numba

compiling Python code using LLVM

These details have been verified by PyPI

Maintainers

esc kc611 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 compiler for Python array and numerical functions

Numba is an Open Source NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the remarkable LLVM compiler infrastructure to compile Python syntax to machine code.

It is aware of NumPy arrays as typed memory regions and so can speed-up code using NumPy arrays. Other, less well-typed code will be translated to Python C-API calls effectively removing the “interpreter” but not removing the dynamic indirection.

Numba is also not a tracing JIT. It compiles your code before it gets run either using run-time type information or type information you provide in the decorator.

Numba is a mechanism for producing machine code from Python syntax and typed data structures such as those that exist in NumPy.

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

If you wanted to compile Numba from source, it is recommended to use conda environment to maintain multiple isolated development environments. To create a new environment for Numba development:

$ conda create -p ~/dev/mynumba python numpy llvmlite

To select the installed version, append “=VERSION” to the package name, where, “VERSION” is the version number. For example:

$ conda create -p ~/dev/mynumba python=2.7 numpy=1.9 llvmlite

to use Python 2.7 and Numpy 1.9.

If you need CUDA support, you should also install the CUDA toolkit:

$ conda install cudatoolkit

This installs the CUDA Toolkit version 8.0, which requires driver version 375.x or later to be installed.

Custom Python Environments

If you’re not using conda, you will need to build llvmlite yourself:

Building and installing llvmlite

See https://github.com/numba/llvmlite for the most up-to-date instructions. You will need a build of LLVM 6.0.x.

$ git clone https://github.com/numba/llvmlite
$ cd llvmlite
$ python setup.py install

Installing Numba

$ git clone https://github.com/numba/numba.git
$ cd numba
$ pip install -r requirements.txt
$ python setup.py build_ext --inplace
$ python setup.py install

or simply

$ pip install numba

If you want to enable CUDA support, you will need to install CUDA Toolkit 8.0. After installing the toolkit, you might have to specify environment variables in order to override the standard search paths:

NUMBAPRO_CUDA_DRIVER: Path to the CUDA driver shared library
NUMBAPRO_NVVM: Path to the CUDA libNVVM shared library file
NUMBAPRO_LIBDEVICE: Path to the CUDA libNVVM libdevice directory which contains .bc files

Documentation

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

Mailing Lists

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

or access it through the Gmane mirror: http://news.gmane.org/gmane.comp.python.numba.user

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

Website

See if our sponsor can help you (which can help this project): https://www.anaconda.com

http://numba.pydata.org

Continuous Integration

https://travis-ci.org/numba/numba

Project details

These details have been verified by PyPI

Maintainers

esc kc611 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

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

This version

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

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numba 0.39.0

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A compiler for Python array and numerical functions

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