• noarch v0.50.0
• osx-64 v0.26.0.dev
• win-32 v0.16dev1
• win-64 v0.30.0.dev

pip install

Authentication Prerequisites:
TOKEN=$(anaconda auth --create --name download-token)

To install this package run one of the following:
pip install -i https://pypi.anaconda.org/t/$TOKEN/sklam/simple numba
pip install -i https://pypi.anaconda.org/t/$TOKEN/sklam/label/airflow/simple numba

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conda install

Authentication Prerequisites:
anaconda login

To install this package run one of the following:
conda install sklam::numba
conda install sklam/label/airflow::numba

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Numba

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.. image:: https://badges.gitter.im/numba/numba.svg :target: https://gitter.im/numba/numba?utmsource=badge&utmmedium=badge&utm_campaign=pr-badge :alt: 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

Supported Platforms

• Operating systems and CPU:

  • Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit), ARMv8 (64-bit)
  • Windows: x86, x86_64
  • macOS: x86_64

• (Optional) Accelerators and GPUs:

  • NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows, macOS (< 10.14)
  • AMD GPUs via ROCm driver on Linux

Dependencies

• Python versions: 3.6-3.8
• llvmlite 0.33.*
• NumPy >=1.15 (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: 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 [email protected]: https://groups.google.com/a/continuum.io/d/forum/numba-users

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

Continuous Integration

.. image:: https://dev.azure.com/numba/numba/apis/build/status/numba.numba?branchName=master :target: https://dev.azure.com/numba/numba/build/latest?definitionId=1?branchName=master :alt: Azure Pipelines