Enhance app.py to improve timestamp retrieval for NBA and NFL datasets. Added error handling to fallback on alternative data sources if primary timestamps are unavailable, ensuring robustness in data processing for player projections.

app.py

@@ -70,9 +70,15 @@ def init_baselines():
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     nfl_fd_sd_raw = raw_display.sort_values(by='Median', ascending=False)
-
-    nba_timestamp = nba_dk_sd_raw['timestamp'].values[0]
-    nfl_dk_timestamp = nfl_dk_sd_raw['timestamp'].values[0]
+    try:
+        nba_timestamp = nba_dk_sd_raw['timestamp'].values[0]
+    except:
+        nba_timestamp = nba_fd_sd_raw['timestamp'].values[0]
+    
+    try:
+        nfl_dk_timestamp = nfl_dk_sd_raw['timestamp'].values[0]
+    except:
+        nfl_dk_timestamp = nfl_fd_sd_raw['timestamp'].values[0]
 
     nba_dk_id_dict = dict(zip(nba_dk_sd_raw['player_id'], nba_dk_sd_raw['player_id']))
     nfl_dk_id_dict = dict(zip(nfl_dk_sd_raw['player_id'], nfl_dk_sd_raw['player_id']))