NumPy is the fundamental package for scientific computing with Python. It contains among other things:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code
  • useful linear algebra, Fourier transform, and random number capabilities

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

NumPy is licensed under the BSD licenseopen in new window, enabling reuse with few restrictions.

Getting Started

To install NumPy, we strongly recommend using a scientific Python distribution. See Installing the SciPy Stackopen in new window for details.

Many high quality online tutorials, courses, and books are available to get started with NumPy. For a quick introduction to NumPy we provide the NumPy Tutorialopen in new window. We also recommend the SciPy Lecture Notesopen in new window for a broader introduction to the scientific Python ecosystem.

For more information on the SciPy Stack (for which NumPy provides the fundamental array data structure), see scipy.orgopen in new window.


The most up-to-date NumPy documentation can be found at Latest (development) versionopen in new window. It includes a user guide, full reference documentation, a developer guide, meta information, and “NumPy Enhancement Proposals” (which include the NumPy Roadmap and detailed plans for major new features).

A complete archive of documentation for all NumPy releases (minor versions; bug fix releases don’t contain significant documentation changes) since 2009 can be found at https://docs.scipy.orgopen in new window.

Support NumPy

If you have found NumPy to be useful in your work, research or company, please consider making 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.

Donations are managed by the NumFOCUS Foundation, which is the legal and fiscal umbrella for the project. NumFOCUS is a 501(c)3 non-profit foundation, so if you are subject to US Tax law, your contribution is tax-deductible. NumPy’s Steering Councilopen in new window will make the decisions on how to best use any funds received. Technical and infrastructure priorities are documented on the NumPy Roadmapopen in new window.


Donate Now!open in new window

Institutional Partners

Institutional Partners are organizations that support the project by employing NumPy contributors, with contributing to the project as part of their official duties. Current Institutional Partners include:



NumPy receives direct funding from the following sources:

Gordon and Betty Moore FoundationAlfred P. Sloan FoundationTidelift