Refactor portfolio loading logic in app.py: ensure portfolio is only loaded if not already in session state, and add minimum lineup edge input for filtering.

app.py

@@ -76,33 +76,33 @@ with tab1:
                 del st.session_state['portfolio']
             if 'export_portfolio' in st.session_state:
                 del st.session_state['export_portfolio']
-
-        if portfolio_file:
-            if saber_toggle == 'Yes':
-                st.session_state['export_portfolio'], st.session_state['portfolio'] = load_ss_file(portfolio_file, st.session_state['csv_file'])
-                st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
-                st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
-                st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
-                st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
-            else:
-                st.session_state['export_portfolio'], st.session_state['portfolio'] = load_file(portfolio_file)
-                st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
-                st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
-                st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
-                st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
-            # Check if Stack column exists in the portfolio
-            if 'Stack' in st.session_state['portfolio'].columns:
-                # Create dictionary mapping index to Stack values
-                stack_dict = dict(zip(st.session_state['portfolio'].index, st.session_state['portfolio']['Stack']))
-                st.write(f"Found {len(stack_dict)} stack assignments")
-                st.session_state['portfolio'] = st.session_state['portfolio'].drop(columns=['Stack'])
-            else:
-                stack_dict = None
-                st.info("No Stack column found in portfolio")
-            if st.session_state['portfolio'] is not None:
-                st.success('Portfolio file loaded successfully!')
-                st.session_state['portfolio'] = st.session_state['portfolio'].apply(lambda x: x.replace(player_wrong_names_mlb, player_right_names_mlb))
-                st.dataframe(st.session_state['portfolio'].head(10))
+        if 'portfolio' not in st.session_state:
+            if portfolio_file:
+                if saber_toggle == 'Yes':
+                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_ss_file(portfolio_file, st.session_state['csv_file'])
+                    st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
+                    st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
+                    st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
+                    st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
+                else:
+                    st.session_state['export_portfolio'], st.session_state['portfolio'] = load_file(portfolio_file)
+                    st.session_state['export_portfolio'] = st.session_state['export_portfolio'].dropna(how='all')
+                    st.session_state['export_portfolio'] = st.session_state['export_portfolio'].reset_index(drop=True)
+                    st.session_state['portfolio'] = st.session_state['portfolio'].dropna(how='all')
+                    st.session_state['portfolio'] = st.session_state['portfolio'].reset_index(drop=True)
+                # Check if Stack column exists in the portfolio
+                if 'Stack' in st.session_state['portfolio'].columns:
+                    # Create dictionary mapping index to Stack values
+                    stack_dict = dict(zip(st.session_state['portfolio'].index, st.session_state['portfolio']['Stack']))
+                    st.write(f"Found {len(stack_dict)} stack assignments")
+                    st.session_state['portfolio'] = st.session_state['portfolio'].drop(columns=['Stack'])
+                else:
+                    stack_dict = None
+                    st.info("No Stack column found in portfolio")
+                if st.session_state['portfolio'] is not None:
+                    st.success('Portfolio file loaded successfully!')
+                    st.session_state['portfolio'] = st.session_state['portfolio'].apply(lambda x: x.replace(player_wrong_names_mlb, player_right_names_mlb))
+                    st.dataframe(st.session_state['portfolio'].head(10))
 
     with col3:
         st.subheader("Projections File")
@@ -693,13 +693,12 @@ with tab3:
                 
             with col2:
                 sport_var = st.selectbox("Select Sport", ['NFL', 'MLB', 'NBA', 'NHL', 'MMA'])
-                st.info("It currently does not matter what sport you select, it may matter in the future.")
                 type_var = st.selectbox("Select Game Type", ['Classic', 'Showdown'])
 
             with col3:
                 Contest_Size = st.number_input("Enter Contest Size", value=25000, min_value=1, step=1)
                 strength_var = st.selectbox("Select field strength", ['Average', 'Sharp', 'Weak'])
-                
+
         if site_var == 'Draftkings':
             if type_var == 'Classic':
                 map_dict = {
@@ -779,13 +778,14 @@ with tab3:
                 axis=1
             )
 
-        col1, col2 = st.columns([9, 1])
-        with col2:
+        col1, col2 = st.columns([1, 10])
+        with col1:
             with st.form(key='filter_form'):
                 max_dupes = st.number_input("Max acceptable dupes?", value=1000, min_value=1, step=1)
                 min_salary = st.number_input("Min acceptable salary?", value=1000, min_value=1000, step=100)
                 max_salary = st.number_input("Max acceptable salary?", value=60000, min_value=1000, step=100)
                 max_finish_percentile = st.number_input("Max acceptable finish percentile?", value=.50, min_value=0.005, step=.001)
+                min_lineup_edge = st.number_input("Min acceptable Lineup Edge?", value=-.5, min_value=-1, step=.001)
                 player_names = set()
                 for col in st.session_state['portfolio'].columns:
                     if col not in excluded_cols:
@@ -799,12 +799,13 @@ with tab3:
                 
                 submitted = st.form_submit_button("Submit")
 
-        with col1:
+        with col2:
             st.session_state['portfolio'] = predict_dupes(st.session_state['portfolio'], map_dict, site_var, type_var, Contest_Size, strength_var)
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Dupes'] <= max_dupes]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] >= min_salary]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= max_salary]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Finish_percentile'] <= max_finish_percentile]
+            st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Lineup Edge'] >= min_lineup_edge]
             if stack_dict is not None:
                 if stack_toggle == 'All Stacks':
                     st.session_state['portfolio'] = st.session_state['portfolio']