Update app.py

app.py

@@ -3,23 +3,13 @@ import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from datetime import datetime
+from base64 import b64encode
 
 # Define emoji list
-EMOJI_LIST = {
-    4: "🎂",
-    6: "🍀",
-    8: "🍄",
-    10: "🍁",
-    12: "🍂",
-    20: "🍃",
-    50: "🍒",
-    100: "🌟"
-}
+EMOJI_LIST = {4: "🎂", 6: "🍀", 8: "🍄", 10: "🍁", 12: "🍂", 20: "🍃", 50: "🍒", 100: "🌟"}
 
-# Define the dice types
+# Define the dice types and default number of rolls
 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
@@ -38,18 +28,15 @@ def plot_tokens(health_tokens, coin_tokens):
 # 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 username and number of rolls
+username = st.text_input("Enter your username:")
+num_rolls = st.slider("Choose the number of rolls:", 1, 1000000, DEFAULT_ROLLS)
 
-# Get dice types and roll dice
-history = {}
+# Roll dice for each type and accumulate high rolls and tokens
+history = {"health_tokens": [0], "coin_tokens": [0]}
 for dice_type in DICE_TYPES:
     rolls = roll_dice(num_rolls, dice_type)
+    highest_rolls = sum(roll == dice_type for roll in rolls)
     st.write(f"Results for {dice_type}-sided dice:")
     for roll in rolls:
         st.write(f"{EMOJI_LIST[dice_type]} {roll}")
@@ -57,44 +44,21 @@ for dice_type in DICE_TYPES:
             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
+    history[f"{dice_type}-sided dice high rolls"] = highest_rolls
+    history["roll_history"] = {**history.get("roll_history", {}), dice_type: rolls}
+    history["health_tokens"].append(history.get("20-sided dice high rolls", 0))
+    history["coin_tokens"].append(history.get("100-sided dice high rolls", 0))
 
-# Plot tokens
-if "health_tokens" not in history:
-    history["health_tokens"] = [0]
-if "coin_tokens" not in history:
-    history["coin_tokens"] = [0]
+# Plot token accumulation
 st.write("Token Accumulation:")
 plot_tokens(history["health_tokens"], history["coin_tokens"])
 
-# Save history to CSV file
+# Create DataFrame and save to CSV file
+df = pd.concat([pd.DataFrame(history["roll_history"]), pd.DataFrame(history["health_tokens"], columns=["Health Tokens"]), pd.DataFrame(history["coin_tokens"], columns=["Coin Tokens"])], axis=1)
 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
+filename = f"{username}_{timestamp}.csv"
 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()
-
+st.markdown(f'<a href="data:file/csv;base64,{b64encode(open(filename, "rb").read()).decode()}" download="{filename}">Download CSV File</a>', unsafe_allow_html=True)