Add small field preset functionality in app.py: integrate new preset options for lineup targeting, enhancing user experience and providing better control over portfolio management.

app.py

@@ -20,6 +20,7 @@ from global_func.load_csv import load_csv
 from global_func.find_csv_mismatches import find_csv_mismatches
 from global_func.trim_portfolio import trim_portfolio
 from global_func.get_portfolio_names import get_portfolio_names
+from global_func.small_field_preset import small_field_preset
 
 freq_format = {'Finish_percentile': '{:.2%}', 'Lineup Edge': '{:.2%}', 'Win%': '{:.2%}'}
 stacking_sports = ['MLB', 'NHL', 'NFL']
@@ -50,7 +51,7 @@ with tab1:
 
     with col1:
         st.subheader("Draftkings/Fanduel CSV")
-        st.info("Upload the player pricing CSV from the site you are playing on. This is used in late swap exporting and/or with SaberSim portfolios, but is not necessary for the portfolio management functions.")
+        st.info("Upload the player pricing CSV from the site you are playing on")
 
         upload_csv_col, csv_template_col = st.columns([3, 1])
         with upload_csv_col:
@@ -80,7 +81,7 @@ with tab1:
     
     with col2:
         st.subheader("Portfolio File")
-        st.info("Go ahead and upload a portfolio file here. Only include player columns and an optional 'Stack' column if you are playing MLB.")
+        st.info("Go ahead and upload a portfolio file here. Only include player columns.")
 
         upload_toggle = st.selectbox("What source are you uploading from?", options=['SaberSim (Just IDs)', 'Draftkings/Fanduel (Names + IDs)', 'Other (Just Names)'])
         if upload_toggle == 'SaberSim (Just IDs)' or upload_toggle == 'Draftkings/Fanduel (Names + IDs)':
@@ -124,7 +125,6 @@ with tab1:
                     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))
@@ -132,7 +132,7 @@ with tab1:
 
     with col3:
         st.subheader("Projections File")
-        st.info("upload a projections file that has 'player_names', 'salary', 'median', 'ownership', and 'captain ownership' (Needed for Showdown) columns. Note that the salary for showdown needs to be the FLEX salary, not the captain salary.")
+        st.info("upload a projections file that has 'player_names', 'salary', 'median', 'ownership', and 'captain ownership' columns. Note that the salary for showdown needs to be the FLEX salary, not the captain salary.")
         
         # Create two columns for the uploader and template button
         upload_col, template_col = st.columns([3, 1])
@@ -1000,7 +1000,7 @@ with tab2:
                                 parsed_frame = parsed_frame[~parsed_frame['Stack'].isin(stack_remove)]
                             else:
                                 parsed_frame = parsed_frame
-                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False)
+                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
                         st.session_state['export_merge'] = st.session_state['working_frame'].copy()
 
             with st.expander('Micro Filter Options'):
@@ -1065,11 +1065,10 @@ with tab2:
                         if size_include:
                             parsed_frame = parsed_frame[parsed_frame['Size'].isin(size_include)]
                             
-                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False)
+                        st.session_state['working_frame'] = parsed_frame.sort_values(by='median', ascending=False).reset_index(drop=True)
                         st.session_state['export_merge'] = st.session_state['working_frame'].copy()
 
             with st.expander('Trimming Options'):
-                st.info("Make sure you filter before trimming if you want to filter, trimming before a filter will reset your portfolio")
                 with st.form(key='trim_form'):
                     st.write("Sorting and trimming variables:")
                     perf_var, own_var = st.columns(2)
@@ -1102,85 +1101,14 @@ with tab2:
                         st.session_state['working_frame'] = trim_portfolio(parsed_frame, trim_slack_var, performance_type, own_type, performance_threshold_high, performance_threshold_low, own_threshold_high, own_threshold_low)
                         st.session_state['working_frame'] = st.session_state['working_frame'].sort_values(by='median', ascending=False)
                         st.session_state['export_merge'] = st.session_state['working_frame'].copy()
+            with st.expander('Presets'):
+                with st.form(key='Small Field Preset'):
+                    lineup_target = st.number_input("Lineup Target", value=150, min_value=1, step=1)
+                    parsed_frame = small_field_preset(st.session_state['working_frame'], lineup_target)
+                    st.session_state['working_frame'] = parsed_frame.sort_values(by='Own', ascending=False)
+                    st.session_state['export_merge'] = st.session_state['working_frame'].copy()
 
