Faster loops for NumPy using multithreading and other tricks

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for quansight-bot from gravatar.com quansight-bot

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Matti Picus
  • Requires: Python >=3.6
Classifiers

Project description

numpy-threading-extensions

Faster loops for NumPy using multithreading and other tricks. The first release will target NumPy binary and unary ufuncs. Eventually we will enable overriding other NumPy functions, and provide an C-based (non-Python) API for extending via third-party functions.

Travis CI Build Status

Coverage Status

License: MIT

Installation

pip install accelerated_numpy

You can also install the in-development version 0.0.1 with:

pip install https://github.com/Quansight/numpy-threading-extensions/archive/v0.0.1.zip

or latest with

pip install https://github.com/Quansight/numpy-threading-extensions/archive/main.zip

Documentation

To use the project:

    import accelerated_numpy
    accelerated_numpy.initialize()

Development

To run all the tests run::

    tox

Note, to combine the coverage data from all the tox environments run:

OS Command
Windows set PYTEST_ADDOPTS=--cov-append
tox
Other PYTEST_ADDOPTS=--cov-append tox

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for quansight-bot from gravatar.com quansight-bot

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Matti Picus
  • Requires: Python >=3.6
Classifiers

Release history Release notifications | RSS feed

This version

0.1.0

Download files

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

Source Distribution

accelerated-numpy-0.1.0.tar.gz (76.7 kB view details)

Uploaded Source

Built Distributions

accelerated_numpy-0.1.0-cp38-cp38-win_amd64.whl (325.4 kB view details)

Uploaded CPython 3.8 Windows x86-64

accelerated_numpy-0.1.0-cp38-cp38-manylinux2010_x86_64.whl (765.2 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

accelerated_numpy-0.1.0-cp38-cp38-manylinux1_x86_64.whl (765.1 kB view details)

Uploaded CPython 3.8

accelerated_numpy-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl (149.8 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

accelerated_numpy-0.1.0-cp37-cp37m-win_amd64.whl (325.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

accelerated_numpy-0.1.0-cp37-cp37m-manylinux2010_x86_64.whl (763.0 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

accelerated_numpy-0.1.0-cp37-cp37m-manylinux1_x86_64.whl (763.0 kB view details)

Uploaded CPython 3.7m

accelerated_numpy-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl (149.8 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

accelerated_numpy-0.1.0-cp36-cp36m-win_amd64.whl (325.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

accelerated_numpy-0.1.0-cp36-cp36m-manylinux2010_x86_64.whl (763.0 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

accelerated_numpy-0.1.0-cp36-cp36m-manylinux1_x86_64.whl (763.0 kB view details)

Uploaded CPython 3.6m

accelerated_numpy-0.1.0-cp36-cp36m-macosx_10_9_x86_64.whl (149.8 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file accelerated-numpy-0.1.0.tar.gz.

File metadata

  • Download URL: accelerated-numpy-0.1.0.tar.gz
  • Upload date:
  • Size: 76.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated-numpy-0.1.0.tar.gz
Algorithm Hash digest
SHA256 f7421565cf0db9d1404e46fb5c7edf55624677999c81b8162d94a37da6984b78
MD5 495ab2cf5cbea43b909bee78648144cc
BLAKE2b-256 cc6b46b7263d87bdd94338f57cc41a92d46c21c3727391b3b63d1df2217e688f

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 325.4 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 9ad4dbf6d4b311801c378f192586c54ec4db559cbb88ae4b58421458603ad0ae
MD5 444e4f5fa1557ea210429f4f67b99695
BLAKE2b-256 96f4b886598205ce0134d7068ca29147c9826097e59097037f00096b9dd4bf4e

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp38-cp38-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 765.2 kB
  • Tags: CPython 3.8, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 ac2b565169f60e4cc3783a88b1d3cd6b7254eb911692e6eb955b8524596a86fe
MD5 50d488ec91d698229f06004d434cd5ac
BLAKE2b-256 e11b8fb1f3b9fd34d1606f1a1b87cfd852a0643fbded444a1942f771e2cd4ef7

