Welcome to scikit-network’s documentation!

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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

Resources

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.

Citing

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

@article{JMLR:v21:20-412,
  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

Reference

Tutorials

Use cases

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