Kedro – An open-source framework for data science code

Kedro is an open-source Python framework designed to enhance the development of production-ready data science code by integrating software engineering best practices. It provides a structured approach to managing complex data and machine-learning pipelines, allowing data scientists to focus on problem-solving rather than the intricacies of code management. Key features include pipeline visualization through Kedro-Viz, a versatile Data Catalog for managing various data formats and sources, and support for numerous integrations with tools like Amazon SageMaker and Apache Spark. Kedro also offers a project template for standardizing project organization, dedicated IDE support for Visual Studio Code, and a dataset-driven workflow that simplifies task management within pipelines. Additionally, it emphasizes coding standards through test-driven development and provides flexible deployment options across various platforms. Kedro has been successfully implemented in production environments, such as at Telkomsel and Beamery, where it has significantly improved workflow efficiency and data handling capabilities. The framework is maintained by the Linux Foundation and has a supportive community for users.

- Kedro is an open-source framework for building production-ready data science code.

- It standardizes project organization and simplifies complex data pipeline management.

- Key features include pipeline visualization, a versatile Data Catalog, and extensive integration options.

- Kedro supports coding standards and offers flexible deployment strategies.

- It has been successfully used in production by companies like Telkomsel and Beamery.