NumPy is the fundamental package for array computing with Python.
Project description
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()'
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Hashes for numpy-1.23.0-pp38-pypy38_pp73-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 94b170b4fa0168cd6be4becf37cb5b127bd12a795123984385b8cd4aca9857e5 |
|
MD5 | 4f8142288202a32c682d01921d6c2c78 |
|
BLAKE2b-256 | 0bbd254a5f5be3105b6ee6fb0af2eccf700125a0701d15c3e6681c7ab712cb08 |
Hashes for numpy-1.23.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d0d2094e8f4d760500394d77b383a1b06d3663e8892cdf5df3c592f55f3bff66 |
|
MD5 | fef1d20265135737fbc0f91ca4441990 |
|
BLAKE2b-256 | 03039d2695dbcd168fec1e6033950f5be3fa2770d20db0cda2b36a925ecbbe09 |
Hashes for numpy-1.23.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f9c3fc2adf67762c9fe1849c859942d23f8d3e0bee7b5ed3d4a9c3eeb50a2f07 |
|
MD5 | e1462428487dc599cdffb723dec642c4 |
|
BLAKE2b-256 | cd372f84785e78b6a14e54a6cd78f6f12161835fb4868bcf1b6d36ebded68bad |
Hashes for numpy-1.23.0-cp310-cp310-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 97a76604d9b0e79f59baeca16593c711fddb44936e40310f78bfef79ee9a835f |
|
MD5 | 877322db5a62634eef4e351db99a070d |
|
BLAKE2b-256 | 341c1c9ec57f522822e7507fb5cf69b153f857405518d8f50fa4ff94f43385be |
Hashes for numpy-1.23.0-cp310-cp310-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2b2da66582f3a69c8ce25ed7921dcd8010d05e59ac8d89d126a299be60421171 |
|
MD5 | b8f06ce4054acc147845a9643bd36082 |
|
BLAKE2b-256 | 0afb03f410814f9321761f25faa257554671ff77c1a746e4641002ad90972773 |
Hashes for numpy-1.23.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d54b3b828d618a19779a84c3ad952e96e2c2311b16384e973e671aa5be1f6187 |
|
MD5 | 03c3df83b8327910482a7d24ebe9213b |
|
BLAKE2b-256 | 7a888404fbe4f6472e4e54106a8faacae1279a244422bc88f5ee3e33ba2dd72b |
Hashes for numpy-1.23.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f1d88ef79e0a7fa631bb2c3dda1ea46b32b1fe614e10fedd611d3d5398447f2f |
|
MD5 | 219017660861fdec59b852630e3fef2a |
|
BLAKE2b-256 | 85f906e90e66b9c4148ef044329da0a1c8e4f76bbf8f618a8367470f531b6433 |
Hashes for numpy-1.23.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 196cd074c3f97c4121601790955f915187736f9cf458d3ee1f1b46aff2b1ade0 |
|
MD5 | e657684ea521c50de0197aabfb44e78d |
|
BLAKE2b-256 | e6aa323e1cf4f25025c6f67dcf179db754142f92847c9d592599dc01b78de460 |
Hashes for numpy-1.23.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 58bfd40eb478f54ff7a5710dd61c8097e169bc36cc68333d00a9bcd8def53b38 |
|
MD5 | 21839aaeab3088e685d7c8d0e1856a23 |
|
BLAKE2b-256 | 8665fe6f20a40d05fc909cab9c3c17f259b03a1fbf87a6b3a7b92ca0376582e8 |
Hashes for numpy-1.23.0-cp39-cp39-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fc431493df245f3c627c0c05c2bd134535e7929dbe2e602b80e42bf52ff760bc |
|
MD5 | ff126a84dcf91700f9ca13ff606d109f |
|
BLAKE2b-256 | aab2a122ec818608b6020a8cdd7a9cc40896c5747aba8a6b4d36625e7927a540 |
