Admin panel enhancements

app.py

@@ -421,18 +421,12 @@ def fetch_latest_predictions(match_id):
         return pd.DataFrame()
 
 
-def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
-    # Fetch latest predictions from the dataset repo
-    predictions = fetch_latest_predictions(match_id)
+def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match, outcome_only=False):
 
-    outcomes = load_dataset("Jay-Rajput/DIS_IPL_Outcomes", split="train")  # Load existing match outcomes
+    # Load existing match outcomes
+    outcomes = load_dataset("Jay-Rajput/DIS_IPL_Outcomes", split="train")  
     outcomes_df = pd.DataFrame(outcomes)
 
-    # Load existing match outcomes and user data from the test split
-    users = load_dataset("Jay-Rajput/DIS_IPL_Leads", split="train")
-    # Convert users dataset to pandas DataFrame
-    users_df = pd.DataFrame(users)
-
     # Directly update or add the match outcome
     outcome_exists = False
     for idx, outcome in outcomes_df.iterrows():
@@ -442,36 +436,42 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
             outcome_exists = True
             break
     if not outcome_exists:
-        # outcomes.add_item({"match_id": match_id, "winning_team": winning_team, "man_of_the_match": man_of_the_match})
         new_outcome = {"match_id": match_id, "winning_team": winning_team, "man_of_the_match": man_of_the_match}
-        # Append the new outcome to the DataFrame
         outcomes_df = pd.concat([outcomes_df, pd.DataFrame([new_outcome])], ignore_index=True)
         outcomes = Dataset.from_pandas(outcomes_df)
 
-    # Update user points based on prediction accuracy
-    for idx, prediction in predictions.iterrows():
-        user_name = prediction['user_name']
-        predicted_winner = prediction['predicted_winner']
-        predicted_motm = prediction['predicted_motm']
-        bid_points = prediction['bid_points']
-
-        # Update points based on prediction accuracy
-        points = users_df[user_name][0]['0']
-        if predicted_winner == winning_team:
-            points += 2000 + bid_points
-            if predicted_motm == man_of_the_match:
-                points += 500
-        else:
-            points -= 200 + bid_points
+    if not outcome_only:  # Update user scores only if outcome_only is False
+        # Load predictions only if necessary
+        predictions = fetch_latest_predictions(match_id)
+
+        # Load users' data only if necessary
+        users = load_dataset("Jay-Rajput/DIS_IPL_Leads", split="train")
+        users_df = pd.DataFrame(users)
+
+        # Update user points based on prediction accuracy
+        for idx, prediction in predictions.iterrows():
+            user_name = prediction['user_name']
+            predicted_winner = prediction['predicted_winner']
+            predicted_motm = prediction['predicted_motm']
+            bid_points = prediction['bid_points']
+
+            # Update points based on prediction accuracy
+            points = users_df[user_name][0]['0']
+            if predicted_winner == winning_team:
+                points += 2000 + bid_points
+                if predicted_motm == man_of_the_match:
+                    points += 500
+            else:
+                points -= 200 + bid_points
 
-        # Update user's points in the DataFrame
-        users_df[user_name][0]['0'] = points
+            # Update user's points in the DataFrame
+            users_df[user_name][0]['0'] = points
+
+        users.to_json(USERS_JSON)
+        updated_dataset = Dataset.from_pandas(users_df)
+        updated_dataset.push_to_hub("Jay-Rajput/DIS_IPL_Leads", split="train")
 
-    users.to_json(USERS_JSON)
     outcomes.to_json(OUTCOMES)
-    # Convert the updated DataFrame back to a Hugging Face Dataset and push updates
-    updated_dataset = Dataset.from_pandas(users_df)
-    updated_dataset.push_to_hub("Jay-Rajput/DIS_IPL_Leads", split="train")
     outcomes.push_to_hub("Jay-Rajput/DIS_IPL_Outcomes", split="train")
 
 
@@ -520,9 +520,18 @@ with st.sidebar:
                     players = []
                     man_of_the_match = expander.text_input("Man of the Match (Type if not listed)", key="man_of_the_match_fallback")
 
+                # Add checkbox for outcome only submission
+                outcome_only = expander.checkbox("Submit Outcome Only", key="outcome_only_checkbox")
+
                 if expander.button("Submit Match Outcome", key="submit_outcome"):
-                    update_leaderboard_and_outcomes(selected_match_id, winning_team, man_of_the_match)
-                    expander.success("Match outcome submitted and leaderboard updated!")
+                    if outcome_only:
+                        # Submit match outcome without updating user scores
+                        update_leaderboard_and_outcomes(selected_match_id, winning_team, man_of_the_match, outcome_only=True)
+                        expander.success("Match outcome submitted!")
+                    else:
+                        # Submit match outcome and update user scores
+                        update_leaderboard_and_outcomes(selected_match_id, winning_team, man_of_the_match)
+                        expander.success("Match outcome submitted and leaderboard updated!")
             else:
                 expander.write("No matches available for the selected date.")
         else: