Update app.py

app.py

@@ -20,28 +20,27 @@ def load_leaderboard_data(csv_file_path):
         return pd.DataFrame(columns=UGI_COLS)  # Return an empty dataframe with the correct columns
 
 # Update the leaderboard table based on the search query and parameter range filters
-def update_table(df: pd.DataFrame, query: str, param_ranges: dict) -> pd.DataFrame:
+def update_table(df: pd.DataFrame, query: str, param_ranges: list) -> pd.DataFrame:
     filtered_df = df
-    if any(param_ranges.values()):
+    if any(param_ranges):
         conditions = []
-        for param_range, checked in param_ranges.items():
-            if checked:
-                if param_range == '~1.5':
-                    conditions.append((filtered_df['Params'] < 2.5))
-                elif param_range == '~3':
-                    conditions.append(((filtered_df['Params'] >= 2.5) & (filtered_df['Params'] < 6)))
-                elif param_range == '~7':
-                    conditions.append(((filtered_df['Params'] >= 6) & (filtered_df['Params'] < 9.5)))
-                elif param_range == '~13':
-                    conditions.append(((filtered_df['Params'] >= 9.5) & (filtered_df['Params'] < 16)))
-                elif param_range == '~20':
-                    conditions.append(((filtered_df['Params'] >= 16) & (filtered_df['Params'] < 28)))
-                elif param_range == '~34':
-                    conditions.append(((filtered_df['Params'] >= 28) & (filtered_df['Params'] < 40)))
-                elif param_range == '~50':
-                    conditions.append(((filtered_df['Params'] >= 40) & (filtered_df['Params'] < 60)))
-                elif param_range == '~70+':
-                    conditions.append((filtered_df['Params'] >= 60))
+        for param_range in param_ranges:
+            if param_range == '~1.5':
+                conditions.append((filtered_df['Params'] < 2.5))
+            elif param_range == '~3':
+                conditions.append(((filtered_df['Params'] >= 2.5) & (filtered_df['Params'] < 6)))
+            elif param_range == '~7':
+                conditions.append(((filtered_df['Params'] >= 6) & (filtered_df['Params'] < 9.5)))
+            elif param_range == '~13':
+                conditions.append(((filtered_df['Params'] >= 9.5) & (filtered_df['Params'] < 16)))
+            elif param_range == '~20':
+                conditions.append(((filtered_df['Params'] >= 16) & (filtered_df['Params'] < 28)))
+            elif param_range == '~34':
+                conditions.append(((filtered_df['Params'] >= 28) & (filtered_df['Params'] < 40)))
+            elif param_range == '~50':
+                conditions.append(((filtered_df['Params'] >= 40) & (filtered_df['Params'] < 60)))
+            elif param_range == '~70+':
+                conditions.append((filtered_df['Params'] >= 60))
         
         if conditions:
             filtered_df = filtered_df[pd.concat(conditions, axis=1).any(axis=1)]
@@ -110,13 +109,13 @@ with GraInter:
     outputs = leaderboard_table
     
     search_bar.change(
-        fn=lambda query, param_ranges: update_table(leaderboard_df, query, dict(zip(['~1.5', '~3', '~7', '~13', '~20', '~34', '~50', '~70+'], param_ranges))),
+        fn=lambda query, param_ranges: update_table(leaderboard_df, query, param_ranges),
         inputs=inputs,
         outputs=outputs
     )
     
     filter_columns_size.change(
-        fn=lambda query, param_ranges: update_table(leaderboard_df, query, dict(zip(['~1.5', '~3', '~7', '~13', '~20', '~34', '~50', '~70+'], param_ranges))),
+        fn=lambda query, param_ranges: update_table(leaderboard_df, query, param_ranges),
         inputs=inputs,
         outputs=outputs
     )