Hashes for numpy-1.23.0-cp39-cp39-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d6ca8dabe696c2785d0c8c9b0d8a9b6e5fdbe4f922bde70d57fa1a2848134f95 |
|
MD5 | 49185f219512403ef23d43d6f2adbefd |
|
BLAKE2b-256 | b1db9125172436997928dd9987c1bf552513dc055bf4e302c747d9ae5ad473be |
Hashes for numpy-1.23.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 092f5e6025813e64ad6d1b52b519165d08c730d099c114a9247c9bb635a2a450 |
|
MD5 | 6ff50a994f6006349b5f1415e4da6f45 |
|
BLAKE2b-256 | da0e496e529f440f528273f6847e14d7b132b0556a824fc2af36e8afd8e6a020 |
Hashes for numpy-1.23.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 79a506cacf2be3a74ead5467aee97b81fca00c9c4c8b3ba16dbab488cd99ba10 |
|
MD5 | 06d5cd49de096482944dead2eb92d783 |
|
BLAKE2b-256 | 532eacd76ea66fd4b5e02dd572101c2628a134f3fdedcaef10175dab2d5398aa |
Hashes for numpy-1.23.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 98e8e0d8d69ff4d3fa63e6c61e8cfe2d03c29b16b58dbef1f9baa175bbed7860 |
|
MD5 | ba5729353c3521ed7ee72c796e77a546 |
|
BLAKE2b-256 | 8ba56b5a75f87cb330460398e8c7be7399d9f1c75c9b1a73888d4952a50184b0 |
Hashes for numpy-1.23.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1c29b44905af288b3919803aceb6ec7fec77406d8b08aaa2e8b9e63d0fe2f160 |
|
MD5 | dc2a5c5d2223f7b45a45f7f760d0f2db |
|
BLAKE2b-256 | afe3e2cbfbf5b36706416aea1f17ec4ef454360e8e0177782dda43befcb43177 |
Hashes for numpy-1.23.0-cp38-cp38-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5043bcd71fcc458dfb8a0fc5509bbc979da0131b9d08e3d5f50fb0bbb36f169a |
|
MD5 | 60c7d27cf92dadb6d206df6e65b1032f |
|
BLAKE2b-256 | 14eedd565fd9cfcb08c50dd406d463afcb74f95cde1e1f5477cc2edcf28a3683 |
Hashes for numpy-1.23.0-cp38-cp38-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fe8b9683eb26d2c4d5db32cd29b38fdcf8381324ab48313b5b69088e0e355379 |
|
MD5 | 449bfa2d55aff3e722d2fc85a7549620 |
|
BLAKE2b-256 | b083d0e88feb2af9b66f11aac16b2ca2cc5e7450e297c1b922d32bf5beabe088 |
Hashes for numpy-1.23.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ae8adff4172692ce56233db04b7ce5792186f179c415c37d539c25de7298d25d |
|
MD5 | 771a1f7e488327645bac5b54dd2f6286 |
|
BLAKE2b-256 | 936dd63d5fb9077d3b29ae2792624b3705b8689023cae0f89f9bf72146c34b59 |
Hashes for numpy-1.23.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ac86f407873b952679f5f9e6c0612687e51547af0e14ddea1eedfcb22466babd |
|
MD5 | 22d43465791814fe50e03ded430bd80c |
|
BLAKE2b-256 | 616441216b0c4aba7e41aff0e8cdfd91bcd4b08e1089d347d90f5ba7bc191ba2 |
Hashes for numpy-1.23.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f0f18804df7370571fb65db9b98bf1378172bd4e962482b857e612d1fec0f53e |
|
MD5 | 5514a0030e5cf065e916950737d6d129 |
|
BLAKE2b-256 | 82f68d883503328426abf4292b102cf4fe0c86abcde99cf3aeea4f7c0ed1765b |
Hashes for numpy-1.23.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d8cc87bed09de55477dba9da370c1679bd534df9baa171dd01accbb09687dac3 |
|
MD5 | 7bb54f95e74306eff733466b6343695f |
|
BLAKE2b-256 | 1a8911ffd13e174d5cdfa55065dd51620a11c3c63275ef855bb1f8c36c01e1e9 |