Real-Time Stock Sentiment Analyzer

This project fetches real-time stock prices and news headlines, performs sentiment analysis, and visualizes the results.

Features

• Fetch real-time stock prices using yfinance
• Fetch news headlines using NewsAPI
• Sentiment analysis combining TextBlob and VADER (NLTK), falling back to VADER when the two disagree strongly
• Interactive dashboard with Streamlit
• Sample data mode for trying the app without API keys or a network connection
• Dockerized for easy deployment
• CI pipeline with GitHub Actions (black, flake8)
• Sentiment Summary: Displays a bar chart of positive, negative, and neutral news counts for quick insights.

Usage

1. Create a .env file in the project root and add your NewsAPI key (only needed for Real-Time mode):

NEWS_API_KEY=your_news_api_key_here

2. Install dependencies: pip install -r requirements.txt
3. Run app: streamlit run src/app.py
4. Select between Real-Time or Sample Data mode.
   • Real-Time fetches live stock prices (yfinance) and news (NewsAPI) for the ticker you enter.
   • Sample Data uses the bundled data/sample_stock.csv for stock prices and still fetches live news, so it works without a NewsAPI key.
5. Enter stock ticker in the app and click Fetch Data.
6. Or run with Docker:

docker build -t stock-sentiment-app .
docker run -p 8501:8501 --env-file .env stock-sentiment-app

Project Structure

• src/ - Source code
  • app.py - Streamlit entry point
  • fetch_stock.py - Stock price retrieval via yfinance
  • fetch_news.py - News retrieval via NewsAPI
  • sentiment.py - TextBlob/VADER sentiment analysis
  • visualization.py - Chart rendering
• data/ - Sample historical CSV used by Sample Data mode
• Dockerfile - Container setup
• .github/workflows/ - CI pipeline
• requirements.txt - Dependencies
• README.md - Project overview