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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() |