app.py

import polars as pl
import numpy as np
import pandas as pd
import api_scraper
scrape = api_scraper.MLB_Scrape()
from functions import df_update
from functions import pitch_summary_functions
update = df_update.df_update()
from stuff_model import feature_engineering as fe
from stuff_model import stuff_apply
import requests
import joblib
from matplotlib.gridspec import GridSpec
from shiny import App, reactive, ui, render
from shiny.ui import h2, tags
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
from functions.pitch_summary_functions import *
from shiny import App, reactive, ui, render
from shiny.ui import h2, tags

colour_palette = ['#FFB000','#648FFF','#785EF0',
                  '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']


year_list = [2017,2018,2019,2020,2021,2022,2023,2024,2025,2026]



level_dict =  {'1':'MLB',
               '11':'AAA',
              # '12':'AA',
               #'13':'A+',
               '14':'A',
               '16':'ROK',
               '17':'AFL',
               '22':'College',
               '21':'Prospects',
               '51':'International' }

function_dict={
    'velocity_kdes':'Velocity Distributions',
    'break_plot':'Pitch Movement',
    'tj_stuff_roling':'Rolling tjStuff+ by Pitch',
    'tj_stuff_roling_game':'Rolling tjStuff+ by Game',
    'location_plot_lhb':'Locations vs LHB',
    'location_plot_rhb':'Locations vs RHB',
    'pitch_usage':'Pitch Usage',
}


split_dict =  {'all':'All',
               'left':'LHH',
               'right':'RHH'}

split_dict_hand =  {'all':['L','R'],
               'left':['L'],
               'right':['R']}


type_dict =  {'R':'Regular Season',
               'S':'Spring',
               'P':'Playoffs' }



# List of MLB teams and their corresponding ESPN logo URLs
mlb_teams = [
    {"team": "AZ", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/ari.png&h=500&w=500"},
    {"team": "ATH", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/oak.png&h=500&w=500"},
    {"team": "ATL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/atl.png&h=500&w=500"},
    {"team": "BAL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bal.png&h=500&w=500"},
    {"team": "BOS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bos.png&h=500&w=500"},
    {"team": "CHC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chc.png&h=500&w=500"},
    {"team": "CWS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chw.png&h=500&w=500"},
    {"team": "CIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cin.png&h=500&w=500"},
    {"team": "CLE", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cle.png&h=500&w=500"},
    {"team": "COL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/col.png&h=500&w=500"},
    {"team": "DET", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/det.png&h=500&w=500"},
    {"team": "HOU", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/hou.png&h=500&w=500"},
    {"team": "KC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/kc.png&h=500&w=500"},
    {"team": "LAA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/laa.png&h=500&w=500"},
    {"team": "LAD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/lad.png&h=500&w=500"},
    {"team": "MIA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mia.png&h=500&w=500"},
    {"team": "MIL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mil.png&h=500&w=500"},
    {"team": "MIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/min.png&h=500&w=500"},
    {"team": "NYM", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nym.png&h=500&w=500"},
    {"team": "NYY", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nyy.png&h=500&w=500"},
    {"team": "PHI", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/phi.png&h=500&w=500"},
    {"team": "PIT", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/pit.png&h=500&w=500"},
    {"team": "SD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sd.png&h=500&w=500"},
    {"team": "SF", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sf.png&h=500&w=500"},
    {"team": "SEA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sea.png&h=500&w=500"},
    {"team": "STL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/stl.png&h=500&w=500"},
    {"team": "TB", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tb.png&h=500&w=500"},
    {"team": "TEX", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tex.png&h=500&w=500"},
    {"team": "TOR", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tor.png&h=500&w=500"},
    {"team": "WSH", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/wsh.png&h=500&w=500"},
    {"team": "ZZZ", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/leagues/500/mlb.png&w=500&h=500"}   
]


df_image = pd.DataFrame(mlb_teams)
image_dict = df_image.set_index('team')['logo_url'].to_dict()
image_dict_flip = df_image.set_index('logo_url')['team'].to_dict()



import requests

import os
CAMPAIGN_ID = os.getenv("CAMPAIGN_ID")
ACCESS_TOKEN = os.getenv("ACCESS_TOKEN")
BACKUP_PW = os.getenv("BACKUP_PW")
ADMIN_PW = os.getenv("ADMIN_PW")

url = f"https://www.patreon.com/api/oauth2/v2/campaigns/{CAMPAIGN_ID}/members"

headers = {
    "Authorization": f"Bearer {ACCESS_TOKEN}"
}

# Simple parameters, requesting the member's email and currently entitled tiers
params = {
    "fields[member]": "full_name,email",  # Request the member's email
    "include": "currently_entitled_tiers",  # Include the currently entitled tiers
    "page[size]": 10000  # Fetch up to 1000 patrons per request
}

response = requests.get(url, headers=headers, params=params)


