Create app.py

app.py

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+import streamlit as st
+import backtrader as bt
+import yfinance as yf
+import matplotlib.pyplot as plt
+from datetime import datetime
+
+# Define the trading strategy
+class SmaCross(bt.Strategy):
+    params = dict(
+        pfast=10,  # period for the fast moving average
+        pslow=30   # period for the slow moving average
+    )
+
+    def __init__(self):
+        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
+        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
+        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal
+
+    def next(self):
+        if not self.position:  # not in the market
+            if self.crossover > 0:  # if fast crosses slow to the upside
+                self.buy()  # enter long
+
+        elif self.crossover < 0:  # in the market & cross to the downside
+            self.close()  # close long position
+
+# Function to run backtest and return cerebro
+def run_backtest(data):
+    cerebro = bt.Cerebro()
+    cerebro.addstrategy(SmaCross)
+    feed = bt.feeds.PandasData(dataname=data)
+    cerebro.adddata(feed)
+    cerebro.broker.setcash(10000)
+    cerebro.addsizer(bt.sizers.AllInSizer, percents=95)  # Use 95% of the portfolio for each trade
+    cerebro.run()
+    return cerebro
+
+# Initialize session state for running status
+if 'running' not in st.session_state:
+    st.session_state.running = False
+
+# Streamlit app layout
+st.title('Cryptocurrency Trading Bot Simulation')
+
+# Sidebar for user input
+st.sidebar.header('User Input Parameters')
+selected_crypto = st.sidebar.selectbox('Select cryptocurrency', ('BTC-USD', 'ETH-USD', 'LTC-USD'))
+start_date = st.sidebar.date_input('Start date', datetime(2020, 1, 1))
+end_date = st.sidebar.date_input('End date', datetime(2021, 1, 1))
+
+# Function to handle start button
+def start_bot():
+    st.session_state.running = True
+
+# Function to handle stop button
+def stop_bot():
+    st.session_state.running = False
+
+# Buttons to start/stop the bot
+st.sidebar.button('Start Bot', on_click=start_bot)
+st.sidebar.button('Stop Bot', on_click=stop_bot)
+
+# Display bot status
+if st.session_state.running:
+    st.success('Bot is running!')
+    # Fetch historical data from yfinance
+    data = yf.download(selected_crypto, start=start_date, end=end_date)
+    
+    # Check if data was successfully fetched
+    if not data.empty:
+        # Run backtest
+        cerebro = run_backtest(data)
+
+        # Show results
+        st.header('Simulation Results')
+        st.write(f'Final Portfolio Value: ${cerebro.broker.getvalue():,.2f}')
+        
+        # Plot the results manually using matplotlib
+        fig, ax = plt.subplots()
+        for data in cerebro.datas:
+            ax.plot(data.datetime.array, data.close.array, label='Close')
+            ax.legend()
+        
+        # Show the plot
+        st.pyplot(fig)
+else:
+    st.error('Bot is stopped!')