Today we announced a collaboration with NumFOCUS to support three linchpin projects within the Python scientific and technical computing ecosystem—NumPy, SciPy, and pandas. Working with NumFOCUS, the fiscal sponsor behind these projects, allows us to deepen our support for community-led Python projects through the Tidelift Subscription, a managed open source subscription for application dependencies. It follows our recently announced partnership with the Python Software Foundation to support the widely used Pallets Projects for web application development.
The Tidelift Subscription uses a layered approach to cover millions of open source packages that power applications today. Tidelift works directly with independent maintainers of the most widely used projects and pays them to provide an enterprise-grade experience for companies using their software, including software updates, licensing verification and indemnification, maintenance, code improvement, and more.
Partnering with NumFOCUS means Tidelift now provides income through NumFOCUS to support the maintenance of SciPy, NumPy, and pandas. The project maintainers proactively work with Tidelift’s security response team, confirm licensing of their packages, certify authorship of their code, and provide other services to our enterprise customers. We’re also giving the maintainers anonymized analytics about how enterprise teams are using their open source packages. This is one of the top requests maintainers have asked us for so they can better understand commercial use of their projects.
Adding NumPy, SciPy, and pandas to our Python coverage is exciting for Tidelift and our customers because the projects are fundamental to nearly all numerical operations in Python. Together they’re three of the most powerful Python libraries for technical and scientific computing, and indispensable to academics, business analysts, and data scientists.
PyData projects help researchers take on elemental questions ranging from promoting ethics and accountability in AI and machine learning to discovering new therapeutics faster. Commercially, data scientists use the projects to analyze customer behavior for companies like Revlon and Salesforce, and to create mathematical models supporting business operations at JPMorgan, BAE Systems, and Amgen.
Use of NumPy, SciPy, and pandas continues to evolve as they’ve become the most commonly used packages on GitHub to support machine learning and data science projects.
At Tidelift, we’re inspired by the work of the independent maintainers behind the PyData projects. By supporting them through non-profit, community-led organizations like NumFOCUS, we’re helping ensure the security, maintenance, and overall health of these projects—and helping development teams create even more amazing applications with robust, well-supported open source components.