Use multiple dfs to make functions run in parallel

gradio_function.py

@@ -39,6 +39,9 @@ def clone_df(fn):
     return fn(*args, **kwargs)
   return _fn
 
+def copy_dataframe(df, num_copy_to):
+  return [df.clone() for _ in range(num_copy_to)]
+
 # location maps
 def fit_pred_kde(data, X, Y):
   kde = gaussian_kde(data)

pitcher_dashboard.py

@@ -78,6 +78,19 @@ def create_pitcher_dashboard():
               pitch_velos.append(gr.Plot(show_label=False, elem_classes='pitch-velo', visible=visible))
               pitch_locs.append(gr.Plot(label='Pitch Location', elem_classes='pitch-loc', visible=visible))
 
+    download_file_fn = create_set_download_file_fn('files/player.csv')
+    plot_loc_summary = lambda df: plot_loc(df)
+    fn_configs = {
+      download_file_fn: dict(inputs=[], outputs=download_file),
+      plot_usage: dict(inputs=[player], outputs=usage),
+      plot_velo_summary: dict(inputs=[app_league_df, player], outputs=velo_summary),
+      plot_loc_summary: dict(inputs=[], outputs=loc_summary),
+      plot_pitch_cards: dict(inputs=[app_league_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
+    }
+    for k in fn_configs.keys():
+      fn_configs[k]['df'] = gr.State(df)
+      fn_configs[k]['inputs'] = [fn_configs[k]['df']] + fn_configs[k]['inputs']
+
     (
         player
         .input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
@@ -93,14 +106,20 @@ def create_pitcher_dashboard():
     # app_df.change(plot_pitch_cards, inputs=[app_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
     app_pitch_stats.change(update_velo_stats, inputs=[app_pitch_stats, app_league_pitch_stats], outputs=velo_stats)
 
-    (
-        app_df
-        .change(create_set_download_file_fn('files/player.csv'), inputs=app_df, outputs=download_file)
-        .then(plot_usage, inputs=[app_df, player], outputs=usage)
-        .then(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
-        .then(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
-        .then(plot_pitch_cards, inputs=[app_df, app_league_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
-    )
+    # (
+    #     app_df
+    #     .change(create_set_download_file_fn('files/player.csv'), inputs=app_df, outputs=download_file)
+    #     .then(plot_usage, inputs=[app_df, player], outputs=usage)
+    #     .then(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
+    #     .then(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
+    #     .then(plot_pitch_cards, inputs=[app_df, app_league_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
+    # )
+
+    app_df.change(lambda df: copy_dataframe(df, len(fn_configs)), inputs=app_df, outputs=[config['df'] for config in fn_configs.values()])
+
+    for fn, config in fn_configs.items():
+      config['df'].change(fn, inputs=config['inputs'], outputs=config['outputs'])
+
 
     gr.Markdown('## Bugs and other notes')
     with gr.Accordion('Click to open', open=False):