VALID_PASSWORDS = []
if response.status_code == 200:
    data = response.json()
    for patron in data['data']:
        try:
            tiers = patron['relationships']['currently_entitled_tiers']['data']
            if any(tier['id'] == '9078921' for tier in tiers):
                full_name = patron['attributes']['email']
                VALID_PASSWORDS.append(full_name)
        except KeyError:
            continue
VALID_PASSWORDS.append(BACKUP_PW)
VALID_PASSWORDS.append(ADMIN_PW)

from shiny import App, reactive, ui, render
from shiny.ui import h2, tags

from datetime import datetime

def is_valid_date(date_str):
    try:
        datetime.strptime(date_str, "%Y-%m-%d")  # Attempt to parse the date
        return True
    except ValueError:
        return False  # If parsing fails, it's not in the correct format

# Define the login UI
login_ui = ui.page_fluid(
    ui.card(
        ui.h2([
            "TJStats Pitching Summary App ",
            ui.tags.a("(@TJStats)", href="https://twitter.com/TJStats", target="_blank")
        ]),
        ui.p(
            "This App is available to Superstar Patrons. Please enter your Patreon email address in the box below. If you're having trouble, please refer to the ", 
            ui.tags.a("Patreon post", href="https://www.patreon.com/posts/116064432", target="_blank"),
            "."
        ),
        ui.input_password("password", "Enter Patreon Email (or Password from Link):", width="50%"),
        ui.tags.input(
            type="checkbox",
            id="authenticated",
            value=False,
            disabled=True
        ),
        ui.input_action_button("login", "Login", class_="btn-primary"),
        ui.output_text("login_message"),
    )
)


# Define the UI layout for the app
main_ui = ui.page_sidebar(
    ui.sidebar(
        # Row for selecting season and level
        ui.row(
            ui.column(4, ui.input_select('year_input', 'Select Season', year_list, selected=2026)),
            ui.column(4, ui.input_select('level_input', 'Select Level', level_dict)),
            ui.column(4, ui.input_select('type_input', 'Select Type', type_dict,selected='R'))
        ),
        # Row for the action button to get player list
        ui.row(ui.input_action_button("player_button", "Get Player List", class_="btn-primary")),
        # Row for selecting the player
        ui.row(ui.column(12, ui.output_ui('player_select_ui', 'Select Player'))),
        # Row for selecting the date range
        ui.row(ui.column(12, ui.output_ui('date_id', 'Select Date'))),

        # Rows for selecting plots and split options
        ui.row(
            ui.column(4, ui.input_select('plot_id_1', 'Plot Left', function_dict, multiple=False, selected='velocity_kdes')),
            ui.column(4, ui.input_select('plot_id_2', 'Plot Middle', function_dict, multiple=False, selected='break_plot')),
            ui.column(4, ui.input_select('plot_id_3', 'Plot Right', function_dict, multiple=False, selected='pitch_usage'))
        ),
        ui.row(
            ui.column(6, ui.input_select('split_id', 'Select Split', split_dict, multiple=False)),
            ui.column(6, ui.input_numeric('rolling_window', 'Rolling Window (for tjStuff+ Plot)', min=1, value=50))
        ),
        ui.row(
            ui.column(6, ui.input_switch("switch", "Custom Team?", False)),
            ui.column(6, ui.input_select('logo_select', 'Select Custom Logo', image_dict_flip, multiple=False))
        ),
        
        # Row for the action button to generate plot
        ui.row(ui.input_action_button("generate_plot", "Generate Plot", class_="btn-primary")),
        width="400px"  # Added this parameter to control sidebar width
    ),
            