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp38-cp38-manylinux1_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp38-cp38-manylinux1_x86_64.whl
  • Upload date:
  • Size: 765.1 kB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 8b71ebc9b238d6ee14fa8c153c1bfcc60bfb63545b9b73e18e752d6c1bf0c05e
MD5 00be15e61b96c31bfbeb339f9b956055
BLAKE2b-256 ceda3785ad6f384330d6d7c4593487a0e186fe043c6436dacb122e9d7f88e00d

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 149.8 kB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 08e1534491bafd6104969b796f0dbeb480f4de1fc74b8dba74a2029882696a52
MD5 a1dc58c27615be11199e504747c238b8
BLAKE2b-256 44cdf9596f595a8200a4ebacca336859a1fdae51bac3f98813278949e90b5d89

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 325.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 8f5be63f40b434026255c15b1d2acbe9eab446bdfae8451c24b4ee20bc47f632
MD5 7276bb1a7c3c0a206c41047c5faefa96
BLAKE2b-256 071fa12587ce1bd8204433d799609c2de096fbbe5897cca2942e47f822aa7b7c

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp37-cp37m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 763.0 kB
  • Tags: CPython 3.7m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 044a7fe5a26e936d81d52b281a7ae7715256c937ab22f99adef2e5633a4f30b0
MD5 9f64cfd1c2990cd05554d64c15f88b1f
BLAKE2b-256 3f202573a70bf77c2cb0b830d3a25ef4d164c614c0f080773538531ebcc4cbc4

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 763.0 kB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c05cc071eee9ce528dfa9b06ddd9d464f173a5f3136beadaaa4fb6e7e510fa5f
MD5 d15d1b178dd49e40b30afb5a997f5a9a
BLAKE2b-256 9ac34d2d61904feacd5564b6643687122b01930bdb9dfb3c801e0c8ffc3f62ae

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 149.8 kB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 43fc701523522a8c5500bf88edc5f99ef54405e6558183b8851a99d1833be4c5
MD5 5131059b55ab1b0bf1245dcd1b7e8b48
BLAKE2b-256 526c85f90cbe5725c27cce80a609252d544d80f5b8d15adfb7e0bc5ccd081849

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 325.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 db4a13a8c56ae4671629cac1611eca9245b2e1d28b1099cac3acf278acab8035
MD5 6de95920b30b7c9c70a1b540123d46a1
BLAKE2b-256 eea3b736c70282a220eb548f49f68faa297838d4876e8c64c55e7d1bbdfc4575

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp36-cp36m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 763.0 kB
  • Tags: CPython 3.6m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bf1cb5191e5a7e62a5a8e7c30d66aa8d04b9db9ee5c26e70c02c164618b91dd5
MD5 4c9f38254b73604c5bae9a6ccb519a1b
BLAKE2b-256 e18173ae050a6472596368acada1be392b45714968a065767cb95a18026a56dd

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 763.0 kB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 56d7281a3a5979003f5474f31c7856d930576a85d79c0027121cf6748cd3488a
MD5 7b26c7879fc5d283b1b4997bee602f2e
BLAKE2b-256 91dd6d829adf835f3893eed0d317612b41da1491c8294df4adc8439dedb2d915

See more details on using hashes here.

File details

Details for the file accelerated_numpy-0.1.0-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: accelerated_numpy-0.1.0-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 149.8 kB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.6

File hashes

Hashes for accelerated_numpy-0.1.0-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4f488d7628aa0c234c64f8a593e3c93f211fce36caa32feb8d004e4814a695b3
MD5 93b9eb0eeb5fd8b5a9b65849217bdafb
BLAKE2b-256 4bd31fe9b56b609cf91f0929986fc4c129cbe451abd0cd61a12f0ba12ce4154b

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