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The fundamental package for scientific computing with Python.
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ENH: preserve subclasses in ufunc.outer
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.circleci BUILD: pin sphinx to before-2.0.0 Mar 28, 2019
.github DOC: add a Code of Conduct document. Sep 1, 2018
benchmarks Add benchmark for sorting random array. Apr 8, 2019
branding/icons add .gitattributes and fix line endings Oct 31, 2010
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tools TST: use POWER8 OpenBLAS for CI Apr 5, 2019
.appveyor.yml MAINT: Prepare master for 1.17.0 development. Dec 8, 2018
.coveragerc TST: Add `.coveragerc` file for coverage testing. Apr 4, 2018
.ctags.d DEV: add ctags option file Dec 11, 2018
.gitignore ENH: preliminary numeric timsort Jan 21, 2019
.gitmodules Add Numpydoc as a git submodule Jul 25, 2013
.lgtm.yml Fix C/C++ build Dec 10, 2018
.mailmap DOC: Post NumPy 1.16.2 release update. Feb 27, 2019
.travis.yml TST: use POWER8 OpenBLAS for CI Apr 5, 2019
INSTALL.rst.txt DOC: update build info in INSTALL.rst.txt Jan 7, 2019
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pytest.ini DEV: cleanup imports and some assignments (from LGTM) Mar 17, 2019 Add project_urls to setup Apr 12, 2019
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NumPy is the fundamental package needed 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


  • NumPy versions ≥ 1.15 require pytest
  • NumPy versions < 1.15 require nose

Tests can then be run after installation with:

python -c 'import numpy; numpy.test()'

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