# Code Destiny and Density is equal to one hundred.

st.Markdown("TODO: A code density slider bar shows and adjusts the size of lines.  Any way to compress the lines yet make it readable as optimal list of sets will do.  Match language from good math books.')
            
import streamlit as st
import numpy as np
import pandas as pd
import plotly.express as px

st.title('Random Dice Game')

dice_types = [{'name': 'Six-sided Dice', 'sides': 6, 'emoji': '🎲'},
              {'name': 'Twenty-sided Dice', 'sides': 20, 'emoji': '🎯'},
              {'name': 'Thirty-sided Dice', 'sides': 30, 'emoji': '🎯'},
              {'name': 'One Hundred-sided Dice', 'sides': 100, 'emoji': '🎲'}]

if 'name' not in st.session_state:
    st.session_state.name = ''
if 'dice_roll_history' not in st.session_state:
    st.session_state.dice_roll_history = pd.DataFrame()

dice_type = st.selectbox('Choose a type of dice', dice_types, format_func=lambda d: f"{d['name']} {d['emoji']}")
num_rolls = st.slider('How many times do you want to roll the dice?', 1, 1000000, 1000)

rolls = np.random.randint(1, dice_type['sides'] + 1, num_rolls, dtype=np.uint64)
roll_counts = pd.Series(rolls).value_counts().sort_index()

fig = px.sunburst(names=[f'Roll {i}' for i in roll_counts.index],
                  parents=['Dice Rolls'] * dice_type['sides'],
                  values=roll_counts.values,
                  color=[f'Roll {i}' for i in roll_counts.index],
                  color_discrete_sequence=px.colors.qualitative.Dark24,
                  maxdepth=2)
fig.update_layout(title='Dice Roll Distribution', margin=dict(l=20, r=20, t=40, b=20), width=800, height=600)

show_labels = st.checkbox('Show Labels', value=True)
if not show_labels:
    fig.update_traces(textinfo='none')
fig.show()

bonus_match = False
for dice in dice_types:
    if rolls[0] == dice['sides']:
        bonus_match = True
        bonus_dice_type = dice['name']
        bonus_dice_emoji = dice['emoji']
        break

dice_roll_history = st.session_state.dice_roll_history
new_roll_data = pd.DataFrame({'Roll': rolls,
                              'Count': np.ones(num_rolls, dtype=np.uint64),
                              'DiceNumberOfSides': [dice_type['sides']] * num_rolls,
                              'DiceRollerName': [st.session_state.name] * num_rolls})
if bonus_match:
    new_roll_data['BonusMatchToDiceName'] = [bonus_dice_type] * num_rolls
    new_roll_data['BonusMatchToDiceEmoji'] = [bonus_dice_emoji] * num_rolls
dice_roll_history = dice_roll_history.append(new_roll_data, ignore_index=True)
st.session_state.dice_roll_history = dice_roll_history

if st.button('Download Results'):
    filename = f'dice_roll_history_{st.session_state.name}.csv'
    st.download_button(label='Download CSV', data=dice_roll_history.to_csv(index=False), file_name=filename, mime='text/csv')

if st.session_state.dice_roll_history.shape[0] > 0:
    st.markdown('### Dice Roll History')
    st.dataframe(st.session_state.dice_roll_history)