Made flatten data more flexible by creating a method for labeling list indexes which can be overwritten by other users

cdplib/FlattenData.py

@@ -62,15 +62,17 @@ class FlattenData():
         '''
         assert(isinstance(dataframe, pd.DataFrame)),\
             "Parameter 'dataframe' be of DataFrame type"
-        if incoming_key is not None:
-            assert(isinstance(incoming_key, str)),\
-                "Parameter 'incoming_key' be of String type"
+        if incoming_key is not None and not isinstance(incoming_key, str):
+            incoming_key = str(incoming_key)
+
 
         result_dict = {}
         
         for index, row in dataframe.iterrows():
             temp_result_dict = {}
             for key, value in row.iteritems():
+                if not isinstance(key, str):
+                    key = str(key)
                 small_key = key
                 if incoming_key is not None:
                     key = incoming_key + '_' + key
@@ -101,16 +103,17 @@ class FlattenData():
         '''
         assert(isinstance(dictionary, dict)),\
             "Parameter 'dictionary' be of Dictionary type"
-        if incoming_key is not None:
-            assert(isinstance(incoming_key, str)),\
-                "Parameter 'incoming_key' be of String type"
+        if incoming_key is not None and not isinstance(incoming_key, str):
+            incoming_key = str(incoming_key)
 
 
         result_dict = {}
         for key in dictionary:
-            small_key = key
-
             temp_data = dictionary[key]
+            if not isinstance(key, str):
+                key = str(key)
+
+            small_key = key
             if incoming_key is not None:
                 key = incoming_key + '_' + key
             temp_result = {}
@@ -137,9 +140,9 @@ class FlattenData():
 
         assert(isinstance(data_list, list)),\
             "Parameter 'data_list' be of List type"
-        if incoming_key is not None:
-            assert(isinstance(incoming_key, str)),\
-                "Parameter 'incoming_key' be of String type"
+        if incoming_key is not None and not isinstance(incoming_key, str):
+            incoming_key = str(incoming_key)
+
 
         result_dict = {}
         for iteration, item in enumerate(data_list):
@@ -147,17 +150,13 @@ class FlattenData():
             temp_dataframe = item
             temp_result = {}
             key = incoming_key
-            
+            if not isinstance(key, str):
+                key = str(key)
+
             if incoming_key is not None:
-                # OEBB SPECIFIC IF STATEMENT
-                if type(data_list[iteration]) is dict and 'stationsnummer' in data_list[iteration].keys():
-                        key = incoming_key + '_' + str(data_list[iteration]['stationsnummer'])
-                
-                elif type(data_list[iteration]) is dict and 'stationsnummer' in data_list[iteration].keys() and 'stage' in data_list[iteration].keys() :
-                        key = incoming_key + '_' + str(data_list[iteration]['stationsnummer']) + '_' + str(data_list[iteration]['stage'])
                 
-                else:
-                    key = incoming_key + '_' + str(iteration)
+                list_iterator = add_list_iterator(data_list, iteration)
+                key = incoming_key + '_' + list_iterator
             else:
                 key = str(iteration)
             if type(temp_dataframe) == list:
@@ -196,4 +195,9 @@ class FlattenData():
                     return self.flatten(data, labels_to_ignore=labels_to_ignore) 
 
         return data   
+
+
+    # Create class that inherits FlattenData and overwrite this function for specific implementations.
+    def add_list_iterator(self, data_list: list, iteration: int):
+        return str(iteration)