Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows. The video-streaming giant uses machine learning across all aspects of its business, from screenplay analysis, to optimizing production schedules, predicting churn, pricing, translation, and optimizing its giant content distribution network. According to Netflix software engineers, Metaflow was built to help boost the productivity of its data scientists who like to express business logic through Python code but don't want to spend too much time thinking about engineering issues, such as object hierarchies, packaging issues, or dealing with obscure APIs unrelated to their work. The idea behind Metaflow was to give Netflix data scientists the ability to see early on whether a prototyped model would fail in production, allowing them to fix whatever the issue was and ideally speed up deployment times. Netflix in February revealed that Metaflow had helped reduce median deployment times from four months to just seven days.