src/streamlit_app.py

import streamlit as st
import numpy as np
import pandas as pd
import pymongo

st.set_page_config(layout="wide")

@st.cache_resource
def init_conn():
        uri = st.secrets['mongo_uri']
        client = pymongo.MongoClient(uri, retryWrites=True, serverSelectionTimeoutMS=500000)
        db = client["MLB_Database"]

        return db
    
db = init_conn()

st.markdown("""
<style>
    /* Tab styling */
    .stTabs [data-baseweb="tab-list"] {
        gap: 8px;
        padding: 4px;
    }
    .stTabs [data-baseweb="tab"] {
        height: 50px;
        white-space: pre-wrap;
        background-color: #DAA520;
        color: white;
        border-radius: 10px;
        gap: 1px;
        padding: 10px 20px;
        font-weight: bold;
        transition: all 0.3s ease;
    }
    .stTabs [aria-selected="true"] {
        background-color: #DAA520;
        border: 3px solid #FFD700;
        color: white;
    }
    .stTabs [data-baseweb="tab"]:hover {
        background-color: #FFD700;
        cursor: pointer;
    }
    div[data-baseweb="select"] > div {
        background-color: #DAA520;
        color: white;
    }
    div{
        box-sizing: content-box !important;
    }
</style>""", unsafe_allow_html=True)

@st.cache_resource(ttl = 61)
def init_baselines():

    db_pulls = ['Bullpen_Data', 'Hitter_Agg_Merge', 'Hitter_Long_Merge', 'Hitter_Short_Merge', 'Pitcher_Agg_Merge', 'Pitcher_Long_Merge', 'Pitcher_Short_Merge',
                'Slate_Hitters_Merge', 'Slate_Team_Merge', 'Starting_Pitchers', 'True_AVG_Split', 'Pitcher_Info', 'Hitter_Info']

    for table in db_pulls:
        collection = db[table] 
        cursor = collection.find()
        df = pd.DataFrame(cursor)

        if table == 'Bullpen_Data':
            bp_data = df
        elif table == 'Hitter_Agg_Merge':
            hitter_agg = df
        elif table == 'Hitter_Long_Merge':
            hitter_long = df
        elif table == 'Hitter_Short_Merge':
            hitter_short = df
        elif table == 'Pitcher_Agg_Merge':
            pitcher_agg = df
        elif table == 'Pitcher_Long_Merge':
            pitcher_long = df
        elif table == 'Pitcher_Short_Merge':
            pitcher_short = df
        elif table == 'Slate_Hitters_Merge':
            slate_hitters = df
        elif table == 'Slate_Team_Merge':
            slate_team = df
        elif table == 'Starting_Pitchers':  
            starting_pitchers = df
        elif table == 'True_AVG_Split':
            true_avg_split = df
        elif table == 'Pitcher_Info':
            pitcher_info = df
        elif table == 'Hitter_Info':    
            hitter_info = df

    return bp_data, hitter_agg, hitter_long, hitter_short, pitcher_agg, pitcher_long, pitcher_short, slate_hitters, slate_team, starting_pitchers, true_avg_split, pitcher_info, hitter_info

bp_data, hitter_agg, hitter_long, hitter_short, pitcher_agg, pitcher_long, pitcher_short, slate_hitters, slate_team, starting_pitchers, true_avg_split, pitcher_info, hitter_info = init_baselines()

pitcher_tab, hitter_tab, team_tab = st.tabs(['Pitchers', 'Hitters', 'Team'])

with pitcher_tab:
    with st.expander('Info and Display Options'):
        st.info('Note: Splits options are available for all baseline tables, they do not apply to True AVG, HWSr, or the Overview tables')
        col1, col2, col3 = st.columns(3)
        with col1:
            site_var_sp = st.selectbox('Site', ['DraftKings', 'FanDuel'], key = 'site_var_sp')
        with col2:
            table_var_sp = st.selectbox('Table', ['True AVG Splits', 'HWSr Splits', 'Current Slate Overview', 'Active Baselines', 'League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines'], key = 'table_var_sp')
        with col3:
            splits_var_sp = st.selectbox('Splits', ['Overall', 'RHH', 'LHH'], key = 'splits_var_sp')
    
    if table_var_sp == 'True AVG Splits':
        st.dataframe(true_avg_split)
    elif table_var_sp == 'HWSr Splits':
        st.dataframe(true_avg_split)
    elif table_var_sp == 'Current Slate Overview':
        st.dataframe(starting_pitchers)
    elif table_var_sp == 'Active Baselines':
        st.dataframe(pitcher_info)
    elif table_var_sp == 'League Aggregate Baselines':
        st.dataframe(pitcher_agg)
    elif table_var_sp == 'League Short Term Baselines':
        st.dataframe(pitcher_short)
    elif table_var_sp == 'League Long Term Baselines':
        st.dataframe(pitcher_long)

with hitter_tab:
    with st.expander('Info and Display Options'):
        st.info('Note: Splits options are available for all baseline tables')
        col1, col2, col3 = st.columns(3)
        with col1:
            site_var_hitter = st.selectbox('Site', ['DraftKings', 'FanDuel'], key = 'site_var_hitter')
        with col2:
            table_var_hitter = st.selectbox('Table', ['Active Baselines', 'League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines'], key = 'table_var_hitter')
        with col3:
            splits_var_hitter = st.selectbox('Splits', ['Overall', 'RHP', 'LHP'], key = 'splits_var_hitter')

    if table_var_hitter == 'Current Slate Overview':
        st.dataframe(starting_pitchers)
    elif table_var_hitter == 'Active Baselines':
        st.dataframe(hitter_info)
    elif table_var_hitter == 'League Aggregate Baselines':
        st.dataframe(hitter_agg)
    elif table_var_hitter == 'League Short Term Baselines':
        st.dataframe(hitter_short)
    elif table_var_hitter == 'League Long Term Baselines':
        st.dataframe(hitter_long)

with team_tab:
    with st.expander('Info and Display Options'):
        col1, col2, col3 = st.columns(3)
        with col1:
            site_var_team= st.selectbox('Site', ['DraftKings', 'FanDuel'], key = 'site_var_team')
        with col2:
            table_var_team = st.selectbox('Table', ['Team Baselines', 'Bullpen Baselines'], key = 'table_var_team')
    
    if table_var_team == 'Team Baselines':
        st.dataframe(slate_team)
    elif table_var_team == 'Bullpen Baselines':
        st.dataframe(bp_data)