This documentation is currently being updated for release 0.99 of NetworkX. This update includes significant changes to the underlying Graph and DiGraph objects to reflect our common use case of weighted graphs and to improve performance. See the API changes for detailed information.

High productivity software for complex networks

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

Quick Example

>>> 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)]

Documentation

Tutorial start here Reference guide to all functions and classes Examples using the library Gallery network drawings

Contents a complete overview Search Page search the documentation General Index all functions, classes, terms Module Index quick access to all documented modules

Features:

• 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

Get NetworkX

NetworkX is available as an easy-installable package on the Python Package Index.

The code can be found on the NetworkX SVN server at http://networkx.lanl.gov/svn/networkx/trunk.