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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_
.. _scipy: https://www.scipy.org
.. _scikit-learn: https://scikit-learn.org/
Resources
- Free software: BSD license
- GitHub: https://github.com/sknetwork-team/scikit-network
- Documentation: https://scikit-network.readthedocs.io
Quick Start
Install scikit-network:
.. code-block:: console
$ pip install scikit-network
Import scikit-network in a Python project::
import sknetwork as skn
See examples in the tutorials; the notebooks are available here_.
Citing
If you want to cite scikit-network, please refer to the publication in
the Journal of Machine Learning Research <https://jmlr.org>_:
.. code::
@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}
}
.. _here: https://github.com/sknetwork-team/scikit-network/tree/master/docs/tutorials