numba

compiling Python code using LLVM

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: http://numba.pydata.org

Dependencies

llvmlite
NumPy (version 1.9 or higher)
funcsigs (for Python 2)

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: http://numba.pydata.org/numba-doc/latest/user/installing.html

Documentation

http://numba.pydata.org/numba-doc/latest/index.html

Mailing Lists

Join the Numba mailing list numba-users@continuum.io: https://groups.google.com/a/continuum.io/d/forum/numba-users

Some old archives are at: http://librelist.com/browser/numba/

Continuous Integration

Project details

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

0.45.1

Aug 2, 2019

0.45.0

Jul 19, 2019

0.44.1

Jun 18, 2019

This version

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.

Files for numba, version 0.44.0
Filename, size	File type	Python version	Upload date	Hashes
Filename, size numba-0.44.0-cp27-cp27m-macosx_10_9_x86_64.whl (1.8 MB)	File type Wheel	Python version cp27	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp27-cp27mu-manylinux1_i686.whl (3.3 MB)	File type Wheel	Python version cp27	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp27-cp27mu-manylinux1_x86_64.whl (3.4 MB)	File type Wheel	Python version cp27	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp27-cp27m-win32.whl (1.8 MB)	File type Wheel	Python version cp27	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp27-cp27m-win_amd64.whl (1.8 MB)	File type Wheel	Python version cp27	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp35-cp35m-macosx_10_9_x86_64.whl (1.8 MB)	File type Wheel	Python version cp35	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp35-cp35m-manylinux1_i686.whl (3.3 MB)	File type Wheel	Python version cp35	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp35-cp35m-manylinux1_x86_64.whl (3.4 MB)	File type Wheel	Python version cp35	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp35-cp35m-win32.whl (1.8 MB)	File type Wheel	Python version cp35	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp35-cp35m-win_amd64.whl (1.8 MB)	File type Wheel	Python version cp35	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp36-cp36m-macosx_10_9_x86_64.whl (1.8 MB)	File type Wheel	Python version cp36	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp36-cp36m-manylinux1_i686.whl (3.3 MB)	File type Wheel	Python version cp36	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp36-cp36m-manylinux1_x86_64.whl (3.4 MB)	File type Wheel	Python version cp36	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp36-cp36m-win32.whl (1.8 MB)	File type Wheel	Python version cp36	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp36-cp36m-win_amd64.whl (1.8 MB)	File type Wheel	Python version cp36	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp37-cp37m-macosx_10_9_x86_64.whl (1.8 MB)	File type Wheel	Python version cp37	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp37-cp37m-manylinux1_i686.whl (3.3 MB)	File type Wheel	Python version cp37	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp37-cp37m-manylinux1_x86_64.whl (3.4 MB)	File type Wheel	Python version cp37	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp37-cp37m-win32.whl (1.8 MB)	File type Wheel	Python version cp37	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0-cp37-cp37m-win_amd64.whl (1.8 MB)	File type Wheel	Python version cp37	Upload date May 30, 2019	Hashes View hashes
Filename, size numba-0.44.0.tar.gz (1.7 MB)	File type Source	Python version None	Upload date May 30, 2019	Hashes View hashes

Hashes for numba-0.44.0-cp27-cp27m-macosx_10_9_x86_64.whl

Hashes for numba-0.44.0-cp27-cp27m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`372acfc202ed279d51698390d2c59a3e5ed4e03c04500a90c0847d04a09ddf83`
MD5	`4ca03f4ef783da23d4db03a8721ec97f`
BLAKE2-256	`d1739c93d7c8ef6832ea240a24a781c98f05ed0b2550bd818e4c6a35eb3bc999`

Hashes for numba-0.44.0-cp27-cp27mu-manylinux1_i686.whl

Hashes for numba-0.44.0-cp27-cp27mu-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`02b71c417b1e6ef28902cc978f3727cd6d8aeb7ce7cef5c8a6799c1f032ebc75`
MD5	`ca839b44926326d11d11f07d7320233f`
BLAKE2-256	`f0336c7eed010280b2997aa22c2e33158a0c50ad23f2200771ec029f69ec0eef`

