Welcome to scikit-network’s documentation!

logo sknetwork https://img.shields.io/pypi/v/scikit-network.svg https://github.com/sknetwork-team/scikit-network/actions/workflows/ci_checks.yml/badge.svg Documentation Status https://codecov.io/gh/sknetwork-team/scikit-network/branch/master/graph/badge.svg https://img.shields.io/pypi/pyversions/scikit-network.svg

Python package for the analysis of large graphs:

  • Memory-efficient representation as sparse matrices in the CSR format of scipy

  • Fast algorithms

  • Simple API inspired by scikit-learn


Quick Start

Install scikit-network:

$ pip install scikit-network

Import scikit-network:

import sknetwork

See our tutorials; the notebooks are available here.

You can also have a look at some use cases.


If you want to cite scikit-network, please refer to the publication in the Journal of Machine Learning Research:

  author  = {Thomas Bonald and Nathan de Lara and Quentin Lutz and Bertrand Charpentier},
  title   = {Scikit-network: Graph Analysis in Python},
  journal = {Journal of Machine Learning Research},
  year    = {2020},
  volume  = {21},
  number  = {185},
  pages   = {1-6},
  url     = {http://jmlr.org/papers/v21/20-412.html}

Getting started