-NetworkX is a Python-based package for the creation, manipulation, and
-study of the structure, dynamics, and function of complex networks.
+NetworkX is a Python language software package for the creation,
+manipulation, and study of the structure, dynamics, and function of complex networks.
-The structure of a graph or network is encoded in the **edges**
-(connections, links, ties, arcs, bonds) between **nodes** (vertices,
-sites, actors). If unqualified, by graph we mean an undirected
-graph, i.e. no multiple edges are allowed. By a network we usually
-mean a graph with weights (fields, properties) on nodes and/or edges.
+With NetworkX you can load and store networks in standard and nonstandard data formats, generate many types of random and classic networks, analyze network structure, build network models, design new network algorithms, draw networks, and much more.
The potential audience for NetworkX includes mathematicians,
-physicists, biologists, computer scientists, and social scientists. The
-current state of the art of the science of
-complex networks is presented in Albert and Barabási [BA02]_, Newman
+physicists, biologists, computer scientists, and social scientists. Good
+reviews of the state-of-the-art in the science of
+complex networks are presented in Albert and Barabási [BA02]_, Newman
[Newman03]_, and Dorogovtsev and Mendes [DM03]_. See also the classic
texts [Bollobas01]_, [Diestel97]_ and [West01]_ for graph theoretic
results and terminology. For basic graph algorithms, we recommend the
texts of Sedgewick, e.g. [Sedgewick01]_ and [Sedgewick02]_ and the
survey of Brandes and Erlebach [BE05]_.
+NetworkX is intended to provide
+- tools for the study the structure and
+ dynamics of social, biological, and infrastructure networks,
+- a standard programming interface and graph implementation that is suitable
+- a rapid development environment for collaborative, multidisciplinary
+- an interface to existing numerical algorithms and code written in C,
+- the ability to painlessly slurp in large nonstandard data sets.
The Python programming language
-Why Python? Past experience showed this approach to maximize
-productivity, power, multi-disciplinary scope (applications include large communication, social, data and biological
-networks), and platform independence. This philosophy does not exclude
-using whatever other language is appropriate for a specific subtask,
-since Python is also an excellent "glue" language [Langtangen04]_.
-Equally important, Python is free, well-supported and a joy to use.
+Python is a powerful programming language that allows simple and flexible representations of networks, and clear and concise expressions of network algorithms (and other algorithms too). Python has a vibrant and growing ecosystem of packages that NetworkX uses to provide more features such as numerical linear algebra and drawing. In addition
+Python is also an excellent "glue" language for putting together pieces of software from other languages which allows reuse of legacy code and engineering of high-performance algorithms [Langtangen04]_.
+Equally important, Python is free, well-supported, and a joy to use.
+In order to make the most out of NetworkX you will want to know how to write basic programs in Python.
Among the many guides to Python, we recommend the documentation at
http://www.python.org and the text by Alex Martelli [Martelli03]_.
NetworkX is free software; you can redistribute it and/or
-modify it under the terms of the :doc:`
NetworkX License </reference/legal>`.
+modify it under the terms of the :doc:` License </reference/legal>`.
We welcome contributions from the community. Information on
NetworkX development is found at the NetworkX Developer Zone
-NetworkX is intended to:
-- Be a tool to study the structure and
- dynamics of social, biological, and infrastructure networks
-- Provide ease-of-use and rapid
- development in a collaborative, multidisciplinary environment
-- Be an Open-source software package that can provide functionality
- to a diverse community of active and easily participating users
-- Provide an easy interface to
- existing code bases written in C, C++, and FORTRAN
-- Painlessly slurp in large nonstandard data sets
-- Provide a standard API and/or graph implementation that is
- suitable for many applications.
-- NetworkX was inspired by Guido van Rossum's 1998 Python
- graph representation essay [vanRossum98]_.
+NetworkX was born in May 2002. The original version was designed and written by Aric Hagberg, Dan Schult, and Pieter Swart in 2002 and 2003.
+The first public release was in April 2005.
-- First public release in April 2005. Version 1.0 released in 2009.
+Many people have contributed to the success of NetworkX. Some of the contributors are listed in the :doc:`credits. </reference/credits>`