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https://github.com/numpy/numpy
The fundamental package for scientific computing with Python.
https://github.com/numpy/numpy
numpy python
Last synced: about 2 months ago
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The fundamental package for scientific computing with Python.
- Host: GitHub
- URL: https://github.com/numpy/numpy
- Owner: numpy
- License: other
- Created: 2010-09-13T23:02:39.000Z (about 14 years ago)
- Default Branch: main
- Last Pushed: 2024-04-13T23:31:50.000Z (5 months ago)
- Last Synced: 2024-04-14T06:41:10.413Z (5 months ago)
- Topics: numpy, python
- Language: Python
- Homepage: https://numpy.org
- Size: 135 MB
- Stars: 26,246
- Watchers: 593
- Forks: 9,263
- Open Issues: 2,113
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE.txt
- Citation: CITATION.bib
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README
[](
https://numfocus.org)
[](
https://pypi.org/project/numpy/)
[](
https://anaconda.org/conda-forge/numpy)
[](
https://stackoverflow.com/questions/tagged/numpy)
[](
https://doi.org/10.1038/s41586-020-2649-2)
[](https://securityscorecards.dev/viewer/?uri=github.com/numpy/numpy)
NumPy is the fundamental package for scientific computing with Python.
- **Website:** https://www.numpy.org
- **Documentation:** https://numpy.org/doc
- **Mailing list:** https://mail.python.org/mailman/listinfo/numpy-discussion
- **Source code:** https://github.com/numpy/numpy
- **Contributing:** https://www.numpy.org/devdocs/dev/index.html
- **Bug reports:** https://github.com/numpy/numpy/issues
- **Report a security vulnerability:** https://tidelift.com/docs/security
It provides:
- 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
Testing:
NumPy requires `pytest` and `hypothesis`. Tests can then be run after installation with:
python -c "import numpy, sys; sys.exit(numpy.test() is False)"
Code of Conduct
----------------------
NumPy is a community-driven open source project developed by a diverse group of
[contributors](https://numpy.org/teams/). The NumPy leadership has made a strong
commitment to creating an open, inclusive, and positive community. Please read the
[NumPy Code of Conduct](https://numpy.org/code-of-conduct/) for guidance on how to interact
with others in a way that makes our community thrive.
Call for Contributions
----------------------
The NumPy project welcomes your expertise and enthusiasm!
Small improvements or fixes are always appreciated. If you are considering larger contributions
to the source code, please contact us through the [mailing
list](https://mail.python.org/mailman/listinfo/numpy-discussion) first.
Writing code isn’t the only way to contribute to NumPy. You can also:
- review pull requests
- help us stay on top of new and old issues
- develop tutorials, presentations, and other educational materials
- maintain and improve [our website](https://github.com/numpy/numpy.org)
- develop graphic design for our brand assets and promotional materials
- translate website content
- help with outreach and onboard new contributors
- write grant proposals and help with other fundraising efforts
For more information about the ways you can contribute to NumPy, visit [our website](https://numpy.org/contribute/).
If you’re unsure where to start or how your skills fit in, reach out! You can
ask on the mailing list or here, on GitHub, by opening a new issue or leaving a
comment on a relevant issue that is already open.
Our preferred channels of communication are all public, but if you’d like to
speak to us in private first, contact our community coordinators at
[email protected] or on Slack (write [email protected] for
an invitation).
We also have a biweekly community call, details of which are announced on the
mailing list. You are very welcome to join.
If you are new to contributing to open source, [this
guide](https://opensource.guide/how-to-contribute/) helps explain why, what,
and how to successfully get involved.