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Numba
.. image:: https://badges.gitter.im/numba/numba.svg :target: https://gitter.im/numba/numba?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge :alt: Gitter
.. image:: https://img.shields.io/badge/discuss-on%20discourse-blue :target: https://numba.discourse.group/ :alt: Discourse
.. image:: https://zenodo.org/badge/3659275.svg :target: https://zenodo.org/badge/latestdoi/3659275 :alt: Zenodo DOI
.. image:: https://img.shields.io/pypi/v/numba.svg :target: https://pypi.python.org/pypi/numba/ :alt: PyPI
.. image:: https://dev.azure.com/numba/numba/_apis/build/status/numba.numba?branchName=main :target: https://dev.azure.com/numba/numba/_build/latest?definitionId=1?branchName=main :alt: Azure Pipelines
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
Please follow the instructions:
https://numba.readthedocs.io/en/stable/user/installing.html
Please have a look and the demo notebooks via the mybinder service:
https://mybinder.org/v2/gh/numba/numba-examples/master?filepath=notebooks
Numba has a discourse forum for discussions:
FAQs
compiling Python code using LLVM
We found that numba demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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