https://github.com/numba/numba

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

compiler cuda llvm numpy parallel python

Last synced: about 1 month 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 (over 12 years ago)
• Default Branch: main
• Last Pushed: 2024-05-07T15:18:41.000Z (about 1 month ago)
• Last Synced: 2024-05-07T16:35:11.013Z (about 1 month ago)
• Topics: compiler, cuda, llvm, numpy, parallel, python
• Language: Python
• Homepage: https://numba.pydata.org/
• Size: 74.7 MB
• Stars: 9,478
• Watchers: 202
• Forks: 1,097
• Open Issues: 1,589
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGE_LOG
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Codeowners: .github/CODEOWNERS

Lists

• Virtualization-Emulation-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 / Interfaces)
• awesome-robotic-tooling - numba - NumPy aware dynamic Python compiler using LLVM. (Sensor Processing / Parallel Processing)
• 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)
• Pop_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. (ML frameworks & applications / Winetricks)
• Oracle-Cloud-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 & applications)
• Linux-Mint-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 & applications)
• 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)
• macOS-iOS-iPadOS-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 & applications / Objective-C Tools, Libraries, and Frameworks)
• VMware-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 & applications)
• 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)
• 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)
• SQL-NoSQL-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. (Distributed Systems Tools / Parallel Systems Courses & Tutorials)
• Developer-Handbook - 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. (Tools / Mesh networks)
• Zorin-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. (ML frameworks & applications)
• awesome-production-machine-learning - Numba - A compiler for Python array and numerical functions. (Optimized Computation)
• Debian-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 & applications)
• SUSE-openSUSE-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 & applications)
• awesome-sciml - numba/numba: NumPy aware dynamic Python compiler using LLVM
• IoT-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 & applications / Interfaces)
• awesome-stars - numba/numba - `★9574` NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-list - numba - NumPy aware dynamic Python compiler (Compilers)
• awesome-compiling-python - Numba
• Self-Hosting-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 & applications / Interfaces)
• awesome-llvm - numba
• awesome-systematic-trading - numba - commit/numba/numba/main) - NumPy aware dynamic Python compiler using LLVM (Basic Components / Python Performance Booster)
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• awesome-production-machine-learning - Numba - A compiler for Python array and numerical functions (Optimized computation frameworks)
• Awesome-AIML-Data-Ops - Numba - A compiler for Python array and numerical functions (Optimized calculation frameworks)
• Awesome-AIML-Data-Ops - Numba - A compiler for Python array and numerical functions (Optimized calculation frameworks)
• awesome-production-machine-learning - Numba - A compiler for Python array and numerical functions (Compiler optimisation frameworks)
• awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-robotic-tooling - numba - NumPy aware dynamic Python compiler using LLVM. (Sensor Processing / Parallel Processing)
• awesome-cython - Numba - A Just-In-Time Compiler for Numerical Functions in Python. (Software / Alternatives)
• awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-python-geo-packages - Numba
• 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. (CUDA Tools Libraries, and Frameworks)
• awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• AWS-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 & applications / Interfaces)
• awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-python-implementations - Numba - NumPy aware dynamic Python compiler using LLVM (Compilers / Dead projects)
• awesome-starts - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
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• starred-awesome - numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-projects - numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-stars - numba - NumPy aware dynamic Python compiler using LLVM (Python)
• Unity-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 / viii. Linear Regression)
• 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)
• DSP-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-python-machine-learning - Numba - A Just-In-Time Compiler for Numerical Functions in Python. (Uncategorized / Uncategorized)
• awesome-stars - numba - NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-list - Numba - NumPy aware dynamic Python compiler using LLVM. (Linear Algebra / Statistics Toolkit / General Purpose Tensor Library)
• awesome-stars - numba/numba - `★9219` NumPy aware dynamic Python compiler using LLVM (Python)
• awesome-python - numba - Python JIT compiler to LLVM aimed at scientific Python. (Implementations)
• Distributed-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)
• awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• Computer-Vision-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 / viii. Linear Regression)
• my-awesome-stars - numba/numba - NumPy aware dynamic Python compiler using LLVM (Python)
• 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. (CUDA Tools Libraries, and Frameworks)
• 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. (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)
• Parallel-Computing-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)
• 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)
• 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. (CUDA 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)
• 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. (CUDA Tools Libraries, and Frameworks)
• 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)
• Unreal-Engine-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 / viii. Linear Regression)
• StarryDivineSky - numba/numba

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