Zero Lap to Hero: Building a Formula 1 Analytics Stack with Python, dbt, and Postgres

A comprehensive guide to building a Formula 1 analytics pipeline using Python, dbt, and PostgreSQL. The article addresses the challenge of migrating from the discontinued Ergast API and evaluates alternatives including FastF1, OpenF1, Sportmonks, and Jolpica. It recommends Jolpica as the best successor for existing Ergast projects due to backward compatibility, while FastF1 is better for new analysis workflows. The series will cover building a production-ready data ingestion system, implementing dbt transformations, and creating analytics for race insights.