working on curate_data to remove formatting issues in csv

ebay_api.py

@@ -106,12 +106,14 @@ class ShoppingApi:
         For some reason item_id_results can only be passed as argument in executor.map
         if the variable is made within function
         '''
-        data = {} # TODO I think you need to append a list of dictionaries rather than update a dictionary of dictionaries. Training var will require an updated dictionary though
+        data = [] # TODO I think you need to append a list of dictionaries rather than update a dictionary of dictionaries. Training var will require an updated dictionary though
         finding = FindingApi(4, 2)
         item_id_results = finding.get_ids_from_cats()
         with concurrent.futures.ThreadPoolExecutor() as executor:
             for future in executor.map(self.get_item_from_findItemsByCategory, item_id_results):
-                print(future)
+                #  print(future)
+                for item in future:
+                        data.append(item) # The end result should be a list of dicts where each dict in the list is a listing
                 # data.update(future)
         return data # TODO each future is a list of dictionaries because the output of any multithreader in this method is a list. 
     # data dictionary can't update from list of dicts unless iterated over. Might need a different way to update. 
@@ -145,10 +147,10 @@ class CurateData:
     def extract_nvl(self, item):
         names = []
         values = []
-        nvl = item['itemspecifics']['namevaluelist']
+        nvl = item['ItemSpecifics']['NameValueList']
         for nvl_dict in nvl:
-            names.append(nvl_dict['name'])
-            values.append(nvl_dict['value'])
+            names.append(nvl_dict['Name'])
+            values.append(nvl_dict['Value'])
         nvl_dict = dict(zip(names, values))
         return nvl_dict
 
@@ -179,8 +181,9 @@ class CurateData:
                 nvl_dict = self.extract_nvl(item)
                 training.update(nvl_dict)
 
-        df = pd.json_normalize(training) # TODO FIX INDENT HERE?
-        df.to_csv('training.csv', mode='a')
+                df = pd.json_normalize(training) # TODO FIX INDENT HERE?
+                df.to_csv('training.csv', mode='a')
+        return training
 
 def main():
     '''
@@ -197,6 +200,7 @@ def main():
     data = shopping.conky()
     curate = CurateData()
     curate.update_df(data)
+    return data
 
 if __name__ == "__main__":
     main()