Update main.py

main.py

@@ -673,8 +673,10 @@ def _scrape_player_index_brscraper():
 
 def get_player_career_stats_brscraper(player_name, seasons_to_check=10, playoffs=False):
     if not BRSCRAPER_AVAILABLE:
+        logging.error("BRScraper is not available. Cannot fetch player career stats.")
         return pd.DataFrame()
     all_rows = []
+    
     # This function should only try to fetch data for the specific seasons requested,
     # not all available seasons, to avoid unnecessary calls and "invalid season" warnings.
     # However, the current design of `getPlayerStats` endpoint passes `selected_seasons`
@@ -688,32 +690,34 @@ def get_player_career_stats_brscraper(player_name, seasons_to_check=10, playoffs
     for season_str in seasons_to_try:
         end_year = int(season_str.split('–')[1])
         try:
-            logging.info(f"Attempting nba.get_stats for {player_name} in {season_str} (year: {end_year}, playoffs: {playoffs})...")
+            logging.info(f"DEBUG: Calling nba.get_stats for player '{player_name}' in season {season_str} (year: {end_year}, playoffs: {playoffs})...")
+            
             df_season = nba.get_stats(end_year, info='per_game', playoffs=playoffs, rename=False)
             
             if df_season.empty:
-                logging.warning(f"nba.get_stats returned empty DataFrame for {player_name} in {season_str}.")
-                continue # Skip to next season if DataFrame is empty
+                logging.warning(f"DEBUG: nba.get_stats returned empty DataFrame for {player_name} in {season_str}. Skipping this season.")
+                continue 
 
             if 'Player' not in df_season.columns:
-                logging.warning(f"DataFrame for {player_name} in {season_str} has no 'Player' column. Columns: {df_season.columns.tolist()}")
-                continue # Skip if 'Player' column is missing
+                logging.warning(f"DEBUG: DataFrame for {player_name} in {season_str} has no 'Player' column. Columns: {df_season.columns.tolist()}. Skipping this season.")
+                continue 
 
             row = df_season[df_season['Player'] == player_name]
             if not row.empty:
                 row = row.copy()
                 row['Season'] = season_str
                 all_rows.append(row)
-                logging.info(f"Found stats for {player_name} in {season_str}.")
+                logging.info(f"DEBUG: Found stats for {player_name} in {season_str}. Appending row.")
             else:
-                logging.info(f"Player {player_name} not found in {season_str} stats.")
+                logging.info(f"DEBUG: Player {player_name} not found in {season_str} stats (after getting season data).")
 
         except Exception as e:
-            logging.warning(f"Could not fetch {season_str} {'playoff' if playoffs else 'regular season'} stats for {player_name}: {e}")
             # This is where the "not a valid season" error comes from. It's a warning, not a fatal error for the loop.
+            logging.warning(f"DEBUG: Exception when fetching {season_str} {'playoff' if playoffs else 'regular season'} stats for {player_name}: {e}")
+            # traceback.print_exc() # Uncomment for full traceback if needed
 
     if not all_rows:
-        logging.warning(f"No stats found for {player_name} across all attempted seasons.")
+        logging.warning(f"DEBUG: No stats found for {player_name} across all attempted seasons. Returning empty DataFrame.")
         return pd.DataFrame()
     
     df = pd.concat(all_rows, ignore_index=True)