numba

compiling Python code using LLVM

These details have been verified by PyPI

Maintainers

esc seibert Siu.Kwan.Lam teoliphant

These details have not been verified by PyPI

Project links

Homepage

Development Status
- 4 - Beta
Intended Audience
- Developers
License
- OSI Approved :: BSD License
Operating System
- OS Independent
Programming Language
Topic
- Software Development :: Compilers

Project description

A Just-In-Time Compiler for Numerical Functions in Python

Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax.

Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.

For more information about Numba, see the Numba homepage: https://numba.pydata.org

Supported Platforms

Operating systems and CPUs:
- Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit), ARMv8 (64-bit).
- Windows: x86, x86_64.
- macOS: x86_64, (M1/Arm64, unofficial support only).
- *BSD: (unofficial support only).
(Optional) Accelerators and GPUs:
- NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows, macOS (< 10.14).

Dependencies

Python versions: 3.7-3.9
llvmlite 0.37.*
NumPy >=1.17,<1.21 (can build with 1.11 for ABI compatibility).

Optionally:

SciPy >=1.0.0 (for numpy.linalg support).

Installing

The easiest way to install Numba and get updates is by using the Anaconda Distribution: https://www.anaconda.com/download

$ conda install numba

For more options, see the Installation Guide: https://numba.readthedocs.io/en/stable/user/installing.html

Documentation

https://numba.readthedocs.io/en/stable/index.html

Mailing Lists

Numba has a discourse forum for discussions:

https://numba.discourse.groups

Some old mailing list archives are at:

Continuous Integration

Project details

These details have been verified by PyPI

Maintainers

esc seibert Siu.Kwan.Lam teoliphant

These details have not been verified by PyPI

Project links

Homepage

Development Status
- 4 - Beta
Intended Audience
- Developers
License
- OSI Approved :: BSD License
Operating System
- OS Independent
Programming Language
Topic
- Software Development :: Compilers

