131 lines
5.4 KiB
Plaintext
131 lines
5.4 KiB
Plaintext
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Metadata-Version: 2.1
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Name: numpy
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Version: 1.24.3
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Summary: Fundamental package for array computing in Python
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Home-page: https://www.numpy.org
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Author: Travis E. Oliphant et al.
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Maintainer: NumPy Developers
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Maintainer-email: numpy-discussion@python.org
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License: BSD-3-Clause
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Download-URL: https://pypi.python.org/pypi/numpy
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Project-URL: Bug Tracker, https://github.com/numpy/numpy/issues
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Project-URL: Documentation, https://numpy.org/doc/1.24
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Project-URL: Source Code, https://github.com/numpy/numpy
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Platform: Windows
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Platform: Linux
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Platform: Solaris
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Platform: Mac OS-X
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Platform: Unix
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Science/Research
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: BSD License
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Classifier: Programming Language :: C
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3 :: Only
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Topic :: Software Development
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Classifier: Topic :: Scientific/Engineering
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Classifier: Typing :: Typed
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Classifier: Operating System :: Microsoft :: Windows
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Classifier: Operating System :: POSIX
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Classifier: Operating System :: Unix
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Classifier: Operating System :: MacOS
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Requires-Python: >=3.8
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Description-Content-Type: text/markdown
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License-File: LICENSE.txt
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License-File: LICENSES_bundled.txt
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<h1 align="center">
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<img src="/branding/logo/primary/numpylogo.svg" width="300">
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</h1><br>
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[](
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https://numfocus.org)
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[](
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https://pypi.org/project/numpy/)
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[](
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https://anaconda.org/conda-forge/numpy)
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[](
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https://stackoverflow.com/questions/tagged/numpy)
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[](
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https://doi.org/10.1038/s41586-020-2649-2)
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[](https://api.securityscorecards.dev/projects/github.com/numpy/numpy)
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NumPy is the fundamental package for scientific computing with Python.
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- **Website:** https://www.numpy.org
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- **Documentation:** https://numpy.org/doc
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- **Mailing list:** https://mail.python.org/mailman/listinfo/numpy-discussion
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- **Source code:** https://github.com/numpy/numpy
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- **Contributing:** https://www.numpy.org/devdocs/dev/index.html
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- **Bug reports:** https://github.com/numpy/numpy/issues
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- **Report a security vulnerability:** https://tidelift.com/docs/security
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It provides:
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- a powerful N-dimensional array object
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- sophisticated (broadcasting) functions
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- tools for integrating C/C++ and Fortran code
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- useful linear algebra, Fourier transform, and random number capabilities
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Testing:
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NumPy requires `pytest` and `hypothesis`. Tests can then be run after installation with:
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python -c 'import numpy; numpy.test()'
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Code of Conduct
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----------------------
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NumPy is a community-driven open source project developed by a diverse group of
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[contributors](https://numpy.org/teams/). The NumPy leadership has made a strong
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commitment to creating an open, inclusive, and positive community. Please read the
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[NumPy Code of Conduct](https://numpy.org/code-of-conduct/) for guidance on how to interact
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with others in a way that makes our community thrive.
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Call for Contributions
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----------------------
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The NumPy project welcomes your expertise and enthusiasm!
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Small improvements or fixes are always appreciated. If you are considering larger contributions
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to the source code, please contact us through the [mailing
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list](https://mail.python.org/mailman/listinfo/numpy-discussion) first.
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Writing code isn’t the only way to contribute to NumPy. You can also:
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- review pull requests
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- help us stay on top of new and old issues
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- develop tutorials, presentations, and other educational materials
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- maintain and improve [our website](https://github.com/numpy/numpy.org)
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- develop graphic design for our brand assets and promotional materials
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- translate website content
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- help with outreach and onboard new contributors
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- write grant proposals and help with other fundraising efforts
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For more information about the ways you can contribute to NumPy, visit [our website](https://numpy.org/contribute/).
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If you’re unsure where to start or how your skills fit in, reach out! You can
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ask on the mailing list or here, on GitHub, by opening a new issue or leaving a
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comment on a relevant issue that is already open.
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Our preferred channels of communication are all public, but if you’d like to
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speak to us in private first, contact our community coordinators at
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numpy-team@googlegroups.com or on Slack (write numpy-team@googlegroups.com for
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an invitation).
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We also have a biweekly community call, details of which are announced on the
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mailing list. You are very welcome to join.
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If you are new to contributing to open source, [this
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guide](https://opensource.guide/how-to-contribute/) helps explain why, what,
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and how to successfully get involved.
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