida_hexrays.cinsn_t__print(self, *args)\",\n \"def my_print(self):\\n if self.__size == 0:\\n print(\\\"\\\")\\n return\\n [print(\\\"\\\") for x in range(0, self.__position[1])]\\n for i in range(0, self.__size):\\n [print(\\\" \\\", end=\\\"\\\") for i in range(0, self.__position[0])]\\n [print(\\\"#\\\", end=\\\"\\\") for j in range(0, self.__size)]\\n print(\\\"\\\")\",\n \"def sequential_print_statements():\\n pass\",\n \"def print_post():\\n print('| | |'),\",\n \"def print_(*args, **kwargs):\\r\\n fp = kwargs.pop(\\\"file\\\", sys.stdout)\\r\\n if fp is None:\\r\\n return\\r\\n def write(data):\\r\\n if not isinstance(data, basestring):\\r\\n data = str(data)\\r\\n fp.write(data)\\r\\n want_unicode = False\\r\\n sep = kwargs.pop(\\\"sep\\\", None)\\r\\n if sep is not None:\\r\\n if isinstance(sep, unicode):\\r\\n want_unicode = True\\r\\n elif not isinstance(sep, str):\\r\\n raise TypeError(\\\"sep must be None or a string\\\")\\r\\n end = kwargs.pop(\\\"end\\\", None)\\r\\n if end is not None:\\r\\n if isinstance(end, unicode):\\r\\n want_unicode = True\\r\\n elif not isinstance(end, str):\\r\\n raise TypeError(\\\"end must be None or a string\\\")\\r\\n if kwargs:\\r\\n raise TypeError(\\\"invalid keyword arguments to print()\\\")\\r\\n if not want_unicode:\\r\\n for arg in args:\\r\\n if isinstance(arg, unicode):\\r\\n want_unicode = True\\r\\n break\\r\\n if want_unicode:\\r\\n newline = unicode(\\\"\\\\n\\\")\\r\\n space = unicode(\\\" \\\")\\r\\n else:\\r\\n newline = \\\"\\\\n\\\"\\r\\n space = \\\" \\\"\\r\\n if sep is None:\\r\\n sep = space\\r\\n if end is None:\\r\\n end = newline\\r\\n for i, arg in enumerate(args):\\r\\n if i:\\r\\n write(sep)\\r\\n write(arg)\\r\\n write(end)\",\n \"def print_(*args, **kwargs):\\r\\n fp = kwargs.pop(\\\"file\\\", sys.stdout)\\r\\n if fp is None:\\r\\n return\\r\\n def write(data):\\r\\n if not isinstance(data, basestring):\\r\\n data = str(data)\\r\\n fp.write(data)\\r\\n want_unicode = False\\r\\n sep = kwargs.pop(\\\"sep\\\", None)\\r\\n if sep is not None:\\r\\n if isinstance(sep, unicode):\\r\\n want_unicode = True\\r\\n elif not isinstance(sep, str):\\r\\n raise TypeError(\\\"sep must be None or a string\\\")\\r\\n end = kwargs.pop(\\\"end\\\", None)\\r\\n if end is not None:\\r\\n if isinstance(end, unicode):\\r\\n want_unicode = True\\r\\n elif not isinstance(end, str):\\r\\n raise TypeError(\\\"end must be None or a string\\\")\\r\\n if kwargs:\\r\\n raise TypeError(\\\"invalid keyword arguments to print()\\\")\\r\\n if not want_unicode:\\r\\n for arg in args:\\r\\n if isinstance(arg, unicode):\\r\\n want_unicode = True\\r\\n break\\r\\n if want_unicode:\\r\\n newline = unicode(\\\"\\\\n\\\")\\r\\n space = unicode(\\\" \\\")\\r\\n else:\\r\\n newline = \\\"\\\\n\\\"\\r\\n space = \\\" \\\"\\r\\n if sep is None:\\r\\n sep = space\\r\\n if end is None:\\r\\n end = newline\\r\\n for i, arg in enumerate(args):\\r\\n if i:\\r\\n write(sep)\\r\\n write(arg)\\r\\n write(end)\",\n \"def debugprint(r, prefix='', depth=-1, done=None, print_type=False,\\r\\n file=sys.stdout, print_destroy_map=False,\\r\\n print_view_map=False, order=None, ids='CHAR',\\r\\n stop_on_name=False, prefix_child=None):\\r\\n if depth == 0:\\r\\n return\\r\\n\\r\\n if order is None:\\r\\n order = []\\r\\n\\r\\n if done is None:\\r\\n done = dict()\\r\\n\\r\\n if print_type:\\r\\n type_str = ' <%s>' % r.type\\r\\n else:\\r\\n type_str = ''\\r\\n\\r\\n if prefix_child is None:\\r\\n prefix_child = prefix\\r\\n\\r\\n def get_id_str(obj):\\r\\n if obj in done:\\r\\n id_str = done[obj]\\r\\n elif ids == \\\"id\\\":\\r\\n id_str = \\\"[@%s]\\\" % str(id(r))\\r\\n elif ids == \\\"int\\\":\\r\\n id_str = \\\"[@%s]\\\" % str(len(done))\\r\\n elif ids == \\\"CHAR\\\":\\r\\n id_str = \\\"[@%s]\\\" % char_from_number(len(done))\\r\\n elif ids == \\\"\\\":\\r\\n id_str = \\\"\\\"\\r\\n done[obj] = id_str\\r\\n return id_str\\r\\n\\r\\n if hasattr(r.owner, 'op'):\\r\\n # this variable is the output of computation,\\r\\n # so just print out the apply\\r\\n a = r.owner\\r\\n\\r\\n r_name = getattr(r, 'name', '')\\r\\n # normally if the name isn't set, it'll be None, so\\r\\n # r_name is None here\\r\\n if r_name is None:\\r\\n r_name = ''\\r\\n\\r\\n if print_destroy_map:\\r\\n destroy_map_str = str(getattr(r.owner.op, 'destroy_map', ''))\\r\\n else:\\r\\n destroy_map_str = ''\\r\\n\\r\\n if print_view_map:\\r\\n view_map_str = str(getattr(r.owner.op, 'view_map', ''))\\r\\n else:\\r\\n view_map_str = ''\\r\\n if destroy_map_str and destroy_map_str != '{}':\\r\\n destroy_map_str = 'd=' + destroy_map_str\\r\\n if view_map_str and view_map_str != '{}':\\r\\n view_map_str = 'v=' + view_map_str\\r\\n\\r\\n o = ''\\r\\n if order:\\r\\n o = str(order.index(r.owner))\\r\\n already_printed = a in done # get_id_str put it in the dict\\r\\n id_str = get_id_str(a)\\r\\n\\r\\n if len(a.outputs) == 1:\\r\\n print >> file, '%s%s %s%s \\\\'%s\\\\' %s %s %s' % (prefix, a.op,\\r\\n id_str,\\r\\n type_str, r_name,\\r\\n destroy_map_str,\\r\\n view_map_str,\\r\\n o)\\r\\n else:\\r\\n print >> file, '%s%s.%i %s%s \\\\'%s\\\\' %s %s %s' % (prefix, a.op,\\r\\n a.outputs.index(r),\\r\\n id_str, type_str,\\r\\n r_name,\\r\\n destroy_map_str,\\r\\n view_map_str,\\r\\n o)\\r\\n if not already_printed:\\r\\n if (not stop_on_name or\\r\\n not (hasattr(r, 'name') and r.name is not None)):\\r\\n new_prefix = prefix_child + ' |'\\r\\n new_prefix_child = prefix_child + ' |'\\r\\n for idx, i in enumerate(a.inputs):\\r\\n if idx == len(a.inputs) - 1:\\r\\n new_prefix_child = prefix_child + ' '\\r\\n\\r\\n debugprint(i, new_prefix, depth=depth - 1, done=done,\\r\\n print_type=print_type, file=file, order=order,\\r\\n ids=ids, stop_on_name=stop_on_name,\\r\\n prefix_child=new_prefix_child)\\r\\n else:\\r\\n #this is an input variable\\r\\n id_str = get_id_str(r)\\r\\n print >> file, '%s%s %s%s' % (prefix, r, id_str, type_str)\\r\\n\\r\\n return file\",\n \"def bpprint(self, out=None):\\n if out is None:\\n out = sys.stdout\\n print(self.bpformat(), file=out)\",\n \"def vprint(expr, **settings):\\n\\n outstr = vsprint(expr, **settings)\\n\\n import builtins\\n if (outstr != 'None'):\\n builtins._ = outstr\\n print(outstr)\",\n \"def _pprint(params, offset=0, printer=repr):\\n # Do a multi-line justified repr:\\n options = numpy.get_printoptions()\\n numpy.set_printoptions(precision=5, threshold=64, edgeitems=2)\\n params_list = list()\\n this_line_length = offset\\n line_sep = ',\\\\n' + (1 + offset // 2) * ' '\\n for i, (k, v) in enumerate(sorted(params.items())):\\n if isinstance(v, float):\\n # use str for representing floating point numbers\\n # this way we get consistent representation across\\n # architectures and versions.\\n this_repr = '%s=%s' % (k, str(v))\\n else:\\n # use repr of the rest\\n this_repr = '%s=%s' % (k, printer(v))\\n if len(this_repr) > 500:\\n this_repr = this_repr[:300] + '...' + this_repr[-100:]\\n if i > 0:\\n if this_line_length + len(this_repr) >= 75 or '\\\\n' in this_repr:\\n params_list.append(line_sep)\\n this_line_length = len(line_sep)\\n else:\\n params_list.append(', ')\\n this_line_length += 2\\n params_list.append(this_repr)\\n this_line_length += len(this_repr)\\n\\n numpy.set_printoptions(**options)\\n lines = ''.join(params_list)\\n # Strip trailing space to avoid nightmare in doctests\\n lines = '\\\\n'.join(l.rstrip(' ') for l in lines.split('\\\\n'))\\n return lines\",\n \"def print_(*args, **kwargs):\\n fp = kwargs.pop(\\\"file\\\", sys.stdout)\\n if fp is None:\\n return\\n\\n def write(data):\\n if not isinstance(data, basestring):\\n data = str(data)\\n fp.write(data)\\n want_unicode = False\\n sep = kwargs.pop(\\\"sep\\\", None)\\n if sep is not None:\\n if isinstance(sep, unicode):\\n want_unicode = True\\n elif not isinstance(sep, str):\\n raise TypeError(\\\"sep must be None or a string\\\")\\n end = kwargs.pop(\\\"end\\\", None)\\n if end is not None:\\n if isinstance(end, unicode):\\n want_unicode = True\\n elif not isinstance(end, str):\\n raise TypeError(\\\"end must be None or a string\\\")\\n if kwargs:\\n raise TypeError(\\\"invalid keyword arguments to print()\\\")\\n if not want_unicode:\\n for arg in args:\\n if isinstance(arg, unicode):\\n want_unicode = True\\n break\\n if want_unicode:\\n newline = unicode(\\\"\\\\n\\\")\\n space = unicode(\\\" \\\")\\n else:\\n newline = \\\"\\\\n\\\"\\n space = \\\" \\\"\\n if sep is None:\\n sep = space\\n if end is None:\\n end = newline\\n for i, arg in enumerate(args):\\n if i:\\n write(sep)\\n write(arg)\\n write(end)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.75577617","0.73375154","0.6986672","0.698475","0.6944995","0.692333","0.6899106","0.6898902","0.68146646","0.6806209","0.6753795","0.67497987","0.6744008","0.6700308","0.6691256","0.6674591","0.6658083","0.66091245","0.6606931","0.6601862","0.6563738","0.6561717","0.65549695","0.6494838","0.6473391","0.64491546","0.6411177","0.6340302","0.6339321","0.6335031","0.6332035","0.6315847","0.631272","0.6297732","0.62969106","0.6283717","0.6279154","0.6271603","0.62673396","0.6265511","0.62629336","0.6258366","0.6258278","0.62501305","0.6248315","0.62459755","0.6244254","0.6242083","0.62393075","0.62156516","0.6208198","0.62068796","0.62062824","0.62062824","0.6194123","0.6189738","0.6183852","0.6183035","0.61697906","0.61614454","0.6160741","0.61544997","0.61528033","0.6150831","0.6147288","0.61380607","0.613793","0.61300766","0.61278135","0.6125416","0.6114217","0.61126333","0.6100682","0.60998785","0.6096818","0.6081694","0.6076982","0.6072701","0.6060028","0.60581726","0.6055044","0.6055044","0.6055044","0.6055044","0.6055044","0.6055044","0.6043662","0.6037599","0.60336643","0.6030174","0.60290223","0.60242903","0.6016989","0.6004274","0.60005474","0.60005474","0.60003483","0.599558","0.59923434","0.5979316","0.59777945"],"string":"[\n \"0.75577617\",\n \"0.73375154\",\n \"0.6986672\",\n \"0.698475\",\n \"0.6944995\",\n \"0.692333\",\n \"0.6899106\",\n \"0.6898902\",\n \"0.68146646\",\n \"0.6806209\",\n \"0.6753795\",\n \"0.67497987\",\n \"0.6744008\",\n \"0.6700308\",\n \"0.6691256\",\n \"0.6674591\",\n \"0.6658083\",\n \"0.66091245\",\n \"0.6606931\",\n \"0.6601862\",\n \"0.6563738\",\n \"0.6561717\",\n \"0.65549695\",\n \"0.6494838\",\n \"0.6473391\",\n \"0.64491546\",\n \"0.6411177\",\n \"0.6340302\",\n \"0.6339321\",\n \"0.6335031\",\n \"0.6332035\",\n \"0.6315847\",\n \"0.631272\",\n \"0.6297732\",\n \"0.62969106\",\n \"0.6283717\",\n \"0.6279154\",\n \"0.6271603\",\n \"0.62673396\",\n \"0.6265511\",\n \"0.62629336\",\n \"0.6258366\",\n \"0.6258278\",\n \"0.62501305\",\n \"0.6248315\",\n \"0.62459755\",\n \"0.6244254\",\n \"0.6242083\",\n \"0.62393075\",\n \"0.62156516\",\n \"0.6208198\",\n \"0.62068796\",\n \"0.62062824\",\n \"0.62062824\",\n \"0.6194123\",\n \"0.6189738\",\n \"0.6183852\",\n \"0.6183035\",\n \"0.61697906\",\n \"0.61614454\",\n \"0.6160741\",\n \"0.61544997\",\n \"0.61528033\",\n \"0.6150831\",\n \"0.6147288\",\n \"0.61380607\",\n \"0.613793\",\n \"0.61300766\",\n \"0.61278135\",\n \"0.6125416\",\n \"0.6114217\",\n \"0.61126333\",\n \"0.6100682\",\n \"0.60998785\",\n \"0.6096818\",\n \"0.6081694\",\n \"0.6076982\",\n \"0.6072701\",\n \"0.6060028\",\n \"0.60581726\",\n \"0.6055044\",\n \"0.6055044\",\n \"0.6055044\",\n \"0.6055044\",\n \"0.6055044\",\n \"0.6055044\",\n \"0.6043662\",\n \"0.6037599\",\n \"0.60336643\",\n \"0.6030174\",\n \"0.60290223\",\n \"0.60242903\",\n \"0.6016989\",\n \"0.6004274\",\n \"0.60005474\",\n \"0.60005474\",\n \"0.60003483\",\n \"0.599558\",\n \"0.59923434\",\n \"0.5979316\",\n \"0.59777945\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":10699,"cells":{"query":{"kind":"string","value":"Returns true if both objects are equal"},"document":{"kind":"string","value":"def __eq__(self, other):\n if not isinstance(other, ExportResponseMetadata):\n return False\n\n return self.__dict__ == other.__dict__"},"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 __eq__(self, other):\n return are_equal(self, other)","def __eq__(self, other):\n return are_equal(self, other)","def __eq__(self,other):\n try: return self.object==other.object and isinstance(self,type(other))\n except: return False","def __eq__(self, other):\n if isinstance(self, other.__class__):\n return self.__dict__ == other.__dict__\n return False","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return self.__dict__ == other.__dict__\n return False","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return self.__dict__ == other.__dict__\n return False","def __eq__(self, other):\r\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n # Ensure same class and values match\n if isinstance(other, self.__class__):\n return self.__dict__ == other.__dict__\n else:\n return False","def is_equal(self, a, b):\n return a is b","def is_equal(self, a, b):\n return a == b","def __eq__(self, other):\n return self is other","def __eq__(self, other):\n return self is other","def __eq__(self, other):\r\n if isinstance(other, self.__class__):\r\n return self.__dict__ == other.__dict__\r\n else:\r\n return False","def is_equal(o1: object, o2: object) -> bool:\n if o1 is None and o2 is None:\n return True\n if o1 is None:\n return False\n return o1 == o2","def __eq__(self,other):\n return self is other","def is_equal(self, a, b):\n return a.X[0] == b.X[0]","def __eq__(self, other):\n return type(self) == type(other) and self.id == other.id","def __eq__(self, other) -> bool:\n if json.dumps(self.data,sort_keys=True) == json.dumps(other.data,sort_keys=True):\n return True\n else:\n return False","def __eq__(self, other):\n if not isinstance(other, Single2HaObject):\n return False\n\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.__dict__ == other","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return self.__hash__() == other.__hash__()\n return False","def __eq__(self, other):\n if self.__class__ != other.__class__:\n return False\n if self.primary != other.primary:\n return False\n return True","def __eq__(self, other) -> bool:\n if other is None:\n return False\n return self.__hash__() == other.__hash__()","def __eq__(self, other):\n if not isinstance(other, ObjectInfo):\n return False\n\n return self.__dict__ == other.__dict__","def __eq__(self: _TT, other: object) -> bool:\n return self.eq(other) # type: ignore","def __eq__(self, other):\n return id(self) == id(other)","def __eq__(self, other) -> bool:\n return type(self) == type(other) and \\\n self._id == other.id and \\\n self.code == other.code and \\\n self.name == other.name and \\\n self.gender == other.gender and \\\n self.date_of_birth == other.date_of_birth","def equals(self, other): # -> bool:\n ...","def equals(self, obj: object) -> bool:\n ...","def __eq__(self, other):\n for attr in self._attrs_to_save:\n try:\n if getattr(self, attr) != getattr(other, attr):\n return False\n except AttributeError:\n return False\n return True","def __eq__(self, other):\n if type(other) is type(self):\n return (self.x == other.x and self.y == other.y and self.z == other.z)\n return False","def __eq__(self, other):\n if isinstance(other, self.__class__):\n return self.x == other.x and self.y == other.y\n return False","def __eq__(self, other: object) -> bool:\n if not isinstance(other, self.__class__):\n return NotImplemented\n\n return (\n self.name,\n self.submit_at,\n self.subreddit,\n self.title,\n self.body_template,\n ) == (\n other.name,\n other.submit_at,\n other.subreddit,\n other.title,\n other.body_template,\n )","def __eq__(self, other):\n # Check that we share the same class as this object\n if not isinstance(other, type(self)):\n return False\n\n return hash(self) == hash(other)","def __eq__(self, other):\n if not isinstance(other, PreviewObjectAutofill):\n return False\n\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return equal(self, other)","def __eq__(self, other: Any) -> bool:\n return self.__class__ is other.__class__ and self.identifier == other.identifier","def __eq__(self, other):\n return self.__id == other.get_id()","def __eq__ (self, other):\n if type(self) == type(other):\n return self._m == other._m\n else:\n return False","def __eq__(self, other):\n if not isinstance(other, Referent):\n return False\n\n return self.__dict__ == other.__dict__","def __eq__(self, other):\n return self.properties == other.properties","def __eq__(self, other):\n return self.items() == other.items()","def __eq__(self, other):\n return hash(self) == hash(other)","def __eq__(self, other):\n return hash(self) == hash(other)","def __eq__(self, other):\n return hash(self) == hash(other)","def __eq__(self, other):\n return self.x == other.x and self.y == other.y","def __eq__(self, other):\n\n if self is other:\n return True\n return hash(self) == hash(other)","def __eq__(self, other):\n if other._field1 == self._field1:\n return True\n return False","def same_as(self, other):\n return super().__eq__(other)","def __eq__(self, other):\n try:\n return other and \\\n self.id == other.id\n\n except AttributeError:\n return False","def __eq__(self, other):\r\n\t\treturn self._to_pylist() == other._to_pylist()","def __eq__(self, other):\n if not isinstance(other, Fiddle):\n return False\n\n return self.__dict__ == other.__dict__"],"string":"[\n \"def __eq__(self, other):\\n return are_equal(self, other)\",\n \"def __eq__(self, other):\\n return are_equal(self, other)\",\n \"def __eq__(self,other):\\n try: return self.object==other.object and isinstance(self,type(other))\\n except: return False\",\n \"def __eq__(self, other):\\n if isinstance(self, other.__class__):\\n return self.__dict__ == other.__dict__\\n return False\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return self.__dict__ == other.__dict__\\n return False\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return self.__dict__ == other.__dict__\\n return False\",\n \"def __eq__(self, other):\\r\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n # Ensure same class and values match\\n if isinstance(other, self.__class__):\\n return self.__dict__ == other.__dict__\\n else:\\n return False\",\n \"def is_equal(self, a, b):\\n return a is b\",\n \"def is_equal(self, a, b):\\n return a == b\",\n \"def __eq__(self, other):\\n return self is other\",\n \"def __eq__(self, other):\\n return self is other\",\n \"def __eq__(self, other):\\r\\n if isinstance(other, self.__class__):\\r\\n return self.__dict__ == other.__dict__\\r\\n else:\\r\\n return False\",\n \"def is_equal(o1: object, o2: object) -> bool:\\n if o1 is None and o2 is None:\\n return True\\n if o1 is None:\\n return False\\n return o1 == o2\",\n \"def __eq__(self,other):\\n return self is other\",\n \"def is_equal(self, a, b):\\n return a.X[0] == b.X[0]\",\n \"def __eq__(self, other):\\n return type(self) == type(other) and self.id == other.id\",\n \"def __eq__(self, other) -> bool:\\n if json.dumps(self.data,sort_keys=True) == json.dumps(other.data,sort_keys=True):\\n return True\\n else:\\n return False\",\n \"def __eq__(self, other):\\n if not isinstance(other, Single2HaObject):\\n return False\\n\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.