In the past we've talked about the improving tooling for applying good engineering practices in data science projects. Kedro is another good addition in this space. It's a development workflow framework for data science projects that brings a standardized approach to building production-ready data and machine-learning pipelines. We like the focus on software engineering practices and good design with its emphasis on test-driven development, modularity, versioning and good hygiene practices such as keeping credentials out of the codebase.