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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Newer release available (2.5.1)

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Credits

Author: Travis E. Oliphant et al.

Maintainer: NumPy Developers

License

BSD License (BSD)

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Python >=3.8

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2.5.1

2.5.0

2.5.0rc1 pre-release

2.4.6

2.4.5

2.4.4

2.4.3

2.4.2

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Backward compatibility bug

2.4.0rc1 pre-release

2.3.5

2.3.4

2.3.3

2.3.2

2.3.1

2.3.0

2.2.6

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2.2.3

2.2.2

2.2.1

2.2.0

2.1.3

2.1.2

2.1.1

2.1.0

2.0.2

2.0.1

2.0.0

1.26.4

1.26.3

1.26.2

1.26.1

1.26.0

1.25.2

1.25.1

1.25.0

1.24.4

1.24.3

1.24.2

1.24.1

1.24.0

This release

1.23.5

1.23.4

1.23.3

1.23.2

1.23.1

1.23.0

1.22.4

1.22.3

1.22.2

1.22.1

1.22.0

1.21.6

1.21.5

1.21.4

1.21.3

1.21.2

1.21.1

1.21.0

1.20.3

1.20.2

1.20.1

1.20.0

1.19.5

1.19.4

1.19.3

1.19.2

1.19.1

1.19.0

1.18.5

1.18.4

1.18.3

1.18.2

1.18.1

1.18.0

1.17.5

1.17.4

1.17.3

1.17.2

1.17.1

1.17.0

1.16.6

1.16.5

1.16.4

1.16.3

1.16.2

1.16.1

1.16.0

1.15.4

1.15.3

1.15.2

1.15.1

1.15.0

1.14.6

1.14.5

1.14.4

1.14.3

1.14.2

1.14.1

1.14.0

1.13.3

1.13.1

1.13.0

1.12.1

1.12.0

1.11.3

1.11.2

1.11.1

1.11.0

1.10.4

1.10.3

1.10.2

1.10.1

1.10.0

1.9.3

1.9.2

1.9.1

1.9.0

1.8.2

1.8.1

1.8.0

1.7.2

1.7.1

1.7.0

1.6.2

1.6.1

1.6.0

1.5.1

1.5.0

1.4.1

1.4.0

1.3.0

1.2.1

1.2.0

1.1.1

1.0.4

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1.0

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