enhanced admin panel

app.py

@@ -13,7 +13,6 @@ from huggingface_hub import CommitScheduler, HfApi
 
 # File paths as constants
 PREDICTIONS_CSV = 'dis_predictions.csv'
-PREDICTIONS_FOLDER = "ipl_predictions"  # Folder where JSON files are saved locally
 USERS_JSON = 'leaders/users.json'
 MATCHES_JSON = 'matches.json'
 OUTCOMES_JSON = 'match_outcomes.json'
@@ -21,13 +20,10 @@ PLAYERS_JSON = 'players.json'
 image_path = 'ipl_image.png'
 
 
-prediction_id = uuid.uuid4().hex
-# Save prediction to a local JSON file for CommitScheduler to handle
-prediction_file = Path("ipl_predictions/") / f"prediction_{prediction_id}.json"
-PREDICTIONS_FOLDER = prediction_file.parent
+PREDICTIONS_FOLDER = Path("ipl_predictions")
 PREDICTIONS_FOLDER.mkdir(parents=True, exist_ok=True)
 
-users_file = Path("leaders/") / f"users.json"
+users_file = Path("leaders") / f"users.json"
 USERS_FOLDER = users_file.parent
 USERS_FOLDER.mkdir(parents=True, exist_ok=True)
 
@@ -36,7 +32,7 @@ scheduler = CommitScheduler(
     repo_id="DIS_IPL_Dataset",
     repo_type="dataset",
     folder_path=PREDICTIONS_FOLDER,  # Local folder where predictions are saved temporarily
-    path_in_repo="predictions",  # Path in dataset repo where predictions will be saved
+    path_in_repo="ipl_predictions",  # Path in dataset repo where predictions will be saved
     every=2,  # Push every 240 minutes (4 hours)
 )
 
@@ -44,7 +40,7 @@ scheduler = CommitScheduler(
 scheduler = CommitScheduler(
     repo_id="DIS_IPL_Dataset",
     repo_type="dataset",
-    folder_path=USERS_FOLDER,  # Local folder where predictions are saved temporarily
+    folder_path=USERS_FOLDER,  # Local folder where users are saved temporarily
     path_in_repo="leaders",  # Path in dataset repo where predictions will be saved
     every=2,  # Push every 240 minutes (4 hours)
 )
@@ -157,6 +153,7 @@ def submit_prediction(
         st.error(f"Your bid points exceed the 20% limit of your total points. Maximum allowed bid points: {max_bid_points}")
         return
 
+    prediction_id = uuid.uuid4().hex
     prediction_date = datetime.now().strftime('%Y-%m-%d')
 
     prediction_data = {
@@ -168,6 +165,10 @@ def submit_prediction(
         'bid_points': bid_points,
         'prediction_date': prediction_date  # Include the prediction date
     }
+    
+    # Construct the filename to include match_id for easier retrieval
+    prediction_file_name = f"prediction_{match_id}_{prediction_id}.json"
+    prediction_file = PREDICTIONS_FOLDER / prediction_file_name
 
     with scheduler.lock:
         with prediction_file.open("a") as file:
@@ -346,9 +347,25 @@ with st.expander("Leaderboard 🏆"):
 ############################# Admin Panel ##################################
 ADMIN_PASSPHRASE = "admin123"
 
-def save_users(users):
-    with open(USERS_JSON, 'w') as file:
-        json.dump(users, file, indent=4)
+from huggingface_hub import Repository
+
+# Define the local path to clone the repository
+local_repo_path = "DIS_IPL_Dataset"
+# Define your dataset repository name on Hugging Face Hub
+repo_id = "Jay-Rajput/DIS_IPL_Dataset"
+# Clone the repository (this only needs to be done once)
+repo = Repository(local_dir=local_repo_path, clone_from=repo_id)
+
+
+def fetch_latest_predictions(match_id):
+    # Assuming predictions are stored in the "ipl_predictions" directory in your dataset repo
+    predictions_path = Path("ipl_predictions")
+    latest_predictions = []
+    for prediction_file in predictions_path.glob(f"prediction_{match_id}_*.json"):
+        with open(prediction_file, 'r') as file:
+            prediction_data = json.load(file)
+            latest_predictions.append(prediction_data)
+    return latest_predictions
 
 
 def save_match_outcomes(outcomes):
@@ -357,9 +374,13 @@ def save_match_outcomes(outcomes):
 