Hashes for numba-0.44.0-cp27-cp27mu-manylinux1_x86_64.whl

Hashes for numba-0.44.0-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`a42cff977d15bf927f1b9525250a316d811ebe9988b725971242e2b5d8af9254`
MD5	`27db01decb303ecdfb34556189f9816b`
BLAKE2-256	`61038a944f5dcf7ebe39f94a560e578c34bcb1ae03419332c520485bb3208daa`

Hashes for numba-0.44.0-cp27-cp27m-win32.whl

Hashes for numba-0.44.0-cp27-cp27m-win32.whl
Algorithm	Hash digest
SHA256	`f8dfd14da94f4df64be8959aa9a9f804f4836fd5fe106272157c68b53367bcf8`
MD5	`6304c3a21fe87c41dc1810c54ed6bcab`
BLAKE2-256	`59b73a69336b4acf4f9e3b490ccb468406a75f95fbcc92b46afa6297beaa1f1a`

Hashes for numba-0.44.0-cp27-cp27m-win_amd64.whl

Hashes for numba-0.44.0-cp27-cp27m-win_amd64.whl
Algorithm	Hash digest
SHA256	`d4564df0b38e0750e6dc6b5326d60c75cb16a9c0ddb2275fc7c7f03e1f691863`
MD5	`7a008ba927014108bf226d884cdd0718`
BLAKE2-256	`2b309fcd6b09f5c3ed811d91b08fda039f56d2015ed1c88585f19fc7d040e2ea`

Hashes for numba-0.44.0-cp35-cp35m-macosx_10_9_x86_64.whl

Hashes for numba-0.44.0-cp35-cp35m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`0331ee6a4cbeece6b22fe71068cbf2ca450b82ab2397124c26728f5c30c779aa`
MD5	`39396e8a60bedddd9545200cd2ddc417`
BLAKE2-256	`36cfdebe4cd0a31ecf4d97557e7e53a7fa55f2cb5020d8527a21fe4c5ae59a44`

Hashes for numba-0.44.0-cp35-cp35m-manylinux1_i686.whl

Hashes for numba-0.44.0-cp35-cp35m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`be62a7dfa45dba7d677b0a6554a5445e2edf6548ebbd66913855e700338ca5dd`
MD5	`c8faac1a855521a11c16912c6f90df04`
BLAKE2-256	`c6c5ccdd95554e9ed459e7767e1ada4491016a1939d2c9641cd01527ff966c3c`

Hashes for numba-0.44.0-cp35-cp35m-manylinux1_x86_64.whl

Hashes for numba-0.44.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`6b8be1d8c9b69d3fede48deabda17db10ccc68367c7ba141f15303ac7d9204e5`
MD5	`99339c5149c8aac6740471dd2314bff3`
BLAKE2-256	`1e2171a9c0cff6831f61ad76fe0357d482d0e0e07d5c774962364e72955f60c0`

Hashes for numba-0.44.0-cp35-cp35m-win32.whl

Hashes for numba-0.44.0-cp35-cp35m-win32.whl
Algorithm	Hash digest
SHA256	`eb3c980093fa2300ea1fab6242bfb3fdcdceb07c55d3be4814c24488d294d3f5`
MD5	`ece3cfd37940efdccbc7e9024f8f8bbd`
BLAKE2-256	`e83db61ad86456364230ce9aa6b52a7fbac7af84a8b6272c0984706a12f36204`

Hashes for numba-0.44.0-cp35-cp35m-win_amd64.whl

Hashes for numba-0.44.0-cp35-cp35m-win_amd64.whl
Algorithm	Hash digest
SHA256	`01db8615724004abf6217825b774ff06be19939600f82657634cfe4a57394012`
MD5	`d6c08ad8bd05928e52819de513074571`
BLAKE2-256	`d386d4c7c5b0ed0164806bb397be9cc49ddb9340793b1bf7ab66d31fa4788823`

Hashes for numba-0.44.0-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for numba-0.44.0-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`93562a54d53677df80773d7a3722ea9d6d4d7ff5eba5c193caab6b72dc67bf0e`
MD5	`1fe004ba86bab9c9b5d9b9515abcd2ef`
BLAKE2-256	`a6ca5ba482722f95e4517b1e493cb08db04578378f80bc0ae8fe397ecdd2f835`

