Create app.py

app.py

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+import yfinance as yf
+import pandas as pd
+import plotly.graph_objects as go
+import streamlit as st
+
+# Sidebar inputs for stock symbol and period
+sidebar = st.sidebar
+symbol = sidebar.text_input("Enter stock symbol:", "AAPL")
+data = yf.download(symbol, start="2020-01-01", end="2021-01-01")
+
+# New sidebar inputs for defining the Fibonacci period
+fib_start_date = sidebar.date_input("Select Fibonacci start date", value=pd.to_datetime("2020-01-01"), min_value=pd.to_datetime(data.index.min()), max_value=pd.to_datetime(data.index.max()))
+fib_end_date = sidebar.date_input("Select Fibonacci end date", value=pd.to_datetime("2021-01-01"), min_value=pd.to_datetime(data.index.min()), max_value=pd.to_datetime(data.index.max()))
+
+# Ensure start date is before end date
+if fib_start_date >= fib_end_date:
+    st.error('Error: End date must be after start date.')
+else:
+    # Filter data for the selected Fibonacci period
+    fib_data = data.loc[fib_start_date:fib_end_date]
+
+    # Find high and low prices within the Fibonacci period
+    high_price = fib_data['High'].max()
+    low_price = fib_data['Low'].min()
+
+    # Calculate Fibonacci Levels
+    price_diff = high_price - low_price
+    fib_levels = [0, 0.236, 0.382, 0.5, 0.618, 0.786, 1]
+    fib_values = [high_price - price_diff * level for level in fib_levels]
+
+    # Plotting
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x=data.index, y=data['Close'], name='Close Price', line=dict(color='black')))
+
+    # Plot Fibonacci levels
+    for i, val in enumerate(fib_values):
+        fig.add_hline(y=val, line_dash="dot", annotation_text=f'Fib {fib_levels[i]*100}%', annotation_position="right")
+
+    # Calculate and plot moving averages
+    for ma in [20, 50, 200]:
+        data[f'MA{ma}'] = data['Close'].rolling(window=ma).mean()
+        fig.add_trace(go.Scatter(x=data.index, y=data[f'MA{ma}'], name=f'{ma}-Period MA'))
+
+    # Display the chart
+    st.plotly_chart(fig)