131 lines
5.4 KiB
Plaintext
131 lines
5.4 KiB
Plaintext
Metadata-Version: 2.1
|
||
Name: numpy
|
||
Version: 1.24.3
|
||
Summary: Fundamental package for array computing in Python
|
||
Home-page: https://www.numpy.org
|
||
Author: Travis E. Oliphant et al.
|
||
Maintainer: NumPy Developers
|
||
Maintainer-email: numpy-discussion@python.org
|
||
License: BSD-3-Clause
|
||
Download-URL: https://pypi.python.org/pypi/numpy
|
||
Project-URL: Bug Tracker, https://github.com/numpy/numpy/issues
|
||
Project-URL: Documentation, https://numpy.org/doc/1.24
|
||
Project-URL: Source Code, https://github.com/numpy/numpy
|
||
Platform: Windows
|
||
Platform: Linux
|
||
Platform: Solaris
|
||
Platform: Mac OS-X
|
||
Platform: Unix
|
||
Classifier: Development Status :: 5 - Production/Stable
|
||
Classifier: Intended Audience :: Science/Research
|
||
Classifier: Intended Audience :: Developers
|
||
Classifier: License :: OSI Approved :: BSD License
|
||
Classifier: Programming Language :: C
|
||
Classifier: Programming Language :: Python
|
||
Classifier: Programming Language :: Python :: 3
|
||
Classifier: Programming Language :: Python :: 3.8
|
||
Classifier: Programming Language :: Python :: 3.9
|
||
Classifier: Programming Language :: Python :: 3.10
|
||
Classifier: Programming Language :: Python :: 3.11
|
||
Classifier: Programming Language :: Python :: 3 :: Only
|
||
Classifier: Programming Language :: Python :: Implementation :: CPython
|
||
Classifier: Topic :: Software Development
|
||
Classifier: Topic :: Scientific/Engineering
|
||
Classifier: Typing :: Typed
|
||
Classifier: Operating System :: Microsoft :: Windows
|
||
Classifier: Operating System :: POSIX
|
||
Classifier: Operating System :: Unix
|
||
Classifier: Operating System :: MacOS
|
||
Requires-Python: >=3.8
|
||
Description-Content-Type: text/markdown
|
||
License-File: LICENSE.txt
|
||
License-File: LICENSES_bundled.txt
|
||
|
||
<h1 align="center">
|
||
<img src="/branding/logo/primary/numpylogo.svg" width="300">
|
||
</h1><br>
|
||
|
||
|
||
[](
|
||
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://api.securityscorecards.dev/projects/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; numpy.test()'
|
||
|
||
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
|
||
numpy-team@googlegroups.com or on Slack (write numpy-team@googlegroups.com 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.
|
||
|
||
|