numpy-1.26.1.dist-info/METADATA

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Metadata-Version: 2.1
Name: numpy
Version: 1.26.1
Summary: Fundamental package for array computing in Python
Home-page: https://numpy.org
Author: Travis E. Oliphant et al.
Maintainer-Email: NumPy Developers <[email protected]>
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<h1 align="center">
<img src="https://raw.githubusercontent.com/numpy/numpy/main/branding/logo/primary/numpylogo.svg" width="300">
</h1><br>


[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](
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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.
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