 
 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)
+    
     outcomes = load_data(OUTCOMES_JSON)  # Load existing match outcomes
-    predictions = load_predictions(PREDICTIONS_CSV)  # Load existing predictions
-    users = load_users(USERS_JSON)  # Load existing user points
+    users_file_path = repo.git_pull("leaders/users.json")
+    with open(users_file_path, 'r') as file:
+        users = json.load(file)
 
     # Directly update or add the match outcome
     outcome_exists = False
@@ -372,22 +393,28 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
         outcomes.append({"match_id": match_id, "winning_team": winning_team, "man_of_the_match": man_of_the_match})
 
     # Update user points based on prediction accuracy
-    for _, prediction in predictions.iterrows():
-        if prediction['match_id'] == match_id:
-            user_name = prediction['user_name']
-            users[user_name] = users.get(user_name, 0)  # Initialize user points if not present
-
-            # Update points based on prediction accuracy
-            if prediction['predicted_winner'] == winning_team:
-                users[user_name] += 1000
-                users[user_name] += prediction['bid_points'] 
-                if prediction['predicted_motm'] == man_of_the_match:
-                    users[user_name] += 400  # Bonus for both correct predictions
-            else:
-                users[user_name] -= 200 + prediction['bid_points']  # Penalty for wrong team prediction
+    for prediction in predictions:
+        user_name = prediction['user_name']
+        users[user_name] = users.get(user_name, 0)  # Initialize user points if not present
+
+        # Update points based on prediction accuracy
+        if prediction['predicted_winner'] == winning_team:
+            users[user_name] += 1000
+            users[user_name] += prediction['bid_points'] 
+            if prediction['predicted_motm'] == man_of_the_match:
+                users[user_name] += 400  # Bonus for both correct predictions
+        else:
+            users[user_name] -= 200 + prediction['bid_points']  # Penalty for wrong team prediction
 
     save_match_outcomes(outcomes)
-    save_users(users)
+    # Save updated users data back to the dataset repo
+    with open(users_file_path, 'w') as file:
+        json.dump(users, file)
+        
+    # Commit changes to the dataset repo
+    repo.git_add(users_file_path)
+    repo.git_commit("Update leaderboard")
+    repo.git_push()
 
 
 with st.sidebar:
@@ -396,11 +423,17 @@ with st.sidebar:
 
     if admin_pass == ADMIN_PASSPHRASE:
         expander.success("Authenticated")
-        matches = get_today_matches()  # This function fetches today's matches
+        
+        all_matches = load_data(MATCHES_JSON)
+        match_outcomes = load_data(OUTCOMES_JSON)
+        submitted_match_ids = [outcome["match_id"] for outcome in match_outcomes]
 
+        # Filter matches to those that do not have outcomes submitted yet
+        matches_without_outcomes = [match for match in all_matches if match["match_id"] not in submitted_match_ids]
+        
         # If matches are available, let the admin select one
-        if matches:
-            match_selection = expander.selectbox("Select Match", matches, format_func=lambda match: f"{match['teams'][0]} vs {match['teams'][1]}", key="match_selection")
+        if matches_without_outcomes:
+            match_selection = expander.selectbox("Select Match", matches_without_outcomes, format_func=lambda match: f"{match['teams'][0]} vs {match['teams'][1]}", key="match_selection")
             selected_match_id = match_selection['match_id']
             teams = match_selection['teams']