skillfed

igraph

High performance graph data structures and algorithms

igraph v1.0.0 3.4M downloads/30d#2,626 on PyPI1,459
Copyleft license GNU General Public License (GPL) Active released

What it is and what it does

igraph is a Python binding to a high-performance C graph library designed for network research and complex network analysis. It provides data structures and algorithms for constructing graphs, computing network metrics, detecting communities, and analyzing structural properties. The package is aimed at researchers and developers working with graph-based problems in biology, physics, social networks, and discrete mathematics.

The library's core functionality is written in C for speed, but is exposed through a Python API. Graph visualization is optional and requires separate installation of Cairo bindings (cairocffi or pycairo); the description notes that cairocffi is recommended for Jupyter notebook compatibility. The package supports Python 3.9 and later, with precompiled wheels for most common platforms, reducing installation complexity compared to pure source builds.

Use it for:

  • Analyze social networks, citation networks, or biological networks to compute centrality measures and detect community structure
  • Perform graph algorithms like shortest paths, spanning trees, or clique detection on large datasets
  • Generate publication-quality network visualizations using Cairo integration for research papers or reports
  • Study discrete mathematical properties of graphs in academic research or algorithm development
  • Build network-based applications requiring fast graph operations on millions of nodes or edges

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

igraph provides a Python interface to a high-performance C graph library for constructing, analyzing, and visualizing networks and complex graphs.

Yes, if you need to work with graphs or networks. igraph is actively maintained, widely used (top 5000 on PyPI), has no known vulnerabilities, and offers substantial performance advantages over pure-Python graph libraries due to its C backend. The copyleft GPL license is a consideration if you plan to redistribute; otherwise it poses no barrier to use. Medium install friction is acceptable given the availability of prebuilt wheels.

Install

igraph on PyPI

pip

pip install igraph

uv

uv add igraph

poetry

poetry add igraph

Installing igraph

Before you install

Medium install friction due to compiled C bindings; however, prebuilt wheels are available for common platforms (macOS, Linux, Windows) and Python versions 3.9–3.13. The package is actively maintained with recent commits and a stable release cadence.

License in practice

Licensed under GNU General Public License (GPL), a copyleft license. Any software that links to or redistributes igraph must comply with GPL terms, including making source code available under compatible terms.

Quickstart

pip install igraph

import igraph as ig

# Create a simple graph
g = ig.Graph.Famous("petersen")
print(g.summary())

Requires Python 3.9 or later. Graph plotting requires separate installation of cairocffi or pycairo; cairocffi is recommended for Jupyter compatibility.

Verify before relying

  • Whether graph plotting requires explicit installation of cairocffi or pycairo, or if igraph functions without them
  • Performance characteristics and scalability limits for large graphs

Package facts

License GNU General Public License (GPL) (copyleft)
Python support supports the current Python release (>=3.9)
Install friction medium — platform-specific wheel
Runtime dependencies 1 — texttable
Maintenance actively maintained — 295 days since the last release
Last repo commit
First released
Downloads 3,425,214/month — #2,626 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: igraph-1.0.0-cp39-abi3-macosx_10_15_x86_64.whl; igraph-1.0.0-cp39-abi3-macosx_11_0_arm64.whl; igraph-1.0.0-cp39-abi3-manylinux_2_28_aarch64.whl; igraph-1.0.0-cp39-abi3-manylinux_2_28_x86_64.whl; igraph-1.0.0-cp39-abi3-musllinux_1_2_aarch64.whl; igraph-1.0.0-cp39-abi3-musllinux_1_2_x86_64.whl; igraph-1.0.0-cp39-abi3-win32.whl; igraph-1.0.0-cp39-abi3-win_amd64.whl; igraph-1.0.0-cp39-abi3-win_arm64.whl; igraph-1.0.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl; igraph-1.0.0-pp311-pypy311_pp73-macosx_11_0_arm64.whl; igraph-1.0.0-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl; igraph-1.0.0-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl; igraph-1.0.0-pp311-pypy311_pp73-win_amd64.whl

Keywords: graph, network, mathematics, math, graph theory, discrete mathematics

Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: CProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Bio-InformaticsTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: MathematicsTopic :: Scientific/Engineering :: PhysicsTopic :: Software Development :: Libraries :: Python Modules

Tags

graph algorithms and analysisnetwork analysis librarycomplex network researchgraph data structuresnetwork visualizationgraph theory computationnetwork metrics and properties
graph-algorithmsnetwork-analysisscientific-computing

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