Graph IO

NetworkX can read and write graphs in many formats. See http://networkx.lanl.gov/reference/readwrite.html for a complete list of currently supported formats.

Reading a graph from a file

>>> G=nx.tetrahedral_graph()

Write to adjacency list format

>>> nx.write_adjlist(G, "tetrahedral.adjlist")

Read from adjacency list format

>>> H=nx.read_adjlist("tetrahedral.adjlist")

Write to edge list format

>>> nx.write_edgelist(G, "tetrahedral.edgelist")

Read from edge list format

>>> H=nx.read_edgelist("tetrahedral.edgelist")

See also Interfacing with other tools below for how to draw graphs with matplotlib or graphviz.

Graphs with multiple edges

See the MultiGraph and MultiDiGraph classes. For example, to build Euler’s famous graph of the bridges of Königsberg over the Pregel river, one can use

>>> K=nx.MultiGraph(name="Königsberg")
>>> K.add_edges_from([("A","B","Honey Bridge"),
...                   ("A","B","Blacksmith's Bridge"),
...                   ("A","C","Green Bridge"),
...                   ("A","C","Connecting Bridge"),
...                   ("A","D","Merchant's Bridge"),
...                   ("C","D","High Bridge"),
...                   ("B","D","Wooden Bridge")])
>>> K.degree("A")
5

Directed Graphs

The DiGraph class provides operations common to digraphs (graphs with directed edges). A subclass of Graph, Digraph adds the following methods to those of Graph:

• out_edges
• out_edges_iter
• in_edges
• in_edges_iter
• has_successor=has_neighbor
• has_predecessor
• successors=neighbors
• successors_iter=neighbors_iter
• predecessors
• predecessors_iter
• out_degree
• out_degree_iter
• in_degree
• in_degree_iter
• reverse

See networkx.DiGraph for more documentation.

Getting and setting edge data

The fastest way to get the data for an edge (n1,n2) is d=G[n1][n2]. But setting G[n1][n2] can make the internal data structure inconsistent.

For Graph and DiGraph to set the edge data just add an edge with the new data: G.add_edge(n1,n2,data)).

For MultiGraph and MultiDiGraph you must remove the old edge first, then add a new edge with the updated data.

There is one special case where you may be able to set the edge data directly: if the edge data is a container (like a list, dictionary or set). For example

>>> G=nx.DiGraph()
>>> G.add_edge(0,1,['a','b','c']) # data is a list
>>> G.edges(data=True)
>>> G[0][1][0]='foo' # set first item in list is set to 'foo'

Interfacing with other tools

NetworkX provides interfaces to Matplotlib and Graphviz for graph layout (node and edge positioning) and drawing. We also use matplotlib for graph spectra and in some drawing operations. Without either, one can still use the basic graph-related functions.

See the graph drawing section for details on how to install and use these tools.

Matplotlib

>>> G=nx.tetrahedral_graph()
>>> nx.draw(G)

Graphviz

>>> G=nx.tetrahedral_graph()
>>> nx.write_dot(G,"tetrahedral.dot")

Specialized Topics

Graphs composed of general objects

For most applications, nodes will have string or integer labels. The power of Python (“everything is an object”) allows us to construct graphs with ANY hashable object as a node. (The Python object None is not allowed as a node). Note however that this will not work with non-Python datastructures, e.g. building a graph on a wrapped Python version of graphviz).

For example, one can construct a graph with Python mathematical functions as nodes, and where two mathematical functions are connected if they are in the same chapter in some Handbook of Mathematical Functions. E.g.

>>> from math import *
>>> G=nx.Graph()
>>> G.add_node(acos)
>>> G.add_node(sinh)
>>> G.add_node(cos)
>>> G.add_node(tanh)
>>> G.add_edge(acos,cos)
>>> G.add_edge(sinh,tanh)
>>> sorted(G.nodes())
[<built-in function acos>, <built-in function cos>, <built-in function sinh>, <built-in function tanh>]

As another example, one can build (meta) graphs using other graphs as the nodes.

We have found this power quite useful, but its abuse can lead to unexpected surprises unless one is familiar with Python. If in doubt, consider using convert_node_labels_to_integers() to obtain a more traditional graph with integer labels.