Infomap
Infomap is a network clustering algorithm based on the Map equation. This repository contains the native CLI, the Python package, the R package, the JavaScript browser worker and Node.js package, the Docker images, the tutorial notebooks, and the source for the published Python documentation.
Start with mapequation.org/infomap/ for the user guide, the Infomap Python API for Python examples and tutorial notebooks, and CHANGELOG.md for release notes.
For contributing, security reporting, and maintainer workflows, see CONTRIBUTING.md, SECURITY.md, BUILD.md, ARCHITECTURE.md, and AGENTS.md.
Install
Python package
Install from PyPI:
pip install infomapInstall optional integrations for common Python graph and analysis workflows:
pip install "infomap[networkx]"
pip install "infomap[igraph]"
pip install "infomap[pandas]"Upgrades use the usual pip flow:
pip install --upgrade infomapThe package also installs the infomap CLI entry point. The Python API reference lives at Infomap Python API.
Quick start with Python:
import networkx as nx
import infomap
graph = nx.karate_club_graph()
result = infomap.run(graph, seed=123, num_trials=20)
print(result.num_top_modules, result.codelength)
print(result.modules()) # {node_id: module_id}infomap.run accepts a NetworkX or igraph graph, a SciPy sparse matrix, a (2, E) edge index, a network file path, or an iterable of links. It returns an immutable Result. If you only need the communities in the graph’s own node labels, use infomap.find_communities(graph, seed=123, num_trials=20), which returns a NetworkX-style list of sets of node labels. Its igraph counterpart infomap.find_igraph_communities returns an igraph.VertexClustering.
For incremental construction – adding nodes and links one at a time – build a Network and run it, reading results off the returned Result:
from infomap import Network, run
net = Network()
net.add_link(0, 1)
net.add_link(1, 2)
result = run(net, two_level=True, num_trials=20, seed=123)
print(result.num_top_modules, result.codelength)
print(result.to_dataframe(columns=["node_id", "module_id", "flow"], index="node_id"))The stateful Infomap class works the same way (im = Infomap(...); im.add_link(...); result = im.run()). Use it to keep one configured engine and run it repeatedly, or to maintain code written against the original API.
For Jupyter, start with the quickstart notebook. It shows the Infomap result summary, dataframe inspection, a copyable static network partition helper, and export paths for further analysis.
R package
Pre-built binaries are published on r-universe; this is the recommended path:
install.packages(
"infomap",
repos = c("https://mapequation.r-universe.dev", "https://cloud.r-project.org")
)Quick start with R:
library(infomap)
im <- Infomap(silent = TRUE, two_level = TRUE, num_trials = 20)
im$add_link(0, 1)
im$add_link(1, 2)
im$run()
print(im$num_top_modules)
print(im$codelength)See ?Infomap for the user-facing constructor plus the InfomapClass method and active-binding reference. The R-specific source README lives at interfaces/R/infomap/README.md.
Homebrew CLI
If you want the native CLI without the Python package, install the tap and formula with:
brew tap mapequation/infomap
brew install infomapOr install directly in one command:
brew install mapequation/infomap/infomapUpgrade the CLI with the normal Homebrew flow:
brew upgrade infomapThe Homebrew formula installs Bash and Zsh completion files into Homebrew’s standard completion directories.
JavaScript package
The package is published on NPM and provides a browser web worker, a Node.js module, and an infomap command line tool:
npm install @mapequation/infomapQuick start in Node.js with the @mapequation/infomap/node entry point:
import { run } from "@mapequation/infomap/node";
const network = "0 1\n0 2\n0 3\n1 2\n3 4\n3 5\n4 5";
const result = await run(network, { args: ["-o", "tree,json", "-2"] });
console.log(result.json.codelength);
console.log(result.tree);Installing the package also provides an infomap command that behaves like the native binary:
npx @mapequation/infomap network.net . --treeThe NPM package page documents browser worker and React usage.
Docker
Multi-arch images are published to GHCR for linux/amd64 and linux/arm64:
ghcr.io/mapequation/infomap:latest
ghcr.io/mapequation/infomap:X.Y.Z
ghcr.io/mapequation/infomap:notebook
ghcr.io/mapequation/infomap:notebook-X.Y.Z
Run the CLI image with:
docker run -it --rm \
-v "$(pwd)":/data \
ghcr.io/mapequation/infomap:latest \
[infomap arguments]Start the notebook image with:
docker run --rm \
-p 8888:8888 \
ghcr.io/mapequation/infomap:notebook \
start.sh jupyter labThe notebook image includes the survey companion notebooks from examples/notebooks and opens in that workspace by default. To keep local copies or outputs, mount a host directory as a separate workspace path:
docker run --rm \
-v "$(pwd)":/home/jovyan/work/local \
-p 8888:8888 \
ghcr.io/mapequation/infomap:notebook \
start.sh jupyter labCI also smoke-tests the Dockerfiles in this repository, and you can build them locally:
docker build -f docker/infomap.Dockerfile -t infomap:local .
docker build -f docker/notebook.Dockerfile -t infomap:notebook-local .Or use the local Compose file:
docker compose run --rm infomapBuild from source
Building locally requires a working gcc or clang toolchain.
git clone git@github.com:mapequation/infomap.git
cd infomap
make build-nativeOn macOS, the default OpenMP-enabled build can require Homebrew libomp. If OpenMP is unavailable, use:
make build-native OPENMP=0This creates the Infomap binary in the repository root. Show the available CLI options with:
./Infomap --helpInstall shell completion scripts manually with:
mkdir -p ~/.zfunc
./Infomap --completion zsh > ~/.zfunc/_Infomap
mkdir -p ~/.local/share/bash-completion/completions
./Infomap --completion bash > ~/.local/share/bash-completion/completions/infomapFor Zsh, make sure fpath contains ~/.zfunc and ~/.zshrc loads compinit. For Bash, make sure ~/.bashrc sources bash-completion.
See BUILD.md for platform-specific maintainer build details.
For maintainer tasks, use:
BUILD.md for local build and verification commands
RELEASING.md for the release flow
ARCHITECTURE.md for ownership and source-of-truth rules
AGENTS.md for repo-local maintenance guidance
CONTRIBUTING.md for pull request and contributor guidance
SECURITY.md for vulnerability reporting
Agent skill
This repository includes an Infomap agent skill in skills/infomap/ for reproducible CLI, Python, R, and notebook research workflows.
Feedback
Usage questions and setup help belong in GitHub Discussions. Bug reports and feature requests belong in GitHub issues.
Terms of use
Infomap is released under a dual license.
The code is available under the GNU General Public License version 3 or any later version; see LICENSE_GPLv3.txt. For a non-copyleft license, contact us.
Release files for infomap 2.16.0
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Transparency logRelease files / infomap-2.16.0-cp311-cp311-win32.whl
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| Size | 1.4 MB |
| Tags | CPython 3.11 macOS 15.0+ ARM64 |
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Transparency logSecurity for infomap 2.16.0
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