Update main.py

main.py

@@ -15,7 +15,7 @@ from firebase_admin import credentials, db, storage, auth
 import firebase_admin
 import logging
 import traceback
-from bs4 import BeautifulSoup, Comment # BeautifulSoup is still needed for parse_table if it's used elsewhere, but not for team stats now.
+from bs4 import BeautifulSoup, Comment # BeautifulSoup is still imported but not used for team stats now.
 
 # Import BRScraper
 try:
@@ -559,7 +559,27 @@ def admin_update_credits(uid):
 # NBA Analytics Hub Data Fetching Utilities
 # ——————————————————————————————————————————————
 
-# Removed fetch_html and parse_table as they are no longer used for team stats.
+# Helper to clean DataFrame column names for Firebase keys
+def clean_firebase_keys(key_name):
+    """Cleans a string to be a valid Firebase Realtime Database key."""
+    if not isinstance(key_name, str):
+        key_name = str(key_name)
+    # Firebase invalid characters: . $ # [ ] /
+    # Replace them with underscores or remove them
+    cleaned_key = key_name.replace('.', '_').replace('$', '').replace('#', '').replace('[', '').replace(']', '').replace('/', '_')
+    # Also handle '%' if it's problematic, though not explicitly listed by Firebase for keys
+    cleaned_key = cleaned_key.replace('%', 'Pct') # Example: W/L% -> W_LPct
+    # Ensure no empty keys
+    if not cleaned_key:
+        return "empty_key_" + str(uuid.uuid4())[:8] # Fallback for completely empty keys
+    return cleaned_key
+
+def clean_df_for_firebase(df):
+    """Applies Firebase key cleaning to all column names of a DataFrame."""
+    if df.empty:
+        return df
+    df.columns = [clean_firebase_keys(col) for col in df.columns]
+    return df
 
 def clean_team_name(team_name):
     """
@@ -786,6 +806,7 @@ def _scrape_dashboard_info_brscraper():
         # MVP Votings for 2025
         mvp_2025_df = nba.get_award_votings('mvp', 2025)
         if not mvp_2025_df.empty:
+            mvp_2025_df = clean_df_for_firebase(mvp_2025_df) # Clean column names
             dashboard_data['mvp_2025_votings'] = mvp_2025_df.replace({np.nan: None}).to_dict(orient='records')
         else:
             dashboard_data['mvp_2025_votings'] = []
@@ -794,6 +815,7 @@ def _scrape_dashboard_info_brscraper():
         # Current Season Playoff Probabilities (East)
         east_probs_df = nba.get_playoffs_probs('east')
         if not east_probs_df.empty:
+            east_probs_df = clean_df_for_firebase(east_probs_df) # Clean column names
             dashboard_data['playoff_probs_east'] = east_probs_df.replace({np.nan: None}).to_dict(orient='records')
         else:
             dashboard_data['playoff_probs_east'] = []
@@ -802,6 +824,7 @@ def _scrape_dashboard_info_brscraper():
         # Current Season Playoff Probabilities (West)
         west_probs_df = nba.get_playoffs_probs('west')
         if not west_probs_df.empty:
+            west_probs_df = clean_df_for_firebase(west_probs_df) # Clean column names
             dashboard_data['playoff_probs_west'] = west_probs_df.replace({np.nan: None}).to_dict(orient='records')
         else:
             dashboard_data['playoff_probs_west'] = []