app2.py

import yfinance as yf
import pandas as pd
import plotly.graph_objects as go
import streamlit as st

# Sidebar inputs for stock symbol
sidebar = st.sidebar
symbol = sidebar.text_input("Enter stock symbol:", "AAPL")
data = yf.download(symbol, start="2020-01-01", end="2021-01-01")

# Check if data is empty
if data.empty:
    st.error("No data available for the selected symbol. Please try another symbol.")
else:
    # Determine the valid date range for Fibonacci analysis
    min_date, max_date = data.index.min().date(), data.index.max().date()

    # Dynamic default dates based on data range
    default_start, default_end = min_date, max_date

    # Sidebar inputs for Fibonacci time frame
    fib_start_date = sidebar.date_input("Fibonacci Start Date", value=default_start, min_value=min_date, max_value=max_date)
    fib_end_date = sidebar.date_input("Fibonacci End Date", value=default_end, min_value=min_date, max_value=max_date)

    if fib_start_date >= fib_end_date:
        st.error("Error: The start date must be before the end date.")
    else:
        # Filter data for Fibonacci analysis
        fib_data = data.loc[fib_start_date:fib_end_date]

        # Calculate high and low prices for Fibonacci levels
        high_price = fib_data['High'].max()
        low_price = fib_data['Low'].min()

        # Fibonacci retracement levels
        fib_levels = [0, 0.236, 0.382, 0.5, 0.618, 0.786, 1]
        price_diff = high_price - low_price

        # Initialize figure for plotting
        fig = go.Figure()

        # Plot close prices and moving averages
        fig.add_trace(go.Scatter(x=data.index, y=data['Close'], name='Close Price', line=dict(color='black')))
        for ma in [20, 50, 200]:
            ma_label = f"MA{ma}"
            data[ma_label] = data['Close'].rolling(window=ma).mean()
            fig.add_trace(go.Scatter(x=data.index, y=data[ma_label], name=ma_label, line=dict(width=2)))

        # Plot Fibonacci levels
        for level in fib_levels:
            value = high_price - (price_diff * level)
            fig.add_hline(y=value, line_dash="dot", annotation_text=f"{level*100}%", annotation_position="right")

        # Display chart
        st.plotly_chart(fig)