__dict__ == other\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return self.__hash__() == other.__hash__()\\n return False\",\n \"def __eq__(self, other):\\n if self.__class__ != other.__class__:\\n return False\\n if self.primary != other.primary:\\n return False\\n return True\",\n \"def __eq__(self, other) -> bool:\\n if other is None:\\n return False\\n return self.__hash__() == other.__hash__()\",\n \"def __eq__(self, other):\\n if not isinstance(other, ObjectInfo):\\n return False\\n\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self: _TT, other: object) -> bool:\\n return self.eq(other) # type: ignore\",\n \"def __eq__(self, other):\\n return id(self) == id(other)\",\n \"def __eq__(self, other) -> bool:\\n return type(self) == type(other) and \\\\\\n self._id == other.id and \\\\\\n self.code == other.code and \\\\\\n self.name == other.name and \\\\\\n self.gender == other.gender and \\\\\\n self.date_of_birth == other.date_of_birth\",\n \"def equals(self, other): # -> bool:\\n ...\",\n \"def equals(self, obj: object) -> bool:\\n ...\",\n \"def __eq__(self, other):\\n for attr in self._attrs_to_save:\\n try:\\n if getattr(self, attr) != getattr(other, attr):\\n return False\\n except AttributeError:\\n return False\\n return True\",\n \"def __eq__(self, other):\\n if type(other) is type(self):\\n return (self.x == other.x and self.y == other.y and self.z == other.z)\\n return False\",\n \"def __eq__(self, other):\\n if isinstance(other, self.__class__):\\n return self.x == other.x and self.y == other.y\\n return False\",\n \"def __eq__(self, other: object) -> bool:\\n if not isinstance(other, self.__class__):\\n return NotImplemented\\n\\n return (\\n self.name,\\n self.submit_at,\\n self.subreddit,\\n self.title,\\n self.body_template,\\n ) == (\\n other.name,\\n other.submit_at,\\n other.subreddit,\\n other.title,\\n other.body_template,\\n )\",\n \"def __eq__(self, other):\\n # Check that we share the same class as this object\\n if not isinstance(other, type(self)):\\n return False\\n\\n return hash(self) == hash(other)\",\n \"def __eq__(self, other):\\n if not isinstance(other, PreviewObjectAutofill):\\n return False\\n\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return equal(self, other)\",\n \"def __eq__(self, other: Any) -> bool:\\n return self.__class__ is other.__class__ and self.identifier == other.identifier\",\n \"def __eq__(self, other):\\n return self.__id == other.get_id()\",\n \"def __eq__ (self, other):\\n if type(self) == type(other):\\n return self._m == other._m\\n else:\\n return False\",\n \"def __eq__(self, other):\\n if not isinstance(other, Referent):\\n return False\\n\\n return self.__dict__ == other.__dict__\",\n \"def __eq__(self, other):\\n return self.properties == other.properties\",\n \"def __eq__(self, other):\\n return self.items() == other.items()\",\n \"def __eq__(self, other):\\n return hash(self) == hash(other)\",\n \"def __eq__(self, other):\\n return hash(self) == hash(other)\",\n \"def __eq__(self, other):\\n return hash(self) == hash(other)\",\n \"def __eq__(self, other):\\n return self.x == other.x and self.y == other.y\",\n \"def __eq__(self, other):\\n\\n if self is other:\\n return True\\n return hash(self) == hash(other)\",\n \"def __eq__(self, other):\\n if other._field1 == self._field1:\\n return True\\n return False\",\n \"def same_as(self, other):\\n return super().__eq__(other)\",\n \"def __eq__(self, other):\\n try:\\n return other and \\\\\\n self.id == other.id\\n\\n except AttributeError:\\n return False\",\n \"def __eq__(self, other):\\r\\n\\t\\treturn self._to_pylist() == other._to_pylist()\",\n \"def __eq__(self, other):\\n if not isinstance(other, Fiddle):\\n return False\\n\\n return self.__dict__ == other.__dict__\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8088132","0.8088132","0.8054589","0.7982687","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.79670393","0.7961088","0.7961088","0.79433626","0.79303336","0.7926563","0.7897525","0.78826123","0.78826123","0.78806067","0.7872423","0.7868354","0.78668815","0.7825702","0.7819993","0.78162885","0.78078854","0.78068274","0.7796298","0.7794721","0.7784825","0.77790844","0.7769397","0.77534705","0.7746211","0.7741107","0.77282816","0.7725766","0.7719537","0.770273","0.7685999","0.7677552","0.76739407","0.7664857","0.76557016","0.7655046","0.76282835","0.7625795","0.76242626","0.76237214","0.76237214","0.76237214","0.7617347","0.7600536","0.7599156","0.7595863","0.75945824","0.7594092","0.75899327"],"string":"[\n \"0.8088132\",\n \"0.8088132\",\n \"0.8054589\",\n \"0.7982687\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.79670393\",\n \"0.7961088\",\n \"0.7961088\",\n \"0.79433626\",\n \"0.79303336\",\n \"0.7926563\",\n \"0.7897525\",\n \"0.78826123\",\n \"0.78826123\",\n \"0.78806067\",\n \"0.7872423\",\n \"0.7868354\",\n \"0.78668815\",\n \"0.7825702\",\n \"0.7819993\",\n \"0.78162885\",\n \"0.78078854\",\n \"0.78068274\",\n \"0.7796298\",\n \"0.7794721\",\n \"0.7784825\",\n \"0.77790844\",\n \"0.7769397\",\n \"0.77534705\",\n \"0.7746211\",\n \"0.7741107\",\n \"0.77282816\",\n \"0.7725766\",\n \"0.7719537\",\n \"0.770273\",\n \"0.7685999\",\n \"0.7677552\",\n \"0.76739407\",\n \"0.7664857\",\n \"0.76557016\",\n \"0.7655046\",\n \"0.76282835\",\n \"0.7625795\",\n \"0.76242626\",\n \"0.76237214\",\n \"0.76237214\",\n \"0.76237214\",\n \"0.7617347\",\n \"0.7600536\",\n \"0.7599156\",\n \"0.7595863\",\n \"0.75945824\",\n \"0.7594092\",\n \"0.75899327\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":106,"numItemsPerPage":100,"numTotalItems":95772,"offset":10600,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NDQ1OTI1MSwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3NzQ0NjI4NTEsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.GPoHig6VPQBX1nh-VnFqn3EBF0WDI_Yvq_VpmeCdn07hmtoWSxcEkNYNJjBCRpy1fKCj7iH3MI-sA9oT5hMJAQ","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 |
|---|---|---|---|---|---|---|
Returns the 2 endpoints of an array of points from a line | def endpoints(line_points):
neighbors = []
for p in line_points:
aux = 0
for q in line_points:
if np.linalg.norm(p-q) == 1:
aux += 1
neighbors.append(aux)
e_points = np.where(np.array(neighbors)==1)
return line_points[e_points] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def endpoints_from_lines(lines):\n \n all_points = []\n for line in lines:\n for i in [0, -1]: # start and end point\n all_points.append(line.coords[i])\n \n unique_points = set(all_points)\n \n return [Point(p) for p in unique_points]",
"def get_line_end_pts(line_segment, ... | [
"0.75531864",
"0.7405382",
"0.69150645",
"0.6756434",
"0.6724094",
"0.6720841",
"0.66821533",
"0.6652843",
"0.6637193",
"0.65996283",
"0.65701735",
"0.6523543",
"0.6521626",
"0.65032506",
"0.6477672",
"0.64699537",
"0.64601064",
"0.6448242",
"0.6385857",
"0.63586706",
"0.6358... | 0.73925066 | 2 |
Get a logger for a specific purpose. Basic usage is to for each module that needs logging, call 'logger = logging.get_logger(__name__)' to set a modulelevel global logger. | def get_logger(name):
return StyleAdapter(logging.getLogger(name)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_logger():\r\n global logger\r\n \r\n if logger:\r\n return logger\r\n else:\r\n return create_logger()",
"def get_logger(name):\n return logging.getLogger(name)",
"def get_logger(module_name):\n def _logger():\n \"\"\" Callable used to obtain current logger object... | [
"0.7938005",
"0.78668797",
"0.78630835",
"0.78493756",
"0.784605",
"0.780038",
"0.7736073",
"0.7707276",
"0.77039444",
"0.76648456",
"0.7646837",
"0.76465005",
"0.7646473",
"0.7603179",
"0.75954074",
"0.7564453",
"0.75037366",
"0.74899465",
"0.747234",
"0.7368471",
"0.7366843... | 0.0 | -1 |
This method is used for both 'xcworkspace' and 'xcodeproj' classes. It returns a list of schemes that are labeled as 'user' or 'shared'. | def schemes(self):
schemes = [];
# shared schemes
if XCSchemeHasSharedSchemes(self.path.obj_path) == True:
shared_path = XCSchemeGetSharedPath(self.path.obj_path);
shared_schemes = XCSchemeParseDirectory(shared_path);
for scheme in shared_schemes:
scheme.shared = True;
scheme.container = self.path;
schemes.append(scheme);
# user schemes
if XCSchemeHasUserSchemes(self.path.obj_path) == True:
user_path = XCSchemeGetUserPath(self.path.obj_path);
user_schemes = XCSchemeParseDirectory(user_path);
for scheme in user_schemes:
scheme.container = self.path;
schemes.append(scheme);
return schemes; | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_known_schemes_for_multi_store():\n return location.SCHEME_TO_CLS_BACKEND_MAP.keys()",
"def getSchemes(clazz):\n return [\"sftp\"]",
"def get_uri_schemes(self):\n return list(sorted(self.backends.with_playlists.keys()))",
"def get_uri_schemes(self) -> list[backend.UriScheme]:\n ... | [
"0.644051",
"0.6145727",
"0.60370487",
"0.60277617",
"0.59321177",
"0.5927999",
"0.58466095",
"0.5695372",
"0.55060184",
"0.549612",
"0.5412193",
"0.53077865",
"0.52500373",
"0.52307934",
"0.5067795",
"0.50209284",
"0.5003262",
"0.49941736",
"0.49602288",
"0.49374494",
"0.490... | 0.7739919 | 0 |
This method is used for both 'xcworkspace' and 'xcodeproj' classes. It returns a two | def hasSchemeWithName(self, scheme_name):
schemes = self.schemes();
found_scheme = None;
scheme_filter = filter(lambda scheme: scheme.name == scheme_name, schemes);
if len(scheme_filter) > 0:
found_scheme = scheme_filter[0];
return (found_scheme != None, found_scheme); | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _GetProjectAndAccount(self):\n if self.config.obfuscate:\n return ('me', 'myself@i')\n if not self.args.IsSpecified('project'):\n named_configs.ActivePropertiesFile().Invalidate()\n project = properties.VALUES.core.project.Get() or '<NO PROJECT SET>'\n account = properties.VALUES.core.acc... | [
"0.5939202",
"0.5331718",
"0.53269327",
"0.52105683",
"0.5156123",
"0.5153325",
"0.50393933",
"0.49730104",
"0.49730104",
"0.49730104",
"0.4952081",
"0.49458227",
"0.49184904",
"0.4889443",
"0.4889362",
"0.4869489",
"0.48354203",
"0.48226613",
"0.4821604",
"0.48084083",
"0.47... | 0.0 | -1 |
Display information about server or target | def func(self):
account = self.account
city_name = 'Phoenix' if not self.args else self.args
a = Astral()
a.solar_depression = 'civil'
city = a[city_name]
if not city:
return
timezone = city.timezone
sun = city.sun(date=datetime.date.today(), local=True)
account.msg('Information for %s/%s\n' % (city_name, city.region))
account.msg('Timezone: %s' % timezone)
account.msg('Latitude: %.02f; Longitude: %.02f' % (city.latitude, city.longitude))
account.msg('Dawn: %s' % str(sun['dawn']))
account.msg('Sunrise: %s' % str(sun['sunrise']))
account.msg('Noon: %s' % str(sun['noon']))
account.msg('Sunset: %s' % str(sun['sunset']))
account.msg('Dusk: %s' % str(sun['dusk'])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def do_serverinfo(self, server):\n print('QManager server:', self._server)\n server_info = self._qm.get_server_info()\n for k, v in server_info.items():\n print(' %s: %s' % (k, v))",
"def server_info(ctx):\n data = ctx.obj.get_server_info()\n output_json_data(data)",
"asy... | [
"0.72389144",
"0.70208263",
"0.6947981",
"0.6858957",
"0.66273963",
"0.6501815",
"0.64122075",
"0.626067",
"0.6243138",
"0.623907",
"0.6233489",
"0.6219578",
"0.6212143",
"0.6208515",
"0.6188572",
"0.6180633",
"0.6169564",
"0.6101906",
"0.6085284",
"0.6084221",
"0.6083808",
... | 0.0 | -1 |
Given map and model estimate resolution by maximizing map CC(map, modelmap). As a byproduct, also provides CC and optimal overall Bfactor. | def __init__(self, map_data, xray_structure, d_min_min=None, nproc=1):
unit_cell = xray_structure.unit_cell()
d_min_end = round(maptbx.d_min_from_map(
map_data=map_data, unit_cell=unit_cell, resolution_factor=0.1),1)
d_min_start = round(maptbx.d_min_from_map(
map_data=map_data, unit_cell=unit_cell, resolution_factor=0.5),1)
if(d_min_min is not None and d_min_start<d_min_min):
d_min_start=d_min_min
step = (d_min_end-d_min_start)/10.
b_range=[0,10,20,30,40,50,60,70,80,90,100,150,200]
if(d_min_end>10):
b_range = b_range + [300,400,500]
result, b_iso, cc, radius = _resolution_from_map_and_model_helper(
map = map_data,
xray_structure = xray_structure,
b_range = b_range,
d_min_start = d_min_start,
d_min_end = d_min_end,
d_min_step = step,
approximate = False,
nproc = nproc,
second = False)
if(cc<0.5):
self.d_min, self.b_iso, self.cc, self.radius = None,None,None,None
else:
if(d_min_min is not None and result<d_min_min):
result=d_min_min
scale=1
if(result<3): scale=2
b_range=[i for i in range(0,506,5)]
d_min_start = round(result-result/2, 1)
d_min_end = round(result+result/2*scale, 1)
if(d_min_min is not None and d_min_start<d_min_min):
d_min_start=d_min_min
self.d_min, self.b_iso, self.cc, self.radius = _resolution_from_map_and_model_helper(
map = map_data,
xray_structure = xray_structure,
b_range = b_range,
d_min_start = d_min_start,
d_min_end = d_min_end,
d_min_step = 0.1,
approximate = True,
nproc = nproc,
second = True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solve(self):\n start = timer()\n # encode into milp\n me = MILPEncoder(MILPSolver.prob,\n MILPSolver.params.logger.LOGFILE, \n MILPSolver.params.INTRA_DEP_CONSTRS,\n MILPSolver.params.INTER_DEP_CONSTRS)\n if MIL... | [
"0.5714574",
"0.57091874",
"0.56935656",
"0.560293",
"0.54859185",
"0.54807884",
"0.5452945",
"0.54312307",
"0.5425042",
"0.5412584",
"0.53376436",
"0.53328913",
"0.5325986",
"0.53229344",
"0.5320904",
"0.5318339",
"0.53176457",
"0.5300573",
"0.5285679",
"0.52541053",
"0.5253... | 0.0 | -1 |
Test if the code is generated by a given feature. | def test_generate(monkeypatch, capsys):
monkeypatch.setattr(sys, "argv", ["", "generate", os.path.join(PATH, "generate.feature")])
main()
out, err = capsys.readouterr()
assert out == textwrap.dedent(
'''
# coding=utf-8
"""Code generation feature tests."""
from pytest_bdd import (
given,
scenario,
then,
when,
)
@scenario('scripts/generate.feature', 'Given and when using the same fixture should not evaluate it twice')
def test_given_and_when_using_the_same_fixture_should_not_evaluate_it_twice():
"""Given and when using the same fixture should not evaluate it twice."""
@given('1 have a fixture (appends 1 to a list) in reuse syntax')
def have_a_fixture_appends_1_to_a_list_in_reuse_syntax():
"""1 have a fixture (appends 1 to a list) in reuse syntax."""
raise NotImplementedError
@given('I have an empty list')
def i_have_an_empty_list():
"""I have an empty list."""
raise NotImplementedError
@when('I use this fixture')
def i_use_this_fixture():
"""I use this fixture."""
raise NotImplementedError
@then('my list should be [1]')
def my_list_should_be_1():
"""my list should be [1]."""
raise NotImplementedError
'''[
1:
].replace(
u"'", u"'"
)
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def need_feature_generation(self):\n if self.feature_cmd_params:\n return True\n return False",
"def need_feature_generation(self):\n if self.feature_cmd_params:\n return True\n return False",
"def is_codegen(self):\r\n return self.has_label('codegen')",
"... | [
"0.65903217",
"0.65903217",
"0.644704",
"0.6116954",
"0.59947085",
"0.5969095",
"0.5945452",
"0.5891829",
"0.5681718",
"0.5662601",
"0.55940044",
"0.5539872",
"0.54797906",
"0.5448133",
"0.54353863",
"0.5412818",
"0.54071283",
"0.533634",
"0.5321914",
"0.53043",
"0.5292037",
... | 0.5757439 | 8 |
Returns a normalized 2D gauss kernel array for convolutions | def gauss_kernel(size, size_y=None):
size = int(size)
if not size_y:
size_y = size
else:
size_y = int(size_y)
x, y = mgrid[-size: size + 1, -size_y: size_y + 1]
g = exp(-(x ** 2 / float(size) + y ** 2 / float(size_y)))
return g / g.sum() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_gauss_kernel(sigma, samples):\n p = ny.ceil (2*ny.sqrt(2*ny.log(2))*sigma)\n r = ny.linspace(-p, p, samples)\n x,y = ny.meshgrid(r, r)\n b=bivariate_normal(x,y,sigma,sigma)\n A=(1/ny.sum(b))\n B=A*b\n return x,y,B",
"def test_gauss_kernel():\n\n gauss = gauss_kernel(2, 5)\n\n a... | [
"0.6883207",
"0.67762655",
"0.64694875",
"0.63874155",
"0.6357571",
"0.63324594",
"0.6317897",
"0.630675",
"0.62914956",
"0.62589204",
"0.62336004",
"0.616739",
"0.6149477",
"0.61113864",
"0.6096338",
"0.605444",
"0.60538787",
"0.60399646",
"0.6037839",
"0.6003877",
"0.599997... | 0.60346377 | 19 |
returns x and y derivatives of a 2D gauss kernel array for convolutions | def gauss_derivative_kernels(size, size_y=None):
size = int(size)
if not size_y:
size_y = size
else:
size_y = int(size_y)
y, x = mgrid[-size: size + 1, -size_y: size_y + 1]
# x and y derivatives of a 2D gaussian with standard dev half of size
# (ignore scale factor)
gx = - x * exp(-(x ** 2 / float((0.5 * size) ** 2) + y ** 2 / float((0.5 * size_y) ** 2)))
gy = - y * exp(-(x ** 2 / float((0.5 * size) ** 2) + y ** 2 / float((0.5 * size_y) ** 2)))
return gx, gy | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gauss_derivatives(im, n, ny=None):\n\n gx, gy = gauss_derivative_kernels(n, size_y=ny)\n\n imx = signal.convolve(im, gx, mode='same')\n imy = signal.convolve(im, gy, mode='same')\n\n return imx, imy",
"def test_gauss_kernel():\n\n gauss = gauss_kernel(2, 5)\n\n assert gauss.shape == (5, 5)\... | [
"0.6464445",
"0.6400031",
"0.6292199",
"0.62704843",
"0.622417",
"0.6203519",
"0.6186446",
"0.6149553",
"0.6084668",
"0.59506327",
"0.5876299",
"0.586569",
"0.58355033",
"0.58145",
"0.58079106",
"0.5799519",
"0.57833916",
"0.5765829",
"0.57556885",
"0.57517755",
"0.5751735",
... | 0.6867467 | 0 |
returns x and y derivatives of an image using gaussian derivative filters of size n. The optional argument ny allows for a different size in the y direction. | def gauss_derivatives(im, n, ny=None):
gx, gy = gauss_derivative_kernels(n, size_y=ny)
imx = signal.convolve(im, gx, mode='same')
imy = signal.convolve(im, gy, mode='same')
return imx, imy | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gauss_derivative_kernels(size, size_y=None):\n size = int(size)\n if not size_y:\n size_y = size\n else:\n size_y = int(size_y)\n y, x = mgrid[-size: size + 1, -size_y: size_y + 1]\n\n # x and y derivatives of a 2D gaussian with standard dev half of size\n # (ignore scale factor... | [
"0.61548144",
"0.5981589",
"0.5959965",
"0.58838403",
"0.58367634",
"0.57715976",
"0.5677056",
"0.5670111",
"0.56048477",
"0.56043017",
"0.55708915",
"0.5549236",
"0.5539912",
"0.5506071",
"0.549919",
"0.54970866",
"0.53928995",
"0.5380421",
"0.53599995",
"0.5349",
"0.5330634... | 0.8174752 | 0 |
Decorator that can be used to cache ReusableBytesIO objects intended for reading. The decorator makes sure the objects are immutable and reset to position 0. The decorated function can either return pure ReusableBytesIO objects or dicts. | def buffer_object_cacher(key=None, maxsize=None):
if not config.enable_caching:
return lambda x: x
def decorator(fun):
# Cache the results.
cached_fun = cachetools.cached(cachetools.LRUCache(maxsize=maxsize),
key=lambda *x,**y: cachetools.keys.hashkey(key(*x,**y)))(fun)
