Graph types¶
NetworkX provides data structures and methods for storing graphs.
All NetworkX graph classes allow (hashable) Python objects as nodes and any Python object can be assigned as an edge attribute.
The choice of graph class depends on the structure of the graph you want to represent.
Which graph class should I use?¶
Graph Type  NetworkX Class 

Undirected Simple  Graph 
Directed Simple  DiGraph 
With Selfloops  Graph, DiGraph 
With Parallel edges  MultiGraph, MultiDiGraph 
Basic graph types¶
Note
NetworkX uses dicts
to store the nodes and neighbors in a graph.
So the reporting of nodes and edges for the base graph classes will not
necessarily be consistent across versions and platforms. If you need the
order of nodes and edges to be consistent (e.g., when writing automated
tests), please see OrderedGraph
,
OrderedDiGraph
, OrderedMultiGraph
,
or OrderedMultiDiGraph
, which behave like the base
graph classes but give a consistent order for reporting of nodes and edges.
Graph Views¶
View of Graphs as SubGraph, Reverse, Directed, Undirected.
In some algorithms it is convenient to temporarily morph a graph to exclude some nodes or edges. It should be better to do that via a view than to remove and then readd. In other algorithms it is convenient to temporarily morph a graph to reverse directed edges, or treat a directed graph as undirected, etc. This module provides those graph views.
The resulting views are essentially readonly graphs that report data from the orignal graph object. We provide an attribute G._graph which points to the underlying graph object.
Note: Since graphviews look like graphs, one can end up with viewofviewofview chains. Be careful with chains because they become very slow with about 15 nested views. For the common simple case of node induced subgraphs created from the graph class, we shortcut the chain by returning a subgraph of the original graph directly rather than a subgraph of a subgraph. We are careful not to disrupt any edge filter in the middle subgraph. In general, determining how to shortcut the chain is tricky and much harder with restricted_views than with induced subgraphs. Often it is easiest to use .copy() to avoid chains.
generic_graph_view (G[, create_using]) 

subgraph_view (G[, filter_node, filter_edge]) 

reverse_view (G) 