Release history Release notifications | RSS feed

0.60.0

Jun 13, 2024

0.60.0rc1 pre-release

May 15, 2024

0.59.1

Mar 19, 2024

0.59.0

Jan 31, 2024

0.59.0rc1 pre-release

Dec 15, 2023

0.58.1

Oct 18, 2023

0.58.0

Sep 21, 2023

0.58.0rc2 pre-release

Sep 12, 2023

0.58.0rc1 pre-release

Aug 18, 2023

0.57.1

Jun 21, 2023

0.57.1rc1 pre-release

Jun 12, 2023

0.57.0

May 2, 2023

0.57.0rc1 pre-release

Apr 6, 2023

0.56.4

Nov 4, 2022

0.56.3

Oct 14, 2022

0.56.2

Sep 2, 2022

0.56.0

Jul 26, 2022

0.56.0rc1 pre-release

Jun 29, 2022

0.55.2

May 26, 2022

0.55.1

Jan 27, 2022

0.55.0

Jan 14, 2022

0.55.0rc1 pre-release

Dec 16, 2021

0.54.1

Oct 8, 2021

0.54.1rc1 pre-release

Sep 24, 2021

0.54.0

Aug 20, 2021

This version

0.54.0rc3 pre-release

Aug 5, 2021

0.54.0rc2 pre-release

Jul 19, 2021

0.53.1

Mar 26, 2021

0.53.0

Mar 12, 2021

0.53.0rc3 pre-release

Mar 5, 2021

0.53.0rc2 pre-release

Feb 26, 2021

0.53.0rc1.post1 pre-release

Feb 9, 2021

0.52.0

Dec 1, 2020

0.52.0rc3 pre-release

Nov 19, 2020

0.52.0rc2 pre-release

Oct 30, 2020

0.51.2

Sep 3, 2020

0.51.1

Aug 27, 2020

0.51.0

Aug 14, 2020

0.51.0rc1 pre-release

Aug 6, 2020

0.50.1

Jun 25, 2020

0.50.0

Jun 11, 2020

0.50.0rc1 pre-release

Jun 4, 2020

0.49.1

May 8, 2020

0.49.1rc1 pre-release

May 1, 2020

0.49.0

Apr 17, 2020

0.48.0

Jan 29, 2020

0.47.0

Jan 3, 2020

0.46.0

Oct 10, 2019

0.45.1

Aug 2, 2019

0.45.0

Jul 19, 2019

0.44.1

Jun 18, 2019

0.44.0

May 30, 2019

0.43.1

Mar 26, 2019

0.43.0

Mar 13, 2019

0.42.1

Feb 1, 2019

0.42.0

Dec 31, 2018

0.41.0

Nov 28, 2018

0.40.1

Oct 10, 2018

0.40.0

Sep 21, 2018

0.39.0

Jul 10, 2018

0.38.1

Jun 1, 2018

0.38.0

Apr 24, 2018

0.37.0

Feb 19, 2018

0.36.2

Dec 20, 2017

0.36.1

Dec 8, 2017

0.35.0

Sep 8, 2017

0.34.0

Jul 7, 2017

0.33.0

May 8, 2017

0.32.0

Apr 10, 2017

0.31.0

Feb 17, 2017

0.30.1

Jan 13, 2017

0.30.0

Dec 22, 2016

0.29.0

Oct 19, 2016

0.28.1

Aug 31, 2016

0.27.0

Jul 11, 2016

0.26.0

May 23, 2016

0.25.0

Apr 4, 2016

0.24.0

Mar 3, 2016

0.23.1

Jan 21, 2016

0.23.0

Jan 14, 2016

0.22.1

Nov 4, 2015

0.22.0

Oct 30, 2015

0.21.0

Sep 14, 2015

0.20.0

Jul 2, 2015

0.19.2

Jun 9, 2015

0.19.1

Jun 5, 2015

0.18.2

Apr 9, 2015

0.18.1

Apr 3, 2015

0.17.0

Feb 4, 2015

0.16.0

Dec 16, 2014

0.15.1

Oct 15, 2014

0.14.0

Sep 11, 2014

0.13.4

Aug 1, 2014

0.13.3

Jul 11, 2014

0.13.2

Jun 9, 2014

0.13.0

Mar 21, 2014

0.12.2

Mar 4, 2014

0.12.1

Feb 20, 2014

0.12.0

Feb 10, 2014

0.11.0

Sep 26, 2013

0.10.1

Sep 4, 2013

0.10.0

Aug 5, 2013

0.9.0

Jun 4, 2013

0.8.1

May 3, 2013

0.8.0

Apr 16, 2013

0.7.2

Mar 20, 2013

0.7.1

Mar 11, 2013

0.7.0

Mar 4, 2013

0.6.0

Feb 5, 2013

0.5.0

Jan 19, 2013

0.3

Nov 11, 2012

0.2

Oct 4, 2012

0.1

Aug 15, 2012

Download files

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

Source Distribution

numba-0.54.0rc3.tar.gz (2.2 MB view hashes)

Uploaded Aug 5, 2021 Source

Built Distributions

numba-0.54.0rc3-cp39-cp39-win_amd64.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 Windows x86-64

numba-0.54.0rc3-cp39-cp39-win32.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 Windows x86

numba-0.54.0rc3-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.4 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 manylinux: glibc 2.17+ x86-64

numba-0.54.0rc3-cp39-cp39-manylinux2014_i686.manylinux_2_17_i686.whl (3.1 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 manylinux: glibc 2.17+ i686

numba-0.54.0rc3-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (3.2 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 manylinux: glibc 2.17+ ARM64

numba-0.54.0rc3-cp39-cp39-macosx_10_14_x86_64.whl (2.2 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.9 macOS 10.14+ x86-64

numba-0.54.0rc3-cp38-cp38-win_amd64.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 Windows x86-64

numba-0.54.0rc3-cp38-cp38-win32.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 Windows x86

numba-0.54.0rc3-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.5 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 manylinux: glibc 2.17+ x86-64

numba-0.54.0rc3-cp38-cp38-manylinux2014_i686.manylinux_2_17_i686.whl (3.1 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 manylinux: glibc 2.17+ i686

numba-0.54.0rc3-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (3.2 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 manylinux: glibc 2.17+ ARM64

numba-0.54.0rc3-cp38-cp38-macosx_10_14_x86_64.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.8 macOS 10.14+ x86-64

numba-0.54.0rc3-cp37-cp37m-win_amd64.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m Windows x86-64

numba-0.54.0rc3-cp37-cp37m-win32.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m Windows x86

numba-0.54.0rc3-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.4 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m manylinux: glibc 2.17+ x86-64

numba-0.54.0rc3-cp37-cp37m-manylinux2014_i686.manylinux_2_17_i686.whl (3.1 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m manylinux: glibc 2.17+ i686

numba-0.54.0rc3-cp37-cp37m-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (3.2 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m manylinux: glibc 2.17+ ARM64

numba-0.54.0rc3-cp37-cp37m-macosx_10_14_x86_64.whl (2.3 MB view hashes)

