Code Editor for app.py

import streamlit as st
import yfinance as yf
import plotly.graph_objects as go
from datetime import datetime, timedelta
import pandas as pd

st.set_page_config(layout="wide")
st.title("Intraday Stock Dashboard")

# Sidebar inputs
with st.sidebar:
    symbol = st.text_input("Stock Symbol", value="AAPL").upper()
    days_back = st.slider("Days to Look Back", min_value=1, max_value=7, value=3)
    interval = st.selectbox(
        "Interval",
        options=["1m", "2m", "5m", "15m", "30m", "60m"],
        index=2
    )

# Get stock data
@st.cache_data(ttl=60)  # Cache for 1 minute
def get_stock_data(symbol, days_back, interval):
    try:
        end = datetime.now()
        start = end - timedelta(days=days_back)
        stock = yf.Ticker(symbol)
        df = stock.history(start=start, end=end, interval=interval)
        return df, stock.info
    except Exception as e:
        st.error(f"Error fetching data: {e}")
        return None, None

df, info = get_stock_data(symbol, days_back, interval)

if df is not None and not df.empty:
    # Company info
    col1, col2, col3 = st.columns(3)
    with col1:
        st.metric("Current Price", f"${df['Close'].iloc[-1]:.2f}", 
                 f"{((df['Close'].iloc[-1] - df['Close'].iloc[-2])/df['Close'].iloc[-2]*100):.2f}%")
    with col2:
        st.metric("Volume", f"{df['Volume'].iloc[-1]:,.0f}")
    with col3:
        if info:
            st.metric("Market Cap", f"${info.get('marketCap', 0)/1e9:.2f}B")

    # Candlestick chart
    fig = go.Figure(data=[go.Candlestick(x=df.index,
                                        open=df['Open'],
                                        high=df['High'],
                                        low=df['Low'],
                                        close=df['Close'])])
    
    fig.update_layout(
        title=f"{symbol} Stock Price",
        yaxis_title="Price (USD)",
        xaxis_title="Date",
        height=600,
        template="plotly_dark"
    )
    st.plotly_chart(fig, use_container_width=True)

    # Volume chart
    volume_fig = go.Figure(data=[go.Bar(x=df.index, y=df['Volume'])])
    volume_fig.update_layout(
        title=f"{symbol} Volume",
        yaxis_title="Volume",
        xaxis_title="Date",
        height=300,
        template="plotly_dark"
    )
    st.plotly_chart(volume_fig, use_container_width=True)

    # Recent trades table
    st.subheader("Recent Trades")
    recent_data = df.tail(10).reset_index()
    recent_data['Datetime'] = recent_data['Datetime'].dt.strftime('%Y-%m-%d %H:%M:%S')
    st.dataframe(recent_data)