Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1

A dynamic video game recommender system is built using FastAPI, PostgreSQL, and Render to provide intelligent suggestions based on a user's game library. The system uses data from the Steamworks API and is designed as a standalone service that could be tied to a front-end application. The overall workflow involves a user adding a game via a POST request, which triggers a background task to update their recommendations. This pipeline calculates similarity scores between the user's games and all other games by using vectorized game tags. This first part of the tutorial covers the system architecture, database setup with PostgreSQL, and the initial data loading process.