Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 import numpy as np
 import pandas as pd
-import plotly.graph_objects as go
+import pygraphviz as pgv
 from datetime import datetime
 from base64 import b64encode
 
@@ -14,13 +14,20 @@ def roll_dice(num_rolls, dice_type):
     return rolls
 
 def plot_tokens(health_tokens, coin_tokens):
-    fig = go.Figure()
+    dot = pgv.AGraph(strict=False, directed=True)
+    dot.node_attr['shape'] = 'plaintext'
+    dot.edge_attr['arrowhead'] = 'none'
+
     health_foods = [FOOD_LIST[i] for i in health_tokens]
     coin_foods = [FOOD_LIST[i] for i in coin_tokens]
-    fig.add_trace(go.Scatter(x=list(range(1, len(health_foods) + 1)), y=health_foods, name="💖 Health"))
-    fig.add_trace(go.Scatter(x=list(range(1, len(coin_foods) + 1)), y=coin_foods, name="💰 Coins"))
-    fig.update_layout(title="Token Accumulation", xaxis_title="Rolls", yaxis_title="Tokens")
-    st.plotly_chart(fig)
+
+    health_tokens_str = " | ".join(health_foods)
+    coin_tokens_str = " | ".join(coin_foods)
+
+    dot.add_edge('Health', health_tokens_str)
+    dot.add_edge('Coins', coin_tokens_str)
+
+    st.graphviz_chart(dot.string())
 
 st.title("🎲 Slot Machine Game")
 username = st.text_input("👤 Enter your username:")
@@ -31,8 +38,10 @@ for dice_type in DICE_TYPES:
     rolls = roll_dice(num_rolls, dice_type)
     highest_rolls = sum(roll == dice_type for roll in rolls)
     coin_tokens_added = 0
+
     dice_results = [f"{FOOD_LIST[dice_type]} {roll}" for roll in rolls]
     st.write(f"🎰 Results for {dice_type}-sided slot machine: {' | '.join(dice_results)}")
+
     for roll in rolls:
         if roll == dice_type:
             st.write(f"🎉 Congratulations! You got the {FOOD_LIST[dice_type]} jackpot! 💰 Adding 3 coins.")
@@ -41,14 +50,17 @@ for dice_type in DICE_TYPES:
             st.write(f"🎉 Congratulations! You got the {FOOD_LIST[dice_type]} maximum value! 💖 Adding 10 health tokens.")
             if dice_type == 100:
                 history["health_tokens"].append(history["health_tokens"][-1] + 10)
+
     history[f"{dice_type}-sided slot machine jackpots"] = highest_rolls
     history["roll_history"] = {**history.get("roll_history", {}), dice_type: rolls}
     history["coin_tokens"].append(history["coin_tokens"][-1] + coin_tokens_added)
-    
+
 st.write("💰💖 Token Accumulation:")
-#plot_tokens(history["health_tokens"], history["coin_tokens"])
+plot_tokens(history["health_tokens"], history["coin_tokens"])
+
 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"{username}_{timestamp}.csv"
 df.to_csv(filename, index=False)
-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)
+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)
+