2021-01-14 08:07:24 +01:00
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# <img alt="NumPy" src="https://cdn.rawgit.com/numpy/numpy/master/branding/icons/numpylogo.svg" height="60">
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[![Travis](https://img.shields.io/travis/numpy/numpy/master.svg?label=Travis%20CI)](
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https://travis-ci.org/numpy/numpy)
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[![Azure](https://dev.azure.com/numpy/numpy/_apis/build/status/azure-pipeline%20numpy.numpy)](
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https://dev.azure.com/numpy/numpy/_build/latest?definitionId=5)
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[![codecov](https://codecov.io/gh/numpy/numpy/branch/master/graph/badge.svg)](
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https://codecov.io/gh/numpy/numpy)
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NumPy is the fundamental package needed 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 versions ≥ 1.15 require `pytest`
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- NumPy versions < 1.15 require `nose`
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Tests can then be run after installation with:
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python -c 'import numpy; numpy.test()'
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Call for Contributions
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----------------------
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NumPy appreciates help from a wide range of different backgrounds.
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Work such as high level documentation or website improvements are valuable
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and we would like to grow our team with people filling these roles.
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Small improvements or fixes are always appreciated and issues labeled as easy
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may be a good starting point.
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If you are considering larger contributions outside the traditional coding work,
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please contact us through the mailing list.
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[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)
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