Update main.py

main.py

@@ -544,8 +544,8 @@ def clean_team_name(team_name):
     if pd.isna(team_name):
         return team_name
     team_name = str(team_name).strip()
-    team_name = re.sub(r'\s*\(\d+\)$', '', team_name) # Remove playoff seeding suffix
-    team_name = team_name.replace('*', '') # Remove asterisks
+    team_name = re.sub(r'\s*\(\d+\)$', '', team_name)
+    team_name = team_name.replace('*', '')
     return team_name
 
 def is_data_stale(timestamp_str, max_age_hours=24):
@@ -573,9 +573,11 @@ def get_team_standings_brscraper(year):
         logging.info(f"Scraping team standings for {year} (cache stale or not found).")
         df = _scrape_team_standings_brscraper(year)
         if not df.empty:
+            # Apply clean_df_for_firebase before saving to cache
+            df_cleaned_for_firebase = clean_df_for_firebase(df.copy()) # Use a copy to avoid modifying original df if it's used later
             db_ref.set({
                 'last_updated': datetime.utcnow().isoformat(),
-                'data': df.to_dict(orient='records')
+                'data': df_cleaned_for_firebase.to_dict(orient='records')
             })
             logging.info(f"Team standings for {year} saved to Firebase cache.")
         return df
@@ -585,7 +587,7 @@ def _scrape_team_standings_brscraper(year):
         logging.error("BRScraper not available for team standings.")
         return pd.DataFrame()
     try:
-        df = nba.get_standings(year, info='total') # Removed rename=False
+        df = nba.get_standings(year, info='total')
         if df.empty:
             logging.warning(f"Could not find team standings for {year} using BRScraper.")
             return pd.DataFrame()
@@ -597,7 +599,7 @@ def _scrape_team_standings_brscraper(year):
         df = df.rename(columns={old_col: new_col for old_col, new_col in column_mapping.items() if old_col in df.columns})
 
         if 'Team' in df.columns:
-            df['Team'] = df['Team'].astype(str) # Ensure string type
+            df['Team'] = df['Team'].astype(str)
             df['Team'] = df['Team'].apply(clean_team_name)
 
         numeric_cols = [col for col in df.columns if col not in ['Team']]
@@ -969,7 +971,6 @@ def get_team_stats():
         if tm_df.empty:
             return jsonify({'error': f'No team data available for {selected_season_str}'}), 404
 
-        # Map input abbreviations to full names for lookup
         full_team_names_map = {
             "ATL": "Atlanta Hawks", "BOS": "Boston Celtics", "BRK": "Brooklyn Nets",
             "CHO": "Charlotte Hornets", "CHI": "Chicago Bulls", "CLE": "Cleveland Cavaliers",
@@ -994,7 +995,6 @@ def get_team_stats():
                 df_dict['Season'] = selected_season_str
                 stats.append(df_dict)
             else:
-                # Add original abbreviation to not_found list
                 original_abbr = next((abbr for abbr, name in full_team_names_map.items() if name == team_full_name_lookup), team_full_name_lookup)
                 teams_with_no_data.append(original_abbr)