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Update app.py
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app.py
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import streamlit as st
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from data_fetcher.yfinance_client import fetch_intraday_data
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from indicators.ema import calculate_ema
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@@ -8,48 +10,53 @@ from signals.strategy import generate_combined_signals
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from utils.plotting import plot_stock_data_with_signals
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import pandas as pd
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# Streamlit app title
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st.title('Stock Intraday Signal App')
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# Introduction and instructions
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st.write("""
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## Introduction
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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.
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## How to Use
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1. Enter a stock symbol in the sidebar.
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2. Choose the date range for the analysis.
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3. Click on "Analyze" to view the stock data, indicators, and signals.
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""")
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# Sidebar inputs
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st.sidebar.header('User Input Parameters')
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stock_symbol = st.sidebar.text_input('Stock Symbol', value='AAPL', max_chars=5)
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start_date = st.sidebar.date_input('Start Date')
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end_date = st.sidebar.date_input('End Date')
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analyze_button = st.sidebar.button('Analyze')
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# Main functionality
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if analyze_button:
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st.write(f"Fetching data for {stock_symbol} from {start_date} to {end_date}...")
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data = fetch_intraday_data(stock_symbol, start_date.isoformat(), end_date.isoformat())
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if data.empty:
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st.error("No data found for the given parameters. Please try different dates or stock symbols.")
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else:
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st.write("Calculating indicators...")
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ema_periods = [20, 50] # Example periods for EMA
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st.write("Generating signals...")
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data = generate_combined_signals(data)
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st.write("Visualizing data, indicators, and signals...")
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plot_stock_data_with_signals(data)
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# app.py
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import streamlit as st
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from data_fetcher.yfinance_client import fetch_intraday_data
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from indicators.ema import calculate_ema
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from utils.plotting import plot_stock_data_with_signals
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import pandas as pd
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# Streamlit app title with emoji
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st.title('Stock Intraday Signal App π')
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# Introduction and instructions with emojis
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st.write("""
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## Introduction π
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Welcome to the Stock Intraday Signal App! This application analyzes stock data to generate buy/sell signals π¦ based on technical indicators such as EMA, RSI, MACD, and Bollinger Bands. It's designed to help day traders π make informed decisions.
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## How to Use π οΈ
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1. Enter a stock symbol in the sidebar. π
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2. Choose the date range for the analysis. ποΈ
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3. Click on "Analyze" to view the stock data, indicators, and signals. π
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""")
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# Sidebar inputs with emojis
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st.sidebar.header('User Input Parameters π')
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stock_symbol = st.sidebar.text_input('Stock Symbol', value='AAPL', max_chars=5)
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start_date = st.sidebar.date_input('Start Date')
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end_date = st.sidebar.date_input('End Date')
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analyze_button = st.sidebar.button('Analyze π')
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# Main functionality
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if analyze_button:
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st.write(f"Fetching data for {stock_symbol} from {start_date} to {end_date}... π")
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data = fetch_intraday_data(stock_symbol, start_date.isoformat(), end_date.isoformat())
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if data.empty:
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st.error("No data found for the given parameters. Please try different dates or stock symbols. β")
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else:
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st.write("Calculating indicators... π")
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ema_periods = [20, 50] # Example periods for EMA
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ema_data = calculate_ema(data['Close'], ema_periods)
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for period, ema_series in ema_data.items():
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data[f'EMA_{period}'] = ema_series
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rsi_results = calculate_rsi(data['Close'])
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data = data.join(rsi_results) # Merge the RSI results back into the main DataFrame
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macd_data = calculate_macd(data['Close'])
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data = pd.concat([data, macd_data], axis=1)
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bb_data = calculate_bollinger_bands(data['Close'])
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data = pd.concat([data, bb_data], axis=1)
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st.write("Generating signals... π¦")
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data = generate_combined_signals(data)
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st.write("Visualizing data, indicators, and signals... π")
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plot_stock_data_with_signals(data)
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