Uploaded Aug 5, 2021 CPython 3.7m macOS 10.14+ x86-64

Hashes for numba-0.54.0rc3.tar.gz

Hashes for numba-0.54.0rc3.tar.gz
Algorithm	Hash digest
SHA256	`8d0082fbf9fda32ee48a8135f449b3a01f04d9813470625072f3ce834fda432f`
MD5	`e31e0eb225868ef47b8b470a0374a840`
BLAKE2b-256	`ec74f6ff055664ac01adac37ad8f5ab5c94d75badfd264fdab209e0f5f1fafef`

Hashes for numba-0.54.0rc3-cp39-cp39-win_amd64.whl

Hashes for numba-0.54.0rc3-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`9449798ac642ee7d95641f11bdd58bbca05b0498d4824244946cedaab1b5f768`
MD5	`30de2451612c40c46c9bd6addb086567`
BLAKE2b-256	`0fc3c2f7f32dd5354135dd358c5916b40559e42a1fb9ece88816b164d5bb5e04`

Hashes for numba-0.54.0rc3-cp39-cp39-win32.whl

Hashes for numba-0.54.0rc3-cp39-cp39-win32.whl
Algorithm	Hash digest
SHA256	`cae1d160114a506776a04458fa2cc891b9f92f349d8e7961b932856e98d3a005`
MD5	`8cc9c52c2d522e3e7ae367695164993a`
BLAKE2b-256	`7b673df834ca8825918d5f3b5dc74cbe2f32a046f739c8bf798cbab20c014ba9`

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm	Hash digest
SHA256	`c08074584fe4892186a0c51468255fc03fabc2fd5bb208ded18257851ec5504b`
MD5	`36a901c2838a2dc2ddad96e214f7c005`
BLAKE2b-256	`60cfedcd71ce00dd63cdae8e4e740fc0f22528e01fa971b30a518a255e943b22`

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_i686.manylinux_2_17_i686.whl

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_i686.manylinux_2_17_i686.whl
Algorithm	Hash digest
SHA256	`4132ef933a683d5e00795712840dd4ece63f2f3c244a26e862ef5a9d57e001cb`
MD5	`5b1ed9a3d010c0ab5056e4d2395105fa`
BLAKE2b-256	`ec1f44e853073283da6f766b598dfbfa59697a9e3d4b87a58c51dede139a72e2`

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl

Hashes for numba-0.54.0rc3-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
Algorithm	Hash digest
SHA256	`36e115a2f88e3a48ef921ce8757298352c0eef3211fda24adf2ff4a3d4daa62c`
MD5	`9b68fb9fddf16eb266fc493d2dd68840`
BLAKE2b-256	`c7e7b18088787930faba93dddbe3730957ddc4f2dc8a50ecce21b1ae1a955f73`

Hashes for numba-0.54.0rc3-cp39-cp39-macosx_10_14_x86_64.whl

Hashes for numba-0.54.0rc3-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`2ae4b97c68160f0dce752d2b8f9e4a340e597e1ec3f58c7426e17cd88d1f896f`
MD5	`751bfc1433e94d4420a8ca9addc543bb`
BLAKE2b-256	`692d244e73d092e5fb9f932c5524fbdbaf8374554d91a1b721f1e78e61035c89`

Hashes for numba-0.54.0rc3-cp38-cp38-win_amd64.whl

Hashes for numba-0.54.0rc3-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`a0990520e023c19808e28842c2c367dcd691c5ff7dc0f78342014acd28d4ca9a`
MD5	`64bb4a951fbb9832892b8e7cb7153816`
BLAKE2b-256	`a9f44efa6274630ca9601f005a0c84fb908f26ebc4a8a51c6e86aab6b087954b`

Hashes for numba-0.54.0rc3-cp38-cp38-win32.whl

Hashes for numba-0.54.0rc3-cp38-cp38-win32.whl
Algorithm	Hash digest
SHA256	`91179b823102cf8d82f60531e4317f0b0fb8d5e8c77b3cda8003af67cd816729`
MD5	`fc7caa28fe9cf156623b6f97b3c01382`
BLAKE2b-256	`1b35c0378a9693ac9cd557e5686e7e99683ab5282ee0030f691aac593892371f`

