numpy

Fundamental package for array computing in Python

numpy Permissive license BSD-3-Clause AND 0BSD AND MIT AND Zlib AND CC0-1.0 Active ★ 32,531 v2.5.2 released 2026-08-09

Install

numpy on PyPI

pip

pip install numpy

uv

uv add numpy

poetry

poetry add numpy

Package facts

License	BSD-3-Clause AND 0BSD AND MIT AND Zlib AND CC0-1.0 (permissive)
Python support	supports the current Python release (>=3.12)
Install friction	medium — platform-specific wheel
Runtime dependencies	none
Maintenance	actively maintained — 4 days since the last release
Last repo commit	2026-08-13
First released	2006-12-02
Popularity	one of the 100 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: numpy-2.5.2-cp312-cp312-macosx_10_13_x86_64.whl; numpy-2.5.2-cp312-cp312-macosx_11_0_arm64.whl; numpy-2.5.2-cp312-cp312-macosx_14_0_arm64.whl; numpy-2.5.2-cp312-cp312-macosx_14_0_x86_64.whl; numpy-2.5.2-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numpy-2.5.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; numpy-2.5.2-cp312-cp312-musllinux_1_2_aarch64.whl; numpy-2.5.2-cp312-cp312-musllinux_1_2_x86_64.whl; numpy-2.5.2-cp312-cp312-win32.whl; numpy-2.5.2-cp312-cp312-win_amd64.whl; numpy-2.5.2-cp312-cp312-win_arm64.whl; numpy-2.5.2-cp313-cp313-macosx_10_13_x86_64.whl; numpy-2.5.2-cp313-cp313-macosx_11_0_arm64.whl; numpy-2.5.2-cp313-cp313-macosx_14_0_arm64.whl; numpy-2.5.2-cp313-cp313-macosx_14_0_x86_64.whl; numpy-2.5.2-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; numpy-2.5.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; numpy-2.5.2-cp313-cp313-musllinux_1_2_aarch64.whl; numpy-2.5.2-cp313-cp313-musllinux_1_2_x86_64.whl; numpy-2.5.2-cp313-cp313-win32.whl

Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: CProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.15Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/EngineeringTopic :: Software DevelopmentTyping :: Typed

About numpy

from the package's own PyPI description — quoted content, verbatim

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AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

NumPy provides a powerful N-dimensional array object and sophisticated computational functions for scientific computing, including linear algebra, Fourier transforms, and random number generation.

Medium install friction due to compiled C extensions across multiple platform wheels, but actively maintained with a release just 4 days old and strong community backing. Pre-built wheels available for Python 3.12–3.15 on all major platforms minimize build-from-source risk.

Multi-license permissive stack (BSD-3-Clause, 0BSD, MIT, Zlib, CC0-1.0) allows broad commercial and private use with minimal restrictions; attribution and license preservation are the primary obligations.

Usage

pip install numpy==2.5.2

import numpy as np
arr = np.array([1, 2, 3])
result = np.sum(arr)

Requires Python ≥3.12; compiled C extensions may require a C compiler if wheels are unavailable for your platform.

Verdict: NumPy 2.5.2 is a production-stable, actively maintained foundation for scientific Python with zero known vulnerabilities, permissive licensing, and top-100 PyPI popularity. Medium install friction is offset by comprehensive pre-built wheels and strong maintenance signals.

Needs verification

Whether the multi-license composition (BSD-3-Clause, 0BSD, MIT, Zlib, CC0-1.0) poses any practical compatibility issues for specific downstream use cases.
Performance or API stability implications of the recent 2.5.2 release relative to earlier 2.x versions.

numerical computing pythonn-dimensional arraysscientific computing librarylinear algebra pythonarray operationsmatrix computationscientific python foundation