Food Price Tracker

A comprehensive web application for tracking food prices across multiple retailers, built with modern technologies and scalable architecture.

🚀 Features

• Price Comparison: Compare prices across multiple retailers
• Price Alerts: Set alerts for price drops on favorite products
• User Authentication: Secure JWT-based authentication
• Favorites: Save favorite products for easy tracking
• Analytics: Track price trends and get insights
• Web Scraping: Automated price collection from major retailers
• Responsive Design: Modern, mobile-friendly interface

🛠️ Tech Stack

Backend

• Node.js with Express.js
• PostgreSQL database
• JWT authentication
• Puppeteer for web scraping
• Docker containerization

Frontend

• React 18 with hooks
• Styled Components for styling
• React Query for data fetching
• React Router for navigation
• Axios for API calls

📦 Installation

Prerequisites

• Node.js 18+
• PostgreSQL 15+
• Docker (optional)

Development Setup

1. Clone the repository

   git clone <repository-url>
   cd FoodPriceTracker

2. Install dependencies

   # Install root dependencies
   npm install
   
   # Install backend dependencies
   cd backend && npm install
   
   # Install frontend dependencies
   cd ../frontend && npm install

3. Set up environment variables

   # Copy environment files
   cp .env.example .env
   cp backend/.env.example backend/.env
   
   # Edit the .env files with your configuration

4. Set up the database

   # Start PostgreSQL (using Docker)
   docker-compose up -d postgres
   
   # Run database migrations
   cd backend && npm run migrate

5. Start the development servers

   # Start both frontend and backend
   npm run dev

Production Deployment

1. Using Docker Compose

   # Build and start all services
   docker-compose up -d

2. Manual Deployment

   # Build frontend
   cd frontend && npm run build
   
   # Start backend
   cd ../backend && npm start

🗄️ Database Schema

The application uses PostgreSQL with the following main tables:

• users: User accounts and authentication
• products: Product information and metadata
• retailers: Store information
• product_prices: Current prices across retailers
• price_history: Historical price data
• price_alerts: User-defined price alerts
• user_favorites: User's favorite products

🔧 API Endpoints

Authentication

• POST /api/auth/register - User registration
• POST /api/auth/login - User login
• GET /api/auth/profile - Get user profile
• PUT /api/auth/profile - Update user profile

Products

• GET /api/products/search - Search products
• GET /api/products/:id - Get product details
• POST /api/products/:id/favorite - Add to favorites
• GET /api/products/favorites/list - Get user favorites

Prices

• GET /api/prices/compare - Compare prices
• GET /api/prices/history - Price history
• GET /api/prices/trending - Trending products
• GET /api/prices/deals - Best deals

Alerts

• GET /api/alerts - Get user alerts
• POST /api/alerts - Create price alert
• PUT /api/alerts/:id - Update alert
• DELETE /api/alerts/:id - Delete alert

🕷️ Web Scraping

The application includes a sophisticated web scraping system that:

• Supports multiple retailers (Walmart, Target, Kroger, etc.)
• Uses Puppeteer for dynamic content
• Implements rate limiting and anti-detection measures
• Stores scraped data in PostgreSQL
• Runs on scheduled intervals

🔒 Security Features

• JWT-based authentication
• Password hashing with bcrypt
• Rate limiting on API endpoints
• CORS configuration
• Input validation with Joi
• SQL injection prevention
• XSS protection headers

📊 Performance Optimizations

• Database indexing for fast queries
• React Query for efficient data fetching
• Image optimization and lazy loading
• Compression middleware
• Connection pooling
• Caching strategies

🧪 Testing

# Run backend tests
cd backend && npm test

# Run frontend tests
cd frontend && npm test

# Run all tests
npm test

📈 Monitoring

• Health check endpoints
• Error logging and monitoring
• Database query performance tracking
• Scraping success/failure rates

🚀 Deployment

Environment Variables

# Database
DB_HOST=localhost
DB_PORT=5432
DB_NAME=food_tracker
DB_USER=postgres
DB_PASSWORD=your_password

# JWT
JWT_SECRET=your_secret_key
JWT_EXPIRES_IN=7d

# Server
PORT=5000
NODE_ENV=production

Docker Deployment

# Build and deploy
docker-compose up -d

# View logs
docker-compose logs -f

# Scale services
docker-compose up -d --scale backend=3

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support and questions:

• Create an issue in the repository
• Check the documentation
• Review the API endpoints

🔮 Future Enhancements

• Mobile app development
• Machine learning price predictions
• Social features and sharing
• Advanced analytics dashboard
• Integration with more retailers
• Real-time notifications
• Price forecasting algorithms