numpy

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
and much more

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

All NumPy wheels distributed on PyPI are BSD licensed.

NumPy requires pytest and hypothesis. Tests can then be run after installation with:

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

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1.21.6

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1.14.0

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1.13.3

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1.13.1

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1.13.0

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1.12.1

Mar 18, 2017

1.12.0

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1.11.3

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1.11.1

Jun 26, 2016

1.11.0

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1.10.4

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1.10.3

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1.10.2

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1.10.1

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1.10.0

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1.9.3

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Mar 1, 2015

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1.7.2

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1.6.2

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1.4.1

Apr 24, 2010

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Dec 28, 2009

1.3.0

Apr 5, 2009

1.2.1

Oct 29, 2008

1.2.0

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1.1.1

Aug 6, 2008

1.0.4

Nov 7, 2007

1.0.3

May 23, 2007

1.0

Oct 25, 2006

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Oct 19, 2006

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numpy 1.23.1

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