<commit_before>NetworkX 
========

*High productivity software for complex networks*
-------------------------------------------------
.. raw:: html

   <div align="left" class="image image align-right image-reference">
    <img align="right" alt="NetworkX art" class="image" height="540"
    src="https://networkx.lanl.gov/images/art.png"  width="270" />
    </div>


About
-----

   NetworkX (NX) is a Python package for the creation, manipulation, and
   study of the structure, dynamics, and functions of complex networks.  
 
   Features:

      - Allows for 1M+ nodes, 10M+ edges
      - Includes standard graph-theoretic and statistical physics functions
      - Easy exchange of network algorithms between applications, 
      	disciplines, and platforms
      - Includes many classic graphs and synthetic networks
      - Nodes and edges can be "anything" 
      	(e.g. time-series, text, images, XML records)
      - Exploits existing code from high-quality legacy software in C, 
        C++, Fortran, etc.
      - Open source (encourages community input)
      - Unit-tested

   Additional benefits due to Python:              
    

      - Allows fast prototyping of new algorithms
      - Easy to teach 
      - Multi-platform
      - Allows easy access to almost any database


Quick Example
-------------

   Just write in Python

   >>> import networkx as NX
   >>> G=NX.Graph()
   >>> G.add_edge(1,2)
   >>> G.add_node("spam")
   >>> print G.nodes()
   [1, 2, 'spam']
   >>> print G.edges()
   [(1, 2)]


Requirements
-------------

   To use NetworkX you need

      - Python version 2.3 or later http://www.python.org/

   Optional packages to enable drawing networks:

      - Matplotlib       http://matplotlib.sourceforge.net/
      - pygraphviz	 http://networkx.lanl.gov/pygraphviz/
      - Graphviz         http://graphviz.org/
      - numpy		 http://numpy.scipy.org/

   Optional useful packages:

      - Ipython          http://ipython.scipy.org/
      - SciPy		 http://scipy.org/
      - PyGSL            http://pygsl.sourceforge.net/
      - sAsync		 http://foss.eepatents.com/sAsync                
      - PyYAML		 http://pyyaml.org/

Download
--------

   You can download NetworkX from 
   http://sourceforge.net/project/showfiles.php?group_id=122233

   You can browse the source at https://networkx.lanl.gov/browser/networkx/trunk

   To access the source repository using subversion, you will need a subversion client (e.g. svn for Linux). Then check out the code using

    svn co https://networkx.lanl.gov/svn/networkx/trunk networkx



Quick Install
-------------

   Installing from source:

      - Download the source (tar.gz or zip file)
      - Unpack and change directory to networkx-x.xx
      - Run "python setup.py install" to build and install
      - (optional) cd networkx/tests and run "python setup_egg.py test" to execute the tests
      
    
   Installing a Python egg from source:

      - Download the source (tar.gz or zip file)
      - Unpack and change directory to networkx-x.xx
      - Run "python setup_egg.py install" to build and install
      - (optional) run "python setup_egg.py test" to execute the tests


   **Windows** (binary installer)
 
      Download the installer, run and follow the instructions.
      Please note that we are not Windows users and have only verified
      that the Windows installer passes the "smoke test".  If you
      have problems we suggest installing from the source distribution.


   NetworkX also may be installed using EasyInstall http://peak.telecommunity.com/DevCenter/EasyInstall

   easy_install networkx


Authors
-------
   
  - <NAME>  http://math.lanl.gov/~hagberg/
  - <NAME>
  - <NAME>



.. raw:: html

   <div align="left" class="image image align-left image-reference"><a
    class="reference" href="http://sourceforge.net/"><img align="left"
    alt="SourceForge.net Logo" class="image" height="31"
    src="http://sourceforge.net/sflogo.php?group_id=122233&amp;type=1"
    width="88" /></a></div>
<commit_msg>Update downloads info<commit_after>NetworkX 
========

*High productivity software for complex networks*
-------------------------------------------------
.. raw:: html

   <div align="left" class="image image align-right image-reference">
    <img align="right" alt="NetworkX art" class="image" height="540"
    src="https://networkx.lanl.gov/images/art.png"  width="270" />
    </div>


About
-----

   NetworkX (NX) is a Python package for the creation, manipulation, and
   study of the structure, dynamics, and functions of complex networks.  
 
   Features:

      - Allows for 1M+ nodes, 10M+ edges
      - Includes standard graph-theoretic and statistical physics functions
      - Easy exchange of network algorithms between applications, 
      	disciplines, and platforms
      - Includes many classic graphs and synthetic networks
      - Nodes and edges can be "anything" 
      	(e.g. time-series, text, images, XML records)
      - Exploits existing code from high-quality legacy software in C, 
        C++, Fortran, etc.
      - Open source (encourages community input)
      - Unit-tested

   Additional benefits due to Python:              
    

      - Allows fast prototyping of new algorithms
      - Easy to teach 
      - Multi-platform
      - Allows easy access to almost any database


Quick Example
-------------

   Just write in Python

   >>> import networkx as NX
   >>> G=NX.Graph()
   >>> G.add_edge(1,2)
   >>> G.add_node("spam")
   >>> print G.nodes()
   [1, 2, 'spam']
   >>> print G.edges()
   [(1, 2)]


Requirements
-------------

   To use NetworkX you need

      - Python version 2.3 or later http://www.python.org/

   Optional packages to enable drawing networks:

      - Matplotlib       http://matplotlib.sourceforge.net/
      - pygraphviz	 http://networkx.lanl.gov/pygraphviz/
      - Graphviz         http://graphviz.org/
      - numpy		 http://numpy.scipy.org/

   Optional useful packages:

      - Ipython          http://ipython.scipy.org/
      - SciPy		 http://scipy.org/
      - PyGSL            http://pygsl.sourceforge.net/
      - sAsync		 http://foss.eepatents.com/sAsync                
      - PyYAML		 http://pyyaml.org/

Download
--------

   - Releases

     - Python Cheese Shop:  http://cheeseshop.python.org/pypi/networkx/
     - NetworkX site: https://networkx.lanl.gov/download/?C=M;O=D

   - Subversion repository: https://networkx.lanl.gov/svn/networkx/trunk


Quick Install
-------------

   Installing from source:

      - Download the source (tar.gz or zip file)
      - Unpack and change directory to networkx-x.xx
      - Run "python setup.py install" to build and install
      - (optional) cd networkx/tests and run "python setup_egg.py test" to execute the tests
      
    
   Installing a Python egg from source:

      - Download the source (tar.gz or zip file)
      - Unpack and change directory to networkx-x.xx
      - Run "python setup_egg.py install" to build and install
      - (optional) run "python setup_egg.py test" to execute the tests


   **Windows** (binary installer)
 
      Download the installer, run and follow the instructions.
      Please note that we are not Windows users and have only verified
      that the Windows installer passes the "smoke test".  If you
      have problems we suggest installing from the source distribution.


   NetworkX also may be installed using EasyInstall http://peak.telecommunity.com/DevCenter/EasyInstall

::

   easy_install networkx


Authors
-------
   
  - <NAME>  http://math.lanl.gov/~hagberg/
  - <NAME>
  - <NAME>



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