Skip to main content

compiling Python code using LLVM

Project description

Gitter

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

Travis CI Azure Pipelines

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

numba-0.44.0.tar.gz (1.7 MB view hashes)

Uploaded Source

Built Distributions

numba-0.44.0-cp37-cp37m-win_amd64.whl (1.8 MB view hashes)

Uploaded CPython 3.7m Windows x86-64

numba-0.44.0-cp37-cp37m-win32.whl (1.8 MB view hashes)

Uploaded CPython 3.7m Windows x86

numba-0.44.0-cp37-cp37m-manylinux1_x86_64.whl (3.4 MB view hashes)

Uploaded CPython 3.7m

numba-0.44.0-cp37-cp37m-manylinux1_i686.whl (3.3 MB view hashes)

Uploaded CPython 3.7m

numba-0.44.0-cp37-cp37m-macosx_10_9_x86_64.whl (1.8 MB view hashes)

Uploaded CPython 3.7m macOS 10.9+ x86-64

numba-0.44.0-cp36-cp36m-win_amd64.whl (1.8 MB view hashes)

Uploaded CPython 3.6m Windows x86-64

numba-0.44.0-cp36-cp36m-win32.whl (1.8 MB view hashes)

Uploaded CPython 3.6m Windows x86

numba-0.44.0-cp36-cp36m-manylinux1_x86_64.whl (3.4 MB view hashes)

Uploaded CPython 3.6m

numba-0.44.0-cp36-cp36m-manylinux1_i686.whl (3.3 MB view hashes)

Uploaded CPython 3.6m

numba-0.44.0-cp36-cp36m-macosx_10_9_x86_64.whl (1.8 MB view hashes)

Uploaded CPython 3.6m macOS 10.9+ x86-64

numba-0.44.0-cp35-cp35m-win_amd64.whl (1.8 MB view hashes)

Uploaded CPython 3.5m Windows x86-64

numba-0.44.0-cp35-cp35m-win32.whl (1.8 MB view hashes)

Uploaded CPython 3.5m Windows x86

numba-0.44.0-cp35-cp35m-manylinux1_x86_64.whl (3.4 MB view hashes)

Uploaded CPython 3.5m

numba-0.44.0-cp35-cp35m-manylinux1_i686.whl (3.3 MB view hashes)

Uploaded CPython 3.5m

numba-0.44.0-cp35-cp35m-macosx_10_9_x86_64.whl (1.8 MB view hashes)

Uploaded CPython 3.5m macOS 10.9+ x86-64

numba-0.44.0-cp27-cp27mu-manylinux1_x86_64.whl (3.4 MB view hashes)

Uploaded CPython 2.7mu

numba-0.44.0-cp27-cp27mu-manylinux1_i686.whl (3.3 MB view hashes)

Uploaded CPython 2.7mu

numba-0.44.0-cp27-cp27m-win_amd64.whl (1.8 MB view hashes)

Uploaded CPython 2.7m Windows x86-64

numba-0.44.0-cp27-cp27m-win32.whl (1.8 MB view hashes)

Uploaded CPython 2.7m Windows x86

numba-0.44.0-cp27-cp27m-macosx_10_9_x86_64.whl (1.8 MB view hashes)

Uploaded CPython 2.7m macOS 10.9+ x86-64

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