Louvain Community Detection

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.. image:: https://readthedocs.org/projects/python-louvain/badge/?version=latest :target: http://python-louvain.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

Installing

To build and install from source, run

.. code-block:: shell

python setup.py install

You can also install from pip with

.. code-block:: shell

pip install python-louvain

The package name on pip is :code:python-louvain but it is imported as :code:community in python. More documentation for this module can be found at http://python-louvain.readthedocs.io/ <http://python-louvain.readthedocs.io/>_

Usage

To use as a Python library

.. code-block:: python

from community import community_louvain
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import networkx as nx

# load the karate club graph
G = nx.karate_club_graph()

# compute the best partition
partition = community_louvain.best_partition(G)

# draw the graph
pos = nx.spring_layout(G)
# color the nodes according to their partition
cmap = cm.get_cmap('viridis', max(partition.values()) + 1)
nx.draw_networkx_nodes(G, pos, partition.keys(), node_size=40, 
                       cmap=cmap, node_color=list(partition.values()))
nx.draw_networkx_edges(G, pos, alpha=0.5)
plt.show()

It can also be run on the command line

.. code-block:: bash

 $ community <filename>

where :code:filename is a binary file as generated by the convert utility distributed with the C implementation at https://sites.google.com/site/findcommunities/ <https://sites.google.com/site/findcommunities/>_ However as this is mostly for debugging purposes its use should be avoided. Instead importing this library for use in Python is recommended.

Documentation

You can find documentation at https://python-louvain.readthedocs.io/ <https://python-louvain.readthedocs.io/>_

To generate documentation, run

.. code-block:: shell

 pip install numpydoc sphinx
 cd docs
 make

Tests

To run tests, run

.. code-block:: shell

 pip install nose
 python setup.py test