    # Main content area with tabs (placed directly in page_sidebar)
    ui.navset_tab(
        ui.nav_panel("Pitching Summary",
               ui.output_text("status"),
               ui.output_plot('plot', width='2100px', height='2100px')
        ),
        ui.nav_panel("Game Summary",
               ui.output_text("status2"),
               ui.output_plot('game_plot', width='2100px', height='2100px')
        ),        
            ui.nav_panel("Table Range",
                                   ui.output_data_frame("grid")),
            ui.nav_panel("Table Game",
                                   ui.output_data_frame("grid_game")),
        id="tabset"
    )
)

# Combined UI with conditional panel
app_ui = ui.page_fluid(
    ui.tags.head(
        ui.tags.script(src="script.js")
    ),

    ui.panel_conditional(
        "!input.authenticated",
        login_ui
    ),
    ui.panel_conditional(
        "input.authenticated",
        main_ui
    )
)


def server(input, output, session):

    @reactive.Effect
    @reactive.event(input.login)
    def check_password():
        if input.password() in VALID_PASSWORDS:
            ui.update_checkbox("authenticated", value=True)
            ui.update_text("login_message", value="")
        else:
            ui.update_text("login_message", value="Invalid password!")
            ui.update_text("password", value="")

    @output
    @render.text
    def login_message():
        return ""
    
    @reactive.calc
    @reactive.event(input.pitcher_id, input.date_id,input.split_id)
    def cached_data():

        year_input = int(input.year_input())
        sport_id = int(input.level_input())
        player_input = int(input.pitcher_id())
        

        start_date = str(input.date_id()[0])
        end_date = str(input.date_id()[1])
        game_list  = scrape.get_player_games_list(sport_id = sport_id,
                                                season = year_input, 
                                                player_id = player_input,
                                                start_date = start_date,
                                                end_date = end_date,
                                                game_type = [input.type_input()])
        
        # if input.tabset() == 'Game Summary':
        #     print(year_input, sport_id, player_input, 'yup')
        #     print(input.date_id())
        #     game_list = [input.date_id()]
            

        data_list = scrape.get_data(game_list_input = game_list[:])

        try:
            df = (stuff_apply.stuff_apply(fe.feature_engineering(update.update(scrape.get_data_df(data_list = data_list).filter(
                                (pl.col("pitcher_id") == player_input)&
                                (pl.col("is_pitch") == True)&
                                (pl.col("start_speed") >= 50)&
                                (pl.col('batter_hand').is_in(split_dict_hand[input.split_id()]))
    
                                )))).with_columns(
                    pl.col('pitch_type').count().over('pitch_type').alias('pitch_count')
                ))
            return df

            
        except TypeError:
            print("NONE")
            return None

    @reactive.calc
    @reactive.event(input.pitcher_id, input.date_id,input.split_id,input.tabset)
    def cached_data_daily():

        year_input = int(input.year_input())
        sport_id = int(input.level_input())
        player_input = int(input.pitcher_id())
        

        # start_date = str(input.date_id()[0])
        # end_date = str(input.date_id()[1])
        game_list  = [int(input.date_id())]
        print(game_list)
        
        # if input.tabset() == 'Game Summary':
        #     print(year_input, sport_id, player_input, 'yup')
        #     print(input.date_id())
        #     game_list = 
            

        data_list = scrape.get_data(game_list_input = game_list[:])

        try:
            df = (stuff_apply.stuff_apply(fe.feature_engineering(update.update(scrape.get_data_df(data_list = data_list).filter(
                                (pl.col("pitcher_id") == player_input)&
                                (pl.col("is_pitch") == True)&
                                (pl.col("start_speed") >= 50)&
                                (pl.col('batter_hand').is_in(split_dict_hand[input.split_id()]))
    
                                )))).with_columns(
                    pl.col('pitch_type').count().over('pitch_type').alias('pitch_count')
                ))
            return df

            
        except TypeError:
            print("NONE")
            return None
                

    @render.ui
    @reactive.event(input.player_button, input.year_input, input.level_input, input.type_input,input.tabset,ignore_none=False)
    def player_select_ui():
        # Get the list of pitchers for the selected level and season
        df_pitcher_info = scrape.get_players(sport_id=int(input.level_input()), season=int(input.year_input()), game_type = [input.type_input()]).filter(
            (pl.col("position").is_in(['P','TWP']))|
            (pl.col("player_id").is_in([686846,806823]))
        
        ).sort("name")
        
        # Create a dictionary of pitcher IDs and names
        pitcher_dict = dict(zip(df_pitcher_info['player_id'], df_pitcher_info['name']))


