Update app.py

app.py

@@ -276,32 +276,17 @@ def server(input, output, session):
             fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01)
 
 
-    @session.download()
+    @session.download(filename="sample_data.csv")
     def download():
-        year_input = int(input.year_input())
-        sport_id = int(input.level_input())
-        player_input = int(input.pitcher_id())
-        start_date = str(input.date_id()[0])
-        end_date = str(input.date_id()[1])
-        # Simulate an expensive data operation
-        game_list  = scrape.get_player_games_list(sport_id = sport_id,
-                                                season = year_input, 
-                                                player_id = player_input,
-                                                start_date = start_date,
-                                                end_date = end_date)
-
-        data_list = scrape.get_data(game_list_input = game_list[:])
-        df = (stuff_apply.stuff_apply(fe.feature_engineering(update.update(scrape.get_data_df(data_list = data_list).filter(
-                            (pl.col("pitcher_id") == player_input)&
-                            (pl.col("is_pitch") == True)&
-                            (pl.col('batter_hand').is_in(split_dict_hand[input.split_id()]))
-
-                            )))).with_columns(
-                pl.col('pitch_type').count().over('pitch_type').alias('pitch_count')
-            ))
+        # Create a string buffer and write the CSV to it
+        sio = StringIO()
+        cached_data().to_pandas().to_csv(sio, index=False)
+        sio.seek(0)
+        content = sio.getvalue()
         
-        yield df.write_csv('data.csv')
-
+        # Return the CSV content
+        return content
+    
 
 app = App(app_ui, server)