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm	Hash digest
SHA256	`2815fbda33cff57db01a971bf7450a4ff94fee83fe812a264c11b2771a66c7b1`
MD5	`0c4e5afcb6418a0ebd8b36999f9af044`
BLAKE2b-256	`1d371200e67f2fca2469c7c6c75e012aec02f18ef8d42cda75692fcabdc9e128`

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_i686.manylinux_2_17_i686.whl

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_i686.manylinux_2_17_i686.whl
Algorithm	Hash digest
SHA256	`4d0298e4661c7b543fe00f60962daaa1269d8b903f4502d1cca39ad974a64695`
MD5	`25e2a3d92cbc93f7ad30b8100e7ff7a5`
BLAKE2b-256	`4d8f73ef79d2004d6fcce7766d99930140d4a36806870e41dc5dac69cc799a92`

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl

Hashes for numba-0.54.0rc3-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
Algorithm	Hash digest
SHA256	`a61c465936b4e267e800a2b18d8cf6b89c4a78e6c590f372de8a4e4a89109da9`
MD5	`6a180130544ba9fdf05ff2cd928db325`
BLAKE2b-256	`a636aea5b0ec22f823f3a0bb66ad72499ccc3bd9e8447346e2bcbf66bed9ae37`

Hashes for numba-0.54.0rc3-cp38-cp38-macosx_10_14_x86_64.whl

Hashes for numba-0.54.0rc3-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`34327b6090019ec48e743c5607949dc0f735f83c84d6f5b570dd441c9a36b473`
MD5	`4a526e547a9af3e6baa4d93e70a43133`
BLAKE2b-256	`87a4efd5e80f22d3485bd2d1ddff3caba3eded86bc8cd3c3ff6fcfdf51fd08f1`

Hashes for numba-0.54.0rc3-cp37-cp37m-win_amd64.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`23bafad556e23a57216c50efdf2ac85236696bacbdc212ad7bfcc78583352cda`
MD5	`fbcae61edd1ca1d45767ba0ece93a3c7`
BLAKE2b-256	`ee0520df13bbc2b68a9ddd2b976bf00a82a84113bee8b0d116719f6c25293f5c`

Hashes for numba-0.54.0rc3-cp37-cp37m-win32.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`5187ada18145c399b7642b5eec8003d8e991d62b5a468438ba2c54f2cff6d444`
MD5	`0e0a898a0510378113d29ac2762cc917`
BLAKE2b-256	`1777541667035e84a670924fae317344f9f0ff114d88518833723da7bdc08879`

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm	Hash digest
SHA256	`cfacaf9ae420203b11c2675ce80562f8250d10073ade8ffa8782a5ba083293b2`
MD5	`bc28f791460b0bcd48933f7b975a9bef`
BLAKE2b-256	`f2dcc2e66993c4f6c42558ca52ed5034dc9b60b42951afae658d74c713e2c462`

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_i686.manylinux_2_17_i686.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_i686.manylinux_2_17_i686.whl
Algorithm	Hash digest
SHA256	`972d66c996392da6b9164d2d72a354559505be63dc376c06fae6d6be9df40d4a`
MD5	`43edf6fbdcf553a962cde2a01269c7e7`
BLAKE2b-256	`e32a3afeecaff285ba205a8647475b082ad49b0ef4e82c8f6225e2d378b29b92`

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_aarch64.manylinux_2_17_aarch64.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
Algorithm	Hash digest
SHA256	`5db89e5c1706f2a9bfb91c8b25e9f4460b780125d19500c440376367f6519179`
MD5	`27e547b285dc1ff9265adde1edaa52fa`
BLAKE2b-256	`e0bd0d61a8155ff3693844154c9641b4452e7552164c34fbe41f12d970ab94ed`

Hashes for numba-0.54.0rc3-cp37-cp37m-macosx_10_14_x86_64.whl

Hashes for numba-0.54.0rc3-cp37-cp37m-macosx_10_14_x86_64.whl
Algorithm	Hash digest
SHA256	`b3564d42c2daad79ccf1e88a302add7ecd8b0e6f3900cb9d644a0525493d7819`
MD5	`39aff839b05369e0742335cb3f01ada9`
BLAKE2b-256	`ed78768ff9937d680f2e1389591bd89803af58468ba3124060c9399c046a4793`