https://github.com/numba/numba

NumPy aware dynamic Python compiler using LLVM
https://github.com/numba/numba

compiler cuda llvm numba numpy parallel python

Last synced: 3 days ago
JSON representation

NumPy aware dynamic Python compiler using LLVM

• Host: GitHub
• URL: https://github.com/numba/numba
• Owner: numba
• License: bsd-2-clause
• Created: 2012-03-08T11:12:43.000Z (almost 13 years ago)
• Default Branch: main
• Last Pushed: 2024-11-25T05:20:49.000Z (17 days ago)
• Last Synced: 2024-12-02T11:06:54.617Z (10 days ago)
• Topics: compiler, cuda, llvm, numba, numpy, parallel, python
• Language: Python
• Homepage: https://numba.pydata.org/
• Size: 75.3 MB
• Stars: 10,017
• Watchers: 198
• Forks: 1,131
• Open Issues: 1,646
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGE_LOG
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

• LiDAR-Guide - Numba - 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. (CUDA Tools)
• NLP-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)
• awesome-systematic-trading - numba - commit/numba/numba/main)  - NumPy aware dynamic Python compiler using LLVM (Basic Components / Python Performance Booster)
• awesome-python-machine-learning - Numba - A Just-In-Time Compiler for Numerical Functions in Python. (Uncategorized / Uncategorized)
• awesome-starts - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-sciml - numba/numba: NumPy aware dynamic Python compiler using LLVM
• awesome-robotic-tooling - numba - NumPy aware dynamic Python compiler using LLVM. (Sensor Processing / Parallel Processing)
• awesome-list - Numba - NumPy aware dynamic Python compiler using LLVM. (Linear Algebra / Statistics Toolkit / General Purpose Tensor Library)
• Chrome-OS-Guide - Numba - 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. (Flutter Tools)
• CUDA-Guide - Numba - 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. (CUDA Tools)
• Vulkan-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)
• Jupyter-Guide - Numba - 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. (ML Frameworks, Libraries, and Tools)
• StarryDivineSky - numba/numba
• CNT-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)
• starred-awesome - numba - NumPy aware dynamic Python compiler using LLVM (Python)
• MATLAB-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)
• awesome-production-machine-learning - Numba - A compiler for Python array and numerical functions. (Optimized Computation)
• Apache-Spark-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• PyTorch-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• CoreML-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• Apache-Kafka-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• gpu-guide - Numba - 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. (Parallel Computing Tools, Libraries, and Frameworks)
• gpu-guide - Numba - 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. (Parallel Computing Tools, Libraries, and Frameworks)
• TensorFlow-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• Apache-Airflow-Guide - Numba - 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. (NLP Tools, Libraries, and Frameworks)
• Autonomous-Systems-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)
• Deep-Learning-Guide - Numba - 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. (CUDA Tools Libraries, and Frameworks)

README

        
*****

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

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:

* https://numba.discourse.group