LF AI & Data Foundation—the organization building an ecosystem to sustain open-source innovation in artificial intelligence (AI) and data open source projects, today is announcing Kedro, an open-source Python framework for creating reproducible, maintainable and modular data science code created by QuantumBlack, a McKinsey company, as its latest Incubation Project.
Kedro was open-sourced two and a half years ago and has experienced impressive community engagement. The Kedro community and user base continue to grow with more than 200,000 monthly downloads, over 100 contributors and a growing number of companies that choose Kedro as their standard for data science code.
Dr. Ibrahim Haddad, Executive Director of LF AI & Data, said: “We’re excited to welcome the Kedro project in LF AI & Data. This open source project provides a framework for creating machine learning code that uniquely applies software engineering best practices, making it easier for developers to deploy into production systems. With the many challenges that exist in creating machine learning products, Kedro is a great addition to our portfolio of project and technology software solutions. We look forward to working with the community to grow the project’s footprint and create new collaboration opportunities for it with our members and other hosted projects.”
Yetunde Dada, product manager on the Kedro project, said: “We are excited about the transition to LF AI & Data because we recognise the importance of open governance for the continued growth of the Kedro user base and contributor community. In addition, we understand that the Kedro project will benefit from a faster pace of innovation and industry-wide adoption.”
QuantumBlack created Kedro based on collective best-practice delivering real-world ML products with vast amounts of raw, unvetted data. Kedro was developed to address the main shortcomings of Jupyter notebooks, one-off scripts, and glue-code because there is a focus on creating maintainable data science code. Additional benefits included enhanced team collaboration when different team members have varied exposure to software engineering concepts.
Ivan Danov, technical lead on the Kedro project, further describes where Kedro fits in the ecosystem: “The easiest way to describe how Kedro is transforming the workflows of data scientists is to look into how React helped front-end developers when building user interfaces. While machine learning can change how we all work, we recognise that many projects fail to transition from prototype to production. Kedro seeks to change this.”
Visit the Kedro get started guide which contains full installation instructions, and try out the spaceflights tutorial which will acquaint you with beginner-to-intermediate capability in Kedro.
LF AI & Data supports projects via a wide range of services, and the first step is joining as an Incubation Project. LF AI & Data will support neutral open governance for the project to help foster its growth. Learn more about Kedro on their GitHub and be sure to subscribe to the Kedro-Announce and Kedro-Technical-Discuss mailing lists to join the community and stay connected on the latest updates.
A warm welcome to Kedro! We look forward to the project’s continued growth and success as part of the LF AI & Data Foundation. To learn about how to host an open-source project with us, visit the LF AI & Data website.
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