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T dS )a«  Functions for computing and measuring community structure.

The functions in this class are not imported into the top-level
:mod:`networkx` namespace. You can access these functions by importing
the :mod:`networkx.algorithms.community` module, then accessing the
functions as attributes of ``community``. For example::

    >>> from networkx.algorithms import community
    >>> G = nx.barbell_graph(5, 1)
    >>> communities_generator = community.girvan_newman(G)
    >>> top_level_communities = next(communities_generator)
    >>> next_level_communities = next(communities_generator)
    >>> sorted(map(sorted, next_level_communities))
    [[0, 1, 2, 3, 4], [5], [6, 7, 8, 9, 10]]

é    )Ú*N)Ú__doc__Ú(networkx.algorithms.community.asyn_fluidÚ(networkx.algorithms.community.centralityÚ%networkx.algorithms.community.kcliqueÚ+networkx.algorithms.community.kernighan_linÚ/networkx.algorithms.community.label_propagationÚ#networkx.algorithms.community.lukesÚ,networkx.algorithms.community.modularity_maxÚ%networkx.algorithms.community.qualityÚ-networkx.algorithms.community.community_utilsÚ%networkx.algorithms.community.louvain© r   r   úM/tmp/pip-target-vg8gfxp4/lib/python/networkx/algorithms/community/__init__.pyÚ<module>   s    