        
        
        # Return a select input for choosing a pitcher
        return ui.input_select("pitcher_id", "Select Pitcher", pitcher_dict, selectize=True)

    @render.ui
    @reactive.event(input.player_button, input.pitcher_id,input.year_input, input.level_input, input.type_input,input.tabset,ignore_none=False)
    def date_id():
        if input.tabset() == 'Pitching Summary' or input.tabset() == 'Table Range':
            # Create a date range input for selecting the date range within the selected year
            return ui.input_date_range("date_id", "Select Date Range",
                                    start=f"{int(input.year_input())}-01-01",
                                    end=f"{int(input.year_input())}-12-31",
                                    min=f"{int(input.year_input())}-01-01",
                                        max=f"{int(input.year_input())}-12-31")
        
        if input.tabset() == 'Game Summary' or input.tabset() == 'Table Game':
            year_input = int(input.year_input())
            sport_id = int(input.level_input())
            player_input = int(input.pitcher_id())
            print('game summary')
            # start_date = str(input.date_id()[0])
            # end_date = str(input.date_id()[1])

            game_list = scrape.get_player_games_list(player_id = player_input, 
                              season = year_input, 
                              sport_id=sport_id, 
                              game_type=[input.type_input()],
                              pitching = True)
            
            schedule_df = scrape.get_schedule(year_input=[year_input],
                    sport_id= [sport_id],
                    game_type = [input.type_input()])
            
            player_schedule_df = schedule_df.filter(pl.col('game_id').is_in(game_list)).to_pandas().sort_values('date')

            player_schedule_df['def'] = player_schedule_df['date'].astype(str) + ' - ' + player_schedule_df['away'] + ' @ ' + player_schedule_df['home'] + ' ' 


            game_dict = dict(zip(player_schedule_df['game_id'], player_schedule_df['def']))
            # print(game_dict)

            return ui.input_select("date_id", "Select Game", game_dict)

    @output
    @render.text
    def status():
        # Only show status when generating
        if input.generate == 0:
            return ""
        return ""   


    

    @output
    @render.plot
    @reactive.event(input.generate_plot, ignore_none=False)   
    def plot():     
        # Show progress/loading notification

       
                       
        with ui.Progress(min=0, max=1) as p:
            p.set(message="Generating plot", detail="This may take a while...")


            p.set(0.3, "Gathering data...")
            year_input = int(input.year_input())
            sport_id = int(input.level_input())
            player_input = int(input.pitcher_id())
            start_date = str(input.date_id()[0])
            end_date = str(input.date_id()[1])
            if not is_valid_date(start_date):
                    fig = plt.figure(figsize=(26,26))
                    fig.text(x=0.1,y=0.9,s='Select Date Range and Generate Plot',fontsize=36,ha='left')
                    return fig         
            print(year_input, sport_id, player_input, start_date, end_date)

            df = cached_data()

            if df is None:
                fig = plt.figure(figsize=(26,26))
                fig.text(x=0.1,y=0.9,s='No Statcast Data For This Pitcher',fontsize=36,ha='left')
                return fig
            
            df = df.clone()
            

            p.set(0.6, "Creating plot...")

  
            #plt.rcParams["figure.figsize"] = [10,10]
            fig = plt.figure(figsize=(26,26))
            plt.rcParams.update({'figure.autolayout': True})
            fig.set_facecolor('white')
            sns.set_theme(style="whitegrid", palette=colour_palette)
            print('this is the one plot')

            gs = gridspec.GridSpec(6, 8,
                                height_ratios=[6,20,12,36,36,6],
                                width_ratios=[4,18,18,18,18,18,18,4])


            gs.update(hspace=0.2, wspace=0.5)

            # Define the positions of each subplot in the grid
            ax_headshot = fig.add_subplot(gs[1,1:3])
            ax_bio = fig.add_subplot(gs[1,3:5])
            ax_logo = fig.add_subplot(gs[1,5:7])

            ax_season_table = fig.add_subplot(gs[2,1:7])

            ax_plot_1 = fig.add_subplot(gs[3,1:3])
            ax_plot_2 = fig.add_subplot(gs[3,3:5])
            ax_plot_3 = fig.add_subplot(gs[3,5:7])

            ax_table = fig.add_subplot(gs[4,1:7])

            ax_footer = fig.add_subplot(gs[-1,1:7])
            ax_header = fig.add_subplot(gs[0,1:7])
            ax_left = fig.add_subplot(gs[:,0])
            ax_right = fig.add_subplot(gs[:,-1])

