src/streamlit_app.py

import pandas as pd
import streamlit as st
import numpy as np
from database import gc

st.set_page_config(layout="wide")

@st.cache_data
def init_baselines():
    sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/10MVGsAHJPUAdK9SJ28ZqjgBgV2xBJSXEka-s2pIxHHE/edit#gid=1858245367')
    worksheet = sh.worksheet('ROO')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.loc[raw_display['Salary'] > 0]
    raw_display = raw_display.loc[raw_display['Median'] > 0]
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    roo_table = raw_display.sort_values(by='Median', ascending=False)
    
    # worksheet = sh.worksheet('Positional_Boosts')
    # raw_display = pd.DataFrame(worksheet.get_all_records())
    # raw_display.replace("", 'Welp', inplace=True)
    # raw_display = raw_display.loc[raw_display['teamname'] != 'Welp']
    # raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    # positional_boosts = raw_display.sort_values(by='Avg_Allowed', ascending=False)
    
    worksheet = sh.worksheet('Overall_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Win_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_win_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Loss_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Overall_BO1_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_bo1 = raw_display
    
    worksheet = sh.worksheet('Overall_BO3_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_bo3 = raw_display
    
    worksheet = sh.worksheet('Overall_BO5_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lck_bo5 = raw_display
    
    sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/10MVGsAHJPUAdK9SJ28ZqjgBgV2xBJSXEka-s2pIxHHE/edit#gid=1858245367')
    worksheet = sh.worksheet('Overall_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Win_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_win_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Loss_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Overall_BO1_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_bo1 = raw_display
    
    worksheet = sh.worksheet('Overall_BO3_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_bo3 = raw_display
    
    worksheet = sh.worksheet('Overall_BO5_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lcs_bo5 = raw_display
    
    sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/1oOJD_QcBeDJ1f7e9FfgUHOQEPT6kvU0Sa9hQ_4B8gqc/edit?gid=1288836099#gid=1288836099')
    worksheet = sh.worksheet('Overall_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Win_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_win_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Loss_Stacks')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Team'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False)
    
    worksheet = sh.worksheet('Overall_BO1_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_bo1 = raw_display
    
    worksheet = sh.worksheet('Overall_BO3_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_bo3 = raw_display
    
    worksheet = sh.worksheet('Overall_BO5_Stats')
    raw_display = pd.DataFrame(worksheet.get_all_records())
    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
    raw_display.replace("", 'Welp', inplace=True)
    raw_display = raw_display.loc[raw_display['Player'] != 'Welp']
    raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
    lec_bo5 = raw_display

    return roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5

roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines()

tab1, tab2, tab3 = st.tabs(["LOL Stacks Table", "LOL Range of Outcomes", "LOL Player Base Stats"])

def convert_df_to_csv(df):
    return df.to_csv().encode('utf-8')

with tab1:
    if st.button("Reset Data", key='reset1'):
              # Clear values from *all* all in-memory and on-disk data caches:
              # i.e. clear values from both square and cube
              st.cache_data.clear()
              roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines()
    league_choice1 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var1')
    if league_choice1 == 'LCK/LPL':
      league_hold = lck_overall_stacks
    elif league_choice1 == 'LCS':
      league_hold = lcs_overall_stacks
    elif league_choice1 == 'LEC':
      league_hold = lec_overall_stacks
    display = league_hold.set_index('Team')
    st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
    st.download_button(
        label="Export Stacks",
        data=convert_df_to_csv(display),
        file_name='LOL_Stacks_export.csv',
        mime='text/csv',
    )
  
with tab2:
    if st.button("Reset Data", key='reset2'):
              # Clear values from *all* all in-memory and on-disk data caches:
              # i.e. clear values from both square and cube
              st.cache_data.clear()
              roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines()
    with st.container():
        col1, col2, col3, col4 = st.columns([4, 2, 2, 2])