# Reset the buffer(s) on every cache-hit so it's readable again.
def rewind_wrapper(*args, **kwargs):
results = cached_fun(*args, **kwargs)
if isinstance(results, dict):
for buffer in results.values():
buffer.seek(0)
else:
results.seek(0)
return results
return rewind_wrapper
return decorator | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_buffer():\n return BytesIO()",
"def cached_load(filepath: str) -> io.BytesIO:\n with open(filepath, 'rb') as f:\n return io.BytesIO(f.read())",
"def disk_memoize(path):\n def decorator(f):\n @functools.wraps(f)\n def g(*a, **kw):\n kwargs = to_kwargs(f, *a, **k... | [
"0.6126323",
"0.59865415",
"0.5825444",
"0.58154047",
"0.57380855",
"0.5698068",
"0.5697662",
"0.55716634",
"0.55687535",
"0.55656105",
"0.5557927",
"0.5528658",
"0.54908526",
"0.5479148",
"0.54592925",
"0.54238856",
"0.54096276",
"0.5385697",
"0.53558767",
"0.5354645",
"0.53... | 0.63631254 | 0 |
Returns a tuple representing the hardware specs. | def getHardware(self):
return (self.vendorId, self.deviceId, self.physicalMemory, self.osInfo, self.cpuSpeed[0]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_hardware_info(self) -> list:\n model = ctypes.create_string_buffer(8)\n model_size = ctypes.c_ulong(8)\n type_num = ctypes.c_ushort()\n channel_num = ctypes.c_ushort()\n notes = ctypes.create_string_buffer(48)\n notes_size = ctypes.c_ulong(48)\n firmware_ve... | [
"0.7078182",
"0.6386408",
"0.60863703",
"0.60038155",
"0.5982613",
"0.59652555",
"0.59633815",
"0.594874",
"0.59447217",
"0.5936363",
"0.58740854",
"0.5844497",
"0.5777375",
"0.5739162",
"0.5714293",
"0.56568074",
"0.5644492",
"0.56364363",
"0.5634876",
"0.563088",
"0.56237",... | 0.7476962 | 0 |
Returns true if the other session or sample has the same hardware specs as this one, false otherwise. | def sameHardware(self, other):
return (self.vendorId == other.vendorId and \
self.deviceId == other.deviceId and \
self.physicalMemory == other.physicalMemory and \
self.osInfo == other.osInfo and \
self.cpuSpeed[0] == other.cpuSpeed[0]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _on_same_device(self, other: \"PArray\") -> bool:\n this_device = self._current_device_index\n return this_device in other._array",
"def match(uspec1, uspec2):\n \n if uspec1.is_power_onoff() and uspec2.is_power_onoff():\n return True\n \n if uspec1.number_windows() != uspec2... | [
"0.6838293",
"0.666635",
"0.65126216",
"0.64928484",
"0.63411206",
"0.6300568",
"0.62982696",
"0.61403143",
"0.6127172",
"0.6109003",
"0.6074839",
"0.60358554",
"0.59964126",
"0.59953624",
"0.5989709",
"0.59614843",
"0.59588736",
"0.59384286",
"0.59161776",
"0.5901873",
"0.58... | 0.7975851 | 0 |
Calculates the average FPS for this player, over all of the player's different sessions. | def calcFrameRate(self):
tot = 0
count = 0
for session in self.sessions:
for sample in session.samples:
if not sample.isLoading:
tot += sample.fps
count += 1
if count:
self.avgFps = tot / count
self.lowFps = (self.avgFps < 10)
self.highFps = (self.avgFps > 25) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_fps(self):\n \n return self.fps, self.average_fps",
"def get_fps(self):\n return self._num_frames / (datetime.now() - self._start).total_seconds()",
"def update_fps(self, fps):\n self.fps_history.append(fps)\n if len(self.fps_history) > FPS_AVERAGES:\n self... | [
"0.635384",
"0.6108307",
"0.6086766",
"0.59754205",
"0.59748524",
"0.5926207",
"0.5866448",
"0.5856975",
"0.58385223",
"0.5776392",
"0.57533216",
"0.57494795",
"0.5631522",
"0.55880743",
"0.5585366",
"0.5568593",
"0.5568593",
"0.5568593",
"0.55296254",
"0.5512434",
"0.5473437... | 0.72921765 | 0 |
Reads the clientfps lines from the indicated logfile, and writes card_performance.csv, without building up large tables. | def quickAnalyzeCards(self, filename):
assert filename.endswith('.txt')
file = open(filename, 'r')
quickCards = {}
for line in file:
line = line.strip()
if not line:
continue
columns = line.split('|')
if columns[1] != 'client-fps':
continue
sample = Sample(line, columns)
if sample.isLoading:
continue
if sample.vendorId == None or sample.deviceId == None:
continue
# Now accumulate this sample into the cards table.
options = quickCards.setdefault((sample.vendorId, sample.deviceId), {})
totFps, count = options.get(sample.gameOptionsCode, (0, 0))
totFps += sample.fps
count += 1
options[sample.gameOptionsCode] = (totFps, count)
file = open('card_performance.csv', 'w')
deviceList = quickCards.keys()
deviceList.sort()
for deviceTuple in deviceList:
options = quickCards[deviceTuple]
codes = options.keys()
codes.sort()
for gameOptionsCode in codes:
totFps, count = options[gameOptionsCode]
avgFps = totFps / count
print >> file, '%s, %s, %s, %s' % (
self.__formatDevice(deviceTuple),
gameOptionsCode, avgFps, count) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def grep_log_files_put_to_csv_output(path):\n log_process = LogProcess()\n log_process.log_path = path\n log_process.output_path = os.path.join(path, \"temp\")\n obj_file.cleanup_dir(log_process.output_path)\n csv_alarm, no_contact = log_process.altc()\n csv_alarm_history = log_process.lgjc()\n ... | [
"0.55250233",
"0.54603183",
"0.5450724",
"0.5413982",
"0.5379444",
"0.53514105",
"0.52793115",
"0.52764195",
"0.5269211",
"0.5259841",
"0.5198763",
"0.5174568",
"0.5164108",
"0.5136736",
"0.5116632",
"0.5114831",
"0.51126087",
"0.5108278",
"0.5103108",
"0.50868624",
"0.507331... | 0.5976573 | 0 |
Reads the clientfps lines from the indicated logfile into the Analyzer. This is the main interface to read raw data from the server. | def readText(self, filename, firstLine = 0, lastLine = None):
assert filename.endswith('.txt')
file = open(filename, 'r')
self.samples = []
li = 0
while li < firstLine:
if not file.readline():
return
li += 1
while lastLine == None or li < lastLine:
line = file.readline()
if not line:
return
li += 1
line = line.strip()
if line:
columns = line.split('|')
if columns[1] == 'client-fps':
self.samples.append(Sample(line, columns)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _read_log(self):\n\n line_regex = compile(r\"\\[I\\]\\s*\\(\\d+ms\\)[^\\d]+(?P<counter>\\d+)\"\n r\"[^\\d]+(?P<timestamp>\\d+(\\.\\d+)?)[^\\d]+\"\n r\"(?P<acceleration>\\d+);\")\n values = []\n with open(self.filepath) as file:\n ... | [
"0.6168366",
"0.61174154",
"0.60710835",
"0.57544655",
"0.5584042",
"0.5498605",
"0.5488151",
"0.547809",
"0.54696566",
"0.54012346",
"0.5350959",
"0.5345476",
"0.53420615",
"0.53355366",
"0.5307551",
"0.5307535",
"0.52456975",
"0.52440536",
"0.5232471",
"0.52123123",
"0.5182... | 0.5063487 | 35 |
Does the work of analyzing all of the data read in the previous call to readText(). This is the meat of the analyzer. | def analyze(self):
self.makeSessions()
self.collectPlayers()
self.__analyze() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def analyse(self):\n logging.info(\"transferring text to CorpusCook...\")\n\n paragraphs = self.text.split('\\n\\n')\n print(\"mean length of splitted lines\", (mean([len(p) for p in paragraphs])))\n\n # If TIKA resolved '\\n'\n if (mean([len(p) for p in paragraphs])) > 80:\n ... | [
"0.68422043",
"0.6633991",
"0.65388185",
"0.637483",
"0.6279562",
"0.6157252",
"0.61434984",
"0.610618",
"0.6089409",
"0.6081509",
"0.60237473",
"0.5994796",
"0.59370583",
"0.59326017",
"0.5893664",
"0.5862024",
"0.5855501",
"0.58262473",
"0.58164513",
"0.58102053",
"0.580787... | 0.0 | -1 |
Write the samples for all players with less than 10 fps average frame rate to the indicated text file. This generates a new log file that may be analyzed independently. | def writeLowPlayers(self, filename):
assert filename.endswith('.txt')
file = open(filename, 'w')
samples = []
for player in self.players:
if player.lowFps:
for session in player.sessions:
for sample in session.samples:
sample.write(file) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def send_logs(self):\n for i in range(30):\n with open('{}-{}.log'.format(self._log_file_path, i), 'a') as log_file:\n for _ in range(self._log_rate):\n log_file.write(self._log_record + '\\n')",
"def debug_file(self, pkt_count, attack_count, data_list, ds_calc_time, ds_vals, metric_means... | [
"0.6171279",
"0.59173375",
"0.5693433",
"0.5600852",
"0.555415",
"0.5504344",
"0.54048634",
"0.53820014",
"0.5346854",
"0.53364265",
"0.53228056",
"0.52732503",
"0.52012616",
"0.5186444",
"0.517446",
"0.5160905",
"0.51368034",
"0.5127677",
"0.51274544",
"0.5126001",
"0.512328... | 0.72644055 | 0 |
Writes the entire analyzer to a pickle file, for saving it across sessions. Not terribly useful, since you can always just read the text file again. This is a little bit faster, though. | def writePickle(self, filename):
assert filename.endswith('.pkl')
file = open(filename, 'wb')
cPickle.dump(self, file, cPickle.HIGHEST_PROTOCOL) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self, filename=\"matpipe.p\"):\n temp_backend = self.learner.backend\n self.learner._backend = self.learner.backend.fitted_pipeline_\n for obj in [self, self.learner, self.reducer, self.cleaner,\n self.autofeaturizer]:\n obj._logger = None\n with o... | [
"0.63167715",
"0.61267745",
"0.61015433",
"0.608488",
"0.6059269",
"0.6031452",
"0.5898048",
"0.58106905",
"0.5757367",
"0.57421386",
"0.571337",
"0.5705606",
"0.56701314",
"0.5667776",
"0.56589854",
"0.56589836",
"0.5654374",
"0.56400377",
"0.56398267",
"0.5634741",
"0.56241... | 0.0 | -1 |
Internal method to collect individual clientfps samples into related sessions. | def makeSessions(self):
sessionDict = {}
self.sessions = []
for sample in self.samples:
session = sessionDict.get(sample.avId, None)
if session:
# Is this still the same session?
elapsedA = sample.date - session.endDate
assert elapsedA >= 0
elapsedB = sample.timeInGame - session.timeInGame
if elapsedB < 0:
# Reported time-in-game smaller than last sample.
session = None
elif elapsedA > 1800 or elapsedB > 1800:
# Too much time elapsed between consecutive
# samples.
session = None
elif not session.sameHardware(sample):
# New hardware.
session = None
if not session:
session = Session(sample)
sessionDict[sample.avId] = session
self.sessions.append(session)
else:
session.addSample(sample)
for session in self.sessions:
session.calcFrameRate() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def collect_samples(self):\n self.replay_buffer = self.collect_initial_batch(\n self.replay_buffer, self.acm_pre_train_samples\n )",
"def collect_samples(self):\n # TODO refactor this to not to duplicate collect from DDPG\n # - not so easy due to logger :(\n col... | [
"0.6620976",
"0.6284045",
"0.59943616",
"0.5915122",
"0.5489073",
"0.5375032",
"0.5372684",
"0.53488225",
"0.532472",
"0.531502",
"0.531284",
"0.5284829",
"0.52701354",
"0.5267627",
"0.52433234",
"0.52414626",
"0.5237697",
"0.5233825",
"0.5217491",
"0.5209853",
"0.5200325",
... | 0.6239438 | 2 |
Internal method to group individual sessions by player. | def collectPlayers(self):
playerDict = {}
self.hardware = {}
for session in self.sessions:
player = playerDict.get(session.avId, None)
if not player:
player = Player(session.avId)
playerDict[session.avId] = player
player.addSession(session)
self.hardware.setdefault((player, session.getHardware()), []).append(session)
self.players = playerDict.values()
for player in self.players:
player.calcFrameRate() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _group_sessions(self, sessions):\n session_dict = collections.defaultdict(list)\n for session in sessions:\n session_dict[session.query].append(session)\n return session_dict",
"def get_groups_of_player(self, player: str) -> list:\n return [group for group in self._grou... | [
"0.6594691",
"0.6511603",
"0.6109347",
"0.6027776",
"0.5668092",
"0.56667185",
"0.5573631",
"0.5494839",
"0.5469459",
"0.5462861",
"0.54250926",
"0.5422447",
"0.54118776",
"0.54043454",
"0.5363722",
"0.5343578",
"0.52973384",
"0.5274449",
"0.52449733",
"0.52271664",
"0.519147... | 0.6386398 | 2 |
The cpu speed is in 100's of MHz. | def __formatCpuSpeed(self, cpuSpeed):
return '%.1f GHz' % (cpuSpeed / 10.0) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cpu_speed(self):\n\t\treturn call_sdk_function('PrlSrvCfg_GetCpuSpeed', self.handle)",
"def speed(self):\n return 1 # speed system not implemented yet",
"def frequency(self):\n return self.reference_clock_speed / 4096 / self.prescale_reg",
"def speed(self) -> int:",
"def speed(self) -> in... | [
"0.74917567",
"0.74589694",
"0.7335953",
"0.7257771",
"0.7257771",
"0.7203033",
"0.7179013",
"0.71334624",
"0.71179646",
"0.71057755",
"0.7099538",
"0.7064058",
"0.7020678",
"0.6938121",
"0.6884253",
"0.687121",
"0.687121",
"0.6864354",
"0.6832936",
"0.6808417",
"0.6804985",
... | 0.73974395 | 2 |
Returns total number of players whose avg fps is less than 10, total number of players whose avg fps is between 10 and 25, and total number of players whose avg fps is more than 25. | def __countPlayers(self, players):
numLow = sum(map(lambda p: p.lowFps, players))
numHigh = sum(map(lambda p: p.highFps, players))
numMed = len(players) - numLow - numHigh
return '%s, %s, %s' % (numLow, numMed, numHigh) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def stats(detections, faces):\n vp, fp, fn, vn = 0, 0, 0, 0\n max_label = np.max(faces[:, 0])\n for i in range(max_label + 1):\n detections_i = get_label_with_index(detections, i)\n faces_i = get_label_with_index(faces, i)\n local_vp = 0\n for face in faces_i:\n foun... | [
"0.60739285",
"0.59108806",
"0.5869163",
"0.5824232",
"0.5684692",
"0.56706446",
"0.56420135",
"0.55896056",
"0.557531",
"0.55514854",
"0.5549805",
"0.551023",
"0.5500134",
"0.54782814",
"0.5471912",
"0.544629",
"0.5406683",
"0.5397825",
"0.5371873",
"0.53278965",
"0.5309981"... | 0.63204354 | 0 |
Reads PCIList, which contains a list of the known PCI devices by vendor ID/device ID. See | def readPCIList(self):
self.vendors = {}
self.devices = {}
vendorId = None
vendorName = None
for line in PCIList.split('\n'):
stripped = line.lstrip()
if not stripped or stripped[0] == ';':
continue
if line[0] != '\t':
# A vendor line.
vendorId, vendorName = line.split('\t', 1)
vendorId = int(vendorId, 16)
self.vendors[vendorId] = vendorName.strip()
else:
# A device line, continuing the previous vendor.
deviceId, deviceName = line[1:].split('\t', 1)
deviceId = deviceId.split(' ', 1)[0]
try:
deviceId = int(deviceId, 16)
except:
deviceId = None
self.devices[(vendorId, deviceId)] = deviceName.strip()
self.addExtraDevices() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_pci_devices(self):\n\n system = self._get_host_details()\n if ('links' in system['Oem']['Hp'] and\n 'PCIDevices' in system['Oem']['Hp']['links']):\n # Get the PCI URI and Settings\n pci_uri = system['Oem']['Hp']['links']['PCIDevices']['href']\n ... | [
"0.6974894",
"0.6744383",
"0.6441267",
"0.59418535",
"0.588758",
"0.5535207",
"0.55204946",
"0.5497702",
"0.5481925",
"0.5473312",
"0.54184794",
"0.5417257",
"0.54155695",
"0.5406843",
"0.5379454",
"0.53526473",
"0.5350712",
"0.53472716",
"0.53472596",
"0.53421974",
"0.532810... | 0.8187731 | 0 |
Adds extra device names that we know explicitly from some external source. | def addExtraDevices(self):
