Refactor player selection handling in Streamlit app to utilize session state for storing filtered player data. This change enhances data management and ensures consistent access to player selections across different operations, improving overall functionality and user experience.

src/streamlit_app.py

@@ -446,20 +446,20 @@ if selected_tab == 'Handbuilder':
 
     # If no teams selected, show all teams
     if selected_teams:
-        player_select_df = handbuild_roo[
+        st.session_state['player_select_df'] = handbuild_roo[
             handbuild_roo['Team'].isin(selected_teams)
         ][['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
     else:
-        player_select_df = handbuild_roo[['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
+        st.session_state['player_select_df'] = handbuild_roo[['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
     
     # If no teams selected, show all teams
     if pos_select3:
         position_mask_2 = handbuild_roo['Position'].apply(lambda x: any(pos in x for pos in pos_select3))
-        player_select_df = player_select_df[position_mask_2][['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
+        st.session_state['player_select_df'] = st.session_state['player_select_df'][position_mask_2][['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
     else:
-        player_select_df = player_select_df[['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
+        st.session_state['player_select_df'] = st.session_state['player_select_df'][['Player', 'Position', 'Team', 'Salary', 'Median', '2x%', 'Own']].drop_duplicates(subset=['Player', 'Team']).copy()
     
-    player_select_df = player_select_df[player_select_df['Salary'] <= salary_var]
+    st.session_state['player_select_df'] = st.session_state['player_select_df'][st.session_state['player_select_df']['Salary'] <= salary_var]
 
     
     with st.expander("Quick Fill Options"):
@@ -470,9 +470,9 @@ if selected_tab == 'Handbuilder':
         if st.button("Quick Fill", key="quick_fill_button"):
             # 1. Get all eligible players from the selected team, not already in the lineup
             current_players = set(st.session_state['handbuilder_lineup']['Player'])
-            team_players = player_select_df[
-                (player_select_df['Team'] == auto_team_var) &
-                (~player_select_df['Player'].isin(current_players))
+            team_players = st.session_state['player_select_df'][
+                (st.session_state['player_select_df']['Team'] == auto_team_var) &
+                (~st.session_state['player_select_df']['Player'].isin(current_players))
             ].copy()
 
             # 2. Sort by Order
@@ -483,9 +483,9 @@ if selected_tab == 'Handbuilder':
                 selected_players = team_players[team_players['Position'] == 'QB'].head(1)
                 selected_players = pd.concat([selected_players, team_players[team_players['Position'] == 'WR'].head(auto_size_var - 1)])
                 if len(selected_players) < auto_size_var:
-                    team_players = player_select_df[
-                        (player_select_df['Team'] == auto_team_var) &
-                        (~player_select_df['Player'].isin(current_players))
+                    team_players = st.session_state['player_select_df'][
+                        (st.session_state['player_select_df']['Team'] == auto_team_var) &
+                        (~st.session_state['player_select_df']['Player'].isin(current_players))
                     ].copy()
 
                     # 2. Sort by Order
@@ -495,9 +495,9 @@ if selected_tab == 'Handbuilder':
                 selected_players = team_players[team_players['Position'] == 'QB'].head(1)
                 selected_players = pd.concat([selected_players, team_players[team_players['Position'].isin(['WR', 'TE'])].head(auto_size_var - 1)])
                 if len(selected_players) < auto_size_var:
-                    team_players = player_select_df[
-                        (player_select_df['Team'] == auto_team_var) &
-                        (~player_select_df['Player'].isin(current_players))
+                    team_players = st.session_state['player_select_df'][
+                        (st.session_state['player_select_df']['Team'] == auto_team_var) &
+                        (~st.session_state['player_select_df']['Player'].isin(current_players))
                     ].copy()
 
                     # 2. Sort by Order
@@ -507,9 +507,9 @@ if selected_tab == 'Handbuilder':
                 selected_players = team_players[team_players['Position'] == 'QB'].head(1)
                 selected_players = pd.concat([selected_players, team_players[team_players['Position'].isin(['RB', 'WR', 'TE'])].head(auto_size_var - 1)])
                 if len(selected_players) < auto_size_var:
-                    team_players = player_select_df[
-                        (player_select_df['Team'] == auto_team_var) &
-                        (~player_select_df['Player'].isin(current_players))
+                    team_players = st.session_state['player_select_df'][
+                        (st.session_state['player_select_df']['Team'] == auto_team_var) &
+                        (~st.session_state['player_select_df']['Player'].isin(current_players))
                     ].copy()
 
                     # 2. Sort by Order
@@ -556,14 +556,14 @@ if selected_tab == 'Handbuilder':
                 return True
         return False
 
-    # player_select_df = player_select_df[player_select_df.apply(is_player_eligible, axis=1)]
-    print(player_select_df.head(10))
+    # st.session_state['player_select_df'] = st.session_state['player_select_df'][st.session_state['player_select_df'].apply(is_player_eligible, axis=1)]
+    print(st.session_state['player_select_df'].head(10))
 
     handbuilder_lineup_build_column, handbuilder_player_select_column = st.columns([1, 2])
     with handbuilder_player_select_column:
         st.subheader("Player Select")
         event = st.dataframe(
-            player_select_df.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Salary', 'Own']).format(precision=2),
+            st.session_state['player_select_df'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Salary', 'Own']).format(precision=2),
             on_select="rerun",
             selection_mode=["single-row"],
             key="player_select_dataframe",
@@ -573,7 +573,7 @@ if selected_tab == 'Handbuilder':
         # If a row is selected, add that player to the lineup and reset selection
         if event and "rows" in event.selection and len(event.selection["rows"]) > 0:
             idx = event.selection["rows"][0]
-            player_row = player_select_df.iloc[[idx]]
+            player_row = st.session_state['player_select_df'].iloc[[idx]]
             eligible_positions = re.split(r'[/, ]+', player_row['Position'].iloc[0])
             # Find the first eligible slot that is not full
             slot_to_fill = None
@@ -640,11 +640,11 @@ if selected_tab == 'Handbuilder':
                         'Own': np.nan
                     })
 
