compiling Python code using LLVM

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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: https://numba.pydata.org and the online documentation: https://numba.readthedocs.io/en/stable/index.html

Installation

Please follow the instructions:

https://numba.readthedocs.io/en/stable/user/installing.html

Demo

Please have a look and the demo notebooks via the mybinder service:

https://mybinder.org/v2/gh/numba/numba-examples/master?filepath=notebooks

Contact

Numba has a discourse forum for discussions:

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0.60.0

0.60.0rc1 pre-release

0.59.1

0.59.0

0.59.0rc1 pre-release

0.58.1

0.58.0

0.58.0rc2 pre-release

0.58.0rc1 pre-release

This version

0.57.1

0.57.1rc1 pre-release

0.57.0

0.57.0rc1 pre-release

0.56.4

0.56.3

0.56.2

0.56.0

0.56.0rc1 pre-release

0.55.2

0.55.1

0.55.0

0.55.0rc1 pre-release

0.54.1

0.54.1rc1 pre-release

0.54.0

0.54.0rc3 pre-release

0.54.0rc2 pre-release

0.53.1

0.53.0

0.53.0rc3 pre-release

0.53.0rc2 pre-release

0.53.0rc1.post1 pre-release

0.52.0

0.52.0rc3 pre-release

0.52.0rc2 pre-release

0.51.2

0.51.1

0.51.0

0.51.0rc1 pre-release

0.50.1

0.50.0

0.50.0rc1 pre-release

0.49.1

0.49.1rc1 pre-release

0.49.0

0.48.0

0.47.0

0.46.0

0.45.1

0.45.0

0.44.1

0.44.0

0.43.1

0.43.0

0.42.1

0.42.0

0.41.0

0.40.1

0.40.0

0.39.0

0.38.1

0.38.0

0.37.0

0.36.2

0.36.1

0.35.0

0.34.0

0.33.0

0.32.0

0.31.0

0.30.1

0.30.0

0.29.0

0.28.1

0.27.0

0.26.0

0.25.0

0.24.0

0.23.1

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0.22.1

0.22.0

0.21.0

0.20.0

0.19.2

0.19.1

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0.18.1

0.17.0

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0.15.1

0.14.0

0.13.4

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0.13.2

0.13.0

0.12.2

0.12.1

0.12.0

0.11.0

0.10.1

0.10.0

0.9.0

0.8.1

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0.7.1

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