import streamlit as st
import requests
import pandas as pd
from datetime import datetime, timedelta

# Hard-coded API key for demonstration purposes
API_KEY = "QR8F9B7T6R2SWTAT"

def fetch_alpha_vantage_intraday(api_key, symbol):
    url = f'https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={symbol}&interval=1min&apikey={api_key}'
    response = requests.get(url)
    alpha_vantage_data = response.json()
    return alpha_vantage_data

def main():
    st.title("Latest Traded Data (Last Hour)")

    # User input for stock symbol
    symbol = st.text_input("Enter Stock Symbol (e.g., IBM):")

    if not symbol:
        st.warning("Please enter a valid stock symbol.")
        st.stop()

    # Use the hard-coded API key
    api_key = API_KEY

    # Set the time interval for fetching historical intraday data
    interval = 1  # 1-minute intervals

    # Fetch Alpha Vantage intraday data
    alpha_vantage_data = fetch_alpha_vantage_intraday(api_key, symbol)

    # Extract relevant data from Alpha Vantage response
    alpha_vantage_time_series = alpha_vantage_data.get(f'Time Series ({interval}min)', {})
    df = pd.DataFrame(alpha_vantage_time_series).T
    df.index = pd.to_datetime(df.index)

    # Filter data for the last hour
    current_time = datetime.now()
    one_hour_ago = current_time - timedelta(hours=1)
    filtered_df = df[df.index >= one_hour_ago]

    # Display the latest traded data for the last hour
    st.subheader("Latest Traded Data (Last Hour):")
    st.write(filtered_df.tail(1))

if __name__ == "__main__":
    main()