Add info_columns_dict initialization in app.py: implement logic to store key metrics from working_frame in session state for improved data tracking, and refactor filtering logic to enhance clarity and maintainability of lineup processing.

app.py

@@ -876,6 +876,16 @@ with tab2:
                     axis=1
                 )
             st.session_state['working_frame'] = predict_dupes(st.session_state['working_frame'], st.session_state['map_dict'], site_var, type_var, Contest_Size, strength_var, sport_var)
+            if 'info_columns_dict' not in st.session_state:
+                st.session_state['info_columns_dict'] = {
+                    'Dupes': st.session_state['working_frame']['Dupes'],
+                    'Finish_percentile': st.session_state['working_frame']['Finish_percentile'],
+                    'Win%': st.session_state['working_frame']['Win%'],
+                    'Lineup Edge': st.session_state['working_frame']['Lineup Edge'],
+                    'Weighted Own': st.session_state['working_frame']['Weighted Own'],
+                    'Geomean': st.session_state['working_frame']['Geomean'],
+                }
+
             if 'trimming_dict_maxes' not in st.session_state:
                 st.session_state['trimming_dict_maxes'] = {
                     'Own': st.session_state['working_frame']['Own'].max(),
@@ -909,28 +919,20 @@ with tab2:
                     
                     submitted = st.form_submit_button("Submit")
                     if submitted:
-                        st.session_state['working_frame'] = predict_dupes(st.session_state['working_frame'], st.session_state['map_dict'], site_var, type_var, Contest_Size, strength_var, sport_var)
-                        if 'trimming_dict_maxes' not in st.session_state:
-                            st.session_state['trimming_dict_maxes'] = {
-                                'Own': st.session_state['working_frame']['Own'].max(),
-                                'Geomean': st.session_state['working_frame']['Geomean'].max(),
-                                'Weighted Own': st.session_state['working_frame']['Weighted Own'].max(),
-                                'median': st.session_state['working_frame']['median'].max(),
-                                'Finish_percentile': st.session_state['working_frame']['Finish_percentile'].max()
-                            }
-                        st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['Dupes'] <= max_dupes]
-                        st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['salary'] >= min_salary]
-                        st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['salary'] <= max_salary]
-                        st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['Finish_percentile'] <= max_finish_percentile]
-                        st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['Lineup Edge'] >= min_lineup_edge]
+                        parsed_frame = st.session_state['working_frame'].copy()
+                        parsed_frame = parsed_frame[parsed_frame['Dupes'] <= max_dupes]
+                        parsed_frame = parsed_frame[parsed_frame['salary'] >= min_salary]
+                        parsed_frame = parsed_frame[parsed_frame['salary'] <= max_salary]
+                        parsed_frame = parsed_frame[parsed_frame['Finish_percentile'] <= max_finish_percentile]
+                        parsed_frame = parsed_frame[parsed_frame['Lineup Edge'] >= min_lineup_edge]
                         if stack_dict is not None:
                             if stack_toggle == 'All Stacks':
-                                st.session_state['working_frame'] = st.session_state['working_frame']
-                                st.session_state['working_frame'] = st.session_state['working_frame'][~st.session_state['working_frame']['Stack'].isin(stack_remove)]
+                                parsed_frame = parsed_frame
+                                parsed_frame = parsed_frame[~parsed_frame['Stack'].isin(stack_remove)]
                             else:
-                                st.session_state['working_frame'] = st.session_state['working_frame'][st.session_state['working_frame']['Stack'].isin(stack_selections)]
-                                st.session_state['working_frame'] = st.session_state['working_frame'][~st.session_state['working_frame']['Stack'].isin(stack_remove)]
-                        st.session_state['working_frame'] = st.session_state['working_frame'].sort_values(by='median', ascending=False)
+                                parsed_frame = parsed_frame[parsed_frame['Stack'].isin(stack_selections)]
+                                parsed_frame = parsed_frame[~parsed_frame['Stack'].isin(stack_remove)]
+                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False)
                         st.session_state['export_merge'] = st.session_state['working_frame'].copy()
 
             with st.expander('Micro Filter Options'):
@@ -944,32 +946,24 @@ with tab2:
                     
                     submitted = st.form_submit_button("Submit")
                     if submitted:
-                        st.session_state['working_frame'] = predict_dupes(st.session_state['working_frame'], st.session_state['map_dict'], site_var, type_var, Contest_Size, strength_var, sport_var)
-                        if 'trimming_dict_maxes' not in st.session_state:
-                            st.session_state['trimming_dict_maxes'] = {
-                                'Own': st.session_state['working_frame']['Own'].max(),
-                                'Geomean': st.session_state['working_frame']['Geomean'].max(),
-                                'Weighted Own': st.session_state['working_frame']['Weighted Own'].max(),
-                                'median': st.session_state['working_frame']['median'].max(),
-                                'Finish_percentile': st.session_state['working_frame']['Finish_percentile'].max()
-                            }
+                        parsed_frame = st.session_state['working_frame'].copy()
                         if player_remove:
                             # Create mask for lineups that contain any of the removed players
-                            player_columns = [col for col in st.session_state['working_frame'].columns if col not in excluded_cols]
-                            remove_mask = st.session_state['working_frame'][player_columns].apply(
+                            player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
+                            remove_mask = parsed_frame[player_columns].apply(
                                 lambda row: not any(player in list(row) for player in player_remove), axis=1
                             )
-                            st.session_state['working_frame'] = st.session_state['working_frame'][remove_mask]
+                            parsed_frame = parsed_frame[remove_mask]
                         
                         if player_lock:
                             # Create mask for lineups that contain all locked players
-                            player_columns = [col for col in st.session_state['working_frame'].columns if col not in excluded_cols]
+                            player_columns = [col for col in parsed_frame.columns if col not in excluded_cols]
                             
-                            lock_mask = st.session_state['working_frame'][player_columns].apply(
+                            lock_mask = parsed_frame[player_columns].apply(
                                 lambda row: all(player in list(row) for player in player_lock), axis=1
                             )
-                            st.session_state['working_frame'] = st.session_state['working_frame'][lock_mask]
-                        st.session_state['working_frame'] = st.session_state['working_frame'].sort_values(by='median', ascending=False)
+                            parsed_frame = parsed_frame[lock_mask]
+                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False)
                         st.session_state['export_merge'] = st.session_state['working_frame'].copy()
 
             with st.expander('Trimming Options'):