Some information about the NumPy project and community
NumPy is an open source project aiming to enable numerical computing with Python. It was created in 2005, building on the early work of the Numeric and Numarray libraries. NumPy will always be 100% open source software, free for all to use and released under the liberal terms of the modified BSD license.
NumPy is developed in the open on GitHub, through the consensus of the NumPy and wider scientific Python community. For more information on our governance approach, please see our Governance Document.
The role of the NumPy Steering Council is to ensure, through working with and serving the broader NumPy community, the long-term well-being of the project, both technically and as a community. The NumPy Steering Council currently consists of the following members (in alphabetical order):
The NumPy project is growing; we have teams for
See the Team page for individual team members.
NumPy receives direct funding from the following sources:
Institutional Partners are organizations that support the project by employing people that contribute to NumPy as part of their job. Current Institutional Partners include:
If you have found NumPy useful in your work, research, or company, please consider a donation to the project commensurate with your resources. Any amount helps! All donations will be used strictly to fund the development of NumPy’s open source software, documentation, and community.
NumPy is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides NumPy with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit numfocus.org for more information.
Donations to NumPy are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax advisor about your particular tax situation.
NumPy’s Steering Council will make the decisions on how to best use any funds received. Technical and infrastructure priorities are documented on the NumPy Roadmap.