Numba
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A Just-In-Time Compiler for Numerical Functions in Python
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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
- Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit),
-
(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
- NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows,
Dependencies
- Python versions: 3.6-3.8
- llvmlite 0.31.*
- NumPy >=1.15 (can build with 1.11 for ABI compatibility)
Optionally:
- Scipy >=1.0.0 (for
numpy.linalgsupport)
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
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:alt: Travis CI
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:alt: Azure Pipelines