-        lineup_display_df = pd.DataFrame(display_rows, columns=display_columns)
+        st.session_state['lineup_display_df'] = pd.DataFrame(display_rows, columns=display_columns)
 
         # Show the lineup table with single-row selection for removal
         event_remove = st.dataframe(
-            lineup_display_df.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn', subset=['Median']).background_gradient(cmap='RdYlGn_r', subset=['Salary', 'Own']).format(precision=2),
+            st.session_state['lineup_display_df'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn', subset=['Median']).background_gradient(cmap='RdYlGn_r', subset=['Salary', 'Own']).format(precision=2),
             on_select="rerun",
             selection_mode=["single-row"],
             key="lineup_remove_dataframe",
@@ -655,8 +655,8 @@ if selected_tab == 'Handbuilder':
         # If a row is selected and not blank, remove that player from the lineup
         if event_remove and "rows" in event_remove.selection and len(event_remove.selection["rows"]) > 0:
             idx = event_remove.selection["rows"][0]
-            player_to_remove = lineup_display_df.iloc[idx]['Player']
-            slot_to_remove = lineup_display_df.iloc[idx]['Slot']
+            player_to_remove = st.session_state['lineup_display_df'].iloc[idx]['Player']
+            slot_to_remove = st.session_state['lineup_display_df'].iloc[idx]['Slot']
             if player_to_remove:  # Only remove if not blank
                 st.session_state['handbuilder_lineup'] = filled_lineup[
                     ~((filled_lineup['Player'] == player_to_remove) & (filled_lineup['Slot'] == slot_to_remove))
@@ -730,10 +730,10 @@ if selected_tab == 'Handbuilder':
     with save_col:
         if st.button("Save Lineup", key='save_lineup_button'):
             if 'saved_lineups' in st.session_state:
-                st.session_state['saved_lineups'].append(lineup_display_df['Player'].tolist())
+                st.session_state['saved_lineups'].append(st.session_state['lineup_display_df']['Player'].tolist())
                 print(st.session_state['saved_lineups'])
             else:
-                st.session_state['saved_lineups'] = [lineup_display_df['Player'].tolist()]
+                st.session_state['saved_lineups'] = [st.session_state['lineup_display_df']['Player'].tolist()]
                 print(st.session_state['saved_lineups'])
     with export_col:
         if 'saved_lineups' in st.session_state and st.session_state['saved_lineups']:
@@ -780,17 +780,17 @@ elif selected_tab == 'Stacks ROO':
             elif split_var1 == 'Full Slate Run':
                 team_var1 = raw_baselines.Team.values.tolist()
     
-    final_stacks = raw_baselines[raw_baselines['Team'].isin(team_var1)]
+    st.session_state['final_stacks'] = raw_baselines[raw_baselines['Team'].isin(team_var1)]
     if view_var == 'Simple':
-        final_stacks = final_stacks[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Salary', 'Median', '60+%', '4x%']]
+        st.session_state['final_stacks'] = st.session_state['final_stacks'][['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Salary', 'Median', '60+%', '4x%']]
     elif view_var == 'Advanced':
-        final_stacks = final_stacks[['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish',
+        st.session_state['final_stacks'] = st.session_state['final_stacks'][['Team', 'QB', 'WR1_TE', 'WR2_TE', 'Total', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish',
                                                         'Top_10_finish', '60+%', '2x%', '3x%', '4x%', 'Own', 'LevX']]
     with st.container():
-        st.dataframe(final_stacks.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='stacks_dataframe')
+        st.dataframe(st.session_state['final_stacks'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='stacks_dataframe')
         st.download_button(
                 label="Export Tables",
-                data=convert_df_to_csv(final_stacks),
+                data=convert_df_to_csv(st.session_state['final_stacks']),
                 file_name='NFL_stacks_export.csv',
                 mime='text/csv',
                 key='stacks_export_button'
@@ -847,12 +847,12 @@ elif selected_tab == 'Player ROO':
     
     if view_var == 'Simple':
         final_Proj = final_Proj[['Player', 'Position', 'Team', 'Salary', 'Median', 'Top_5_finish', '4x%']]
-        disp_proj = final_Proj.set_index('Player')
+        st.session_state['disp_proj'] = final_Proj.set_index('Player')
     elif view_var == 'Advanced':
         final_Proj = final_Proj[['Player', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Ceiling', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '2x%', '3x%', '4x%', 'Own', 'Small_Field_Own', 'Large_Field_Own', 'Cash_Field_Own', 'CPT_Own', 'LevX']]
-        disp_proj = final_Proj.set_index('Player')
+        st.session_state['disp_proj'] = final_Proj.set_index('Player')
     with st.container():
-        st.dataframe(disp_proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='player_dataframe')
+        st.dataframe(st.session_state['disp_proj'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(player_roo_format, precision=2), height=750, use_container_width = True, key='player_dataframe')
         st.download_button(
             label="Export Tables",
             data=convert_df_to_csv(final_Proj),