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import streamlit as st | |
import numpy as np | |
import pandas as pd | |
import plotly.graph_objects as go | |
from datetime import datetime | |
# Define emoji list | |
EMOJI_LIST = { | |
4: "π", | |
6: "π", | |
8: "π", | |
10: "π", | |
12: "π", | |
20: "π", | |
50: "π", | |
100: "π" | |
} | |
# Define the dice types | |
DICE_TYPES = [4, 6, 8, 10, 12, 20, 50, 100] | |
# Define the default number of rolls | |
DEFAULT_ROLLS = 10 | |
# Define a function to roll dice | |
def roll_dice(num_rolls, dice_type): | |
rolls = np.random.randint(1, dice_type + 1, size=num_rolls) | |
return rolls | |
# Define a function to plot tokens | |
def plot_tokens(health_tokens, coin_tokens): | |
fig = go.Figure() | |
fig.add_trace(go.Scatter(x=list(range(1, len(health_tokens) + 1)), y=health_tokens, name="Health")) | |
fig.add_trace(go.Scatter(x=list(range(1, len(coin_tokens) + 1)), y=coin_tokens, name="Coins")) | |
fig.update_layout(title="Token Accumulation", xaxis_title="Rolls", yaxis_title="Tokens") | |
st.plotly_chart(fig) | |
# Define the app | |
st.title("Dice Rolling Game") | |
# Get username | |
st.write("Enter your username:") | |
username = st.text_input("Username") | |
# Get number of rolls | |
st.write("Choose the number of rolls:") | |
num_rolls = st.slider("Number of Rolls", 1, 1000000, DEFAULT_ROLLS) | |
# Get dice types and roll dice | |
history = {} | |
for dice_type in DICE_TYPES: | |
rolls = roll_dice(num_rolls, dice_type) | |
st.write(f"Results for {dice_type}-sided dice:") | |
for roll in rolls: | |
st.write(f"{EMOJI_LIST[dice_type]} {roll}") | |
if roll == dice_type: | |
st.write("Congratulations! You rolled the highest value!") | |
if dice_type == 100: | |
st.write("Adding 10 coins for rolling over 90 on 100-sided dice.") | |
if "coin_tokens" not in history: | |
history["coin_tokens"] = [0] | |
history["coin_tokens"].append(history["coin_tokens"][-1] + 10) | |
if "roll_history" not in history: | |
history["roll_history"] = {} | |
history["roll_history"][dice_type] = rolls | |
# Plot tokens | |
if "health_tokens" not in history: | |
history["health_tokens"] = [0] | |
if "coin_tokens" not in history: | |
history["coin_tokens"] = [0] | |
st.write("Token Accumulation:") | |
plot_tokens(history["health_tokens"], history["coin_tokens"]) | |
# Save history to CSV file | |
timestamp = datetime.now().strftime("%m-%d-%Y-%H-%M-%S") | |
filename = f"{timestamp}.csv" | |
data = {"Username": [username], "Date": [timestamp], **history} | |
# Concatenate all roll histories into a single dictionary | |
all_rolls = {} | |
for dice_type, rolls in history["roll_history"].items(): | |
all_rolls[f"{dice_type}-sided dice"] = rolls | |
all_rolls = pd.DataFrame(all_rolls) | |
# Create a Series for each token type | |
health_tokens = pd.Series(history["health_tokens"], name="Health Tokens") | |
coin_tokens = pd.Series(history["coin_tokens"], name="Coin Tokens") | |
# Concatenate all data into a single DataFrame | |
df = pd.concat([all_rolls, health_tokens, coin_tokens], axis=1) | |
# Save history to CSV file | |
df.to_csv(filename, index=False) | |
# Show download link for CSV file | |
st.write("Download the dice rolling history:") | |
with open(filename, "rb") as f: | |
bytes_data = f.read() | |