Skip to content
/ numba Public
forked from numba/numba

NumPy aware dynamic Python compiler using LLVM

License

Notifications You must be signed in to change notification settings

sklam/numba

 
 

Repository files navigation

Numba

Gitter Discourse

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

Azure Pipelines

About

NumPy aware dynamic Python compiler using LLVM

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 91.8%
  • C 7.4%
  • C++ 0.6%
  • Shell 0.1%
  • Batchfile 0.1%
  • HTML 0.0%