# These tables were extracted from
# pirates/src/piratesgui/GameOptions.py.
ati_device_list = [
["ATI MOBILITY/RADEON X700", 0x5653],
[1, "Radeon X1950 XTX Uber - Limited Edition", 0x7248],
[1, "Radeon X1950 XTX Uber - Limited Edition Secondary", 0x7268],
[1, "Radeon X800 CrossFire Edition", 0x554D],
[1, "Radeon X800 CrossFire Edition Secondary", 0x556D],
[1, "Radeon X850 CrossFire Edition", 0x5D52],
[1, "Radeon X850 CrossFire Edition Secondary", 0x5D72],
["Radeon X550/X700 Series", 0x564F],
["ATI FireGL T2", 0x4154],
["ATI FireGL T2 Secondary", 0x4174],
["ATI FireGL V3100", 0x5B64],
["ATI FireGL V3100 Secondary", 0x5B74],
["ATI FireGL V3200", 0x3E54],
["ATI FireGL V3200 Secondary", 0x3E74],
["ATI FireGL V3300", 0x7152],
["ATI FireGL V3300 Secondary", 0x7172],
["ATI FireGL V3350", 0x7153],
["ATI FireGL V3350 Secondary", 0x7173],
["ATI FireGL V3400", 0x71D2],
["ATI FireGL V3400 Secondary", 0x71F2],
["ATI FireGL V5000", 0x5E48],
["ATI FireGL V5000 Secondary", 0x5E68],
["ATI FireGL V5100", 0x5551],
["ATI FireGL V5100 Secondary", 0x5571],
["ATI FireGL V5200", 0x71DA],
["ATI FireGL V5200 Secondary", 0x71FA],
["ATI FireGL V5300", 0x7105],
["ATI FireGL V5300 Secondary", 0x7125],
["ATI FireGL V7100", 0x5550],
["ATI FireGL V7100 Secondary", 0x5570],
["ATI FireGL V7200", 0x5D50],
["ATI FireGL V7200 ", 0x7104],
["ATI FireGL V7200 Secondary", 0x5D70],
["ATI FireGL V7200 Secondary ", 0x7124],
["ATI FireGL V7300", 0x710E],
["ATI FireGL V7300 Secondary", 0x712E],
["ATI FireGL V7350", 0x710F],
["ATI FireGL V7350 Secondary", 0x712F],
["ATI FireGL X1", 0x4E47],
["ATI FireGL X1 Secondary", 0x4E67],
["ATI FireGL X2-256/X2-256t", 0x4E4B],
["ATI FireGL X2-256/X2-256t Secondary", 0x4E6B],
["ATI FireGL X3-256", 0x4A4D],
["ATI FireGL X3-256 Secondary", 0x4A6D],
["ATI FireGL Z1", 0x4147],
["ATI FireGL Z1 Secondary", 0x4167],
["ATI FireMV 2200", 0x5B65],
["ATI FireMV 2200 Secondary", 0x5B75],
["ATI FireMV 2250", 0x719B],
["ATI FireMV 2250 Secondary", 0x71BB],
["ATI FireMV 2400", 0x3151],
["ATI FireMV 2400 Secondary", 0x3171],
["ATI FireStream 2U", 0x724E],
["ATI FireStream 2U Secondary", 0x726E],
["ATI MOBILITY FIRE GL 7800", 0x4C58],
["ATI MOBILITY FIRE GL T2/T2e", 0x4E54],
["ATI MOBILITY FireGL V3100", 0x5464],
["ATI MOBILITY FireGL V3200", 0x3154],
["ATI MOBILITY FireGL V5000", 0x564A],
["ATI MOBILITY FireGL V5000 ", 0x564B],
["ATI MOBILITY FireGL V5100", 0x5D49],
["ATI MOBILITY FireGL V5200", 0x71C4],
["ATI MOBILITY FireGL V5250", 0x71D4],
["ATI MOBILITY FireGL V7100", 0x7106],
["ATI MOBILITY FireGL V7200", 0x7103],
["ATI MOBILITY RADEON", 0x4C59],
["ATI MOBILITY RADEON 7500", 0x4C57],
["ATI MOBILITY RADEON 9500", 0x4E52],
["ATI MOBILITY RADEON 9550", 0x4E56],
["ATI MOBILITY RADEON 9600/9700 Series", 0x4E50],
["ATI MOBILITY RADEON 9800", 0x4A4E],
["ATI Mobility Radeon HD 2300", 0x7210],
["ATI Mobility Radeon HD 2300 ", 0x7211],
["ATI Mobility Radeon HD 2400", 0x94C9],
["ATI Mobility Radeon HD 2400 XT", 0x94C8],
[1, "ATI Mobility Radeon HD 2600", 0x9581],
[1, "ATI Mobility Radeon HD 2600 XT", 0x9583],
["ATI Mobility Radeon X1300", 0x714A],
["ATI Mobility Radeon X1300 ", 0x7149],
["ATI Mobility Radeon X1300 ", 0x714B],
["ATI Mobility Radeon X1300 ", 0x714C],
["ATI Mobility Radeon X1350", 0x718B],
["ATI Mobility Radeon X1350 ", 0x718C],
["ATI Mobility Radeon X1350 ", 0x7196],
["ATI Mobility Radeon X1400", 0x7145],
["ATI Mobility Radeon X1450", 0x7186],
["ATI Mobility Radeon X1450 ", 0x718D],
["ATI Mobility Radeon X1600", 0x71C5],
["ATI Mobility Radeon X1700", 0x71D5],
["ATI Mobility Radeon X1700 ", 0x71DE],
["ATI Mobility Radeon X1700 XT", 0x71D6],
[1, "ATI Mobility Radeon X1800", 0x7102],
[1, "ATI Mobility Radeon X1800 XT", 0x7101],
[1, "ATI Mobility Radeon X1900", 0x7284],
[1, "ATI Mobility Radeon X2300", 0x718A],
[1, "ATI Mobility Radeon X2300 ", 0x7188],
["ATI MOBILITY RADEON X300", 0x5461],
["ATI MOBILITY RADEON X300 ", 0x5460],
["ATI MOBILITY RADEON X300 ", 0x3152],
["ATI MOBILITY RADEON X600", 0x3150],
["ATI MOBILITY RADEON X600 SE", 0x5462],
["ATI MOBILITY RADEON X700", 0x5652],
["ATI MOBILITY RADEON X700 ", 0x5653],
["ATI MOBILITY RADEON X700 Secondary", 0x5673],
[1, "ATI MOBILITY RADEON X800", 0x5D4A],
[1, "ATI MOBILITY RADEON X800 XT", 0x5D48],
["ATI Radeon 9550/X1050 Series", 0x4153],
["ATI Radeon 9550/X1050 Series Secondary", 0x4173],
["ATI RADEON 9600 Series", 0x4150],
["ATI RADEON 9600 Series ", 0x4E51],
["ATI RADEON 9600 Series ", 0x4151],
["ATI RADEON 9600 Series ", 0x4155],
["ATI RADEON 9600 Series ", 0x4152],
["ATI RADEON 9600 Series Secondary", 0x4E71],
["ATI RADEON 9600 Series Secondary ", 0x4171],
["ATI RADEON 9600 Series Secondary ", 0x4170],
["ATI RADEON 9600 Series Secondary ", 0x4175],
["ATI RADEON 9600 Series Secondary ", 0x4172],
[1, "ATI Radeon HD 2900 XT", 0x9402],
[1, "ATI Radeon HD 2900 XT ", 0x9403],
[1, "ATI Radeon HD 2900 XT ", 0x9400],
[1, "ATI Radeon HD 2900 XT ", 0x9401],
["ATI Radeon X1200 Series", 0x791E],
["ATI Radeon X1200 Series ", 0x791F],
[1, "ATI Radeon X1950 GT", 0x7288],
[1, "ATI Radeon X1950 GT Secondary", 0x72A8],
[1, "ATI RADEON X800 GT", 0x554E],
[1, "ATI RADEON X800 GT Secondary", 0x556E],
[1, "ATI RADEON X800 XL", 0x554D],
[1, "ATI RADEON X800 XL Secondary", 0x556D],
[1, "ATI RADEON X850 PRO", 0x4B4B],
[1, "ATI RADEON X850 PRO Secondary", 0x4B6B],
[1, "ATI RADEON X850 SE", 0x4B4A],
[1, "ATI RADEON X850 SE Secondary", 0x4B6A],
[1, "ATI RADEON X850 XT", 0x4B49],
[1, "ATI RADEON X850 XT Platinum Edition", 0x4B4C],
[1, "ATI RADEON X850 XT Platinum Edition Secondary", 0x4B6C],
[1, "ATI RADEON X850 XT Secondary", 0x4B69],
["ATI Radeon Xpress 1200 Series", 0x793F],
["ATI Radeon Xpress 1200 Series ", 0x7941],
["ATI Radeon Xpress 1200 Series ", 0x7942],
["ATI Radeon Xpress Series", 0x5A61],
["ATI Radeon Xpress Series ", 0x5A63],
["ATI Radeon Xpress Series ", 0x5A62],
["ATI Radeon Xpress Series ", 0x5A41],
["ATI Radeon Xpress Series ", 0x5A43],
["ATI Radeon Xpress Series ", 0x5A42],
["ATI Radeon Xpress Series ", 0x5954],
["ATI Radeon Xpress Series ", 0x5854],
["ATI Radeon Xpress Series ", 0x5955],
["ATI Radeon Xpress Series ", 0x5974],
["ATI Radeon Xpress Series ", 0x5874],
["ATI Radeon Xpress Series ", 0x5975],
["Radeon 9500", 0x4144],
["Radeon 9500 ", 0x4149],
["Radeon 9500 PRO / 9700", 0x4E45],
["Radeon 9500 PRO / 9700 Secondary", 0x4E65],
["Radeon 9500 Secondary", 0x4164],
["Radeon 9500 Secondary ", 0x4169],
["Radeon 9600 TX", 0x4E46],
["Radeon 9600 TX Secondary", 0x4E66],
["Radeon 9600TX", 0x4146],
["Radeon 9600TX Secondary", 0x4166],
["Radeon 9700 PRO", 0x4E44],
["Radeon 9700 PRO Secondary", 0x4E64],
["Radeon 9800", 0x4E49],
["Radeon 9800 PRO", 0x4E48],
["Radeon 9800 PRO Secondary", 0x4E68],
["Radeon 9800 SE", 0x4148],
["Radeon 9800 SE Secondary", 0x4168],
["Radeon 9800 Secondary", 0x4E69],
["Radeon 9800 XT", 0x4E4A],
["Radeon 9800 XT Secondary", 0x4E6A],
["Radeon X1300 / X1550 Series", 0x7146],
["Radeon X1300 / X1550 Series Secondary", 0x7166],
["Radeon X1300 Series", 0x714E],
["Radeon X1300 Series ", 0x715E],
["Radeon X1300 Series ", 0x714D],
["Radeon X1300 Series ", 0x71C3],
["Radeon X1300 Series ", 0x718F],
["Radeon X1300 Series Secondary", 0x716E],
["Radeon X1300 Series Secondary ", 0x717E],
["Radeon X1300 Series Secondary ", 0x716D],
["Radeon X1300 Series Secondary ", 0x71E3],
["Radeon X1300 Series Secondary ", 0x71AF],
["Radeon X1300/X1550 Series", 0x7142],
["Radeon X1300/X1550 Series ", 0x7180],
["Radeon X1300/X1550 Series ", 0x7183],
["Radeon X1300/X1550 Series ", 0x7187],
["Radeon X1300/X1550 Series Secondary", 0x7162],
["Radeon X1300/X1550 Series Secondary ", 0x71A0],
["Radeon X1300/X1550 Series Secondary ", 0x71A3],
["Radeon X1300/X1550 Series Secondary ", 0x71A7],
["Radeon X1550 64-bit", 0x7147],
["Radeon X1550 64-bit ", 0x715F],
["Radeon X1550 64-bit ", 0x719F],
["Radeon X1550 64-bit Secondary", 0x7167],
["Radeon X1550 64-bit Secondary ", 0x717F],
["Radeon X1550 Series", 0x7143],
["Radeon X1550 Series ", 0x7193],
["Radeon X1550 Series Secondary", 0x7163],
["Radeon X1550 Series Secondary ", 0x71B3],
["Radeon X1600 Pro / Radeon X1300 XT", 0x71CE],
["Radeon X1600 Pro / Radeon X1300 XT Secondary", 0x71EE],
["Radeon X1600 Series", 0x7140],
["Radeon X1600 Series ", 0x71C0],
["Radeon X1600 Series ", 0x71C2],
["Radeon X1600 Series ", 0x71C6],
["Radeon X1600 Series ", 0x7181],
["Radeon X1600 Series ", 0x71CD],
["Radeon X1600 Series Secondary", 0x7160],
["Radeon X1600 Series Secondary ", 0x71E2],
["Radeon X1600 Series Secondary ", 0x71E6],
["Radeon X1600 Series Secondary ", 0x71A1],
["Radeon X1600 Series Secondary ", 0x71ED],
["Radeon X1600 Series Secondary ", 0x71E0],
["Radeon X1650 Series", 0x71C1],
["Radeon X1650 Series ", 0x7293],
["Radeon X1650 Series ", 0x7291],
["Radeon X1650 Series ", 0x71C7],
["Radeon X1650 Series Secondary", 0x71E1],
["Radeon X1650 Series Secondary ", 0x72B3],
["Radeon X1650 Series Secondary ", 0x72B1],
["Radeon X1650 Series Secondary ", 0x71E7],
[1, "Radeon X1800 Series", 0x7100],
[1, "Radeon X1800 Series ", 0x7108],
[1, "Radeon X1800 Series ", 0x7109],
[1, "Radeon X1800 Series ", 0x710A],
[1, "Radeon X1800 Series ", 0x710B],
[1, "Radeon X1800 Series ", 0x710C],
[1, "Radeon X1800 Series Secondary", 0x7120],
[1, "Radeon X1800 Series Secondary ", 0x7128],
[1, "Radeon X1800 Series Secondary ", 0x7129],
[1, "Radeon X1800 Series Secondary ", 0x712A],
[1, "Radeon X1800 Series Secondary ", 0x712B],
[1, "Radeon X1800 Series Secondary ", 0x712C],
[1, "Radeon X1900 Series", 0x7243],
[1, "Radeon X1900 Series ", 0x7245],
[1, "Radeon X1900 Series ", 0x7246],
[1, "Radeon X1900 Series ", 0x7247],
[1, "Radeon X1900 Series ", 0x7248],
[1, "Radeon X1900 Series ", 0x7249],
[1, "Radeon X1900 Series ", 0x724A],
[1, "Radeon X1900 Series ", 0x724B],
[1, "Radeon X1900 Series ", 0x724C],
[1, "Radeon X1900 Series ", 0x724D],
[1, "Radeon X1900 Series ", 0x724F],
[1, "Radeon X1900 Series Secondary", 0x7263],
[1, "Radeon X1900 Series Secondary ", 0x7265],
[1, "Radeon X1900 Series Secondary ", 0x7266],
[1, "Radeon X1900 Series Secondary ", 0x7267],
[1, "Radeon X1900 Series Secondary ", 0x7268],
[1, "Radeon X1900 Series Secondary ", 0x7269],
[1, "Radeon X1900 Series Secondary ", 0x726A],
[1, "Radeon X1900 Series Secondary ", 0x726B],
[1, "Radeon X1900 Series Secondary ", 0x726C],
[1, "Radeon X1900 Series Secondary ", 0x726D],
[1, "Radeon X1900 Series Secondary ", 0x726F],
[1, "Radeon X1950 Series", 0x7280],
[1, "Radeon X1950 Series ", 0x7240],
[1, "Radeon X1950 Series ", 0x7244],
[1, "Radeon X1950 Series Secondary", 0x72A0],
[1, "Radeon X1950 Series Secondary ", 0x7260],
[1, "Radeon X1950 Series Secondary ", 0x7264],
["Radeon X300/X550/X1050 Series", 0x5B60],
["Radeon X300/X550/X1050 Series ", 0x5B63],
["Radeon X300/X550/X1050 Series Secondary", 0x5B73],
["Radeon X300/X550/X1050 Series Secondary ", 0x5B70],
["Radeon X550/X700 Series ", 0x5657],
["Radeon X550/X700 Series Secondary", 0x5677],
["Radeon X600 Series", 0x5B62],
["Radeon X600 Series Secondary", 0x5B72],
["Radeon X600/X550 Series", 0x3E50],
["Radeon X600/X550 Series Secondary", 0x3E70],
["Radeon X700", 0x5E4D],
["Radeon X700 PRO", 0x5E4B],
["Radeon X700 PRO Secondary", 0x5E6B],
["Radeon X700 SE", 0x5E4C],
["Radeon X700 SE Secondary", 0x5E6C],
["Radeon X700 Secondary", 0x5E6D],
["Radeon X700 XT", 0x5E4A],
["Radeon X700 XT Secondary", 0x5E6A],
["Radeon X700/X550 Series", 0x5E4F],
["Radeon X700/X550 Series Secondary", 0x5E6F],
[1, "Radeon X800 GT", 0x554B],
[1, "Radeon X800 GT Secondary", 0x556B],
[1, "Radeon X800 GTO", 0x5549],
[1, "Radeon X800 GTO ", 0x554F],
[1, "Radeon X800 GTO ", 0x5D4F],
[1, "Radeon X800 GTO Secondary", 0x5569],
[1, "Radeon X800 GTO Secondary ", 0x556F],
[1, "Radeon X800 GTO Secondary ", 0x5D6F],
[1, "Radeon X800 PRO", 0x4A49],
[1, "Radeon X800 PRO Secondary", 0x4A69],
[1, "Radeon X800 SE", 0x4A4F],
[1, "Radeon X800 SE Secondary", 0x4A6F],
[1, "Radeon X800 Series", 0x4A48],
[1, "Radeon X800 Series ", 0x4A4A],
[1, "Radeon X800 Series ", 0x4A4C],
[1, "Radeon X800 Series ", 0x5548],
[1, "Radeon X800 Series Secondary", 0x4A68],
[1, "Radeon X800 Series Secondary ", 0x4A6A],
[1, "Radeon X800 Series Secondary ", 0x4A6C],
[1, "Radeon X800 Series Secondary ", 0x5568],
[1, "Radeon X800 VE", 0x4A54],
[1, "Radeon X800 VE Secondary", 0x4A74],
[1, "Radeon X800 XT", 0x4A4B],
[1, "Radeon X800 XT ", 0x5D57],
[1, "Radeon X800 XT Platinum Edition", 0x4A50],
[1, "Radeon X800 XT Platinum Edition ", 0x554A],
[1, "Radeon X800 XT Platinum Edition Secondary", 0x4A70],
[1, "Radeon X800 XT Platinum Edition Secondary ", 0x556A],
[1, "Radeon X800 XT Secondary", 0x4A6B],
[1, "Radeon X800 XT Secondary ", 0x5D77],
[1, "Radeon X850 XT", 0x5D52],
[1, "Radeon X850 XT Platinum Edition", 0x5D4D],
[1, "Radeon X850 XT Platinum Edition Secondary", 0x5D6D],
[1, "Radeon X850 XT Secondary", 0x5D72],
]
vendorId = 0x1002
for entry in ati_device_list:
if len(entry) == 3:
flag, deviceName, deviceId = entry
else:
deviceName, deviceId = entry
self.devices[(vendorId, deviceId)] = deviceName.strip()
nvidia_device_list = [
[0x014F, "GeForce 6200"],
[0x00F3, "GeForce 6200"],
[0x0221, "GeForce 6200"],
[0x0163, "GeForce 6200 LE"],
[0x0162, "GeForce 6200SE TurboCache(TM)"],
[0x0161, "GeForce 6200 TurboCache(TM)"],
[0x0162, "GeForce 6200SE TurboCache(TM)"],
[0x0160, "GeForce 6500"],
[1, 0x0141, "GeForce 6600"],
[1, 0x00F2, "GeForce 6600"],
[1, 0x0140, "GeForce 6600 GT"],
[1, 0x00F1, "GeForce 6600 GT"],
[1, 0x0142, "GeForce 6600 LE"],
[1, 0x00F4, "GeForce 6600 LE"],
[1, 0x0143, "GeForce 6600 VE"],
[1, 0x0147, "GeForce 6700 XL"],
[1, 0x0041, "GeForce 6800"],
[1, 0x00C1, "GeForce 6800"],
[1, 0x0047, "GeForce 6800 GS"],
[1, 0x00F6, "GeForce 6800 GS"],
[1, 0x00C0, "GeForce 6800 GS"],
[1, 0x0045, "GeForce 6800 GT"],
[1, 0x00F9, "GeForce 6800 Series GPU"],
[1, 0x00C2, "GeForce 6800 LE"],
[1, 0x0040, "GeForce 6800 Ultra"],
[1, 0x00F9, "GeForce 6800 Series GPU"],
[1, 0x0043, "GeForce 6800 XE"],
[1, 0x0048, "GeForce 6800 XT"],
[1, 0x0218, "GeForce 6800 XT"],
[1, 0x00C3, "GeForce 6800 XT"],
[0x01DF, "GeForce 7300 GS"],
[0x0393, "GeForce 7300 GT"],
[0x01D1, "GeForce 7300 LE"],
[0x01D3, "GeForce 7300 SE"],
[0x01DD, "GeForce 7500 LE"],
[1, 0x0392, "GeForce 7600 GS"],
[1, 0x0392, "GeForce 7600 GS"],
[1, 0x02E1, "GeForce 7600 GS"],
[1, 0x0391, "GeForce 7600 GT"],
[1, 0x0394, "GeForce 7600 LE"],
[1, 0x00F5, "GeForce 7800 GS"],
[1, 0x0092, "GeForce 7800 GT"],
[1, 0x0091, "GeForce 7800 GTX"],
[1, 0x0291, "GeForce 7900 GT/GTO"],
[1, 0x0290, "GeForce 7900 GTX"],
[1, 0x0293, "GeForce 7900 GX2"],
[1, 0x0294, "GeForce 7950 GX2"],
[0x0322, "GeForce FX 5200"],
[0x0321, "GeForce FX 5200 Ultra"],
[0x0323, "GeForce FX 5200LE"],
[0x0326, "GeForce FX 5500"],
[0x0326, "GeForce FX 5500"],
[0x0312, "GeForce FX 5600"],
[0x0311, "GeForce FX 5600 Ultra"],
[0x0314, "GeForce FX 5600XT"],
[0x0342, "GeForce FX 5700"],
[0x0341, "GeForce FX 5700 Ultra"],
[0x0343, "GeForce FX 5700LE"],
[0x0344, "GeForce FX 5700VE"],
[0x0302, "GeForce FX 5800"],
[0x0301, "GeForce FX 5800 Ultra"],
[0x0331, "GeForce FX 5900"],
[0x0330, "GeForce FX 5900 Ultra"],
[0x0333, "GeForce FX 5950 Ultra"],
[0x0324, "GeForce FX Go5200 64M"],
[0x031A, "GeForce FX Go5600"],
[0x0347, "GeForce FX Go5700"],
[0x0167, "GeForce Go 6200/6400"],
[0x0168, "GeForce Go 6200/6400"],
[1, 0x0148, "GeForce Go 6600"],
[1, 0x00c8, "GeForce Go 6800"],
[1, 0x00c9, "GeForce Go 6800 Ultra"],
[1, 0x0098, "GeForce Go 7800"],
[1, 0x0099, "GeForce Go 7800 GTX"],
[1, 0x0298, "GeForce Go 7900 GS"],
[1, 0x0299, "GeForce Go 7900 GTX"],
[0x0185, "GeForce MX 4000"],
[0x00FA, "GeForce PCX 5750"],
[0x00FB, "GeForce PCX 5900"],
[0x0110, "GeForce2 MX/MX 400"],
[0x0111, "GeForce2 MX200"],
[0x0110, "GeForce2 MX/MX 400"],
[0x0200, "GeForce3"],
[0x0201, "GeForce3 Ti200"],
[0x0202, "GeForce3 Ti500"],
[0x0172, "GeForce4 MX 420"],
[0x0171, "GeForce4 MX 440"],
[0x0181, "GeForce4 MX 440 with AGP8X"],
[0x0173, "GeForce4 MX 440-SE"],
[0x0170, "GeForce4 MX 460"],
[0x0253, "GeForce4 Ti 4200"],
[0x0281, "GeForce4 Ti 4200 with AGP8X"],
[0x0251, "GeForce4 Ti 4400"],
[0x0250, "GeForce4 Ti 4600"],
[0x0280, "GeForce4 Ti 4800"],
[0x0282, "GeForce4 Ti 4800SE"],
[0x0203, "Quadro DCC"],
[0x0309, "Quadro FX 1000"],
[0x034E, "Quadro FX 1100"],
[0x00FE, "Quadro FX 1300"],
[0x00CE, "Quadro FX 1400"],
[0x0308, "Quadro FX 2000"],
[0x0338, "Quadro FX 3000"],
[0x00FD, "Quadro PCI-E Series"],
[1, 0x00F8, "Quadro FX 3400/4400"],
[1, 0x00CD, "Quadro FX 3450/4000 SDI"],
[1, 0x004E, "Quadro FX 4000"],
[1, 0x00CD, "Quadro FX 3450/4000 SDI"],
[1, 0x00F8, "Quadro FX 3400/4400"],
[1, 0x009D, "Quadro FX 4500"],
[1, 0x029F, "Quadro FX 4500 X2"],
[0x032B, "Quadro FX 500/FX 600"],
[0x014E, "Quadro FX 540"],
[0x014C, "Quadro FX 540 MXM"],
[0x032B, "Quadro FX 500/FX 600"],
[0X033F, "Quadro FX 700"],
[0x034C, "Quadro FX Go1000"],
[0x00CC, "Quadro FX Go1400"],
[0x031C, "Quadro FX Go700"],
[0x018A, "Quadro NVS with AGP8X"],
[0x032A, "Quadro NVS 280 PCI"],
[0x00FD, "Quadro PCI-E Series"],
[0x0165, "Quadro NVS 285"],
[0x017A, "Quadro NVS"],
[0x018A, "Quadro NVS with AGP8X"],
[0x0113, "Quadro2 MXR/EX"],
[0x017A, "Quadro NVS"],
[0x018B, "Quadro4 380 XGL"],
[0x0178, "Quadro4 550 XGL"],
[0x0188, "Quadro4 580 XGL"],
[0x025B, "Quadro4 700 XGL"],
[0x0259, "Quadro4 750 XGL"],
[0x0258, "Quadro4 900 XGL"],
[0x0288, "Quadro4 980 XGL"],
[0x028C, "Quadro4 Go700"],
[1, 0x0295, "NVIDIA GeForce 7950 GT"],
[0x03D0, "NVIDIA GeForce 6100 nForce 430"],
[0x03D1, "NVIDIA GeForce 6100 nForce 405"],
[0x03D2, "NVIDIA GeForce 6100 nForce 400"],
[0x0241, "NVIDIA GeForce 6150 LE"],
[0x0242, "NVIDIA GeForce 6100"],
[0x0245, "NVIDIA Quadro NVS 210S / NVIDIA GeForce 6150LE"],
[1, 0x029C, "NVIDIA Quadro FX 5500"],
[1, 0x0191, "NVIDIA GeForce 8800 GTX"],
[1, 0x0193, "NVIDIA GeForce 8800 GTS"],
[1, 0x0400, "NVIDIA GeForce 8600 GTS"],
[1, 0x0402, "NVIDIA GeForce 8600 GT"],
[0x0421, "NVIDIA GeForce 8500 GT"],
[0x0422, "NVIDIA GeForce 8400 GS"],
[0x0423, "NVIDIA GeForce 8300 GS"],
]
vendorId = 0x10de
for entry in nvidia_device_list:
if len(entry) == 3:
flag, deviceId, deviceName = entry
else:
deviceId, deviceName = entry
self.devices[(vendorId, deviceId)] = deviceName.strip() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_extra_args(self):\n self.parser.add_argument('--device', dest='device', type=str, help='Device ID, e.g. d--0001')",
"def addDevice(self, node, fullDeviceName, device):",
"def load_devices():",
"def addDeviceDescriptor(string: str, deviceDescriptor: cern.japc.core.DeviceDescriptor) -> None:\n ... | [
"0.6235411",
"0.6018107",
"0.5875037",
"0.5769226",
"0.5737719",
"0.5699172",
"0.5628838",
"0.56115973",
"0.55473393",
"0.5530301",
"0.5512926",
"0.55042124",
"0.54661566",
"0.5442146",
"0.54258853",
"0.5409304",
"0.53862745",
"0.5350149",
"0.53231454",
"0.52631706",
"0.52626... | 0.64580566 | 0 |
Calculates frequencies of samples. | def freq_counts(self, arrs, lens):
no_nans = reduce(np.logical_and, [~np.isnan(a) if bn.anynan(a) else np.ones(self.m).astype(bool) for a in arrs])
combined = reduce(add, [arrs[i][no_nans]*reduce(mul, lens[:i]) for i in range(1, len(arrs))], arrs[0][no_nans])
return np.bincount(combined.astype(np.int32, copy=False), minlength=reduce(mul, lens)).astype(float) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def frequencies(self):\r\n\r\n self.method['Fs'] = self.method.get('Fs', self.input.sampling_rate)\r\n NFFT = self.method.get('NFFT', 64)\r\n Fs = self.method.get('Fs')\r\n freqs = tsu.get_freqs(Fs, NFFT)\r\n lb_idx, ub_idx = tsu.get_bounds(freqs, self.lb, self.ub)\r\n\r\n ... | [
"0.7766813",
"0.7707529",
"0.76741445",
"0.7562953",
"0.7418545",
"0.739534",
"0.7392773",
