Package: scikit-network-dbda093
Python package for the analysis of large graphs:Memory-efficient representation as sparse matrices in the CSR format ofscipyFast algorithmsSimple API inspired byscikit-learnResourcesFree software: BSD licenseGitHub:https://github.com/sknetwork-team/scikit-networkDocumentation:https://scikit-network.readthedocs.ioQuickstartInstall scikit-network:$pipinstallscikit-networkImport scikit-network in a Python project:import sknetwork as sknSee examples in the tutorials; the notebooks are availablehere.CitingIf you want to citescikit-network, please refer to the publication in
theJournal 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}
}History0.20.0 (2020-10-20)Added betweenness algorithm by Tiphaine Viard (#444)0.19.3 (2020-09-17)Added Louvain-based embeddingFix documentation with new dataset website URLs0.19.2 (2020-09-14)Fix documentation with new dataset website URLs.0.19.1 (2020-09-09)Fix visualization featuresFix documentation0.19.0 (2020-09-02)Added link prediction moduleAdded pie-node visualization of membershipsAdded Weisfeiler-Lehman graph coloring by Pierre Pebereau and Alexis Barreaux (#394)Added Force Atlas 2 graph layout by Victor Manach and Rémi Jaylet (#396)Added triangle listing algorithm for directed and undirected graph by Julien Simonnet and Yohann Robert (#376)Added k-core decomposition algorithm by Julien Simonnet and Yohann Robert (#377)Added k-clique listing algorithm by Julien Simonnet and Yohann Robert (#377)Added color map option in visualization moduleUpdated NetSet URL0.18.0 (2020-06-08)Added Katz centralityRefactor connectivity module into paths and topologyRefactor Diffusion into DirichletAdded parsers for adjacency list TSV and GraphMLAdded shortest paths and distances0.17.0 (2020-05-07)Add clustering by label propagationAdd modelsAdd function to build graph from edge listChange a parameter in SVG visualization functionsMinor corrections0.16.0 (2020-04-30)Refactor basics module into connectivityCython version for label propagationMinor corrections0.15.2 (2020-04-24)Clarified requirementsMinor corrections0.15.1 (2020-04-21)Added OpenMP support for all platforms0.15.0 (2020-04-20)Updated ranking module : new pagerank solver, new HITS params, post-processingPolynomes in linear algebraAdded meta.name attribute for BunchMinor corrections0.14.0 (2020-04-17)Added spring layout in embeddingAdded label propagation in classificationAdded save / load functions in dataAdded display edges parameter in svg graph exportsCorrected typos in documentation0.13.3 (2020-04-13)Minor bug0.13.2 (2020-04-13)Added wheels for multiple platforms (OSX, Windows (32 & 64 bits) and many Linux) and Python version (3.6/3.7/3.8)Documentation update (SVG dendrograms, tutorial updates)0.13.1a (2020-04-09)Minor bug0.13.0a (2020-04-09)Changed from Numba to Cython for better performanceAdded visualization moduleAdded k-nearest neighbors classifierAdded Louvain hierarchyAdded predict method in embeddingAdded soft clustering to clustering algorithmsAdded soft classification to classification algorithmsAdded graphs in data moduleVarious API change0.12.1 (2020-01-20)Added heat kernel based node classifierUpdated loaders for WikiLinksFixed file-related issues for Windows0.12.0 (2019-12-10)Added VerboseMixin for verbosity featuresAdded Loaders for WikiLinks & Konect databases0.11.0 (2019-11-28)sknetwork: new API for bipartite graphsnew module: Soft node classificationnew module: Node classificationnew module: data (merge toy graphs + loader)clustering: Spectral Clusteringranking: new algorithmsutils: K-neighborshierarchy: Spectral WardDensedata: loader (Vital Wikipedia)0.10.1 (2019-08-26)Minor bug0.10.0 (2019-08-26)Clustering (and related metrics) for directed and bipartite graphsHierarchical clustering (and related metrics) for directed and bipartite graphsFix bugs on embedding algorithms0.9.0 (2019-07-24)Change parser outputFix bugs in ranking algorithms (zero-degree nodes)Add notebooksImport algorithms from scipy (shortest path, connected components, bfs/dfs)Change SVD embedding (now in decreasing order of singular values)0.8.2 (2019-07-19)Minor bug0.8.1 (2019-07-18)Added diffusion rankingMinor fixesMinor doc tweaking0.8.0 (2019-07-17)Changed Louvain, BiLouvain, Paris and PageRank APIsChanged PageRank methodDocumentation overhaulImproved Jupyter tutorials0.7.1 (2019-07-04)Added Algorithm class for nicer repr of some classesAdded Jupyter notebooks as tutorials in the docsMinor fixes0.7.0 (2019-06-24)Updated PageRankAdded tests for Numba versioning0.6.1 (2019-06-19)Minor bug0.6.0 (2019-06-19)Largest connected componentSimplex projectionSparse Low Rank DecompositionNumba support for ParisVarious fixes and updates0.5.0 (2019-04-18)Unified Louvain.0.4.0 (2019-04-03)Added Louvain for directed graphs and ComboLouvain for bipartite graphs.0.3.0 (2019-03-29)Updated clustering module and documentation.0.2.0 (2019-03-21)First real release on PyPI.0.1.1 (2018-05-29)First release on PyPI.