Enhance contest file loading in app.py and load_contest_file function

- Updated the app.py to include a helper parameter for contest file processing, allowing for additional data handling during file uploads.
- Modified the load_contest_file function to accept an optional helper argument, enabling differentiated processing of contest data based on the presence of helper data.
- Improved the selection and renaming of essential columns in both the main and helper dataframes, enhancing data clarity and usability for further analysis.

app.py

@@ -81,11 +81,15 @@ with tab1:
         elif parse_type == 'Manual':
             st.session_state.clear()
             st.session_state['Contest_file'] = st.file_uploader("Upload Contest File (CSV or Excel)", type=['csv', 'xlsx', 'xls'])
+            st.session_state['Contest_file_helper'] = grab_contest_data(sport_select, name_parse[0], contest_id_map, date_select)
             if 'Contest' in st.session_state:
                 del st.session_state['Contest']
 
         if 'Contest_file' in st.session_state and 'Adj_Contest' not in st.session_state:
-            st.session_state['Contest'], st.session_state['ownership_df'], st.session_state['actual_df'], st.session_state['salary_df'], st.session_state['team_df'], st.session_state['pos_df'], st.session_state['entry_list'], check_lineups = load_contest_file(st.session_state['Contest_file'], sport_select)
+            if 'Contest_file_helper' in st.session_state:
+                st.session_state['Contest'], st.session_state['ownership_df'], st.session_state['actual_df'], st.session_state['salary_df'], st.session_state['team_df'], st.session_state['pos_df'], st.session_state['entry_list'], check_lineups = load_contest_file(st.session_state['Contest_file'], st.session_state['Contest_file_helper'], sport_select)
+            else:
+                st.session_state['Contest'], st.session_state['ownership_df'], st.session_state['actual_df'], st.session_state['salary_df'], st.session_state['team_df'], st.session_state['pos_df'], st.session_state['entry_list'], check_lineups = load_contest_file(st.session_state['Contest_file'], sport_select)
             st.session_state['Contest'] = st.session_state['Contest'].dropna(how='all')
             st.session_state['Contest'] = st.session_state['Contest'].reset_index(drop=True)
             if st.session_state['Contest'] is not None:

global_func/load_contest_file.py

@@ -1,7 +1,7 @@
 import streamlit as st
 import pandas as pd
 
-def load_contest_file(upload, sport):
+def load_contest_file(upload, helper = None, sport = None):
     if sport == 'MLB':
         pos_list = [' P ', ' C ', '1B ', ' 2B ', ' 3B ', ' SS ', ' OF ']
     if upload is not None:
@@ -16,9 +16,14 @@ def load_contest_file(upload, sport):
                     return None
             except:
                 raw_df = upload
+            if helper is not None:
+                helper_df = helper
             
-            # Select and rename essential columns
-            df = raw_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS', 'Salary', 'Team']]
+            # Select and rename essential columns for the actual upload
+            if helper is None:
+                df = raw_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS', 'Salary', 'Team']]
+            else:
+                df = raw_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS']]
             df = df.rename(columns={'Roster Position': 'Pos', '%Drafted': 'Own'})
             
             # Split EntryName into base name and entry count
@@ -32,12 +37,35 @@ def load_contest_file(upload, sport):
             except:
                 df['Own'] = df['Own'].astype(float)
             
+            # Select and rename essential columns for the actual upload
+            if helper is not None:
+                df_helper = helper_df[['EntryId', 'EntryName', 'TimeRemaining', 'Points', 'Lineup', 'Player', 'Roster Position', '%Drafted', 'FPTS', 'Salary', 'Team']]
+                df_helper = df_helper.rename(columns={'Roster Position': 'Pos', '%Drafted': 'Own'})
+                
+                # Split EntryName into base name and entry count
+                df_helper['BaseName'] = df_helper['EntryName'].str.replace(r'\s*\(\d+/\d+\)$', '', regex=True)
+                df_helper['EntryCount'] = df_helper['EntryName'].str.extract(r'\((\d+/\d+)\)')
+                df_helper['EntryCount'] = df_helper['EntryCount'].fillna('1/1')  # Default to 1/1 if no entry count
+                
+                # Convert ownership percentage to float
+                try:
+                    df_helper['Own'] = df_helper['Own'].str.replace('%', '').astype(float)
+                except:
+                    df_helper['Own'] = df_helper['Own'].astype(float)
+            
             # Create separate dataframes for different player attributes
-            ownership_df = df[['Player', 'Own']]
-            fpts_df = df[['Player', 'FPTS']]
-            salary_df = df[['Player', 'Salary']]
-            team_df = df[['Player', 'Team']]
-            pos_df = df[['Player', 'Pos']]
+            if helper is not None:
+                ownership_df = df[['Player', 'Own']]
+                fpts_df = df[['Player', 'FPTS']]
+                salary_df = df_helper[['Player', 'Salary']]
+                team_df = df_helper[['Player', 'Team']]
+                pos_df = df[['Player', 'Pos']]
+            else:
+                ownership_df = df[['Player', 'Own']]
+                fpts_df = df[['Player', 'FPTS']]
+                salary_df = df[['Player', 'Salary']]
+                team_df = df[['Player', 'Team']]
+                pos_df = df[['Player', 'Pos']]
             
             # Create the cleaned dataframe with just the essential columns
             cleaned_df = df[['BaseName', 'Lineup']]