            # Hide axes for footer, header, left, and right
            ax_footer.axis('off')
            ax_header.axis('off')
            ax_left.axis('off')
            ax_right.axis('off')

            sns.set_theme(style="whitegrid", palette=colour_palette)
            fig.set_facecolor('white')

            df_teams = scrape.get_teams()

            player_headshot(player_input=player_input, ax=ax_headshot,sport_id=sport_id,season=year_input)
            player_bio(pitcher_id=player_input, ax=ax_bio,sport_id=sport_id,year_input=year_input)

            if input.switch():

                # Get the logo URL from the image dictionary using the team abbreviation
                logo_url = input.logo_select()
        
                # Send a GET request to the logo URL
                response = requests.get(logo_url)
        
                # Open the image from the response content
                img = Image.open(BytesIO(response.content))
        
                # Display the image on the axis
                ax_logo.set_xlim(0, 1.3)
                ax_logo.set_ylim(0, 1)
                ax_logo.imshow(img, extent=[0.3, 1.3, 0, 1], origin='upper')
        
                # Turn off the axis
                ax_logo.axis('off')
            
            else:
                plot_logo(pitcher_id=player_input, ax=ax_logo, df_team=df_teams,df_players=scrape.get_players(sport_id,year_input))

            stat_summary_table(df=df,
                            ax=ax_season_table,
                            player_input=player_input,
                            split=input.split_id(),
                            sport_id=sport_id,
                            game_type=[input.type_input()],
                            start_date_input= str(input.date_id()[0]),
                              end_date_input=str(input.date_id()[1]))

            # break_plot(df=df_plot,ax=ax2) 
            for x,y,z in zip([input.plot_id_1(),input.plot_id_2(),input.plot_id_3()],[ax_plot_1,ax_plot_2,ax_plot_3],[1,3,5]):
                if x == 'velocity_kdes':
                            velocity_kdes(df,
                            ax=y,
                            gs=gs,
                            gs_x=[3,4],
                            gs_y=[z,z+2],
                            fig=fig)
                if x == 'tj_stuff_roling':
                    tj_stuff_roling(df=df,
                                window=int(input.rolling_window()),
                                ax=y)
                    
                if x == 'tj_stuff_roling_game':
                    tj_stuff_roling_game(df=df, 
                                        window=int(input.rolling_window()),
                                        ax=y)

                if x == 'break_plot':
                    break_plot(df = df,ax=y) 

                if x == 'location_plot_lhb':
                    location_plot(df = df,ax=y,hand='L')

                if x == 'location_plot_rhb':
                    location_plot(df = df,ax=y,hand='R')
                    
                if x == 'pitch_usage':
                    pitch_usage(df = df,ax=y) 

            summary_table(df=df,
                        ax=ax_table)

            plot_footer(ax_footer)   

            # ax_watermark = fig.add_subplot(gs[1:-1,1:-1],zorder=-1) 
            # # Hide axes ticks and labels
            # ax_watermark.set_xticks([])
            # ax_watermark.set_yticks([])
            # ax_watermark.set_frame_on(False)  # Optional: Hide border
            
            # img = Image.open('tj stats circle-01_new.jpg')
            # # Display the image
            # ax_watermark.imshow(img, extent=[0, 1, 0, 1], origin='upper',zorder=-1, alpha=0.1)


            ax_watermark2 = fig.add_subplot(gs[-2:,1:4],zorder=1) 
            ax_watermark2.set_xlim(0,1)
            ax_watermark2.set_ylim(0,1)
            # Hide axes ticks and labels
            ax_watermark2.set_xticks([])
            ax_watermark2.set_yticks([])
            ax_watermark2.set_frame_on(False)  # Optional: Hide border
            
            # Open the image
            img = Image.open('tj stats circle-01_new.jpg')
            # Get the original size
            width, height = img.size
            # Calculate the new size (50% larger)
            new_width = int(width * 0.5)
            new_height = int(height * 0.5)
            # Resize the image
            img_resized = img.resize((new_width, new_height))
            # Display the image
            ax_watermark2.imshow(img, extent=[0.26, 0.46, 0.0,0.2], origin='upper',zorder=-1, alpha=1)

            fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01)



    
    @output
    @render.plot
    @reactive.event(input.generate_plot, ignore_none=False)   
    def game_plot():     
        # Show progress/loading notification
        with ui.Progress(min=0, max=1) as p:
            print(input.date_id(),'TEST')

            if isinstance(input.date_id(), tuple):
                fig = plt.figure(figsize=(26,26))
                fig.text(x=0.1,y=0.9,s='Select Game and Generate Plot',fontsize=36,ha='left')
                return fig                
                

            p.set(message="Generating plot", detail="This may take a while...")

