How to Build an Automated Competitor Price Monitoring System with Python

This comprehensive tutorial outlines the process of building an automated competitor price monitoring system using Python, Streamlit, and various supporting tools such as Firecrawl for AI-driven web scraping, SQLAlchemy for database management, and GitHub Actions for automation. The system is designed to track product prices across multiple e-commerce websites, allowing users to input their products and competitor URLs, and then automatically updating competitor prices every six hours. The setup includes creating a PostgreSQL database for storing product and competitor data, building a user-friendly interface for managing this data, and implementing a cron job via GitHub Actions to ensure regular updates. Emphasizing scalability and legal considerations, the guide also suggests enhancements like email notifications for significant price changes and support for product variants and multiple currencies. It concludes by highlighting the potential for integrating this system with no-code platforms like n8n for users seeking a simpler setup.

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