Saving preds every 12 hours

app.py

@@ -34,7 +34,7 @@ scheduler = CommitScheduler(
     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
-    every=120,  # Push every 240 minutes (4 hours)
+    every=720,  # Push every 240 minutes (4 hours)
 )
 
 # Initialize CommitScheduler
@@ -43,7 +43,7 @@ scheduler = CommitScheduler(
     repo_type="dataset",
     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=120,  # Push every 240 minutes (4 hours)
+    every=720,  # Push every 240 minutes (4 hours)
 )
 
 # Initialize CSV and JSON files if they don't exist
@@ -261,61 +261,61 @@ def display_predictions():
             if 'prediction_id' in todays_predictions.columns:
                 todays_predictions = todays_predictions.drop(columns=['prediction_id', 'prediction_date'])
 
-        
             st.dataframe(todays_predictions, hide_index=True)
         else:
             st.write("No predictions for today's matches yet.")
 
 
-def display_leaderboard():
-    if st.button("Show Leaderboard"):
-        try:
-            users = load_users(USERS_JSON)
-            # Convert the dataset to a pandas DataFrame
-            df_users = pd.DataFrame([{'User': key, 'Points': value} for key, value in users.items()])
-
-            # Sort DataFrame by points in descending order
-            leaderboard = df_users.sort_values(by='Points', ascending=False).reset_index(drop=True)
-            
-            # Add a 'Rank' column starting from 1
-            leaderboard['Rank'] = leaderboard.index + 1
-            
-            # Reorder DataFrame columns so 'Rank' is first
-            df_leaderboard = leaderboard[['Rank', 'User', 'Points']]
-            
-            st.dataframe(df_leaderboard, hide_index=True)
-        except FileNotFoundError:
-            st.write("Leaderboard data not available.")
-
 # def display_leaderboard():
 #     if st.button("Show Leaderboard"):
 #         try:
-#             # Load the 'leaders' configuration or split from your dataset
-#             dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
+#             users = load_users(USERS_JSON)
 #             # Convert the dataset to a pandas DataFrame
-#             df_users = pd.DataFrame(dataset)
-            
-#             # Transform the DataFrame to have 'user_name' and 'points' columns
-#             # Since your JSON structure is quite unique, this step may need adjustment based on how the DataFrame is loaded
-#             users_data = []
-#             for column in df_users.columns:
-#                 points = df_users[column].iloc[0]  # Assuming the first (and only) row contains the points for each user
-#                 users_data.append({'user_name': column, 'points': points})
-
-#             df_leaderboard = pd.DataFrame(users_data)
-            
+#             df_users = pd.DataFrame([{'User': key, 'Points': value} for key, value in users.items()])
+
 #             # Sort DataFrame by points in descending order
-#             df_leaderboard = df_leaderboard.sort_values(by='points', ascending=False)
+#             leaderboard = df_users.sort_values(by='Points', ascending=False).reset_index(drop=True)
             
 #             # Add a 'Rank' column starting from 1
-#             df_leaderboard['Rank'] = range(1, len(df_leaderboard) + 1)
+#             leaderboard['Rank'] = leaderboard.index + 1
             
-#             # Select and order the columns for display
-#             df_leaderboard = df_leaderboard[['Rank', 'User', 'Points']]
+#             # Reorder DataFrame columns so 'Rank' is first
+#             df_leaderboard = leaderboard[['Rank', 'User', 'Points']]
             
 #             st.dataframe(df_leaderboard, hide_index=True)
-#         except Exception as e:
-#             st.write("Failed to load leaderboard data: ", str(e))
+#         except FileNotFoundError:
+#             st.write("Leaderboard data not available.")
+
+
+def display_leaderboard():
+    if st.button("Show Leaderboard"):
+        try:
+            # Load the 'leaders' configuration or split from your dataset
+            dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
+            # Convert the dataset to a pandas DataFrame
+            df_users = pd.DataFrame(dataset)
+            
+            # Transform the DataFrame to have 'user_name' and 'points' columns
+            # Since your JSON structure is quite unique, this step may need adjustment based on how the DataFrame is loaded
+            users_data = []
+            for column in df_users.columns:
+                points = df_users[column].iloc[0]  # Assuming the first (and only) row contains the points for each user
+                users_data.append({'User': column, 'Points': points})
+
+            df_leaderboard = pd.DataFrame(users_data)
+            
+            # Sort DataFrame by points in descending order
+            df_leaderboard = df_leaderboard.sort_values(by='Points', ascending=False)
+            
+            # Add a 'Rank' column starting from 1
+            df_leaderboard['Rank'] = range(1, len(df_leaderboard) + 1)
+            
+            # Select and order the columns for display
+            df_leaderboard = df_leaderboard[['Rank', 'User', 'Points']]
+            
+            st.dataframe(df_leaderboard, hide_index=True)
+        except Exception as e:
+            st.write("Failed to load leaderboard data: ", str(e))
 
 
 # Streamlit UI