@@ -68,7 +68,7 @@ def caching_exists_in_file(self, sql_query, graph_type):
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if not random_id .empty :
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result = random_id ['random_id' ].iloc [0 ]
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dff = pd .read_csv ("./data_storage/{}/{}.csv" .format (graph_type , result ))
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- print ("{} {} {}" .format (graph_type , "file exists" , result ))
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+ # print("{} {} {}".format(graph_type, "file exists", result))
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return True , True , dff
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return False , True , None
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@@ -100,11 +100,11 @@ def store_data_in_dict(self, df, sql_query, graph_type):
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def caching_data_manager (self , df , sql_query , graph_type , calculated_funct = None , details_dict = None ):
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status_file , file_exist , dff = self .caching_exists_in_file (sql_query , graph_type )
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if status_file :
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- print ("{}/{}" .format (graph_type , "exist in file" ))
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+ # print("{}/{}".format(graph_type, "exist in file"))
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return dff
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else :
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- print ("{}/{}" .format (graph_type , "don't exists" ))
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+ # print("{}/{}".format(graph_type, "don't exists"))
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random_str = self .random_string_generator ()
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dict_bkp = self .creating_filtered_backup_file (sql_query , random_str , graph_type )
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dff = psql .sqldf (sql_query , locals ())
@@ -139,7 +139,7 @@ def find(self, df, y_variable, y_variable_predict, mode, param):
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user_id = user_id ['id' ].iloc [0 ]
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self .user_id = user_id
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except Exception as e :
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- print ("inside user track" )
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+ # print("inside user track" )
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user_id_val = self .random_string_generator ()
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user_id_csv = pd .DataFrame (data = {"id" : [user_id_val ]})
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user_id_csv .to_csv ("data_storage/user/user_id.csv" , index = False )
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