Update app.py

app.py

@@ -1,69 +1,66 @@
 import streamlit as st
 import yfinance as yf
 import pandas as pd
-import matplotlib.pyplot as plt
+import plotly.graph_objects as go
 
+# Function to fetch data from Yahoo Finance
 def fetch_data(ticker, start_date, end_date):
     data = yf.download(ticker, start=start_date, end=end_date)
     return data
 
-def calculate_indicators(data):
-    # High and low for the breakout signals
-    data['20 Day High'] = data['High'].rolling(window=20).max()
-    data['20 Day Low'] = data['Low'].rolling(window=20).min()
-    data['55 Day High'] = data['High'].rolling(window=55).max()
-    data['55 Day Low'] = data['Low'].rolling(window=55).min()
-    
+# Calculate indicators based on user-defined window sizes
+def calculate_indicators(data, window_short, window_long):
+    data['High Short'] = data['High'].rolling(window=window_short).max()
+    data['Low Short'] = data['Low'].rolling(window=window_short).min()
+    data['High Long'] = data['High'].rolling(window=window_long).max()
+    data['Low Long'] = data['Low'].rolling(window=window_long).min()
     return data
 
+# Identify buy and sell signals based on breakout strategy
 def identify_signals(data):
-    # Buy signals are generated when the price exceeds the 20-day high
-    data['Buy Signal'] = (data['Close'] > data['20 Day High'].shift(1))
-    # Sell signals are generated when the price drops below the 20-day low
-    data['Sell Signal'] = (data['Close'] < data['20 Day Low'].shift(1))
-    
-    signals = []
-    for index, row in data.iterrows():
-        if row['Buy Signal']:
-            signals.append({'Date': index, 'Signal Type': 'Buy', 'Price': row['Close']})
-        if row['Sell Signal']:
-            signals.append({'Date': index, 'Signal Type': 'Sell', 'Price': row['Close']})
-    
-    return data, pd.DataFrame(signals)
+    data['Buy Signal'] = (data['Close'] > data['High Short'].shift(1))
+    data['Sell Signal'] = (data['Close'] < data['Low Short'].shift(1))
+    return data
 
+# Plotting function using Plotly for interactive charts
 def plot_data(data):
-    plt.figure(figsize=(12, 6))
-    plt.plot(data['Close'], label='Close Price')
-    
-    buy_signals = data[data['Buy Signal']]
-    sell_signals = data[data['Sell Signal']]
-    plt.scatter(buy_signals.index, buy_signals['Close'], marker='^', color='green', s=100, label='Buy Signal')
-    plt.scatter(sell_signals.index, sell_signals['Close'], marker='v', color='red', s=100, label='Sell Signal')
-    
-    plt.title('Stock Price and Turtle Trading Signals')
-    plt.xlabel('Date')
-    plt.ylabel('Price')
-    plt.legend()
-    plt.grid(True)
-    plt.show()
+    fig = go.Figure()
+    # Add traces for Close price, High, and Low bands
+    fig.add_trace(go.Scatter(x=data.index, y=data['Close'], name='Close Price', line=dict(color='blue')))
+    fig.add_trace(go.Scatter(x=data.index, y=data['High Short'], name='High Short', line=dict(dash='dot')))
+    fig.add_trace(go.Scatter(x=data.index, y=data['Low Short'], name='Low Short', line=dict(dash='dot')))
+
+    # Add buy and sell signal markers
+    buys = data[data['Buy Signal']]
+    sells = data[data['Sell Signal']]
+    fig.add_trace(go.Scatter(x=buys.index, y=buys['Close'], mode='markers', name='Buy Signal', marker_symbol='triangle-up', marker_color='green', marker_size=10))
+    fig.add_trace(go.Scatter(x=sells.index, y=sells['Close'], mode='markers', name='Sell Signal', marker_symbol='triangle-down', marker_color='red', marker_size=10))
+
+    # Update layout for better visualization
+    fig.update_layout(title='Stock Price and Trading Signals', xaxis_title='Date', yaxis_title='Price', template='plotly_dark')
+    return fig
 
+# Main application function
 def main():
-    st.title("Turtle Trading Strategy Visualization")
-    ticker = st.text_input("Enter the ticker symbol, e.g., 'AAPL'")
-    start_date = st.date_input("Select the start date")
-    end_date = st.date_input("Select the end date")
-    
+    st.title("Enhanced Turtle Trading Strategy Visualization")
+
+    # Sidebar for user inputs
+    with st.sidebar:
+        ticker = st.text_input("Enter the ticker symbol, e.g., 'AAPL'")
+        start_date = st.date_input("Select the start date")
+        end_date = st.date_input("Select the end date")
+        window_short = st.number_input("Short term window", min_value=5, max_value=60, value=20)
+        window_long = st.number_input("Long term window", min_value=5, max_value=120, value=55)
+
     if st.button("Analyze"):
         data = fetch_data(ticker, start_date, end_date)
-        data = calculate_indicators(data)
-        data, signals = identify_signals(data)
-        plot_data(data)
-        st.pyplot(plt)
-        if not signals.empty:
-            st.write("Trading Signals:")
-            st.dataframe(signals)
+        if not data.empty:
+            data = calculate_indicators(data, window_short, window_long)
+            data = identify_signals(data)
+            fig = plot_data(data)
+            st.plotly_chart(fig, use_container_width=True)
         else:
-            st.write("No trading signals found for the selected period.")
+            st.error("No data found for the selected ticker and date range.")
 
 if __name__ == "__main__":
     main()