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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 |