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from models.cache_store import cache_store from models.cache_store_by_username import cache_store_by_username from models.cache_store_by_date import cache_store_by_date from models.indexes import indexes from models.columns import columns as tablecolumns from datetime import datetime, timedelta, timezone from dateutil.relativedelta import relativedelta from pandas.io.json import json_normalize import json from config.logger import configlogfile from flask import jsonify, make_response import pandas as pd import sys import gc import uuid import pytz """ This function is used to fetch cache details based on valueType and key """ def getData(payLoad, configvalues): from config.logger import configlogfile logging = configlogfile() logging.info("Started to fetch the records for " + str(payLoad) ) cacheStore = [] try: payLoad = payLoad.to_dict() columnMapping = json.loads(configvalues.get('apiconfiguration', 'columnMapping', raw=True)) reversecolumnMapping = {y: x for x, y in columnMapping.items()} validColumns = json.loads(configvalues.get('apiconfiguration', 'validColumns', raw=True)) datecolumns = json.loads(configvalues.get('apiconfiguration', 'dateColumns', raw=True)) logging.debug('Arguments -' + str(payLoad)) # return ((["0000"],str(payLoad['valueType']))) for k, v in reversecolumnMapping.items(): if k in list(payLoad.keys()): payLoad[v] = payLoad.pop(k) # modified the code on 18-Feb to fetch data based on keyspace and then table name recs = indexes.objects().filter(keyspace_name =cache_store.__keyspace__) recs = recs.filter(table_name='cache_store') indexedcolumns = [row.options['target'] for row in recs] recs = tablecolumns.objects().filter(keyspace_name = cache_store.__keyspace__) recs = recs.filter(table_name='cache_store') partitioncolumns = [row.column_name for row in recs if row.kind in ["partition_key"]] partitioncolumns = partitioncolumns + [row.column_name for row in recs if row.kind in ["primary_key", "clustering"]] parametercolumns = partitioncolumns + indexedcolumns partitioncolstofilter = [parametercolumn for parametercolumn in parametercolumns if parametercolumn in list(payLoad.keys())] if (bool(payLoad) == False): return (("200","parameters needs to be passed to fetch values from the cache store")) #query = 'global cacheStoreRecords;cacheStoreRecords=cache_store.objects().all();' else: #return ((["0000"], str(range(len(partitioncolstofilter))))) if set(list(payLoad.keys())).issubset(parametercolumns): for i in range(len(partitioncolstofilter)): if i == 0: if partitioncolstofilter[i] in datecolumns: query = 'global cacheStoreRecords;cacheStoreRecords=cache_store.objects().filter(' + \ partitioncolstofilter[i] + '=datetime.strptime(\'' + \ str((payLoad[partitioncolstofilter[i]])) + '\',\'%Y-%m-%dT%H:%M:%S%z\'));' # return ((["0000"],query)) else: query = 'global cacheStoreRecords;cacheStoreRecords=cache_store.objects().filter(' + \ partitioncolstofilter[i] + '=\'' + str(payLoad[partitioncolstofilter[i]]) + '\');' else: if partitioncolstofilter[i] in datecolumns: query = 'global cacheStoreRecords;cacheStoreRecords=cacheStoreRecords.filter(' + \ partitioncolstofilter[i] + \ '=datetime.strptime(\'' + str( (payLoad[partitioncolstofilter[i]])) + '\',\'%Y-%m-%dT%H:%M:%S%z\'));' # return ((["0000"],query)) else: query = 'global cacheStoreRecords;cacheStoreRecords=cacheStoreRecords.filter(' + \ partitioncolstofilter[i] + \ '=\'' + str(payLoad[partitioncolstofilter[i]]) + '\');' #return ((["0000"],query)) exec(query) else: for i in range(len(parametercolumns)): for k, v in reversecolumnMapping.items(): if v == parametercolumns[i]: parametercolumns[i] = k return (("200",("9003", "Invalid Arguments passed to the API. Valid Arguments are " + ','.join(parametercolumns)))) if len(cacheStoreRecords) == 0: return (("200",{})) #return (("404", ("9007", "cache details could not be found."))) #return ((["9007"], "Details could not be found")) cacheStore = [row.__json__() for row in cacheStoreRecords] #return ((200,cacheStore)) cacheStore = pd.DataFrame.from_dict((cacheStore), orient='columns') cacheStore.fillna('',inplace = True) if len(cacheStore)>0: for column in datecolumns: if column in cacheStore.columns.tolist(): cacheStore[column] = pd.to_datetime(cacheStore[column],unit='ns') cacheStore[column] = cacheStore[column].dt.tz_localize('UTC').dt.tz_convert(configvalues.get('apiconfiguration','timeZone')).dt.strftime('%Y-%m-%dT%H:%M:%S.%f%z') #return (("404",("0000",cacheStore[column].to_list()))) cacheStore[column] = [ "" if columnValue == "NaT" else columnValue for columnValue in cacheStore[column].to_list()] #return (("404",("0000",cacheStore[column].to_list()))) cacheStore = cacheStore[validColumns] validColumns = {k: v for k, v in columnMapping.items() if k in validColumns} cacheStore = cacheStore.rename(columns=(validColumns)) cacheStore = cacheStore.to_dict(orient='records') import unicodedata if len(cacheStore) > 0: #cacheStore = [ {k : ( unicodedata.normalize('NFC',v) if k == 'value' else v ) for k,v in x.items()} for x in cacheStore] cacheStore = [ {k : (v.encode().decode() if k == 'value' else v ) for k,v in x.items()} for x in cacheStore] logging.debug('cacheStore-'+str(cacheStore)) response = {} response = response if len(cacheStore) == 0 else cacheStore[0] if len(cacheStore) == 1 else cacheStore logging.info("Completed fetching the records") gc.collect() return ((200,(response))) except Exception as e: gc.collect() logging.error("Error - {} . Line No - {} ".format(str(e), str(sys.exc_info()[-1].tb_lineno))) return (("500", "Technical exception"))