"0.71362615",
"0.6976485",
"0.69558024",
"0.690897",
"0.6903706",
"0.6876598",
"0.68592876",
"0.6843024",
"0.68283325",
"0.6793091",
"0.67241335",
"0.67124856",
"0.6667002",
"0.66569775... | 0.63803333 | 43 |
Counts the frequencies of samples of given variables ``vars`` and calculates probabilities with additive smoothing. | def get_probs(self, *vars):
freqs = self.freq_counts([self.data.get_column_view(v)[0] for v in vars], [len(v.values) for v in vars])
k = np.prod([len(v.values) for v in vars])
return (freqs + self.alpha) / (np.sum(freqs) + self.alpha*k) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_posterior_probs(vars_):\n vars_.weighted_sums += np.power(vars_.dprime_map[vars_.focus],2) * vars_.visual_field\n vars_.post_probs = np.exp(vars_.weighted_sums) * vars_.prior_prob\n vars_.post_probs /= np.sum(vars_.post_probs)",
"def countVarFreq(list_models_vars_freq):\n list_variables_to... | [
"0.57587546",
"0.5575326",
"0.53477293",
"0.52793074",
"0.51654255",
"0.5154966",
"0.5104432",
"0.50244606",
"0.49709153",
"0.49697486",
"0.49534038",
"0.491249",
"0.4908834",
"0.48904198",
"0.48888883",
"0.48864844",
"0.48855996",
"0.48635137",
"0.4834516",
"0.48303828",
"0.... | 0.7346631 | 0 |
Entropy of a given distribution. | def h(self, probs):
return np.sum(-p*np.log2(p) if p > 0 else 0 for p in np.nditer(probs)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def entropy(dist):\n #dist = array([max(d,1e-100) for d in dist])\n dist = dist + 1e-20\n return dot(dist,(log(1.0/dist) * (1.0/log(2.0))).T)",
"def entropyDistributed(distribution):\n return -sum(map(lambda p : p * log(p, 2), distribution))",
"def _graph_fn_entropy(distribution):\n return d... | [
"0.7871747",
"0.78487754",
"0.76791704",
"0.7365083",
"0.73631096",
"0.73386323",
"0.73318344",
"0.7179662",
"0.7174629",
"0.71570325",
"0.70973134",
"0.7095",
"0.70855933",
"0.7081814",
"0.7046893",
"0.7035079",
"0.70043415",
"0.6972333",
"0.6965106",
"0.69620615",
"0.696116... | 0.0 | -1 |
If not given, computes the absolute total info gain for attributes a and b. Generates an Interaction object. | def attribute_interactions(self, a, b, total_rel_ig_ab=None):
var_a = self.data.domain.variables[a]
var_b = self.data.domain.variables[b]
ig_a = self.info_gains[var_a.name]
ig_b = self.info_gains[var_b.name]
if not total_rel_ig_ab:
ig_ab = ig_a + ig_b - (self.class_entropy + self.h(self.get_probs(var_a, var_b))) + \
self.h(self.get_probs(var_a, var_b, self.data.domain.variables[-1]))
else:
ig_ab = ig_a + ig_b - total_rel_ig_ab * self.class_entropy
inter = Interaction(var_a, var_b, ig_a, ig_b, ig_ab, self.class_entropy)
return inter | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def infoGain(self,attr, data, target_attr):\n remainder = 0\n p = 0\n ent = 0\n for ele in target_attr:\n if ele == 1:\n p +=1\n \n q = p / (len(target_attr)) \n if 0 < q < 1:\n ent = -((q * math.log2(q)) + ((1-q) * math.... | [
"0.6119889",
"0.5544115",
"0.5507098",
"0.54734284",
"0.54698795",
"0.53078294",
"0.53001773",
"0.52430487",
"0.52211547",
"0.5215387",
"0.52137595",
"0.5157385",
"0.51392186",
"0.5137646",
"0.50982416",
"0.5096558",
"0.50840324",
"0.50741106",
"0.50459766",
"0.50332594",
"0.... | 0.6960144 | 0 |
Computes a symetric matrix containing the relative total information gain for all possible pairs of attributes. | def interaction_matrix(self):
self.int_M_called = True
int_M = np.zeros((self.n, self.n))
for k in range(self.n):
for j in range(k+1):
o = self.attribute_interactions(k, j)
int_M[k, j] = o.rel_total_ig_ab # Store total information gain
int_M[j, k] = o.rel_total_ig_ab # TODO: Maybe storing interactions too is not a bad idea
# TODO: We can than easily sort either by total gain or by positive interaction
for k in range(self.n):
int_M[k, k] = self.info_gains[self.data.domain.attributes[k].name]
self.int_matrix = Orange.misc.distmatrix.DistMatrix(int_M) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def information_gain(Y, attr):\n initial_gain = entropy(Y)\n\n temp_Y = Y.tolist()\n temp_attr = attr.tolist()\n\n temp_attr = list(np.unique(attr))\n\n for a in temp_attr:\n l = []\n count = 0\n for j in attr:\n if (j == a):\n l.append(temp_Y[count])\n... | [
"0.6507828",
"0.6414944",
"0.626524",
"0.6232345",
"0.58820426",
"0.5660079",
"0.5539918",
"0.551693",
"0.5509508",
"0.5486035",
"0.5465803",
"0.5443954",
"0.54394644",
"0.5417441",
"0.5393869",
"0.5381921",
"0.5350407",
"0.5318583",
"0.52740175",
"0.52646095",
"0.52236044",
... | 0.5677631 | 5 |
Computes the Interaction objects for n most informative pairs of attributes. For this to work, ``interaction_matrix`` must be called first. It uses a partial sort and then a full sort on the remaining n elements to get the indices of attributes. | def get_top_att(self, n):
if not self.int_M_called:
raise IndexError("Call interaction_matrix first!")
flat_indices = np.argpartition(np.tril(-self.int_matrix, -1).ravel(), n - 1)[:n]
# TODO: Consider using the partial sort from the bottleneck module for faster sorting
row_indices, col_indices = np.unravel_index(flat_indices, self.int_matrix.shape)
min_elements_order = np.argsort(-self.int_matrix[row_indices, col_indices])
row_indices, col_indices = row_indices[min_elements_order], col_indices[min_elements_order]
return [self.attribute_interactions(row_indices[k], col_indices[k],
self.int_matrix[row_indices[k], col_indices[k]]) for k in range(n)] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def interaction_matrix(self):\n\n self.int_M_called = True\n int_M = np.zeros((self.n, self.n))\n for k in range(self.n):\n for j in range(k+1):\n o = self.attribute_interactions(k, j)\n int_M[k, j] = o.rel_total_ig_ab # Store total information gain\n ... | [
"0.60471845",
"0.54465884",
"0.52681583",
"0.5024728",
"0.4996432",
"0.49814323",
"0.49585322",
"0.49543592",
"0.49077043",
"0.4857076",
"0.48561823",
"0.48455074",
"0.4830593",
"0.48272932",
"0.48052135",
"0.47973144",
"0.47867075",
"0.4769542",
"0.47667968",
"0.47630936",
"... | 0.72928554 | 0 |
Train the models with the train dataset | def entrainement(self, trainData, trainLabels, testData, testLabels, test, classes, test_ids):
if self.classifieur == 1:
svc_linear = SVC(probability=True, kernel='linear', gamma='auto')
AdaBoost_params = {
'n_estimators': [5, 10, 15, 20],
'learning_rate': [0.01, 0.05, 0.1, 0.3, 1],
}
clf = AdaBoostClassifier(algorithm='SAMME', base_estimator=svc_linear)
AdaBoost_search = GridSearchCV(clf, param_grid=AdaBoost_params, cv=3)
AdaBoost_search.fit(trainData, trainLabels)
AdaBoost_accuracy = AdaBoost_search.score(testData, testLabels)
print("AdaBoost_search accuracy: {:.2f}%".format(AdaBoost_accuracy * 100))
print("AdaBoost_search search best parameters: {}".format(AdaBoost_search.best_params_))
if self.classifieur == 2:
# construct the set of hyperparameters to tune
k_range = np.arange(2, 31, 1)
hparams = {"n_neighbors": k_range, "metric": ["euclidean", "cityblock"]}
# tune the hyperparameters via a cross-validated grid search
print("tuning hyperparameters via grid search")
clf = KNeighborsClassifier()
grid = GridSearchCV(clf, hparams, cv=3, scoring='accuracy')
grid.fit(trainData, trainLabels)
knn_accuracy = grid.score(testData, testLabels)
print("KNN grid search accuracy: {:.2f}%".format(knn_accuracy * 100))
print("KNN grid search best parameters: {}".format(grid.best_params_))
# kaggle
test_predictions = grid.predict_proba(test)
# Format DataFrame
submission = pd.DataFrame(test_predictions, columns=classes)
submission.insert(0, 'id', test_ids)
submission.reset_index()
# Export Submission
submission.to_csv('submission.csv', index=False)
submission.tail()
if self.classifieur == 3:
# Set the parameters for cross-validation
tuned_parameters = [{'kernel': ['rbf'], 'gamma': [1e-2, 1e-3, 1e-4, 1e-5],
'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000]},
{'kernel': ['sigmoid'], 'gamma': [1e-2, 1e-3, 1e-4, 1e-5],
'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000]},
{'kernel': ['linear'], 'C': [0.001, 0.10, 0.1, 10, 25, 50, 100, 1000]}
]
scores = ['precision', 'recall']
for score in scores:
print("# Tuning hyper-parameters for %s" % score)
print()
clf = GridSearchCV(SVC(C=1, probability=True), tuned_parameters, cv=3,
scoring='%s_macro' % score)
clf.fit(trainData, trainLabels)
svm_accuracy = clf.score(testData, testLabels)
print("SVM grid search accuracy: {:.2f}%".format(svm_accuracy * 100))
print("SVM grid search best parameters: {}".format(clf.best_params_))
# kaggle
test_predictions = clf.predict_proba(test)
# Format DataFrame
submission = pd.DataFrame(test_predictions, columns=classes)
submission.insert(0, 'id', test_ids)
submission.reset_index()
# Export Submission
submission.to_csv('submission.csv', index=False)
submission.tail()
if self.classifieur == 4:
Logistic_Regression_params= {
'penalty': ('l1', 'l2', ), 'C': [0.001, 0.01, 0.1, 1, 10, 11, 20, 100, ], }
clf = LogisticRegression()
param_search = GridSearchCV(clf, param_grid=Logistic_Regression_params, cv=3)
param_search.fit(trainData,trainLabels)
accuracy = param_search.score(testData, testLabels)
print("regression logistic search accuracy: {:.2f}%".format(accuracy * 100))
print("regression logistic search best parameters: {}".format(param_search.best_params_))
if self.classifieur == 5:
Perceptron_params = {
'penalty': ('l1', 'l2', ),
'alpha': [0.0001, 0.1, 0.01, ],
'max_iter': [100, 500, 700], 'tol': [1e-3]}
clf = Perceptron()
perceptron_search = GridSearchCV(clf, param_grid=Perceptron_params, cv=3)
perceptron_search.fit(trainData,trainLabels)
perceptron_accuracy = perceptron_search.score(testData, testLabels)
print("perceptron search accuracy: {:.2f}%".format(perceptron_accuracy * 100))
print("perceptron search best parameters: {}".format(perceptron_search.best_params_))
if self.classifieur == 6:
RandomForest_params= {
'max_depth': (5, 10, 20, 50, 100, 1000),
'n_estimators': (10, 50, 100)}
clf = RandomForestClassifier()
RandomForest_search= RandomizedSearchCV(clf, RandomForest_params, cv=3)
RandomForest_search.fit(trainData, trainLabels)
RandomForest_accuracy = RandomForest_search.score(testData, testLabels)
print("RandomForest search accuracy: {:.2f}%".format(RandomForest_accuracy * 100))
print("RandomForest logistic search best parameters: {}".format(RandomForest_search.best_params_)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(self):\n\t\tself.model.fit(self.training_data, self.training_labels)",
"def train(self, x_data, y_data):\n for model in self.list_of_models:\n model.fit(x_data, y_data)\n self.trained_models.append(model)",
"def set_train(self):\n for m in self.models.values():\n ... | [
"0.85705304",
"0.81666774",
"0.8045999",
"0.8045258",
"0.79215825",
"0.784289",
"0.7838864",
"0.77854425",
"0.7752612",
"0.7748808",
"0.77232707",
"0.76623434",
"0.7646475",
"0.7645696",
"0.7623885",
"0.7589835",
"0.7571589",
"0.7557546",
"0.7549086",
"0.7526105",
"0.7521501"... | 0.0 | -1 |
Returns subdict of `kwargs` with the keys that match the names of arguments in `fun`'s signature. | def filter_extra_accepted_kwargs(fun, kwargs, skip_positional=0):
sig = inspect.signature(fun)
# the params from signature with up to skip_positional filtered out
# (less only if there is not enough of positional args)
params = [(name, param) for i, (name, param) in enumerate(sig.parameters.items())
if i >= skip_positional or param.kind not in
[inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.POSITIONAL_ONLY]]
extra = [
name for (name, param) in params
if param.kind in [inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.KEYWORD_ONLY]
]
return {name: value for name, value in kwargs.items() if name in extra} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def appropriate_kwargs(kwargs, func):\n sig = inspect.signature(func)\n filter_keys = [\n param.name\n for param in sig.parameters.values()\n if param.kind == param.POSITIONAL_OR_KEYWORD and param.name in kwargs.keys()\n ]\n appropriate_dict = {filter_key: kwargs[filter_key] for fi... | [
"0.7756075",
"0.75575936",
"0.7026198",
"0.701601",
"0.6970035",
"0.6854365",
"0.6675852",
"0.6675852",
"0.66426367",
"0.662578",
"0.65232116",
"0.6503449",
"0.647175",
"0.64479893",
"0.61948097",
"0.6167109",
"0.6133175",
"0.6125426",
"0.61196697",
"0.6109005",
"0.6103811",
... | 0.70694536 | 2 |
Returns the list of names of args/kwargs without defaults from `fun` signature. | def get_required_kwargs(fun, skip_positional=0):
sig = inspect.signature(fun)
# the params from signature with up to skip_positional filtered out
# (less only if there is not enough of positional args)
params = [(name, param) for i, (name, param) in enumerate(sig.parameters.items())
if i >= skip_positional or param.kind not in
[inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.POSITIONAL_ONLY]]
return [
name for name, param in params if param.default is inspect.Parameter.empty
and param.kind in [inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.KEYWORD_ONLY]
] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getArgs(func):\n # exclude the defaults at the end (hence the [:-1])\n args = list(utils.flatten(inspect.getargspec(func)[:-1]))\n return set(args).difference(set([None]))",
"def list_kwargs(func):\n \n details = inspect.getargspec(func)\n nopt = len(details.defaults)\n \n return deta... | [
"0.7373131",
"0.70837766",
"0.70198065",
"0.6812793",
"0.6719347",
"0.66698635",
"0.66303456",
"0.65023136",
"0.6472078",
"0.6378711",
"0.63185936",
"0.63058794",
"0.62759775",
"0.6262447",
"0.6222361",
"0.62066025",
"0.6155284",
"0.59993124",
"0.59842724",
"0.5961036",
"0.59... | 0.7168854 | 1 |
Returns the number of arguments that can be passed positionally to the `fun` call. | def get_num_positional_args(fun):
sig = inspect.signature(fun)
return len([
name for name, param in sig.parameters.items() if param.kind in
[inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.POSITIONAL_ONLY]
]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_arg_count(fun):\n if isclass(fun):\n return len(signature(fun.__call__).parameters)\n return len(signature(fun).parameters)",
"def _fun_arg_count(f):\n args = getargspec(f).args\n if args and args[0] == 'self':\n args = args[1:]\n return len(args)",
"def _arg_count(func):\n... | [
"0.82862073",
"0.7959749",
"0.77881014",
"0.7670227",
"0.7434592",
"0.72237825",
"0.7108183",
"0.691844",
"0.68648636",
"0.68646204",
"0.6769415",
"0.6768247",
"0.6761568",
"0.61890286",
"0.6176186",
"0.61286736",
"0.61255735",
"0.60913527",
"0.6069686",
"0.6035605",
"0.60069... | 0.77555364 | 3 |
When a team is created, its survey is automatically created. | def test_create_team_creates_survey(self):
user = User.create(name='User Foo', email='user@foo.com')
user.put()
code = 'trout viper'
team_response = self.testapp.post_json(
'/api/teams',
{
'name': 'Team Foo',
'code': code,
'program_id': self.ep_program.uid,
},
headers=self.login_headers(user),
)
team_dict = json.loads(team_response.body)
survey_result = Survey.get(team_id=team_dict['uid'])
self.assertEqual(len(survey_result), 1)
survey = survey_result[0]
return user, team_dict | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_teams_create(self):\n pass",
"def test_create_team(self):\n pass",
"def test_generate_survey(self):\n\n result = generate_survey.apply((self.user.id,\n self.report.get_daily().id)).get()\n self.assertTrue(result, \"should create a surv... | [
"0.6586207",
"0.6538541",
"0.64314604",
"0.6378735",
"0.63344073",
"0.6198191",
"0.61724335",
"0.6105733",
"0.6045564",
"0.60214174",
"0.59957623",
"0.59651864",
"0.5957437",
"0.5896016",
"0.5873307",
"0.5823892",
"0.5811888",
"0.5769924",
"0.57607037",
"0.5720423",
"0.569084... | 0.75194645 | 0 |
You can get the survey for a team you own. | def test_get_for_team(self):
user, team_dict = self.test_create_team_creates_survey()
response = self.testapp.get(
'/api/teams/{}/survey'.format(team_dict['uid']),
headers=self.login_headers(user),
)
survey_dict = json.loads(response.body)
self.assertTrue(survey_dict['uid'].startswith('Survey')) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_questionnaire(self, url, survey_path):\n pass",
"def getSurveys(self, **kwargs):\n response = self.request(\"getSurveys\", **kwargs)\n # print response\n surveys = None\n if response:\n surveys = OrderedDict()\n for survey in response[\"Result\"][\... | [
"0.6343129",
"0.631515",
"0.6284795",
"0.6031469",
"0.58984464",
"0.58517706",
"0.5640203",
"0.56234926",
"0.5607942",
"0.55881244",
"0.55276686",
"0.5523524",
"0.55202866",
"0.54980105",
"0.5456152",
"0.545253",
"0.53732574",
"0.5364306",
"0.53133166",
"0.52972543",
"0.52571... | 0.757884 | 0 |
You can't get a survey for someone else's team. | def test_get_for_other_forbidden(self):
user, team_dict = self.test_create_team_creates_survey()
other = User.create(name='Other', email='other@foo.com')
other.put()
self.testapp.get(
'/api/teams/{}/survey'.format(team_dict['uid']),
headers=self.login_headers(other),
status=403,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_for_team(self):\n user, team_dict = self.test_create_team_creates_survey()\n response = self.testapp.get(\n '/api/teams/{}/survey'.format(team_dict['uid']),\n headers=self.login_headers(user),\n )\n survey_dict = json.loads(response.body)\n self... | [
"0.7120516",
"0.6282421",
"0.626813",
"0.618336",
"0.6113319",
"0.6037205",
"0.598216",
"0.5848799",
"0.57429224",
"0.5724888",
"0.570673",
"0.5694278",
"0.5633859",
"0.5616271",
"0.56087244",
"0.5571042",
"0.5523372",
"0.55163455",
"0.5508447",
"0.55008894",
"0.54575586",
... | 0.67539746 | 1 |
PUT response has special jwt giving permission on Neptune. | def test_put_issues_allowed_endpoints_jwt(self):
team_id = 'Team_foo'
survey = Survey.create(team_id=team_id)
survey.put()
user = User.create(name='foo', email='foo@bar.com',
owned_teams=[team_id])
user.put()
# Add some classrooms
c1 = Classroom.create(name='C1', team_id=team_id, code='a a',
contact_id='User_contact')
c2 = Classroom.create(name='C2', team_id=team_id, code='b b',
contact_id='User_contact')
Classroom.put_multi([c1, c2])
response = self.testapp.put_json(
'/api/surveys/{}'.format(survey.uid),
{'metrics': ['Metric_001', 'Metric_002']},
headers=self.login_headers(user),
)
jwt = response.headers['Authorization'][7:] # drop "Bearer "
payload, error = jwt_helper.decode(jwt)
# Should include an endpoint for each classroom.
self.assertEqual(
set(payload['allowed_endpoints']),
{
'PUT //neptune/api/codes/a-a',
'PUT //neptune/api/codes/b-b',
},
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_update_movie_not_authenticated(self):\n data = {'title': 'The Mask 2'}\n response = self.client.patch(self.url, data, format='json')\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)",
"def put(self, op_id: str) -> Response:\n data = request.get_json()\n\n ... | [
"0.64163506",
"0.62620705",
"0.61206746",
"0.60228735",
"0.5972664",
"0.5971649",
"0.59323764",
"0.5917572",
"0.5852224",
"0.5852224",
"0.5821447",
"0.58134544",
"0.5795793",
"0.5792033",
"0.57747847",
"0.5765895",
"0.57658184",
"0.5719392",
"0.5705449",
"0.56970286",
"0.5659... | 0.559168 | 30 |
PUT response has special jwt giving permission on Neptune. | def test_put_artifact_url_sends_email(self):
user = User.create(name='foo', email='foo@bar.com')
team = Team.create(name="Foo Team", captain_id=user.uid,
program_id="Program_foo")
survey = Survey.create(team_id=team.uid)
user.owned_teams = [team.uid]
team.put()
survey.put()
user.put()
artifact_url = 'https://www.example.com/artifact'
