Skip to Main content Skip to Navigation
Journal articles

Scikit-network: Graph Analysis in Python

Abstract : Scikit-network is a Python package inspired by scikit-learn for the analysis of large graphs. Graphs are represented by their adjacency matrix in the sparse CSR format of SciPy. The package provides state-of-the-art algorithms for ranking, clustering, classifying, embedding and visualizing the nodes of a graph. High performance is achieved through a mix of fast matrix-vector products (using SciPy), compiled code (using Cython) and parallel processing. The package is distributed under the BSD license, with dependencies limited to NumPy and SciPy. It is compatible with Python 3.6 and newer. Source code, documentation and installation instructions are available online.
Complete list of metadata
Contributor : Thomas Bonald Connect in order to contact the contributor
Submitted on : Friday, September 11, 2020 - 9:40:16 AM
Last modification on : Thursday, December 10, 2020 - 4:47:45 PM


Files produced by the author(s)


  • HAL Id : hal-02923335, version 2
  • ARXIV : 2009.07660



Thomas Bonald, Nathan de Lara, Quentin Lutz, Bertrand Charpentier. Scikit-network: Graph Analysis in Python. Journal of Machine Learning Research, Microtome Publishing, In press. ⟨hal-02923335v2⟩



Record views


Files downloads