Update helper.py

helper.py

@@ -7,49 +7,65 @@ import re
 import pandas as pd
 from sklearn.preprocessing import MinMaxScaler
 
-def assign_main_accounts(updated_data=None):
-    global UPDATED_ASSIGNMENTS
-
-    creators_file = os.path.join(UPLOAD_FOLDER, "creators_file.xlsx")
-    chatter_files = [
-        os.path.join(UPLOAD_FOLDER, "overnight_file.xlsx"),
-        os.path.join(UPLOAD_FOLDER, "day_file.xlsx"),
-        os.path.join(UPLOAD_FOLDER, "prime_file.xlsx"),
-    ]
-
-    if not all(os.path.exists(path) for path in [creators_file] + chatter_files):
-        return "Missing required files. Please upload all necessary files.", None
-
-    try:
-        # Step 1: Assign main accounts
-        updated_chatter_files, account_data = assign_main_accounts(creators_file, chatter_files)
-        print("DEBUG: Updated Chatter Files and Account Data Successfully Generated")
-
-        # Save processed files
-        UPDATED_ASSIGNMENTS = {
-            "chatter_files": updated_chatter_files,
-            "account_data": account_data
-        }
-        for idx, chatter_df in enumerate(updated_chatter_files):
-            chatter_df.to_excel(
-                os.path.join(PROCESSED_FOLDER, f"Updated_{['overnight', 'day', 'prime'][idx]}_file.xlsx"),
-                index=False
-            )
-        account_data.to_excel(os.path.join(PROCESSED_FOLDER, "creators_file.xlsx"), index=False)
-
-        # Step 2: Combine for preview
-        preview_data = []
-        shift_names = ["Overnight", "Day", "Prime"]
-        for idx, chatter_df in enumerate(updated_chatter_files):
-            chatter_df["Shift"] = shift_names[idx]
-            preview_data.append(chatter_df)
-
-        preview_df = pd.concat(preview_data, ignore_index=True)
-        return "Main accounts generated successfully!", preview_df
-
-    except Exception as e:
-        print(f"Error during main account generation: {e}")
-        return f"Error during main account generation: {e}", None
+def assign_main_accounts(creators_file, chatter_files):
+
+    creators = pd.read_excel(creators_file)
+    creators.columns = creators.columns.str.strip()
+
+    column_mapping = {
+        "Creator": "Creator",
+        "Total earnings": "Total earnings",
+        "Subscription": "Subscription",
+        "Active Fans": "ActiveFans",
+        "Total active fans": "ActiveFans",
+    }
+    creators.rename(columns={k: v for k, v in column_mapping.items() if k in creators.columns}, inplace=True)
+
+    required_columns = ["Creator", "Total earnings", "Subscription", "ActiveFans"]
+    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}")
+
+
+    creators["Total earnings"] = creators["Total earnings"].replace("[\$,]", "", regex=True).astype(float)
+    creators["Subscription"] = creators["Subscription"].replace("[\$,]", "", regex=True).astype(float)
+    creators["ActiveFans"] = pd.to_numeric(creators["ActiveFans"], errors="coerce").fillna(0)
+
+
+    scaler = MinMaxScaler()
+    creators[["Earnings_Normalized", "Subscriptions_Normalized"]] = scaler.fit_transform(
+        creators[["Total earnings", "Subscription"]]
+        0.7 * creators["Earnings_Normalized"] + 0.3 * creators["Subscriptions_Normalized"]
+    ) * creators["Penalty Factor"]
+    creators["Rank"] = creators["Score"].rank(ascending=False)
+
+
+    creators = creators.sort_values(by="Rank").reset_index(drop=True)
+
+
+    assignments = {}
+    for idx, chatter_file in enumerate(chatter_files):
+        shift_name = ["overnight", "day", "prime"][idx]
+        if "Final Rating" not in chatters.columns:
+            raise KeyError(f"'Final Rating' column is missing in {chatter_file}")
+
+
+        chatters = chatters.sort_values(by="Final Rating", ascending=False).reset_index(drop=True)
+
+
+        num_chatters = len(chatters)
+        creators_to_assign = creators.iloc[:num_chatters]
+        chatters["Main Account"] = creators_to_assign["Creator"].values
+
+
+        assignments[shift_name] = chatters.to_dict(orient="records")
+
+    assignments["creator_names"] = creators["Creator"].tolist()
+    print("DEBUG: Chatter Data with Main Account Assignments:")
+    print(chatters.head())
+
+
+    return assignments