NumPy: array processing for numbers, strings, records, and objects.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for charlesr.harris from gravatar.com charlesr.harris Avatar for matthew.brett from gravatar.com matthew.brett Avatar for mattip from gravatar.com mattip Avatar for rgommers from gravatar.com rgommers Avatar for teoliphant from gravatar.com teoliphant

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose data-base applications.

There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for charlesr.harris from gravatar.com charlesr.harris Avatar for matthew.brett from gravatar.com matthew.brett Avatar for mattip from gravatar.com mattip Avatar for rgommers from gravatar.com rgommers Avatar for teoliphant from gravatar.com teoliphant

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

2.1.3

2.1.2

2.1.1

2.1.0

2.1.0rc1 pre-release

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

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

This version

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

1.0.3

1.0

1.0rc3 pre-release

1.0rc2 pre-release

1.0rc1 pre-release

1.0b5 pre-release

1.0b4 pre-release

1.0b1 pre-release

0.9.8

0.9.6

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

numpy-1.10.0.post2.zip (4.6 MB view details)

Uploaded Source

numpy-1.10.0.post2.tar.gz (4.1 MB view details)

Uploaded Source

Built Distributions

numpy-1.10.0-cp35-cp35m-manylinux1_x86_64.whl (15.3 MB view details)

Uploaded CPython 3.5m

numpy-1.10.0-cp34-cp34m-manylinux1_x86_64.whl (15.3 MB view details)

Uploaded CPython 3.4m

numpy-1.10.0-cp33-cp33m-manylinux1_x86_64.whl (15.1 MB view details)

Uploaded CPython 3.3m

numpy-1.10.0-cp27-cp27mu-manylinux1_x86_64.whl (15.0 MB view details)

Uploaded CPython 2.7mu

numpy-1.10.0-cp27-cp27m-manylinux1_x86_64.whl (15.0 MB view details)

Uploaded CPython 2.7m

numpy-1.10.0-cp26-cp26mu-manylinux1_x86_64.whl (15.0 MB view details)

Uploaded CPython 2.6mu

numpy-1.10.0-cp26-cp26m-manylinux1_x86_64.whl (15.0 MB view details)

Uploaded CPython 2.6m

File details

Details for the file numpy-1.10.0.post2.zip.

File metadata

  • Download URL: numpy-1.10.0.post2.zip
  • Upload date:
  • Size: 4.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for numpy-1.10.0.post2.zip
Algorithm Hash digest
SHA256 35bc2e3ea058f998c3a54d869a4c8adead8b6c9a26ceb8ee5da28773ae32cb05
MD5 52d2ede7a14ce2a880bf2fce2ff1068a
BLAKE2b-256 d83d2c3204d0f180166cfea7b12c13effe2b49b4667d000411e32308c40c2f07

See more details on using hashes here.

File details

Details for the file numpy-1.10.0.post2.tar.gz.

File metadata

File hashes

Hashes for numpy-1.10.0.post2.tar.gz
Algorithm Hash digest
SHA256 2ebd29edb2f1a4a19e86cfc27c1b2283314d57509b2bfc6606b4f05d620c230b
MD5 5594d8c5c006db8901fca585a29f3620
BLAKE2b-256 5e2091f4ed6fdc3c399fc58e9af1f812a1f5cb002f479494ecacc39b6be96032

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c51659d34965cb62ca98080f49355063fbd0004064c16c671fb8ed088ab12692
MD5 f6d11025dde078dc21afe9a8d96bc461
BLAKE2b-256 3d91ad52f4587f029122d971ff0df91c6d9f13d89787a731cf2ab367869a7037

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp34-cp34m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp34-cp34m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 d924d836466e83221c0812015828a36bfd93c24bb58b3c11e61352458dd581e6
MD5 14c27ca1fb3f71057a4bc510c172ff3a
BLAKE2b-256 29305532e08b7739cc8f400b2d2b87cce02d0259211ca3ce314d35e6ae66d511

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp33-cp33m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp33-cp33m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 124881e12015ff7dcd64640f22944ec04a2a1b27c7c77028a1239c195b2a7b14
MD5 ae381e9305065a856179962e38fdf7fd
BLAKE2b-256 82edca4426942bb4a7889fadb09fb3839febecc32702500cd6a3be8026768d55

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 97a215a6cc010247a0df4d55e874d79d27fe234981ac1005c45cccdb48e9731d
MD5 3f25ccbd7796c8a8987ff72801fa6c3e
BLAKE2b-256 ac70f5aaa1fb1db7a03e01060a88ac98fec555edba5a2467cf551717352ebd93

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 05952e952ed88fb6945d4b741f7472e66be31d0568b97865a051634e7fd01c5d
MD5 d5b99f05bc979a7669b82e37a1e730a8
BLAKE2b-256 e4e17a833a762251a203c6f62a304dce9984bd15cf3474e556a1767c81f87a39

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp26-cp26mu-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp26-cp26mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 189f72f4ff774382187a82dedcae58050fa110c1bb060a98588a649859cf22df
MD5 c3feb1cd45fb3dca6f1c158ef9f75773
BLAKE2b-256 2bbb47a70c9fb37c9dd4eaaeff69482c19fcdb114e751fc60f7a9c404355526d

See more details on using hashes here.

File details

Details for the file numpy-1.10.0-cp26-cp26m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy-1.10.0-cp26-cp26m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 9f917e14e14d9a3123eb651af572fbe1fe7f8da4854ee9b22940587bb527cb23
MD5 0a2d05d03f1b1ed46b6d71f5380d26a5
BLAKE2b-256 ace2d7f789acb26b5c88c7be58ecba8e1d6a48eb0fb17074d790feadbe2318d8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page