NumPy 1.26.2 release
Merge pull request #25128 from charris/prepare-1.26.2

REL: Prepare for the NumPy 1.26.2 release
tree: ded04f5ecb3efc60ceea1a12aedbdf063fcc3ff8
  1. .circleci/
  2. .devcontainer/
  3. .github/
  4. .spin/
  5. benchmarks/
  6. branding/
  7. doc/
  8. meson_cpu/
  9. numpy/
  10. tools/
  11. vendored-meson/
  12. .cirrus.star
  13. .clang-format
  14. .codecov.yml
  15. .coveragerc
  16. .ctags.d
  17. .gitattributes
  18. .gitignore
  19. .gitmodules
  20. .lgtm.yml
  21. .mailmap
  22. azure-pipelines.yml
  23. azure-steps-windows.yml
  24. build_requirements.txt
  25. building_with_meson.md
  26. CITATION.bib
  27. doc_requirements.txt
  28. environment.yml
  29. INSTALL.rst
  30. LICENSE.txt
  31. LICENSES_bundled.txt
  32. linter_requirements.txt
  33. MANIFEST.in
  34. meson.build
  35. meson_options.txt
  36. pavement.py
  37. pyproject.toml
  38. pyproject.toml.setuppy
  39. pytest.ini
  40. README.md
  41. release_requirements.txt
  42. runtests.py
  43. setup.cfg
  44. setup.py
  45. site.cfg.example
  46. test_requirements.txt
  47. THANKS.txt
  48. tox.ini
README.md

Powered by NumFOCUS PyPI Downloads Conda Downloads Stack Overflow Nature Paper OpenSSF Scorecard

NumPy is the fundamental package for scientific computing with Python.

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. The NumPy leadership has made a strong commitment to creating an open, inclusive, and positive community. Please read the NumPy 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 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
  • 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. 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 helps explain why, what, and how to successfully get involved.