import streamlit as st import numpy as np import pandas as pd import time from rapidfuzz import process import re sport_headers = { 'Draftkings': { 'Classic' : { 'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'], 'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'], 'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'WNBA' : ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL'], 'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'MLB' : ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3'], 'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'], 'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'], 'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'], 'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'], 'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'], 'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'], }, 'Showdown' : { 'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], }, }, 'Fanduel': { 'Classic' : { 'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'F1' : ['CPT', 'DRIVER1', 'DRIVER2', 'DRIVER3', 'DRIVER4', 'CONST'], 'SOC' : ['F1', 'F2', 'M1', 'M2', 'D1', 'D2', 'GK', 'UTIL'], 'TENNIS' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'WNBA' : ['G1', 'G2', 'G3', 'F1', 'F2', 'F3', 'F4'], 'NASCAR' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'MLB' : ['P', 'C/1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL'], 'NFL' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST'], 'CFL' : ['QB', 'RB', 'WR1', 'WR2', 'FLEX1', 'FLEX2', 'DST'], 'LOL' : ['CPT', 'TOP', 'JNG', 'MID', 'ADC', 'SUP', 'TEAM'], 'CSGO' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'COD' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'TEAM'], 'NHL' : ['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G'], 'NCAAF' : ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'FLEX', 'SFLEX'], }, 'Showdown' : { 'MMA' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'GOLF' : ['FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'FLEX6'], 'F1' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'SOC' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'TENNIS' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'WNBA' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NASCAR' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'MLB' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'CFL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'LOL' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'CSGO' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'COD' : ['CPT1', 'CPT2', 'FLEX1', 'FLEX2'], 'NHL' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], 'NCAAF' : ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'], }, }, } def load_ss_file(lineups, csv_file, site_var, type_var, sport_var): df = csv_file.copy() try: name_dict = dict(zip(df['ID'], df['Name'])) except: name_dict = dict(zip(df['Id'], df['Nickname'])) # Now load and process the lineups file try: clean_name = re.sub(r' \(\d+\)', '', lineups.name) if clean_name.endswith('.csv'): lineups_df = pd.read_csv(lineups) lineups_df = lineups_df.replace(0, np.nan) elif clean_name.endswith(('.xls', '.xlsx')): lineups_df = pd.read_excel(lineups) lineups_df = lineups_df.replace(0, np.nan) else: st.error('Please upload either a CSV or Excel file for lineups') return None, None lineups_df = lineups_df.dropna(how='any') lineups_df.columns = sport_headers[site_var][type_var][sport_var] export_df = lineups_df.copy() # Map the IDs to names for col in lineups_df.columns: lineups_df[col] = lineups_df[col].map(name_dict) return export_df, lineups_df except Exception as e: st.error(f'Error loading lineups file: {str(e)}') return None, None