app.py

# app.py

import streamlit as st
from data_fetcher.yfinance_client import fetch_intraday_data
from indicators.ema import calculate_ema
from indicators.rsi import calculate_rsi
from indicators.macd import calculate_macd
from indicators.bollinger_bands import calculate_bollinger_bands
from signals.strategy import generate_combined_signals
from utils.plotting import plot_stock_data_with_signals
import pandas as pd

# Streamlit app title with emoji
st.title('Stock Intraday Signal App 📈')

# Introduction and instructions with emojis
st.write("""
## Introduction 🌟
Welcome to the Stock Intraday Signal App! This application analyzes stock data to generate buy/sell signals 🚦 based on technical indicators such as EMA, RSI, MACD, and Bollinger Bands. It's designed to help day traders 📊 make informed decisions.

## How to Use 🛠️
1. Enter a stock symbol in the sidebar. 📝
2. Choose the date range for the analysis. 🗓️
3. Click on "Analyze" to view the stock data, indicators, and signals. 🔍
""")

# Sidebar inputs with emojis
st.sidebar.header('User Input Parameters 📋')
stock_symbol = st.sidebar.text_input('Stock Symbol', value='AAPL', max_chars=5)
start_date = st.sidebar.date_input('Start Date')
end_date = st.sidebar.date_input('End Date')
analyze_button = st.sidebar.button('Analyze 🚀')

# Main functionality
if analyze_button:
    st.write(f"Fetching data for {stock_symbol} from {start_date} to {end_date}... 🔄")
    data = fetch_intraday_data(stock_symbol, start_date.isoformat(), end_date.isoformat())
    
    if data.empty:
        st.error("No data found for the given parameters. Please try different dates or stock symbols. ❌")
    else:
        st.write("Calculating indicators... 🔍")
        ema_periods = [20, 50]  # Example periods for EMA
        ema_data = calculate_ema(data['Close'], ema_periods)
        for period, ema_series in ema_data.items():
            data[f'EMA_{period}'] = ema_series
            
        rsi_results = calculate_rsi(data['Close'])
        data = data.join(rsi_results)  # Merge the RSI results back into the main DataFrame
        
        macd_data = calculate_macd(data['Close'])
        data = pd.concat([data, macd_data], axis=1)
        
        bb_data = calculate_bollinger_bands(data['Close'])
        data = pd.concat([data, bb_data], axis=1)
        
        st.write("Generating signals... 🚦")
        data = generate_combined_signals(data)
        
        st.write("Visualizing data, indicators, and signals... 📊")
        plot_stock_data_with_signals(data)