numba
compiling Python code using LLVM
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python ≥3.10; llvmlite and numpy must be installed (pulled in automatically as runtime dependencies).
- Medium install friction due to compiled dependencies (llvmlite and numpy); however, prebuilt wheels cover Python 3.10–3.14 across macOS (ARM64), Linux (x86_64, aarch64), and Windows (amd64), and the package is actively maintained with a release just 2 days old.
License · maintenance · safety
BSD (permissive) — BSD permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute numba provided you retain the license notice.
last release 2026-08-11 (3 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 86,011,939 downloads/mo, #394 on PyPI
Alternatives
Verify before relying
pip install numba
import numba
@numba.jit
def add(a, b):
return a + b
result = add(1, 2)- Whether the latest release (0.67.0, dated 2026-08-11) is a stable production release or a pre-release candidate.
- Specific performance gains typical for common numerical workloads (e.g., array operations, nested loops).
- GPU support availability and requirements for CUDA/ROCm backends.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
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.
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.
Install
numba on PyPI
Before you install
Medium install friction due to compiled dependencies (llvmlite and numpy); however, prebuilt wheels cover Python 3.10–3.14 across macOS (ARM64), Linux (x86_64, aarch64), and Windows (amd64), and the package is actively maintained with a release just 2 days old.
Requires Python ≥3.10; llvmlite and numpy must be installed (pulled in automatically as runtime dependencies).
License in practice
BSD permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute numba provided you retain the license notice.
Quickstart
pip install numba
import numba
@numba.jit
def add(a, b):
return a + b
result = add(1, 2)Verify before relying
- Whether the latest release (0.67.0, dated 2026-08-11) is a stable production release or a pre-release candidate.
- Specific performance gains typical for common numerical workloads (e.g., array operations, nested loops).
- GPU support availability and requirements for CUDA/ROCm backends.
Package facts
| License | BSD permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagesllvmlitenumpy |
| Maintenance | Actively maintained 3 days since the last release |
| First released | |
| Downloads | 86,011,939 / month, #394 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development :: Compilers |
Evidence: numba-0.67.0-cp310-cp310-macosx_12_0_arm64.whl; numba-0.67.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; numba-0.67.0-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numba-0.67.0-cp310-cp310-win_amd64.whl; numba-0.67.0-cp311-cp311-macosx_12_0_arm64.whl; numba-0.67.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; numba-0.67.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numba-0.67.0-cp311-cp311-win_amd64.whl; numba-0.67.0-cp312-cp312-macosx_12_0_arm64.whl; numba-0.67.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; numba-0.67.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numba-0.67.0-cp312-cp312-win_amd64.whl; numba-0.67.0-cp313-cp313-macosx_12_0_arm64.whl; numba-0.67.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; numba-0.67.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numba-0.67.0-cp313-cp313-win_amd64.whl; numba-0.67.0-cp314-cp314-macosx_12_0_arm64.whl; numba-0.67.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; numba-0.67.0-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numba-0.67.0-cp314-cp314t-macosx_12_0_arm64.whl
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