install

Additional install commands

macOS

Homebrewverified · 100%

brew install numpy

provider-native install command

overview

Package summary

Package for scientific computing with Python

Project links

Commands and aliases

f2py
numpy-config

history

Project history and usage

NumPy is the foundational array package for scientific computing in Python. It supplies the `ndarray`, vectorized operations, broadcasting, linear algebra and numerical routines, a C API, and the `f2py` command-line interface for building Python bindings to Fortran code.

Project history

The official NumPy about page says NumPy was created in 2005, building on Numeric and Numarray. The old SciPy history records the project as a reunion: Travis Oliphant wanted to bring the split Numeric/numarray community back to one array package, refactored Numeric to absorb numarray's features, and after naming discussion the multidimensional array project became NumPy.

Adoption history

NumPy became the array substrate for the Python scientific stack. The 2020 Nature paper 'Array programming with NumPy' describes NumPy as a 2005 unification of Numarray's features with Numeric's small-array performance and C API, and says that by 2020 it underpinned almost every Python library doing scientific or numerical computation, including SciPy, Matplotlib, pandas, scikit-learn, and scikit-image.

How it is used

Users install NumPy directly for dense arrays, vectorized math, broadcasting, random sampling, FFTs, statistics, basic linear algebra, and data interchange with other Python libraries. Package maintainers also care about the compiled-code boundary: `f2py` is distributed with NumPy as both `numpy.f2py` and a standalone command-line tool, making old Fortran routines callable from Python, while the C API supports extensions and downstream projects.

Why package nerds care

For package ecosystems, NumPy is not just a library; it is an ABI, build, and compatibility gravity well. Python packages with native extensions often pin or test against NumPy versions, scientific Linux/macOS distributions ship optimized BLAS/LAPACK stacks underneath it, and Homebrew's formula page showed 333,990 installs over 365 days on July 1, 2026 despite Python users often installing it through pip or conda instead.

Timeline

1990s-2000s: Numeric and then Numarray serve overlapping array-computing communities.
2005: NumPy is created by combining Numeric and Numarray ideas into one project.
2020: Nature publishes 'Array programming with NumPy', documenting its role across scientific Python.

Related projects

Numeric
Numarray
SciPy
Matplotlib
pandas
scikit-learn
scikit-image

Sources

security posture

No protected-tool coverage found yet

No matching local secret-handling manifest was found for numpy. Nucleus package metadata is still published here so future coverage has a stable package URL.

Install behavior

No Homebrew bottle metadata was recorded.

Recommended review

Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.

executables

Installed executables

Command	Kind	Exposure	Note
`f2py`	executable	indexed executable	Discovered from the local executable index.
`numpy-config`	executable	indexed executable	Discovered from the local executable index.

freshness

Version and freshness

These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.

page generated2026-08-03

manager version2.5.1

manager updated2026-07-07

local dataunknown

upstreamnot available

latest detectednot detected

okNo freshness warnings were generated.

install metadata

Package metadata

Package key	brew:numpy
Version	2.5.1
Package manager	Homebrew
Homepage	https://www.numpy.org/
Repository	https://github.com/numpy/numpy
Last updated	2026-07-07T20:38:47Z
Pulse	updated
Bottle	not recorded
Service	none declared

package graph

Links come from deterministic package relationships, av.db category and tag curation, ecosystem matches, and package hub membership.

source trail

Generated from repository data

This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.

Combined YAML source

View the package source record on GitHub.

combined/numpy.yml

Used sources

Geiger risk classifier
Nucleus package database
curated package history
pkgdb category and tag curation

Install numpy with Homebrew