# Not changing the artifact does NOT trigger an email.
self.testapp.put_json(
'/api/surveys/{}'.format(survey.uid),
{'meta': {'artifact_url': ''}},
headers=self.login_headers(user),
)
self.assertEqual(Email.count(), 0)
# Changing it triggers an email.
self.testapp.put_json(
'/api/surveys/{}'.format(survey.uid),
{'meta': {'artifact_use': 'true', 'artifact_url': artifact_url}},
headers=self.login_headers(user),
)
emails = Email.get()
self.assertEqual(len(emails), 1)
email = emails[0]
self.assertIn(artifact_url, email.html)
self.assertIn(team.name, email.html)
# Sending a PUT **without** changing it does NOT trigger an email.
self.testapp.put_json(
'/api/surveys/{}'.format(survey.uid),
{'meta': {'artifact_use': 'true', 'artifact_url': artifact_url}},
headers=self.login_headers(user),
)
self.assertEqual(Email.count(), 1) # same as before | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_update_movie_not_authenticated(self):\n data = {'title': 'The Mask 2'}\n response = self.client.patch(self.url, data, format='json')\n self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)",
"def put(self, op_id: str) -> Response:\n data = request.get_json()\n\n ... | [
"0.64163506",
"0.62620705",
"0.61206746",
"0.60228735",
"0.5972664",
"0.5971649",
"0.59323764",
"0.5917572",
"0.5852224",
"0.5852224",
"0.5821447",
"0.58134544",
"0.5795793",
"0.5792033",
"0.57747847",
"0.5765895",
"0.57658184",
"0.5719392",
"0.5705449",
"0.56970286",
"0.5659... | 0.0 | -1 |
Client dict should have portalfriendly metric labels. | def test_metric_labels(self):
team_id = 'Team_foo'
m1 = Metric.create(name='Foo Condition', label='foo_condition')
m2 = Metric.create(name='Bar Condition', label='bar_condition')
Metric.put_multi([m1, m2])
survey = Survey.create(team_id=team_id, metrics=[m1.uid, m2.uid])
survey.put()
user = User.create(name='foo', email='foo@bar.com',
owned_teams=[team_id])
user.put()
response = self.testapp.get(
'/api/surveys/{}'.format(survey.uid),
headers=self.login_headers(user),
)
logging.info(response.body)
self.assertEqual(
json.loads(response.body)['metric_labels'],
{m1.uid: 'foo_condition', m2.uid: 'bar_condition'},
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_host_configuration_metrics1(self):\n pass",
"def test_get_host_configuration_metrics(self):\n pass",
"def mock_client_fixture():\n with mock.patch(f\"{PROMETHEUS_PATH}.prometheus_client\") as client:\n counter_client = mock.MagicMock()\n client.Counter = mock.MagicMo... | [
"0.58376956",
"0.57469577",
"0.5601619",
"0.5601619",
"0.5514434",
"0.55044305",
"0.5325245",
"0.5324136",
"0.5164732",
"0.5106117",
"0.50848985",
"0.5079339",
"0.5064023",
"0.50074315",
"0.5007054",
"0.4984392",
"0.4983079",
"0.4963031",
"0.49587086",
"0.4958586",
"0.4957912... | 0.57984996 | 1 |
Returns the `path` size in bytes and isvalidate. | def _get_run_info(self, path, creation_date):
total = 0
try:
for entry in os.scandir(path):
# Only evaluates size of files and not folders inside raw/proc
if entry.is_file():
# if it's a file, use stat() function
total += entry.stat().st_size
except NotADirectoryError:
# if `path` isn't a directory, get the file size then
total = os.path.getsize(path)
except PermissionError:
# if for whatever reason we can't open the folder, return 0
return 0
if os.path.isdir(path):
validator = RunValidator(path)
elif path.endswith(".h5"):
validator = FileValidator(H5File(path).files[0])
else:
return 0
try:
validator.run_checks()
except Exception:
pass
return total, str(ValidationError(validator.problems)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getsize(path):\n return get_instance(path).getsize(path)",
"def size(path):",
"def getsize(self, path):\n return os.path.getsize(path)",
"def getsize(path):\n return stat(path).st_size",
"def filesize(self, path):\n arinfo = self._handle.getmember(path)\n return arinfo.si... | [
"0.80022764",
"0.7961166",
"0.7923643",
"0.76660985",
"0.75245374",
"0.75245374",
"0.75192183",
"0.75192183",
"0.7501242",
"0.7407785",
"0.73885095",
"0.7332099",
"0.72183996",
"0.71414423",
"0.7121279",
"0.70584697",
"0.7013595",
"0.6994066",
"0.69744694",
"0.69534856",
"0.6... | 0.0 | -1 |
Validates that the two password inputs match. | def clean_password2(self):
if self.clean_data.get('password1', None) and self.clean_data.get('password2', None) and \
self.clean_data['password1'] == self.clean_data['password2']:
return self.clean_data['password2']
raise forms.ValidationError(u'You must type the same password each time') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_password(password1: str, password2: str) -> bool:\n if password1 == password2:\n return True\n else:\n raise ValueError('Пароли не совпадают')",
"def clean_password(self):\n password1 = self.cleaned_data.get('password1')\n password2 = self.cleaned_data.get('password2')... | [
"0.79399914",
"0.7775991",
"0.75286",
"0.751961",
"0.7506222",
"0.7504838",
"0.745747",
"0.745747",
"0.74129796",
"0.7394356",
"0.7387584",
"0.7368053",
"0.73406",
"0.73406",
"0.7324741",
"0.73213553",
"0.73095393",
"0.7277372",
"0.72607356",
"0.72343296",
"0.7186055",
"0.7... | 0.71904254 | 20 |
Pause pattern while self.pauseNow is True return imediatly if self.playStatus == False | def pauseCheck(self):
while (self.playStatus == False and self.pauseNow == True):
self.isPause = True
time.sleep(.25)
self.isPause = False
return self.playStatus | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pause(self):\n while 1:\n if self.is_paused:\n time.sleep(1)\n else:\n break",
"def pause(self):\n if self.status()['state'] == \"playing\":\n self.toggle_pause()",
"def test_pause(self):\n source = procedural.WhiteNoise(0.5)\n ... | [
"0.7879247",
"0.7591245",
"0.75521106",
"0.7544259",
"0.7394605",
"0.72653115",
"0.72582483",
"0.72100365",
"0.7209901",
"0.7202345",
"0.7187789",
"0.7187789",
"0.7176371",
"0.7118577",
"0.71078545",
"0.70944405",
"0.70625925",
"0.70505774",
"0.70505774",
"0.70348316",
"0.703... | 0.78421515 | 1 |
For now, we are only returning the label for the first authorization. | def get_label(self):
auth = self.authorizations[0]
return auth.label | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_label ( self ):\n if self._label is not None:\n return self._label\n return user_name_for( self.name )",
"def _get_label(self):\n return self.label",
"def _get_label ( self ):\n if self._label is not None:\n return self._label\n return self.name... | [
"0.7064338",
"0.6762954",
"0.65058815",
"0.6465353",
"0.6465353",
"0.6465353",
"0.6465353",
"0.6433205",
"0.6383421",
"0.6355541",
"0.6347802",
"0.6343887",
"0.63365865",
"0.6327651",
"0.6327651",
"0.6300275",
"0.6296131",
"0.6296131",
"0.6296131",
"0.6296131",
"0.6296131",
... | 0.8055274 | 0 |
Loads an image from a file path | def load(image_path):
out = None
#####################################
# START YOUR CODE HERE #
#####################################
# Use skimage io.imread
out = io.imread(image_path)
######################################
# END OF YOUR CODE #
######################################
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_image(file_path):\r\n return Image.open(file_path)",
"def load(path) -> Image:\n return Image.open(path)",
"def load_image(self, path):\n if path:\n self.original_image = cv2.imread(path, 1)\n self.prepare_images()",
"def load_image(path_to_image, image_name):\... | [
"0.8446908",
"0.84077847",
"0.8087019",
"0.806678",
"0.7929188",
"0.7838928",
"0.7817189",
"0.772309",
"0.7489495",
"0.74410564",
"0.7429996",
"0.73706484",
"0.7364877",
"0.7321371",
"0.72911817",
"0.7271072",
"0.7242877",
"0.7225145",
"0.720523",
"0.71573806",
"0.71072674",
... | 0.7374733 | 11 |
Change the value of every pixel by following x_n = 0.5x_p^2 where x_n is the new value and x_p is the original value | def change_value(image):
out = None
#####################################
# START YOUR CODE HERE #
#####################################
image = image / 255
out = np.empty_like(image)
height, width, _ = image.shape
for h in range(height):
for w in range(width):
x_p = image[h,w]
x_n = (x_p * x_p) * 0.5
out[h,w] = x_n
######################################
# END OF YOUR CODE #
######################################
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def change_X(X):\n _X = swap_pixels(X.X)\n\n X.update(_X)\n\n return X",
"def recolorPixels(x,y,px, newColorArray):\r\n for i in range(0+coeff1*x,coeff1+coeff1*x):\r\n for j in range(0+coeff1*y,coeff1+coeff1*y):\r\n px[i,j]=newColorArray[x][y]",
"def set_pixel(self, x, y, value):\... | [
"0.6009499",
"0.6003074",
"0.5953545",
"0.58825284",
"0.5864363",
"0.57073236",
"0.5685161",
"0.56669635",
"0.56421584",
"0.55719",
"0.5569989",
"0.5528347",
"0.55130744",
"0.54917955",
"0.54803175",
"0.5448064",
"0.5439173",
"0.5424856",
"0.5372966",
"0.5365994",
"0.53644747... | 0.7488139 | 0 |
Change image to gray scale | def convert_to_grey_scale(image):
out = None
#####################################
# START YOUR CODE HERE #
#####################################
out = color.rgb2gray(image)
######################################
# END OF YOUR CODE #
######################################
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_to_gray_scale(img):\r\n #reading image\r\n im = Image.open(\"filename\")\r\n\r\n if im.mode != \"L\":\r\n im = im.convert(\"L\")\r\n\r\n return img",
"def convertImageToGrey(self):\n self.cnvImgTest.convertToGreyscale()",
"def gray_scale_img(img):\n if len(img.shape) ==... | [
"0.7942807",
"0.769168",
"0.76889527",
"0.7666961",
"0.76355445",
"0.7625111",
"0.7581593",
"0.7507202",
"0.7507202",
"0.75054574",
"0.7501831",
"0.74930036",
"0.7488352",
"0.7467151",
"0.72188574",
"0.7216018",
"0.7204566",
"0.7200213",
"0.71970624",
"0.71568024",
"0.7147095... | 0.7499669 | 11 |
Find successors (including those that result in dining) to this state. But a state where the cannibals can dine has no successors. | def csuccessors(state):
M1, C1, B1, M2, C2, B2 = state
assert B1 is 1 or B2 is 1
pairs = {}
moves = [(0,1), (1,0), (1,1), (2,0), (0,2)]
if C1 > M1 or C2 > M2:
return pairs # more cannibals than missionaries
if B1 is 1:
B1, B2 = 0, 1
for m, c in moves:
if M1 - m >= 0 and C1 - c >= 0:
state = (M1-m, C1-c, B1, M2+m, C2+c, B2)
action = 'M' * m + 'C' * c + '->'
pairs[state] = action
else:
B1, B2 = 1, 0
for m, c in moves:
if M2 - m >= 0 and C2 - c >= 0:
state = (M1+m, C1+c, B1, M2-m, C2-c, B2)
action = '<-' + 'M' * m + 'C' * c
pairs[state] = action
return pairs | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def successorStates(self, state):\n currentState = state[1]\n successors = []\n for action in Directions.CARDINAL:\n x, y = state[0] # currentPosition\n print(\"State: {}\".format(state[0]))\n dx, dy = Actions.directionToVector(action)\n nextx, n... | [
"0.6894618",
"0.68291223",
"0.67817956",
"0.6704799",
"0.66240865",
"0.64933735",
"0.6401269",
"0.6368074",
"0.63232535",
"0.6315073",
"0.63110363",
"0.6297232",
"0.62779444",
"0.62356126",
"0.6207891",
"0.61754274",
"0.6164512",
"0.61620885",
"0.60629934",
"0.60273325",
"0.5... | 0.6236211 | 13 |
Solve the missionaries and cannibals problem. | def solve(start=(3,3,1,0,0,0), goal=None):
if goal is None:
goal = (0, 0, 0) + start[:3]
if start == goal:
return [start]
explored = set() # explored states
frontier = [ [start] ] # ordered list of paths taken
while frontier:
path = frontier.pop(0)
s = path[-1]
for (state, action) in csuccessors(s).items():
if state not in explored:
explored.add(state)
path2 = path + [action, state]
if state == goal:
return path2
else:
frontier.append(path2) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solve(self):",
"def solve(self):\n for step in self.run.values():\n step.solve()",
"def solve(self):\n pass",
"def solve(self):\n pass",
"def main():\r\n # Instantiate the data problem.\r\n data = create_data_model()\r\n\r\n # Create the routing index manager.\r... | [
"0.6371754",
"0.61560553",
"0.60753506",
"0.60753506",
"0.6040063",
"0.5984552",
"0.5885841",
"0.5864889",
"0.58444935",
"0.5786145",
"0.57801163",
"0.57695884",
"0.57650137",
"0.5738106",
"0.57322955",
"0.57266694",
"0.56898814",
"0.5668505",
"0.5639238",
"0.56376314",
"0.56... | 0.0 | -1 |
Initialize your data structure here. | def __init__(self):
self.nums, self.set = [], set() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _init_empty(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__... | [
"0.7765608",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7595176",
"0.75853467",
"0.7558298",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.74971247",
"0.74971247",
"0.7478105",
"0.7477832",
"0.7477832",
"0.7477832",
... | 0.0 | -1 |
Inserts a value to the set. Returns true if the set did not already contain the specified element. | def insert(self, val: int) -> bool:
if val not in self.set:
self.nums.append(val);
self.set.add(val);
return True;
return False; | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def insert(self, val: int) -> bool:\n if val not in self.set:\n self.set.add(val)\n return True\n return False",
"def insert(self, val: int) -> bool:\n if val not in self.value_set:\n self.value_set.add(val)\n self.values.append(val)\n r... | [
"0.7981581",
"0.76095164",
"0.7475566",
"0.7245517",
"0.721515",
"0.72014433",
"0.7169923",
"0.71647173",
"0.7147763",
"0.7050221",
"0.6949471",
"0.6948543",
"0.692912",
"0.6911351",
"0.69021297",
"0.68781555",
"0.68749684",
"0.68749684",
"0.68749684",
"0.68749684",
"0.687496... | 0.75030303 | 2 |
Removes a value from the set. Returns true if the set contained the specified element. | def remove(self, val: int) -> bool:
if val in self.set:
self.set.remove(val);
self.nums.remove(val);
return True;
return False; | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def remove(self, val: int) -> bool:\n if val in self.set:\n self.set.remove(val)\n return True\n return False",
"def remove(self, val: int) -> bool:\n temp = self.randomSet.pop(val, False)\n return True if temp != False else temp",
"def remove(self, val: int) -... | [
"0.7793552",
"0.7472986",
"0.7311967",
"0.7115737",
"0.70873374",
"0.69927806",
"0.6945106",
"0.68983823",
"0.68566453",
"0.68520516",
"0.68365693",
"0.68351394",
"0.68248504",
"0.6823558",
"0.6823558",
"0.6814836",
"0.67781126",
"0.67604584",
"0.67402226",
"0.6724619",
"0.67... | 0.7555588 | 1 |
Get a random element from the set. | def getRandom(self) -> int:
return self.nums[random.randint(0, len(self.nums) - 1)] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getRandom(self):\n return self.nums[random.randint(0, len(self.nums) - 1)]\n\n # Your RandomizedSet object will be instantiated and called as such:\n # obj = RandomizedSet()\n # param_1 = obj.insert(val)\n # param_2 = obj.remove(val)\n # param_3 = obj.getRandom()",
"... | [
"0.77060276",
"0.738916",
"0.7296881",
"0.72187954",
"0.6871744",
"0.68453854",
"0.68330806",
"0.67740154",
"0.67226046",
"0.6703282",
"0.6665089",
"0.66356236",
"0.66217655",
"0.6612035",
"0.66000897",
"0.6567767",
"0.6477719",
"0.6462421",
"0.64428514",
"0.64162946",
"0.640... | 0.0 | -1 |
Extract data and the respective labels from a file | def get_data(dataf):
with open(dataf) as f:
label = []
e_val = []
for line in f:
label.append(float(line.split()[1]))
e_val.append(-1 * float(line.split()[0]))
return label, e_val | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_data(feature_file, label_file):",
"def get_labeled_data(filename):\n e = []\n y = []\n with open(filename) as f:\n for line in f:\n e.append(line[1:-1])\n y.append(category_mapping[abbreviation_mapping[line[0]]])\n return e, y",
"def extract_labels(filename):\n print('Extracting', fi... | [
"0.78632253",
"0.7686063",
"0.7579877",
"0.7308805",
"0.7265475",
"0.7195249",
"0.7183214",
"0.7164446",
"0.7081873",
"0.7065159",
"0.7054382",
"0.7001995",
"0.69624895",
"0.69351774",
"0.69117355",
"0.69072485",
"0.69013715",
"0.68989193",
"0.68852144",
"0.6870289",
"0.68665... | 0.6445296 | 79 |
Print a ROC curve given lists of coordinates (fpr, tpr) | def roc2(fpr, tpr, roc_auc):
plt.figure()
plt.plot(fpr, tpr, color='darkorange', lw=2, label='ROC curve (area = %0.2f)' % roc_auc)
plt.plot([0, 1], [0, 1], color='navy', lw=1, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic')
plt.legend(loc="lower right")
plt.show() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def draw_roc_curve(fpr, tpr, labels=None, size_inch=(5, 5), dpi=160, show=False, block=False):\n if not isinstance(fpr, np.ndarray) or not isinstance(tpr, np.ndarray):\n raise AssertionError(\"invalid inputs\")\n if fpr.shape != tpr.shape:\n raise AssertionError(\"mismatched input sizes\")\n ... | [
"0.73913735",
"0.7386855",
"0.7301513",
"0.73008204",
"0.72942024",
"0.722823",
"0.7214494",
"0.7154316",
"0.70779616",
"0.70447993",
"0.7016029",
"0.7015976",
"0.6989623",
"0.6985157",
"0.6965045",
"0.6962366",
"0.6947648",
"0.69254315",
"0.6915011",
"0.68359005",
"0.6800327... | 0.7168564 | 7 |
Add an HTML max length validator and/or a CKEditor configuration based on what is configured in settings for the current placeholder. | def get_form(self, request, obj=None, change=False, **kwargs):
form = super().get_form(request, obj=obj, change=change, **kwargs)
placeholder_id = request.GET.get("placeholder_id")
if not placeholder_id and not obj:
return form
if placeholder_id:
placeholder = Placeholder.objects.only("slot").get(id=placeholder_id)
else:
placeholder = obj.placeholder
for configuration in SIMPLETEXT_CONFIGURATION:
if (
"placeholders" not in configuration
or placeholder.slot in configuration["placeholders"]
):
break
else:
configuration = {}
body_field = form.base_fields["body"]
if configuration.get("max_length"):
body_field.validators.append(
HTMLMaxLengthValidator(configuration["max_length"])
)
if configuration.get("ckeditor"):
body_field.widget = TextEditorWidget(
configuration=configuration["ckeditor"]
)
return form | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _adjust_max_comment_length(form, field_name='comment'):\r\n form.base_fields['comment'].max_length = DEFAULT_MAX_COMMENT_LENGTH",
"def clean_content_length(field_name, min_length=0, max_length=500):\n\n @check_field_is_empty(field_name)\n def wrapper(self):\n \"\"\"Decorator wrapper method.\n \"\"... | [
"0.55875015",
"0.5479618",
"0.5419644",
"0.5283157",
"0.52528405",
"0.522794",
"0.52224386",
"0.5122975",
"0.50060946",
"0.50013745",
"0.494857",
"0.49309137",
"0.48792347",
"0.48636127",
"0.48341784",
"0.48145968",
"0.48143637",
"0.4809541",
"0.47800308",
"0.47724333",
"0.47... | 0.45268467 | 51 |
Build plugin context passed to its template to perform rendering | def render(self, context, instance, placeholder):
context = super().render(context, instance, placeholder)
context.update({"instance": instance})
return context | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def render(self):\n\n template_string = parseValues(self.data)[1]\n context = self.context\n\n # Run the prebuild plugins, we can't use the standard method here because\n # plugins can chain-modify the context and data.\n for plugin in self.site._plugins:\n if hasattr(... | [
"0.67031616",
"0.6571523",
"0.6424486",
"0.6072535",
"0.5999363",
"0.582176",
"0.5783573",
"0.5759585",
"0.57382077",
"0.57181376",
"0.56852263",
"0.5682577",
"0.5667774",
"0.5642691",
"0.5627336",
"0.5583352",
"0.55389804",
"0.5489847",
"0.54796433",
"0.54766",
"0.54761475",... | 0.0 | -1 |
Call whoami and expect an output | def test_call_command(self):
p = call('whoami', shell=False, executable=None, path=None)
self.assertIsInstance(p, Response)
self.assertIsInstance(p.stdout, str)
self.assertIsInstance(p.stderr, str) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def whoami(ctx):\n ctx.setup_logger(format='')\n AuthCmd(ctx).whoami()",