         with col2:
-            # with st.expander("Download options"):
-            #     if stack_dict is not None:
-            #         download_type = st.selectbox("Simple or Advanced Download?", options=['Simple', 'Advanced'], key='download_choice')
-            #         if download_type == 'Simple':
-            #             st.session_state['export_file'] = st.session_state['working_frame'].copy()
-            #             for col in st.session_state['export_file'].columns:
-            #                         if col not in excluded_cols:
-            #                             st.session_state['export_file'][col] = st.session_state['export_file'][col].map(st.session_state['export_dict'])
-            #         else:
-            #             with st.form(key='stack_form'):
-            #                 st.subheader("Stack Count Adjustments")
-            #                 st.info("This allows you to fine tune the stacks that you wish to export. If you want to make sure you don't export any of a specific stack you can 0 it out.")
-            #                 # Create a container for stack value inputs
-            #                 sort_container = st.container()
-            #                 with sort_container:
-            #                     sort_var = st.selectbox("Sort export portfolio by:", options=['median', 'Lineup Edge', 'Own'])
-                            
-            #                 # Get unique stack values
-            #                 unique_stacks = sorted(list(set(stack_dict.values())))
-                            
-            #                 # Create a dictionary to store stack multipliers
-            #                 if 'stack_multipliers' not in st.session_state:
-            #                     st.session_state.stack_multipliers = {stack: 0.0 for stack in unique_stacks}
-                            
-            #                 # Create columns for the stack inputs
-            #                 num_cols = 6  # Number of columns to display
-            #                 for i in range(0, len(unique_stacks), num_cols):
-            #                     cols = st.columns(num_cols)
-            #                     for j, stack in enumerate(unique_stacks[i:i+num_cols]):
-            #                         with cols[j]:
-            #                             # Create a unique key for each number input
-            #                             key = f"stack_count_{stack}"
-            #                             # Get the current count of this stack in the portfolio
-            #                             current_stack_count = len(st.session_state['working_frame'][st.session_state['working_frame']['Stack'] == stack])
-            #                             # Create number input with current value and max value based on actual count
-            #                             st.session_state.stack_multipliers[stack] = st.number_input(
-            #                                 f"{stack} count",
-            #                                 min_value=0.0,
-            #                                 max_value=float(current_stack_count),
-            #                                 value=0.0,
-            #                                 step=1.0,
-            #                                 key=key
-            #                             )
-                            
-            #                 portfolio_copy = st.session_state['working_frame'].copy()
-                            
-            #                 submitted = st.form_submit_button("Submit")
-            #                 if submitted:
-            #                     # Create a list to store selected rows
-            #                     selected_rows = []
-                                
-            #                     # For each stack, select the top N rows based on the count value
-            #                     for stack in unique_stacks:
-            #                         if stack in st.session_state.stack_multipliers:
-            #                             count = int(st.session_state.stack_multipliers[stack])
-            #                             # Get rows for this stack
-            #                             stack_rows = portfolio_copy[portfolio_copy['Stack'] == stack]
-            #                             # Sort by median and take top N rows
-            #                             top_rows = stack_rows.nlargest(count, sort_var)
-            #                             selected_rows.append(top_rows)
-
-            #                     # Combine all selected rows
-            #                     portfolio_concat = pd.concat(selected_rows)
-                                
-            #                     # Update export_file with filtered data
-            #                     st.session_state['export_file'] = portfolio_concat.copy()
-            #                     for col in st.session_state['export_file'].columns:
-            #                         if col not in excluded_cols:
-            #                             st.session_state['export_file'][col] = st.session_state['export_file'][col].map(st.session_state['export_dict'])
-            #                     st.write('Export portfolio updated!')
-            #     else:
-            #         st.session_state['export_file'] = st.session_state['working_frame'].copy()
-            #         if 'export_base' not in st.session_state:
-            #             st.session_state['export_base'] = pd.DataFrame(columns=st.session_state['working_frame'].columns)
-            #         for col in st.session_state['export_file'].columns:
-            #                         if col not in excluded_cols:
-            #                             st.session_state['export_file'][col] = st.session_state['export_file'][col].map(st.session_state['export_dict'])
             if 'export_base' not in st.session_state:
                     st.session_state['export_base'] = pd.DataFrame(columns=st.session_state['working_frame'].columns)
             

global_func/small_field_preset.py

@@ -0,0 +1,20 @@
+import pandas as pd
+
+def small_field_preset(portfolio: pd.DataFrame, lineup_target: int):
+    
+    for slack_var in range(0, 1, .1):
+        working_portfolio = portfolio.sort_values(by='Own', ascending = False).reset_index(drop=True)
+        rows_to_drop = []
+        curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var * working_portfolio.loc[0, 'Weighted Own'])
+
+        for i in range(1, len(working_portfolio)):
+            if working_portfolio.loc[i, 'Weighted Own'] > curr_own_type_max:
+                rows_to_drop.append(i)
+            else:
+                curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var * working_portfolio.loc[i, 'Weighted Own'])
+
+        working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
+        if len(working_portfolio) >= lineup_target:
+            return working_portfolio.head(lineup_target)
+        
+    return working_portfolio