            
            p.set(0.3, "Gathering data...")
            year_input = int(input.year_input())
            sport_id = int(input.level_input())
            player_input = int(input.pitcher_id())

            # print(input.game_id())
            # print(year_input, sport_id, player_input)

            # print(year_input, sport_id, player_input, start_date, end_date)

            df = cached_data_daily()

            # start_date = str(df['game_date'][0])
            # end_date = str(df['game_date'][0])
            
            if df is None:
                fig = plt.figure(figsize=(26,26))
                fig.text(x=0.1,y=0.9,s='No Statcast Data For This Pitcher',fontsize=36,ha='left')
                return fig
            
            df = df.clone()
            

            p.set(0.6, "Creating plot...")

  
            #plt.rcParams["figure.figsize"] = [10,10]
            fig = plt.figure(figsize=(26,26))
            plt.rcParams.update({'figure.autolayout': True})
            fig.set_facecolor('white')
            sns.set_theme(style="whitegrid", palette=colour_palette)
            print('this is the one plot')

            gs = gridspec.GridSpec(6, 8,
                                height_ratios=[6,20,12,36,36,6],
                                width_ratios=[4,18,18,18,18,18,18,4])


            gs.update(hspace=0.2, wspace=0.5)

            # Define the positions of each subplot in the grid
            ax_headshot = fig.add_subplot(gs[1,1:3])
            ax_bio = fig.add_subplot(gs[1,3:5])
            ax_logo = fig.add_subplot(gs[1,5:7])

            ax_season_table = fig.add_subplot(gs[2,1:7])

            ax_plot_1 = fig.add_subplot(gs[3,1:3])
            ax_plot_2 = fig.add_subplot(gs[3,3:5])
            ax_plot_3 = fig.add_subplot(gs[3,5:7])

            ax_table = fig.add_subplot(gs[4,1:7])

            ax_footer = fig.add_subplot(gs[-1,1:7])
            ax_header = fig.add_subplot(gs[0,1:7])
            ax_left = fig.add_subplot(gs[:,0])
            ax_right = fig.add_subplot(gs[:,-1])

            # Hide axes for footer, header, left, and right
            ax_footer.axis('off')
            ax_header.axis('off')
            ax_left.axis('off')
            ax_right.axis('off')

            sns.set_theme(style="whitegrid", palette=colour_palette)
            fig.set_facecolor('white')

            df_teams = scrape.get_teams()

            player_headshot(player_input=player_input, ax=ax_headshot,sport_id=sport_id,season=year_input)
            player_bio(pitcher_id=player_input, ax=ax_bio,sport_id=sport_id,year_input=year_input)

            if input.switch():

                # Get the logo URL from the image dictionary using the team abbreviation
                logo_url = input.logo_select()
        
                # Send a GET request to the logo URL
                response = requests.get(logo_url)
        
                # Open the image from the response content
                img = Image.open(BytesIO(response.content))
        
                # Display the image on the axis
                ax_logo.set_xlim(0, 1.3)
                ax_logo.set_ylim(0, 1)
                ax_logo.imshow(img, extent=[0.3, 1.3, 0, 1], origin='upper')
        
                # Turn off the axis
                ax_logo.axis('off')
            
            else:
                plot_logo(pitcher_id=player_input, ax=ax_logo, df_team=df_teams,df_players=scrape.get_players(sport_id,year_input))

            stat_summary_table(df=df,
                            ax=ax_season_table,
                            player_input=player_input,
                            split=input.split_id(),
                            sport_id=sport_id,
                            game_type=[input.type_input()],
                              start_date_input=None,
                              end_date_input=None)