"def whoami(self):",
"def whoami():\n all_informations = run('uname -a',quiet=True)\n fqdn = run('hostname -f',quiet=True)\n print(yellow('Informations : ')+all_informations)\n print(yellow('FQDN : ')+fqdn)",
"def run_... | [
"0.7652164",
"0.7329425",
"0.73260736",
"0.67614555",
"0.6689236",
"0.65300286",
"0.6431658",
"0.6374339",
"0.6258411",
"0.6235286",
"0.60788286",
"0.6035754",
"0.6007168",
"0.5951228",
"0.5930895",
"0.59141916",
"0.5905599",
"0.5892375",
"0.5845104",
"0.5716784",
"0.56899244... | 0.71804494 | 3 |
PROVN representation of qualified name in a string. | def provn_representation(self):
return '"%s" %%%% xsd:anyURI' % self._uri | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _namespace_to_unicode(self):\n\t\treturn u\":\".join(self.namespace_parts)",
"def fully_qualified_name(self) -> str:\n return pulumi.get(self, \"fully_qualified_name\")",
"def get_qualified_name(self):\n return self.attributes[\"qualifiedName\"]",
"def provn_representation(self):\n r... | [
"0.6337318",
"0.62333804",
"0.6226227",
"0.6200508",
"0.61675906",
"0.614249",
"0.61223435",
"0.60970294",
"0.6077363",
"0.60522175",
"0.60409945",
"0.6036419",
"0.5949034",
"0.59314924",
"0.5897743",
"0.5884507",
"0.5878005",
"0.5872136",
"0.58412665",
"0.582367",
"0.5798794... | 0.56616455 | 30 |
Namespace of qualified name. | def namespace(self):
return self._namespace | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getNamespace(self):\n pass;",
"def namespace(self):\n assert self._namespace\n return self._namespace",
"def namespace(self):\n name = self._name if self._name is not None else '<unnamed>'\n if self._parent is None:\n return name\n return '.'.join([self._parent.... | [
"0.79194593",
"0.77542627",
"0.7565962",
"0.74886805",
"0.7448928",
"0.7448831",
"0.7446291",
"0.73636454",
"0.72533864",
"0.7240882",
"0.71560305",
"0.71484077",
"0.7054701",
"0.7054701",
"0.7054701",
"0.6985228",
"0.6875989",
"0.68536323",
"0.68068796",
"0.6781957",
"0.6757... | 0.7325897 | 8 |
Local part of qualified name. | def localpart(self):
return self._localpart | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def strip_local_prefix(self, stmt, qname):\n pref, colon, name = qname.partition(\":\")\n if colon and pref == stmt.i_module.i_prefix:\n return name\n else:\n return qname",
"def local_var_name(global_name):\n return global_name.split(':')[-1].split('.')[-1]",
... | [
"0.7030537",
"0.6942859",
"0.68614817",
"0.67557806",
"0.67522043",
"0.67152476",
"0.66734105",
"0.6602574",
"0.6508001",
"0.63670015",
"0.6364165",
"0.62062585",
"0.615663",
"0.615663",
"0.6099846",
"0.60868347",
"0.60564834",
"0.5949142",
"0.5933793",
"0.5860535",
"0.586053... | 0.5870647 | 19 |
PROVN representation of qualified name in a string. | def provn_representation(self):
return "'%s'" % self._str | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _namespace_to_unicode(self):\n\t\treturn u\":\".join(self.namespace_parts)",
"def fully_qualified_name(self) -> str:\n return pulumi.get(self, \"fully_qualified_name\")",
"def get_qualified_name(self):\n return self.attributes[\"qualifiedName\"]",
"def full_namespace(self) -> str:\n ... | [
"0.6337318",
"0.62333804",
"0.6226227",
"0.61675906",
"0.614249",
"0.61223435",
"0.60970294",
"0.6077363",
"0.60522175",
"0.60409945",
"0.6036419",
"0.5949034",
"0.59314924",
"0.5897743",
"0.5884507",
"0.5878005",
"0.5872136",
"0.58412665",
"0.582367",
"0.57987946",
"0.579400... | 0.6200508 | 3 |
Indicates whether the identifier provided is contained in this namespace. | def contains(self, identifier):
uri = identifier if isinstance(identifier, six.string_types) else (
identifier.uri if isinstance(identifier, Identifier) else None
)
return uri.startswith(self._uri) if uri else False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __contains__(self, identifier):\n # following breaks some tests, what is the expected behaviour?\n # return any(m.unique_id.endswith(identifier) for m in self)\n return any(m.unique_id == identifier for m in self)",
"def is_declared(self, identifier: str) -> bool:\n if identifier ... | [
"0.695668",
"0.6656405",
"0.6532839",
"0.64874536",
"0.6400062",
"0.63559645",
"0.6343124",
"0.6330577",
"0.6319895",
"0.6311052",
"0.6293539",
"0.62231743",
"0.619792",
"0.6197703",
"0.6196918",
"0.6167409",
"0.6140008",
"0.60929984",
"0.60690624",
"0.60648376",
"0.60636157"... | 0.77918166 | 0 |
Returns the qualified name of the identifier given using the namespace prefix. | def qname(self, identifier):
uri = identifier if isinstance(identifier, six.string_types) else (
identifier.uri if isinstance(identifier, Identifier) else None
)
if uri and uri.startswith(self._uri):
return QualifiedName(self, uri[len(self._uri):])
else:
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prefix_to_ns(self, prefix):\n defin = self.module.i_ctx.get_module(\n self.module.i_prefixes[prefix][0])\n return defin.search_one(\"namespace\").arg",
"def _getPrefix(self, namespaceURI):\r\n prefixDict = self._getPrefixDict()\r\n if prefixDict.has_key(namespaceURI):\r... | [
"0.769194",
"0.7337281",
"0.7326206",
"0.7299526",
"0.72524375",
"0.7053602",
"0.69734764",
"0.69541156",
"0.6775588",
"0.6710584",
"0.67020273",
"0.66632754",
"0.66148424",
"0.65285033",
"0.6503347",
"0.64935726",
"0.64636904",
"0.64574414",
"0.6445418",
"0.6430217",
"0.6414... | 0.6731498 | 9 |
Init new stack based on Dynamic Array DO NOT CHANGE THIS METHOD IN ANY WAY | def __init__(self):
self.da = DynamicArray() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create(self):\n if self.size == 0:\n self.size = int(input(\"Enter size of the stack to be created: \"))\n self.arr = [None] * self.size",
"def __init__(self):\n self.data = ArrayStack(10)",
"def __init__(self):\n self.stack = collections.deque([])",
"def create_sta... | [
"0.7457198",
"0.7331999",
"0.7084405",
"0.70811796",
"0.69233215",
"0.69006336",
"0.686873",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.6843798",
"0.67822534",
"0.6761566",
"0.6733388",
... | 0.5693851 | 96 |
Return content of stack in humanreadable form DO NOT CHANGE THIS METHOD IN ANY WAY | def __str__(self) -> str:
out = "STACK: " + str(self.da.length()) + " elements. ["
out += ', '.join([str(self.da.get_at_index(_))
for _ in range(self.da.length())])
return out + ']' | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __repr__(self):\n return str(self.stack)",
"def getStackString(self):\n return \"\".join(self.stack[:0:-1])",
"def __str__(self) -> str:\n res = '*** top of stack ***\\n'\n\n # iterate through the stack.\n # Note: we are using our __iter__ method here\n for element... | [
"0.786926",
"0.7739289",
"0.76698506",
"0.7501194",
"0.7452612",
"0.72843957",
"0.72662354",
"0.72662354",
"0.72662354",
"0.72662354",
"0.72380555",
"0.70351225",
"0.698751",
"0.698751",
"0.69223225",
"0.69223225",
"0.6841419",
"0.6660907",
"0.649776",
"0.6488226",
"0.6484695... | 0.65129346 | 18 |
Return True is the stack is empty, False otherwise DO NOT CHANGE THIS METHOD IN ANY WAY | def is_empty(self) -> bool:
return self.da.is_empty() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def empty(self) -> bool:\n if len(self.stack)==0:\n return True\n else:\n return False",
"def empty(self):\r\n return self.stack == []",
"def empty(self):\r\n return len(self.stack) == 0",
"def empty(self):\n return self.stack == []",
"def is_empty(s... | [
"0.9123999",
"0.90650344",
"0.9026214",
"0.895296",
"0.8951374",
"0.8931137",
"0.8931137",
"0.8905325",
"0.8888884",
"0.88337415",
"0.87710994",
"0.87356853",
"0.8720948",
"0.8720948",
"0.8673681",
"0.8637049",
"0.86131716",
"0.85480964",
"0.8546706",
"0.8510701",
"0.8494888"... | 0.0 | -1 |
Return number of elements currently in the stack DO NOT CHANGE THIS METHOD IN ANY WAY | def size(self) -> int:
return self.da.length() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def size(self):\n return self.N # Number of items in the stack",
"def size(self): #returns the size or number of items in the stack\n if self.is_empty():\n return 0\n else:\n return self.num_items",
"def __len__(self):\n return len(self.stack)",
... | [
"0.8630269",
"0.8159148",
"0.80723697",
"0.79899883",
"0.7947353",
"0.7894318",
"0.78837955",
"0.78837955",
"0.7862439",
"0.76882833",
"0.75424826",
"0.74320614",
"0.69482553",
"0.69482553",
"0.69375956",
"0.6909171",
"0.6868728",
"0.67909694",
"0.6777687",
"0.67611516",
"0.6... | 0.0 | -1 |
push function adds the values into the dynamic array | def push(self, value: object) -> None:
self.da.append(value)
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def push(self, value): ################# <-\n self.lst = self.lst +[value]",
"def add(self, value):\n self.arr.append(value)",
"def push(self, value):\n self.last = self.current\n self.current = np.array(value)",
"def add_values(self, *values, replace=False):\n\n if replace... | [
"0.67537516",
"0.6736303",
"0.64801556",
"0.62559104",
"0.6243577",
"0.6235336",
"0.62251127",
"0.62170935",
"0.62170935",
"0.6210711",
"0.62074614",
"0.62074614",
"0.61923796",
"0.6175564",
"0.61663246",
"0.6152777",
"0.61274415",
"0.6088337",
"0.6059232",
"0.60531515",
"0.6... | 0.62030673 | 12 |
pop function removes the top element of the stack and returns it. If the stack is empty, it raises Stack Exception | def pop(self) -> object:
if self.is_empty()== True: # if size of array is 0, raise exception
raise StackException
else:
top_stack = self.da.get_at_index(self.size()-1) # initialize the top of the stack (last element)
self.da.remove_at_index(self.size()-1) # remove it
return top_stack # return variable
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pop():\n stack = _get_stack()\n return _pop(stack)",
"def pop(self):\n if not self.isEmpty():\n self.top -= 1\n return self.stack.pop()\n else:\n raise Exception(\"Stack Underflow\")",
"def pop(self):\n # Making sure that the stack is not empty\n ... | [
"0.8852038",
"0.86380845",
"0.86031",
"0.8600234",
"0.84228384",
"0.83492935",
"0.834905",
"0.831788",
"0.82513225",
"0.82470196",
"0.82214785",
"0.82048887",
"0.8192677",
"0.8191675",
"0.81529903",
"0.81526566",
"0.8116631",
"0.80768657",
"0.80718434",
"0.807138",
"0.8042891... | 0.86377245 | 2 |
top function returns the top of stack without removing it | def top(self) -> object:
if self.is_empty()== True: # if size of array is 0, raise exception
raise StackException
return self.da.get_at_index(self.size()-1) # return the top of the stack (last element)
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def top(stack):\n if empty_stack(stack):\n raise IndexError(\"Stack is empty!\")\n else:\n return stack.top.value",
"def top(self):\n if self.stack == []:\n return None\n return self.stack[-1]",
"def top(state):\n if len(state[STACK]) <= 0:\n return -1\n ... | [
"0.8395421",
"0.83918774",
"0.8216723",
"0.8180373",
"0.8177605",
"0.80990005",
"0.7987349",
"0.7987349",
"0.79455775",
"0.7768455",
"0.7682946",
"0.7681656",
"0.7681302",
"0.765822",
"0.76458704",
"0.7643049",
"0.76326025",
"0.76272935",
"0.757025",
"0.7557962",
"0.7517474",... | 0.74650156 | 22 |
Retrieves credentials to run functional tests Credentials are either read from the environment or from a config file ('functional_creds.conf'). Environment variables override those from the config file. The 'functional_creds.conf' file is the clean and new way to use (by default tox 2.0 does not pass environment variables). | def credentials():
username = os.environ.get('OS_USERNAME')
password = os.environ.get('OS_PASSWORD')
tenant_name = (os.environ.get('OS_TENANT_NAME') or
os.environ.get('OS_PROJECT_NAME'))
auth_url = os.environ.get('OS_AUTH_URL')
config = configparser.RawConfigParser()
if config.read(_CREDS_FILE):
username = username or config.get('admin', 'user')
password = password or config.get('admin', 'pass')
tenant_name = tenant_name or config.get('admin', 'tenant')
auth_url = auth_url or config.get('auth', 'uri')
return {
'username': username,
'password': password,
'tenant_name': tenant_name,
'uri': auth_url
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cfg_credentials(context):\n arguments = {\n '--config': context.config_file,\n 'authorize': False,\n 'account_summary': False\n }\n pychex_cli = PychexCli(arguments)\n pychex_cli.read_config()\n # Check that the values pulled from the read_config method match what we\n # ... | [
"0.67632484",
"0.66186816",
"0.6517438",
"0.6489512",
"0.64814514",
"0.64630115",
"0.6462314",
"0.64449906",
"0.64166945",
"0.64114285",
"0.6402676",
"0.64013535",
"0.6397005",
"0.6397005",
"0.63863087",
"0.6372507",
"0.6362634",
"0.63454527",
"0.6343021",
"0.6340192",
"0.634... | 0.6198195 | 38 |
Verify that output table has headers item listed in field_names. | def assertTableHeaders(self, output_lines, field_names):
table = self.parser.table(output_lines)
headers = table['headers']
for field in field_names:
self.assertIn(field, headers) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def assert_show_fields(self, show_output, field_names):\n\n # field_names = ['name', 'description']\n # show_output = [{'name': 'fc2b98d8faed4126b9e371eda045ade2'},\n # {'description': 'description-821397086'}]\n # this next line creates a flattened list of all 'keys' (like 'na... | [
"0.71665496",
"0.69928867",
"0.69691926",
"0.6916123",
"0.6892314",
"0.682082",
"0.6780092",
"0.67301995",
"0.6690977",
"0.66392064",
"0.6528734",
"0.6500211",
"0.6498844",
"0.64815634",
"0.6458742",
"0.64520425",
"0.63763213",
"0.62508994",
"0.62471277",
"0.6220344",
"0.6196... | 0.84269035 | 0 |
Check presence of common object properties. | def assert_object_details(self, expected, items):
for value in expected:
self.assertIn(value, items) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_properties(self):\r\n for prop in self.mandatory_properties:\r\n if not hasattr(self, prop):\r\n raise NameError(prop)",
"def _has_valid_mandatory_properties(self):\n for prop in self.mandatory_properties:\n if not hasattr(self, prop):\n ... | [
"0.68361294",
"0.6376488",
"0.6125492",
"0.6087755",
"0.57784665",
"0.57475066",
"0.5743678",
"0.57321405",
"0.5681644",
"0.56455135",
"0.56306636",
"0.5630123",
"0.56212044",
"0.55530804",
"0.55530804",
"0.55285686",
"0.5517225",
"0.5502944",
"0.54334295",
"0.5424331",
"0.53... | 0.0 | -1 |
Create a dictionary from an output | def _get_property_from_output(self, output):
obj = {}
items = self.parser.listing(output)
for item in items:
obj[item['Property']] = str(item['Value'])
return obj | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parse_output(output):\n lines = output.splitlines()[3:-1]\n r = {}\n for line in lines:\n kv = filter(None, line.split('|'))\n kv = [x.strip() for x in kv]\n r.update({kv[0]: kv[1]})\n return r",
"def _get_output_dictionary(self):\n\n return_dictionary = {}\n\n ... | [
"0.7458908",
"0.6636358",
"0.6539277",
"0.64794725",
"0.6453821",
"0.64392745",
"0.6378547",
"0.6347167",
"0.6300203",
"0.62663984",
"0.6249434",
"0.6200246",
"0.617561",
"0.6171171",
"0.61182153",
"0.6114068",
"0.61129606",
"0.60749435",
"0.6059385",
"0.6053162",
"0.60514975... | 0.6664644 | 1 |
Wait until object reaches given status. | def wait_for_object_status(self, object_name, object_id, status,
timeout=120, interval=3):
cmd = self.object_cmd(object_name, 'show')
start_time = time.time()
while time.time() - start_time < timeout:
if status in self.cinder(cmd, params=object_id):
break
time.sleep(interval)
else:
self.fail("%s %s did not reach status %s after %d seconds."
% (object_name, object_id, status, timeout)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def wait_for_status(self, status):\n code = self.instance.state['Code']\n while code != status:\n time.sleep(3)\n self.instance.reload()\n code = self.instance.state['Code']",
"def check_completion(self):\n\n time.sleep(3)\n while self.status == 0:\n ... | [
"0.73892504",
"0.72170204",
"0.71951866",
"0.70215213",
"0.6863582",
"0.6744071",
"0.6706966",
"0.66450965",
"0.6635064",
"0.65745586",
"0.6519117",
"0.6512439",
"0.65002567",
"0.6495888",
"0.6489756",
"0.6467292",
"0.6467292",
"0.6445491",
"0.6445491",
"0.64176154",
"0.64089... | 0.7880691 | 0 |
Check that object deleted successfully. | def check_object_deleted(self, object_name, object_id, timeout=60):
cmd = self.object_cmd(object_name, 'show')
try:
start_time = time.time()
while time.time() - start_time < timeout:
if object_id not in self.cinder(cmd, params=object_id):
break
except exceptions.CommandFailed:
pass
else:
self.fail("%s %s not deleted after %d seconds."
% (object_name, object_id, timeout)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _objectDeleted(self, obj):\n pass",
"def do_deleting(self, request, obj, obj_display, obj_id):\n try:\n with transaction.atomic(savepoint=False):\n self.log_deletion(request, obj, obj_display)\n self.delete_model(request, obj)\n\n return s... | [
"0.7490332",
"0.7215603",
"0.7164006",
"0.7086588",
"0.70412916",
"0.70006657",
"0.69678736",
"0.6930805",
"0.6886216",
"0.68708795",
"0.68376404",
"0.68198115",
"0.6819284",
"0.6812539",
"0.679975",
"0.67971224",
"0.6778325",
"0.6737792",
"0.6717377",
"0.66977274",
"0.669110... | 0.7400769 | 1 |
Delete specified object by ID. | def object_delete(self, object_name, object_id):
cmd = self.object_cmd(object_name, 'list')
cmd_delete = self.object_cmd(object_name, 'delete')
if object_id in self.cinder(cmd):
self.cinder(cmd_delete, params=object_id) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_object(self, id):\n return self.request(\n \"{0}/{1}\".format(self.version, id), method=\"DELETE\"\n )",
"def delete_object(self, id):\n self.request(id, post_args={\"method\": \"delete\"})",
"def delete(self, id):\n raise NotImplementedError",
"def delete(se... | [
"0.8803958",
"0.87934405",
"0.81774986",
"0.8085157",
"0.80095756",
"0.7923544",
"0.7919969",
"0.7898343",
"0.78820676",
"0.77202994",
"0.7683921",
"0.7647502",
"0.7644657",
"0.764196",
"0.7593901",
"0.75881594",
"0.7587561",
"0.7587561",
"0.7587561",
"0.7587561",
"0.7587561"... | 0.7656951 | 11 |
A simple solution that runs in O(N) in time and space | def simple_solution(self, dominoes: str) -> str:
dominoes = list(dominoes)
nodes = [(-1, 'L')] + [(i, x) for i, x in enumerate(dominoes) if x != '.'] + [
(len(dominoes), 'R')]
for (i, x), (j, y) in zip(nodes, nodes[1:]):
if x == y:
for k in range(i + 1, j):
dominoes[k] = x
elif x == 'R' and y == 'L':
k, l = i, j
while k < l:
dominoes[k] = x
dominoes[l] = y
k, l = k + 1, l - 1
if ((j - i + 1) % 2) != 0:
dominoes[(j + i) // 2] = '.'
return ''.join(dominoes) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solution(number): # O(N)\n m = {\n 0: 0,\n 1: 1\n } # O(1)\n\n for i in range(2, number + 1): # O(N)\n m[i] = m[i - 1] + m[i - 2] ... | [
"0.67670864",
"0.6457243",
"0.63699317",
"0.63602734",
"0.63394123",
"0.62733823",
"0.625933",
"0.6256404",
"0.62069196",
"0.611461",
"0.61137253",
"0.6109911",
"0.61087",
"0.60923487",
"0.6089412",
"0.6086909",
"0.6074533",
"0.60509086",
"0.6021961",
"0.60112464",
"0.6007973... | 0.0 | -1 |
Another solution that runs in O(N) in time and space | def prefix_sums(self, dominoes: str) -> str:
dominoes = list(dominoes)
R = [1 if dominoes[0] == 'R' else 0]
L = [1 if dominoes[-1] == 'L' else 0]
for domino in dominoes[1:]:
if domino == 'L':
R.append(0)
elif domino == 'R':
R.append(1)
else:
R.append(R[-1] + 1 if R[-1] > 0 else 0)
for domino in reversed(dominoes[:-1]):
if domino == 'R':
L.append(0)
elif domino == 'L':
L.append(1)
else:
L.append(L[-1] + 1 if L[-1] > 0 else 0)
for i in range(len(dominoes)):
j = len(dominoes) - i - 1
if R[i] == L[j]:
dominoes[i] = '.'
