networkx

Python package for creating and manipulating graphs and networks

networkx Permissive license BSD-3-Clause Active ★ 17,190 v3.6.1 released 2025-12-08

Install

networkx on PyPI

pip

pip install networkx

uv

uv add networkx

poetry

poetry add networkx

Package facts

License	BSD-3-Clause (permissive)
Python support	supports the current Python release (!=3.14.1,>=3.11)
Install friction	low — pure-Python wheel
Runtime dependencies	none
Maintenance	actively maintained — 248 days since the last release
Last repo commit	2026-08-13
First released	2007-04-13
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: networkx-3.6.1-py3-none-any.whl

Keywords: Networks, Graph Theory, Mathematics, network, graph, discrete mathematics, math

Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Bio-InformaticsTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: MathematicsTopic :: Scientific/Engineering :: PhysicsTopic :: Software Development :: Libraries :: Python Modules

About networkx

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

NetworkX

.. image:: https://github.com/networkx/networkx/actions/workflows/test.yml/badge.svg?branch=main :target: https://github.com/networkx/networkx/actions/workflows/test.yml

.. image:: https://img.shields.io/pypi/v/networkx.svg? :target: https://pypi.python.org/pypi/networkx

.. image:: https://img.shields.io/pypi/l/networkx.svg? :target: https://github.com/networkx/networkx/blob/main/LICENSE.txt

.. image:: https://img.shields.io/pypi/pyversions/networkx.svg? :target: https://pypi.python.org/pypi/networkx

.. image:: https://img.shields.io/github/labels/networkx/networkx/good%20first%20issue?color=green&label=contribute :target: https://github.com/networkx/networkx/contribute

.. image:: https://insights.linuxfoundation.org/api/badge/health-score?project=networkx :target: https://insights.linuxfoundation.org/project/networkx

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

Website (including documentation): https://networkx.org
Mailing list: https://groups.google.com/forum/#!forum/networkx-discuss
Source:...

Read as markdown · JSON record · Source repository · Homepage · Docs

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

NetworkX creates, manipulates, and analyzes complex networks and graphs, providing algorithms for pathfinding, connectivity, centrality, and structural analysis of network data.

Installs cleanly with zero runtime dependencies and a pure-Python wheel. Actively maintained with recent releases; last commit 2026-08-13 and 248 days since the latest release indicate steady development.

Released under BSD-3-Clause (permissive), allowing use in commercial and proprietary projects with minimal restrictions beyond attribution.

Usage

pip install networkx

import networkx as nx
G = nx.Graph()
G.add_edge("A", "B", weight=4)
G.add_edge("B", "D", weight=2)
nx.shortest_path(G, "A", "D", weight="weight")

Requires Python 3.11 or later (3.14.1 excluded); check your Python version before install.

Verdict: NetworkX is a mature, actively maintained graph library with no security vulnerabilities, permissive licensing, and zero dependencies. Its top-1000 popularity tier and production-stable status make it a reliable choice for network analysis work.

Needs verification

Whether optional dependencies (referenced in install docs as networkx[default]) introduce material install friction for typical use cases.
Performance characteristics for very large graphs relative to domain-specific alternatives.

graph algorithms pythonnetwork analysis libraryshortest path algorithmgraph theory pythonnetwork structure analysiscomplex networks pythongraph manipulation tools