            # break_plot(df=df_plot,ax=ax2) 
            for x,y,z in zip([input.plot_id_1(),input.plot_id_2(),input.plot_id_3()],[ax_plot_1,ax_plot_2,ax_plot_3],[1,3,5]):
                if x == 'velocity_kdes':
                            velocity_kdes(df,
                            ax=y,
                            gs=gs,
                            gs_x=[3,4],
                            gs_y=[z,z+2],
                            fig=fig)
                if x == 'tj_stuff_roling':
                    tj_stuff_roling(df=df,
                                window=int(input.rolling_window()),
                                ax=y)
                    
                if x == 'tj_stuff_roling_game':
                    tj_stuff_roling_game(df=df, 
                                        window=int(input.rolling_window()),
                                        ax=y)

                if x == 'break_plot':
                    break_plot(df = df,ax=y) 

                if x == 'location_plot_lhb':
                    location_plot(df = df,ax=y,hand='L')

                if x == 'location_plot_rhb':
                    location_plot(df = df,ax=y,hand='R')
                    
                if x == 'pitch_usage':
                    pitch_usage(df = df,ax=y) 

            summary_table(df=df,
                        ax=ax_table)

            plot_footer(ax_footer)   

            ax_watermark = fig.add_subplot(gs[1:-1,1:-1],zorder=-1) 
            # Hide axes ticks and labels
            ax_watermark.set_xticks([])
            ax_watermark.set_yticks([])
            ax_watermark.set_frame_on(False)  # Optional: Hide border
            
            img = Image.open('tj stats circle-01_new.jpg')
            # Display the image
            ax_watermark.imshow(img, extent=[0, 1, 0, 1], origin='upper',zorder=-1, alpha=0.1)


            ax_watermark2 = fig.add_subplot(gs[-2:,1:4],zorder=1) 
            ax_watermark2.set_xlim(0,1)
            ax_watermark2.set_ylim(0,1)
            # Hide axes ticks and labels
            ax_watermark2.set_xticks([])
            ax_watermark2.set_yticks([])
            ax_watermark2.set_frame_on(False)  # Optional: Hide border
            
            # Open the image
            img = Image.open('tj stats circle-01_new.jpg')
            # Get the original size
            width, height = img.size
            # Calculate the new size (50% larger)
            new_width = int(width * 0.5)
            new_height = int(height * 0.5)
            # Resize the image
            img_resized = img.resize((new_width, new_height))
            # Display the image
            ax_watermark2.imshow(img, extent=[0.26, 0.46, 0.0,0.2], origin='upper',zorder=-1, alpha=1)

            fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01)



    @output
    @render.data_frame
    @reactive.event(input.generate_plot, ignore_none=False)   
    def grid():

        start_date = str(input.date_id()[0])
        if not is_valid_date(start_date):
             return pd.DataFrame({"Message": ["Select range to generate table"]})
        df = cached_data()
        df = df.clone()
        features_table = ['start_speed',
            'spin_rate',
            'extension',
            'ivb',
            'hb',
            'x0',
            'z0']
        
        
        
        selection = ['game_id','pitcher_id','pitcher_name','batter_id','batter_name','pitcher_hand',
                      'batter_hand','balls','strikes','play_code','event_type','pitch_type','vaa','haa']+features_table+['tj_stuff_plus','pitch_grade']



        return render.DataGrid(
                df.select(selection).to_pandas().round(1),
                row_selection_mode='multiple',
                 height='700px',
                width='fit-content',
                filters=True,
            )


    @output
    @render.data_frame
    @reactive.event(input.generate_plot, ignore_none=False)   
    def grid_game():
        if isinstance(input.date_id(), tuple):
                return pd.DataFrame({"Message": ["Select game to generate table"]})
                     
        df = cached_data_daily()
        df = df.clone()
        features_table = ['start_speed',
            'spin_rate',
            'extension',
            'ivb',
            'hb',
            'x0',
            'z0']
        
        
        
        selection = ['game_id','pitcher_id','pitcher_name','batter_id','batter_name','pitcher_hand',
                      'batter_hand','balls','strikes','play_code','event_type','pitch_type','vaa','haa']+features_table+['tj_stuff_plus','pitch_grade']



        return render.DataGrid(
                df.select(selection).to_pandas().round(1),
                row_selection_mode='multiple',
                 height='700px',
                width='fit-content',
                filters=True,
            )

    
app = App(app_ui, server)