Update helper.py

helper.py

@@ -13,23 +13,23 @@ from sklearn.preprocessing import MinMaxScaler
 def assign_main_accounts(creators_file, chatter_files):
     """
     Process creators and chatter files to assign main accounts to chatters and prepare data for scheduling.
+    Returns the combined assignments for preview and the processed creator file.
     """
     # Load and process creators data
     creators = pd.read_excel(creators_file)
-    creators.columns = creators.columns.str.strip()  # Clean up column names
+    creators.columns = creators.columns.str.strip()
 
-    # Ensure required columns are present
+    # Ensure required columns
     required_columns = ["Creator", "Total earnings", "Subscription", "Total active fans"]
     missing_columns = [col for col in required_columns if col not in creators.columns]
     if missing_columns:
         raise KeyError(f"Missing required columns in creators file: {missing_columns}")
 
-    # Normalize and calculate scores for creators
+    # Normalize and rank creators
     creators["Total earnings"] = creators["Total earnings"].replace("[\$,]", "", regex=True).astype(float)
     creators["Subscription"] = creators["Subscription"].replace("[\$,]", "", regex=True).astype(float)
     creators["Total active fans"] = creators["Total active fans"].fillna(0).astype(int)
 
-    # Scale data for ranking
     scaler = MinMaxScaler()
     creators[["Earnings_Normalized", "Subscriptions_Normalized"]] = scaler.fit_transform(
         creators[["Total earnings", "Subscription"]]
@@ -40,38 +40,38 @@ def assign_main_accounts(creators_file, chatter_files):
     ) * creators["Penalty Factor"]
     creators["Rank"] = creators["Score"].rank(ascending=False)
 
-    # Sort creators by rank
     creators = creators.sort_values(by="Rank").reset_index(drop=True)
 
-    # Save processed creator file with Creator and ActiveFans only
-    processed_creator_file = os.path.join(PROCESSED_FOLDER, "creators_file.xlsx")
-    creators[["Creator", "Total active fans"]].rename(
+    # Save processed creator file
+    processed_creator_file = creators[["Creator", "Total active fans"]].rename(
         columns={"Total active fans": "ActiveFans"}
-    ).to_excel(processed_creator_file, index=False)
-    print(f"DEBUG: Processed creators file saved to {processed_creator_file}")
+    )
 
     # Assign main accounts to chatters
+    combined_assignments = []
     updated_chatter_files = []
     for idx, chatter_file in enumerate(chatter_files):
-        shift_name = ["overnight", "day", "prime"][idx]
+        shift_name = ["Overnight", "Day", "Prime"][idx]
         chatters = pd.read_excel(chatter_file)
         chatters.columns = chatters.columns.str.strip()
 
         if "Final Rating" not in chatters.columns:
             raise KeyError(f"'Final Rating' column is missing in {chatter_file}")
 
-        # Sort chatters by performance
         chatters = chatters.sort_values(by="Final Rating", ascending=False).reset_index(drop=True)
-
-        # Match top creators with top chatters
         num_chatters = len(chatters)
         top_creators = creators.iloc[:num_chatters]
         chatters["Main Account"] = top_creators["Creator"].values
+        chatters["Shift"] = shift_name
 
-        # Append updated chatter data
         updated_chatter_files.append(chatters)
+        combined_assignments.append(chatters)
+
+    # Combine all assignments for display
+    combined_assignments_df = pd.concat(combined_assignments, ignore_index=True)
+
+    return updated_chatter_files, processed_creator_file, combined_assignments_df
 
-    return updated_chatter_files, processed_creator_file