        with col1:
            league_choice2 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var2')
            if league_choice2 == 'LCK/LPL':
              league_hold = roo_table[roo_table['league'] == 'LCK']
            elif league_choice2 == 'LCS':
              league_hold = roo_table[roo_table['league'] == 'LCS']
            elif league_choice2 == 'LEC':
              league_hold = roo_table[roo_table['league'] == 'LEC']
        with col2:
            model_choice = st.radio("What table would you like to display?", ('Overall', 'Wins', 'Losses'), key='roo_table')
            if model_choice == 'Overall':
              hold_display = league_hold[league_hold['type'] == 'Overall']
            elif model_choice == 'Wins':
              hold_display = league_hold[league_hold['type'] == 'Wins']
            elif model_choice == 'Losses':
              hold_display = league_hold[league_hold['type'] == 'Losses']
        with col3:
            pos_var1 = st.selectbox('View specific position?', options = ['All', 'TOP', 'JNG', 'MID', 'ADC', 'SUP'], key = 'roo_posvar')
        with col4:
            team_var1 = st.multiselect('View specific team?', options = hold_display['Team'].unique(), key = 'roo_teamvar')
    display = hold_display.set_index('Player')
    if team_var1:
          display = display[display['Team'].isin(team_var1)]
    if pos_var1 == 'All':
          display = display
    elif pos_var1 != 'All':
          display = display[display['Position'].str.contains(pos_var1)]
    display = display.drop(columns=['type', 'league', 'Timestamp'])
    display['Cpt_Own'] = (display['Own'] / 2) * ((100 - (100-display['Own']))/100)
    display['Cpt_Own'] = np.where(display['Position'] == 'TEAM', display['Cpt_Own'].clip(upper=.25), display['Cpt_Own'])
    scale_var = display['Cpt_Own'].sum()
    display['Cpt_Own'] = display['Cpt_Own'] * (100 / scale_var)
    st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=750, use_container_width = True)
    st.download_button(
        label="Export Range of Outcomes",
        data=convert_df_to_csv(display),
        file_name='LOL_ROO_export.csv',
        mime='text/csv',
    )

with tab3:
    if st.button("Reset Data", key='reset3'):
              # Clear values from *all* all in-memory and on-disk data caches:
              # i.e. clear values from both square and cube
              st.cache_data.clear()
              roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines()
    with st.container():
        col1, col2, col3, col4 = st.columns([4, 2, 2, 2])

        with col1:
            league_choice3 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var3')
        with col2:
            gametype_choice = st.radio("What format are the games being played?", ('Best of 1', 'Best of 3', 'Best of 5'), key='player_stats')
        with col3:
            pos_var2 = st.selectbox('View specific position?', options = ['All', 'TOP', 'JNG', 'MID', 'ADC', 'SUP'], key = 'proj_posvar')
        with col4:
            team_var2 = st.multiselect('View specific team?', options = hold_display['Team'].unique(), key = 'proj_teamvar')
            
    if league_choice3 == 'LCK/LPL':
        if gametype_choice == 'Best of 1':
          hold_display = lck_bo1
        elif gametype_choice == 'Best of 3':
          hold_display = lck_bo3
        elif gametype_choice == 'Best of 5':
          hold_display = lck_bo5
        display = hold_display.set_index('Player')
    elif league_choice3 == 'LCS':
        if gametype_choice == 'Best of 1':
          hold_display = lcs_bo1
        elif gametype_choice == 'Best of 3':
          hold_display = lcs_bo3
        elif gametype_choice == 'Best of 5':
          hold_display = lcs_bo5
        display = hold_display.set_index('Player')
    elif league_choice3 == 'LEC':
        if gametype_choice == 'Best of 1':
          hold_display = lec_bo1
        elif gametype_choice == 'Best of 3':
          hold_display = lec_bo3
        elif gametype_choice == 'Best of 5':
          hold_display = lec_bo5
        display = hold_display.set_index('Player')
    if team_var2:
          display = display[display['Team'].isin(team_var2)]
    if pos_var2 == 'All':
          display = display
    elif pos_var2 != 'All':
          display = display[display['Position'].str.contains(pos_var2)]
    st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=750, use_container_width = True)
    st.download_button(
        label="Export Baselines",
        data=convert_df_to_csv(display),
        file_name='LOL_Baselines_export.csv',
        mime='text/csv',
    )