elif R[i] == 0 or L[j] == 0:
dominoes[i] = 'R' if L[j] == 0 else 'L'
else:
dominoes[i] = 'R' if R[i] < L[j] else 'L'
return ''.join(dominoes) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solution(number): # O(N)\n m = {\n 0: 0,\n 1: 1\n } # O(1)\n\n for i in range(2, number + 1): # O(N)\n m[i] = m[i - 1] + m[i - 2] ... | [
"0.65543354",
"0.6385863",
"0.6259286",
"0.62479013",
"0.62419236",
"0.62313765",
"0.6225552",
"0.61846197",
"0.6164834",
"0.6109419",
"0.6085789",
"0.60311127",
"0.600526",
"0.5996835",
"0.5993575",
"0.59864",
"0.59821874",
"0.596685",
"0.59272826",
"0.59256256",
"0.5907769"... | 0.0 | -1 |
There are N dominoes in a line, and we place each domino vertically upright. In the beginning, we simultaneously push some of the dominoes either to the left or to the right. After each second, each domino that is falling to the left pushes the adjacent domino on the left. Similarly, the dominoes falling to the right push their adjacent dominoes standing on the right. When a vertical domino has dominoes falling on it from both sides, it stays still due to the balance of the forces. For the purposes of this question, we will consider that a falling domino expends no additional force to a falling or already fallen domino. Given a string "S" representing the initial state. S[i] = 'L', if the ith domino has been pushed to the left; S[i] = 'R', if the ith domino has been pushed to the right; S[i] = '.', if the ith domino has not been pushed. Return a string representing the final state. | def pushDominoes(self, dominoes: str) -> str:
return self.simple_solution(dominoes) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pushDominoes(self, dominoes: str) -> str:\n\n N = len(dominoes)\n dist_R = [-1] * N\n dist_L = [-1] * N\n\n count = -1\n for i in range(N):\n if dominoes[i] == 'R':\n count = 0\n elif dominoes[i] == 'L':\n count = -1\n ... | [
"0.6008191",
"0.57589865",
"0.5368744",
"0.53219604",
"0.5282038",
"0.5232123",
"0.52019006",
"0.5195394",
"0.5173366",
"0.5168104",
"0.51569736",
"0.5141222",
"0.51304805",
"0.5118984",
"0.5097344",
"0.50960946",
"0.5071667",
"0.5049941",
"0.5035389",
"0.5035274",
"0.5012075... | 0.0 | -1 |
check sparsemaxloss kernel against numpy | def _test_sparsemax_loss_against_numpy(self, dtype, random, use_gpu):
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1
tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)
np_loss = self._np_sparsemax_loss(z, q).astype(dtype)
self.assertAllCloseAccordingToType(
np_loss, tf_loss_out, half_atol=1e-2, half_rtol=5e-3)
self.assertShapeEqual(np_loss, tf_loss_op) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_positive(self, dtype, random, use_gpu):\n z = random.uniform(low=-3, high=3, size=(test_obs, 10))\n q = np.zeros((test_obs, 10))\n q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1\n\n tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)\n\n... | [
"0.6425822",
"0.64143616",
"0.6307287",
"0.61605656",
"0.6009254",
"0.5761981",
"0.5626876",
"0.5618227",
"0.5602798",
"0.5556589",
"0.55460817",
"0.55382633",
"0.5535278",
"0.5496034",
"0.5479103",
"0.545446",
"0.5430234",
"0.542532",
"0.5417887",
"0.54107744",
"0.5393759",
... | 0.6560093 | 0 |
check sparsemaxloss transfers nan | def _test_sparsemax_loss_of_nan(self, dtype, random, use_gpu):
q = np.asarray([[0, 0, 1], [0, 0, 1], [0, 0, 1]])
z_nan = np.asarray([[0, np.nan, 0], [0, np.nan, np.nan],
[np.nan, np.nan, np.nan]]).astype(dtype)
_, tf_loss_nan = self._tf_sparsemax_loss(z_nan, q, dtype, use_gpu)
self.assertAllCloseAccordingToType([np.nan, np.nan, np.nan], tf_loss_nan) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_of_inf(self, dtype, random, use_gpu):\n q = np.asarray([[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 0, 1]])\n z_neg = np.asarray([\n [0, -np.inf, 0],\n [0, -np.inf, -np.inf],\n [-np.inf, -np.inf, 0],\n [-np.inf, -np.inf, -np.inf],\n ]).astype(dtype)\n z_pos... | [
"0.6993612",
"0.68045354",
"0.6742524",
"0.64270777",
"0.6119363",
"0.59418494",
"0.5930874",
"0.5891737",
"0.583687",
"0.58328086",
"0.57153714",
"0.567385",
"0.56433874",
"0.5623153",
"0.5609487",
"0.5586741",
"0.5584325",
"0.5562963",
"0.5493455",
"0.5464474",
"0.54510564"... | 0.7484194 | 0 |
check sparsemaxloss is infinity safe | def _test_sparsemax_loss_of_inf(self, dtype, random, use_gpu):
q = np.asarray([[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 0, 1]])
z_neg = np.asarray([
[0, -np.inf, 0],
[0, -np.inf, -np.inf],
[-np.inf, -np.inf, 0],
[-np.inf, -np.inf, -np.inf],
]).astype(dtype)
z_pos = np.asarray([[0, np.inf, 0], [0, np.inf,
np.inf], [np.inf, np.inf, 0],
[np.inf, np.inf, np.inf]]).astype(dtype)
z_mix = np.asarray([[0, np.inf, 0], [0, np.inf, -np.inf],
[-np.inf, np.inf, 0], [-np.inf, np.inf,
-np.inf]]).astype(dtype)
_, tf_loss_neg = self._tf_sparsemax_loss(z_neg, q, dtype, use_gpu)
self.assertAllCloseAccordingToType([0.25, np.inf, 0, np.nan], tf_loss_neg)
_, tf_loss_pos = self._tf_sparsemax_loss(z_pos, q, dtype, use_gpu)
self.assertAllCloseAccordingToType([np.nan, np.nan, np.nan, np.nan],
tf_loss_pos)
_, tf_loss_mix = self._tf_sparsemax_loss(z_mix, q, dtype, use_gpu)
self.assertAllCloseAccordingToType([np.nan, np.nan, np.nan, np.nan],
tf_loss_mix) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_of_nan(self, dtype, random, use_gpu):\n q = np.asarray([[0, 0, 1], [0, 0, 1], [0, 0, 1]])\n z_nan = np.asarray([[0, np.nan, 0], [0, np.nan, np.nan],\n [np.nan, np.nan, np.nan]]).astype(dtype)\n\n _, tf_loss_nan = self._tf_sparsemax_loss(z_nan, q, dtype, use_... | [
"0.72919095",
"0.7114687",
"0.6878583",
"0.6437763",
"0.6230124",
"0.6111207",
"0.60838383",
"0.60647756",
"0.6005",
"0.58566064",
"0.5836664",
"0.5805594",
"0.57603514",
"0.5743544",
"0.5705851",
"0.56542385",
"0.5634526",
"0.5634205",
"0.56317574",
"0.5618935",
"0.55948126"... | 0.7511145 | 0 |
check sparsemaxloss proposition 3 | def _test_constant_add(self, dtype, random, use_gpu):
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
c = random.uniform(low=-3, high=3, size=(test_obs, 1))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), np.random.randint(0, 10, size=test_obs)] = 1
_, tf_loss_zpc = self._tf_sparsemax_loss(z + c, q, dtype, use_gpu)
_, tf_loss_z = self._tf_sparsemax_loss(z, q, dtype, use_gpu)
self.assertAllCloseAccordingToType(
tf_loss_zpc,
tf_loss_z,
float_atol=5e-6,
float_rtol=5e-6,
half_atol=1e-2,
half_rtol=1e-2) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_positive(self, dtype, random, use_gpu):\n z = random.uniform(low=-3, high=3, size=(test_obs, 10))\n q = np.zeros((test_obs, 10))\n q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1\n\n tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)\n\n... | [
"0.66934943",
"0.6259219",
"0.60644525",
"0.5932874",
"0.5896964",
"0.57575476",
"0.5734909",
"0.57317626",
"0.5721183",
"0.5685912",
"0.5658947",
"0.56559056",
"0.56359863",
"0.5633538",
"0.55814755",
"0.5575781",
"0.5545625",
"0.55320644",
"0.55299217",
"0.552717",
"0.55233... | 0.0 | -1 |
check sparsemaxloss proposition 4 | def _test_sparsemax_loss_positive(self, dtype, random, use_gpu):
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1
tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)
self.assertAllCloseAccordingToType(np.abs(tf_loss_out), tf_loss_out)
self.assertShapeEqual(np.zeros(test_obs), tf_loss_op) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_zero(self, dtype, random, use_gpu):\n # construct z and q, such that z_k >= 1 + max_{j!=k} z_k holds for\n # delta_0 = 1.\n z = random.uniform(low=-3, high=3, size=(test_obs, 10))\n z[:, 0] = np.max(z, axis=1) + 1.05\n\n q = np.zeros((test_obs, 10))\n q[:, 0] = 1\n\n t... | [
"0.6196355",
"0.6067124",
"0.6020071",
"0.5861591",
"0.58333623",
"0.5814174",
"0.5738434",
"0.56803995",
"0.5659591",
"0.5651032",
"0.56506085",
"0.5645035",
"0.5634631",
"0.5630038",
"0.56013834",
"0.55691886",
"0.5534191",
"0.5532042",
"0.5531974",
"0.5514072",
"0.5472693"... | 0.660775 | 0 |
check sparsemaxloss proposition 5 | def _test_sparsemax_loss_zero(self, dtype, random, use_gpu):
# construct z and q, such that z_k >= 1 + max_{j!=k} z_k holds for
# delta_0 = 1.
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
z[:, 0] = np.max(z, axis=1) + 1.05
q = np.zeros((test_obs, 10))
q[:, 0] = 1
tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)
tf_sparsemax_op, tf_sparsemax_out = self._tf_sparsemax(z, dtype, use_gpu)
self.assertAllCloseAccordingToType(np.zeros(test_obs), tf_loss_out)
self.assertShapeEqual(np.zeros(test_obs), tf_loss_op)
self.assertAllCloseAccordingToType(q, tf_sparsemax_out)
self.assertShapeEqual(q, tf_sparsemax_op) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_positive(self, dtype, random, use_gpu):\n z = random.uniform(low=-3, high=3, size=(test_obs, 10))\n q = np.zeros((test_obs, 10))\n q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1\n\n tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu)\n\n... | [
"0.6566375",
"0.6140244",
"0.6020924",
"0.583102",
"0.5816435",
"0.5766244",
"0.57547736",
"0.5742387",
"0.5733611",
"0.5728958",
"0.569015",
"0.56716436",
"0.5660839",
"0.56137866",
"0.5600897",
"0.55933416",
"0.55928576",
"0.5521913",
"0.54795593",
"0.5471057",
"0.54647976"... | 0.61877185 | 1 |
check sparsemaxloss Rop, against estimatedloss Rop | def _test_gradient_against_estimate(self, dtype, random, use_gpu):
z = random.uniform(low=-3, high=3, size=(test_obs, 10)).astype(dtype)
q = np.zeros((test_obs, 10)).astype(dtype)
q[np.arange(0, test_obs), np.random.randint(0, 10, size=test_obs)] = 1
logits = array_ops.placeholder(dtype, name='z')
sparsemax_op = sparsemax(logits)
loss_op = sparsemax_loss(logits, sparsemax_op, q)
with self.test_session(use_gpu=use_gpu):
err = gradient_checker.compute_gradient_error(
logits, z.shape, loss_op, (test_obs,), x_init_value=z, delta=1e-9)
self.assertLess(err, 1e-4) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test(args, model, device, data, target):\n model.eval()\n test_loss = 0\n correct = 0\n data, target = data.to(device), target.to(device)\n output = model(data)\n # Final result will be average of averages of the same size\n test_loss += F.nll_loss(output, target, reduction='mean').item()\... | [
"0.59559137",
"0.5920649",
"0.5891724",
"0.58784205",
"0.5843466",
"0.5749206",
"0.5714167",
"0.5698575",
"0.5662596",
"0.56607074",
"0.56145835",
"0.55982244",
"0.55072397",
"0.54940027",
"0.54862463",
"0.5481414",
"0.547548",
"0.54676175",
"0.5464912",
"0.5449157",
"0.54412... | 0.0 | -1 |
check sparsemaxloss Rop, against numpy Rop | def _test_gradient_against_numpy(self, dtype, random, use_gpu):
z = random.uniform(low=-3, high=3, size=(test_obs, 10))
q = np.zeros((test_obs, 10))
q[np.arange(0, test_obs), np.random.randint(0, 10, size=test_obs)] = 1
logits = constant_op.constant(z.astype(dtype), name='z')
sparsemax_op = sparsemax(logits)
loss_op = sparsemax_loss(logits, sparsemax_op, q.astype(dtype))
loss_grad_op = gradients_impl.gradients(loss_op, [logits])[0]
with self.test_session(use_gpu=use_gpu):
tf_grad = loss_grad_op.eval()
np_grad = self._np_sparsemax_loss_grad(z, q).astype(dtype)
self.assertAllCloseAccordingToType(
np_grad, tf_grad, half_atol=1e-2, half_rtol=5e-3)
self.assertShapeEqual(np_grad, loss_grad_op) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _test_sparsemax_loss_against_numpy(self, dtype, random, use_gpu):\n z = random.uniform(low=-3, high=3, size=(test_obs, 10))\n q = np.zeros((test_obs, 10))\n q[np.arange(0, test_obs), random.randint(0, 10, size=test_obs)] = 1\n\n tf_loss_op, tf_loss_out = self._tf_sparsemax_loss(z, q, dtype, use_gpu... | [
"0.608403",
"0.5973735",
"0.571578",
"0.5632115",
"0.54965043",
"0.5486409",
"0.5408095",
"0.5354363",
"0.5288926",
"0.5264263",
"0.5211011",
"0.5193525",
"0.5165354",
"0.51506674",
"0.50947654",
"0.50944364",
"0.50929224",
"0.508245",
"0.5064704",
"0.50560075",
"0.5050354",
... | 0.54233766 | 6 |
Accepts rows of timesortable data | def put(self, data):
if len(data) == 0:
return []
new_data = []
sorted_data = self._sort(data)
sorted_data_iterator = iter(sorted_data)
earliest_data = next(sorted_data_iterator)
earliest_timestamp = self.get_hash(earliest_data)
new_buffer = OrderedDict()
try:
for timestamp in self.buffer:
if timestamp < earliest_timestamp:
pass
else:
while True:
if earliest_timestamp in self.buffer:
pass
else:
new_buffer[earliest_timestamp] = True
new_data.append(earliest_data)
earliest_data = next(sorted_data_iterator)
earliest_timestamp = self.get_hash(earliest_data)
if timestamp < earliest_timestamp:
break
while True:
new_buffer[earliest_timestamp] = True
new_data.append(earliest_data)
earliest_data = next(sorted_data_iterator)
earliest_timestamp = self.get_hash(earliest_data)
except StopIteration:
pass
self.buffer = new_buffer
return new_data | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _sort_time(self):\n time = np.copy(self.data[\"time\"][:])\n ind_sorted = np.argsort(time)\n ind_valid: list[int] = []\n for ind in ind_sorted:\n if time[ind] not in time[ind_valid]:\n ind_valid.append(ind)\n n_time = len(time)\n for key, arra... | [
"0.62110686",
"0.5617712",
"0.5604052",
"0.55013937",
"0.5485576",
"0.54825485",
"0.5480284",
"0.53317887",
"0.5248092",
"0.5174748",
"0.5161101",
"0.51461595",
"0.51112086",
"0.51031595",
"0.50956035",
"0.50943315",
"0.5072948",
"0.5051467",
"0.49987826",
"0.4959382",
"0.495... | 0.0 | -1 |
ExportResponseMetadata a model defined in Swagger | def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501
self._export_host = None
self._export_date = None
self._requested_object_list = None
self._exported_object_list = None
self.discriminator = None
if export_host is not None:
self.export_host = export_host
if export_date is not None:
self.export_date = export_date
if requested_object_list is not None:
self.requested_object_list = requested_object_list
if exported_object_list is not None:
self.exported_object_list = exported_object_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def get_model_metadata(\n self,\n model_name: str,\n model_version: str = ...,\n headers: dict[str, t.Any] = ...,\n as_json: t.Literal[False] = ...,\n ) -> service_pb2.ModelMetadataResponse:",
"def api_documentation(api: str, summary: str, in_model: BaseModel,\n ... | [
"0.6050486",
"0.5972756",
"0.5801244",
"0.56295675",
"0.5604811",
"0.55415565",
"0.5516606",
"0.5497246",
"0.54778665",
"0.54568404",
"0.5436918",
"0.54210794",
"0.5404738",
"0.53839225",
"0.5312669",
"0.5309557",
"0.53045684",
"0.52979773",
"0.5291329",
"0.52629024",
"0.5245... | 0.0 | -1 |
Sets the export_host of this ExportResponseMetadata. | def export_host(self, export_host):
self._export_host = export_host | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def response_host(self, response_host):\n\n self._response_host = response_host",
"def response_host(self, response_host):\n\n self._response_host = response_host",
"def host(self, host):\n\n self._host = host",
"def host(self, host):\n\n self._host = host",
"def host(self, host... | [
"0.7138213",
"0.7138213",
"0.644298",
"0.644298",
"0.644298",
"0.644298",
"0.6365714",
"0.6363546",
"0.6119689",
"0.5977553",
"0.5908788",
"0.58681583",
"0.5725987",
"0.5704862",
"0.5632454",
"0.5604846",
"0.5604846",
"0.5506752",
"0.5506752",
"0.5476766",
"0.54253507",
"0.... | 0.8150576 | 0 |
Sets the export_date of this ExportResponseMetadata. | def export_date(self, export_date):
self._export_date = export_date | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_date(self, date):\n self.data['date'] = date",
"def set_date(self, date):\n self.date = date\n return",
"def set_date(self, date):\n self.date = date",
"def date(self, date):\n\n self._date = date",
"def date(self, date):\n\n self._date = date",
"def date... | [
"0.64057446",
"0.63387674",
"0.63318104",
"0.62219906",
"0.62219906",
"0.62219906",
"0.62219906",
"0.62219906",
"0.6208642",
"0.6150361",
"0.6148115",
"0.597754",
"0.59448314",
"0.59330714",
"0.5932477",
"0.5932477",
"0.59302837",
"0.59251916",
"0.5893984",
"0.5889508",
"0.58... | 0.8478781 | 0 |
Sets the requested_object_list of this ExportResponseMetadata. | def requested_object_list(self, requested_object_list):
self._requested_object_list = requested_object_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exported_object_list(self, exported_object_list):\n\n self._exported_object_list = exported_object_list",
"def set_response_list(self, r_list):\n self.response_list = r_list",
"def set_objects(self, objects: list):\n self._objects = objects",
"def set_object_list(self, query, fields,... | [
"0.65758",
"0.58558273",
"0.5800644",
"0.5349972",
"0.51523393",
"0.5088856",
"0.5084719",
"0.5048292",
"0.50420725",
"0.5036184",
"0.50234246",
"0.50130266",
"0.4954567",
"0.4948551",
"0.49092585",
"0.49018076",
"0.49018076",
"0.48524174",
"0.48476678",
"0.47991368",
"0.4791... | 0.843938 | 0 |
Sets the exported_object_list of this ExportResponseMetadata. | def exported_object_list(self, exported_object_list):
self._exported_object_list = exported_object_list | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, export_host=None, export_date=None, requested_object_list=None, exported_object_list=None): # noqa: E501 # noqa: E501\n\n self._export_host = None\n self._export_date = None\n self._requested_object_list = None\n self._exported_object_list = None\n self.discr... | [
"0.57387066",
"0.572405",
"0.5720836",
"0.50837755",
"0.5052673",
"0.4954005",
"0.49233595",
"0.48638776",
"0.48131937",
"0.47819278",
"0.47225076",
"0.47225076",
"0.47171348",
"0.46870238",
"0.46680313",
"0.46198332",
"0.46057516",
"0.45436734",
"0.45278898",
"0.45272794",
"... | 0.8515711 | 0 |
Returns the model properties as a dict | def to_dict(self):
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
if issubclass(ExportResponseMetadata, dict):
for key, value in self.items():
result[key] = value
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_dict(self):\n return self.properties",
"def to_dict(self):\n return self.properties",
"def get_properties(self):\n return self.properties",
"def asdict(self):\n return self._prop_dict",
"def json(self):\n rv = {\n prop: getattr(self, prop)\n f... | [
"0.7751993",
"0.7751993",
"0.73391134",
"0.7334895",
"0.7297356",
"0.727818",
"0.7159078",
"0.71578115",
"0.71494967",
"0.71494967",
"0.71283495",
"0.71275014",
"0.7122587",
"0.71079814",
"0.7060394",
"0.7043251",
"0.7034103",
"0.70233124",
"0.69635814",
"0.69586295",
"0.6900... | 0.0 | -1 |
Returns the string representation of the model | def to_str(self):
return pprint.pformat(self.to_dict()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __str__(self):\n return super().__str__() + self.model.__str__()",
"def __str__(self) -> str:\n # noinspection PyUnresolvedReferences\n opts = self._meta\n if self.name_field:\n result = str(opts.get_field(self.name_field).value_from_object(self))\n else:\n ... | [
"0.85856134",
"0.7814518",
"0.77898884",
"0.7751367",
"0.7751367",
"0.7712228",
"0.76981676",
"0.76700574",
"0.7651133",
"0.7597206",
"0.75800353",
"0.7568254",
"0.7538184",
"0.75228703",
"0.7515832",
"0.7498764",
"0.74850684",
"0.74850684",
"0.7467648",
"0.74488163",
"0.7442... | 0.0 | -1 |
For `print` and `pprint` | def __repr__(self):
return self.to_str() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pprint(*args, **kwargs):\n if PRINTING:\n print(*args, **kwargs)",
"def print_out():\n pass",
"def custom_print(*objects):\n print(*objects, sep=OFS, end=ORS)",
"def _print(self, *args):\n return _ida_hexrays.vd_printer_t__print(self, *args)",
"def _printable(self):\n ... | [
"0.75577617",
"0.73375154",
"0.6986672",
"0.698475",
"0.6944995",
"0.692333",
"0.6899106",
"0.6898902",
"0.68146646",
"0.6806209",
"0.6753795",
"0.67497987",
"0.6744008",
"0.6700308",
"0.6691256",
"0.6674591",
"0.6658083",
"0.66091245",
"0.6606931",
"0.6601862",
"0.6563738",
... | 0.0 | -1 |
Returns true if both objects are equal | def __eq__(self, other):
if not isinstance(other, ExportResponseMetadata):
return False
return self.__dict__ == other.__dict__ | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self,other):\n try: return self.object==other.object and isinstance(self,type(other))\n except: return False",
"def __eq__(self, other):\n if i... | [
"0.8088132",
"0.8088132",
"0.8054589",
"0.7982687",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
"0.79670393",
... | 0.0 | -1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.