--- id: numba version: "0.67.0" license: BSD license_treatment: permissive maintenance: active --- # numba — compiling Python code using LLVM License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI ## Install pip install numba uv add numba poetry add numba ## Description ***** Numba ***** .. image:: https://img.shields.io/badge/discuss-on%20discourse-blue :target: https://numba.discourse.group/ :alt: Discourse .. image:: https://zenodo.org/badge/doi/10.5281/zenodo.4343230.svg :target: https://doi.org/10.5281/zenodo.4343230 :alt: Zenodo .. 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... ## AI interpretation — verify before relying Numba is a just-in-time compiler that accelerates numerically-focused Python code by compiling it to machine code via LLVM, with support for NumPy functions, loop parallelization, and GPU code generation. Verdict: Numba is a mature, actively maintained compiler for numerical Python with no known vulnerabilities, permissive licensing, and broad platform coverage. Medium install friction is offset by strong maintenance signals and top-1000 popularity, making it a solid choice for performance-critical numerical workloads. [View on SkillFed](https://skillfed.io/packages/numba) · [View on PyPI](https://pypi.org/project/numba/)