Hashes for numba-0.44.0-cp36-cp36m-manylinux1_i686.whl

Hashes for numba-0.44.0-cp36-cp36m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`b23e07f24403727d4688a95fb05b837c034e8b480e21caa3026afcf9e9e19ab8`
MD5	`88f3dfb078282ce42fbf39e9405cce7f`
BLAKE2-256	`72a9139cb790dad96164847a5d3dd4c0795ec910e42ba9438f93d4211644d199`

Hashes for numba-0.44.0-cp36-cp36m-manylinux1_x86_64.whl

Hashes for numba-0.44.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`878e772687ed90b01aa00013cd477d2a73697d330f4c59e7598c08e6c96ae6fc`
MD5	`d6c737f48f10dde80b5281bbceeedcc4`
BLAKE2-256	`148beff047afc373ff9f72a6ab29952a51ee076b3640fcda5a6d7500899cb9d4`

Hashes for numba-0.44.0-cp36-cp36m-win32.whl

Hashes for numba-0.44.0-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`fbcaad20d1083d814fe3cb19c95f577b629016e1589b944657a7fa72c0e91a8a`
MD5	`d61608cefdc2489407862192e527f383`
BLAKE2-256	`73a44036ce4ace033a35237c5016ab8b4245b10ecd6c2242c27f96a00c0cd2bb`

Hashes for numba-0.44.0-cp36-cp36m-win_amd64.whl

Hashes for numba-0.44.0-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`c8cc6b7b3b7ac77f66fb6cb0a474e9673e80218f8a38b2905a6ed26bba30d293`
MD5	`e1b41f451ed1ed7bd47add56130bc3b1`
BLAKE2-256	`35b064300b587ce727c78c5f6b1351ca391537ca0cb8ab9b02bc4d09c7e5fb4b`

Hashes for numba-0.44.0-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for numba-0.44.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`9c5e662a5c9a51e01cd43bed242da3a8d17b3177d8e12ac3ef68257514964804`
MD5	`bf2fb98669274bfbd016fc224bc1a35e`
BLAKE2-256	`f92674667403aeb324b0405768e0be44c26ed4ddf1e8a9c3f9744b7823b2c121`

Hashes for numba-0.44.0-cp37-cp37m-manylinux1_i686.whl

Hashes for numba-0.44.0-cp37-cp37m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`f417f64d5c97fc929b9db440c616247d7a27bf7893177b47235851c9b3fbe3ea`
MD5	`12fae99c5154f258bf4b1e7e14ad1280`
BLAKE2-256	`371ce8c696e3f890a1564a8f47870f0cd5a6e4e53cc0c75acc82f87b5af35eee`

Hashes for numba-0.44.0-cp37-cp37m-manylinux1_x86_64.whl

Hashes for numba-0.44.0-cp37-cp37m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`88d446fa366911519bc6d4844d551f65d8dd76a435fcf0753e6b7f7e43adb12a`
MD5	`a7f5149555dbc87b5c1ae35c6168ba02`
BLAKE2-256	`6713073449f4e1e1ea52304d25e4ebb4edc5ffe1d676892474a71d6f987878c2`

Hashes for numba-0.44.0-cp37-cp37m-win32.whl

Hashes for numba-0.44.0-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`41f7e7e7199cb3985392ab968e3f97f41941fe26e7fef7756664a142ddcc8df4`
MD5	`1f574bee399379028771066a224fea1a`
BLAKE2-256	`86bb0d72894ab1464b86ae8e1793600d10030e770dcb990eb5b6c5a20b7cd263`

Hashes for numba-0.44.0-cp37-cp37m-win_amd64.whl

Hashes for numba-0.44.0-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`1cc784f6231e202d762020ca3e4a9daa011a860acda9c69fee6cccb2ab587666`
MD5	`712c2e9257684b97366b07259a39ba9d`
BLAKE2-256	`1ea59322e03e05b318caba8e4796bfd23d9f871ea00f7d19fcd5840665e5beff`

Hashes for numba-0.44.0.tar.gz

Hashes for numba-0.44.0.tar.gz
Algorithm	Hash digest
SHA256	`56421bfc62f3c7c996ff11d5db7fc410909564e41b55379a82b9188fa4aa22f9`
MD5	`2a4c09597238b6104a4b0889a52b0b6f`
BLAKE2-256	`db6a52a7c3f7da7962e1c6a5948d56f053af3a20fd23b58284258a90f14d00c5`