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    "info": {
        "author": "Bertrand Charpentier",
        "author_email": "bercha@kth.se",
        "bugtrack_url": null,
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        "description": "python-paris: Hierarchical graph clustering algorithm (paris) and dendrogram processing\n=========================\n\nparis is a Python module that provides an implementation of the hierarchical clustering algorithm for graphs, paris.\nIt provides four algorithms able to process dendrograms in order to extract best clusters, clusterings or distances.\n\nInstallation\n------------\n\nInstall the latest version of cylouvain using ``pip`` ::\n\n    $ pip install python_paris\n\nDependencies\n------------\n\ncylouvain requires:\n\n- Python (>= 2.7 or >= 3.4)\n- NumPy\n- NetworkX\n\nSimple example\n--------------\n\nBuild a simple graph with NetworkX::\n\n    >>> import networkx as nx\n    >>> graph = nx.Graph()\n    >>> graph.add_nodes_from(['0', '1', '2', '3', '4', '5'])\n    >>> graph.add_edges_from([(0, 1, 1), (0, 2, 1), (1, 2, 1), (2, 3, 1),\n                              (3, 4, 1), (3, 5, 1), (4, 5, 1)])\n\nCompute a clustering hierarchy of the nodes using paris::\n\n    >>> from python_paris import paris\n    >>> dendrogram = paris(graph)\n\nCompute the best clusters, clusterings and distances::\n\n    >>> best_cluster = best_cluster_cut(dendrogram)\n    >>> best_homogneous_clustering = best_homogeneous_cut(dendrogram)\n    >>> best_heterogneous_clustering = best_heterogeneous_cut(dendrogram)\n    >>> best_distance = best_distance\n\nLicense\n-------\n\nReleased under the Apache License 2.0 licence::\n\n   Copyright (C) 2018 Bertrand Charpentier <bercha@kth.se>\n",
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        "license": "Apache License 2.0",
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