import streamlit as st from thronetrader import StrategicSignals import requests import pandas as pd # Hard-coded API key for demonstration purposes API_KEY = "QR8F9B7T6R2SWTAT" def fetch_alpha_vantage_data(api_key): url = f'https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol=IBM&interval=5min&apikey={api_key}' response = requests.get(url) alpha_vantage_data = response.json() return alpha_vantage_data def main(): st.title("Stock Trend Predictor") # Use the hard-coded API key api_key = API_KEY # Fetch Alpha Vantage data alpha_vantage_data = fetch_alpha_vantage_data(api_key) # Extract relevant data from Alpha Vantage response alpha_vantage_time_series = alpha_vantage_data.get('Time Series (5min)', {}) df = pd.DataFrame(alpha_vantage_time_series).T df.index = pd.to_datetime(df.index) df = df.dropna(axis=0) # Print DataFrame for observation st.subheader("Raw Data:") st.write(df) # Uncomment the next line if you want to stop the execution here to observe the data # st.stop() if __name__ == "__main__": main() def main(): st.title("Strategic Trading Signals") # Input for stock symbol symbol = st.text_input("Enter stock symbol (e.g., AAPL):", "AAPL") # Display strategic trading signals strategic_signals = StrategicSignals(symbol=symbol) st.subheader("Bollinger Bands Signals:") bollinger_bands_signals = strategic_signals.get_bollinger_bands_signals() st.write(bollinger_bands_signals) st.subheader("Breakout Signals:") breakout_signals = strategic_signals.get_breakout_signals() st.write(breakout_signals) st.subheader("Crossover Signals:") crossover_signals = strategic_signals.get_crossover_signals() st.write(crossover_signals) st.subheader("MACD Signals:") macd_signals = strategic_signals.get_macd_signals() st.write(macd_signals) st.subheader("RSI Signals:") rsi_signals = strategic_signals.get_rsi_signals() st.write(rsi_signals) if __name__ == "__main__": main()