Merge pull request #5 from Hestia-Homes/feature/make_dashboard_better_for_one

add attempt type so i know what type of work it is

backend/src/dashboard/scripts/quick_one.py

@@ -5,9 +5,6 @@ s3 = FileManager()
 key, path, data = s3.download_and_read_latest()
 hubspot_data = jsonReader(data)
 
-
-counter, deals = hubspot_data.generate_solar_numbers_df()
-
-counter
-deals
+df  = hubspot_data.generate_df_via_product_type("Empty Cavity - ECO4")
+df
 

backend/src/dashboard/services/hubspot_client_async.py

@@ -273,6 +273,7 @@ class HubSpotClientAsync:
                 "outcome_surveyor",
                 "submission_date",
                 "expected_commencement_date",
+                "attempt_type",
             ]
         )
         

backend/src/dashboard/services/json_reader.py

@@ -1,5 +1,7 @@
 from pprint import pprint
 from collections import defaultdict
+import pandas as pd
+
 
 
 
@@ -29,18 +31,32 @@ class jsonReader:
                     self.deals_by_line_item[name].append(deal)
         self.line_item_names = list(self.deals_by_line_item.keys())
 
-    def generate_empty_cavity_numbers_df(self):
-        count=0
-        for deals in self.deals_by_line_item["Empty Cavity - ECO4"]:
-            count +=1 
+    def generate_df_via_product_type(self, product_type):
+        rows = []
+        for deals in self.deals_by_line_item[product_type]:
             if deals['attempts'] != []:
-                return count, deals
-        return count, deals
+                row = self._return_df_from_deal_info(deals, product_type)
+                rows.append(row)
+
+        if rows:
+            return pd.concat(rows, ignore_index=True)
+        else:
+            return
+
+    
+    def _return_df_from_deal_info(self, deal, product_type):
+        print(deal)
+        data = {
+            "submission_date": deal.get("submission_date", None),
+            "expected_commencement_date": deal.get("expected_commencement_date", None),
+            "work_type": product_type,
+            "price": next(
+                    (item["price"] for item in deal["line_items"] if product_type in item["name"]),
+                    None
+                ) 
+        }
+        return pd.DataFrame([data])
     
-    def _return_df_from_deal_info(self, deal):
-
-        pass
-
     def find_all_job_with_line_item(self):
         for i, deal in enumerate(self.raw_data):
             if len(deal["line_items"])>0: