Product Tracker

A web application that tracks product prices and availability from various e-commerce sites including Amazon, Walmart, Newegg, Best Buy, Microcenter, and B&H Photo.

Features

• Track product prices from multiple retailers
• Get notified when prices drop or products become available
• Set price drop targets
• View price history
• Configure check intervals
• Timezone support

Dockerized Setup

The application is containerized using Docker for easy deployment and management.

Prerequisites

• Docker
• Docker Compose

Environment Variables

You can customize the application by setting the following environment variables:

• SECRET_KEY: Secret key for the Flask application (default: your-secret-key-here)
• DEBUG: Set to 1 to enable debug mode (default: 0)
• TWOCAPTCHA_API_KEY: API key for 2captcha service (required for solving CAPTCHAs on Newegg)
• CHECK_INTERVAL_MINUTES: How often to check products in minutes (default: 15)
• CHECK_INTERVAL_SECONDS: Additional seconds for check interval (default: 0)
• DEFAULT_TIMEZONE: Default timezone for displaying times (default: UTC)

Building and Running

1. Clone the repository:

   git clone <repository-url>
   cd product-tracker
   

2. Build and start the Docker container:

   docker-compose up -d
   

3. Access the application:

   http://localhost:5000
   

Stopping the Container

docker-compose down

Viewing Logs

docker-compose logs -f

Persistence

The application data is stored in Docker volumes to ensure persistence across container restarts:

• app_data: Contains the SQLite database
• app_logs: Contains the application logs

Updating

To update the application:

1. Pull the latest changes:

   git pull
   

2. Rebuild and restart the container:

   docker-compose up -d --build
   

Development

Running Locally Without Docker

1. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up environment variables or create a .env file.

4. Initialize the database:

   python create_db.py
   

5. Run the application:

   python run.py
   

License

MIT License