Note
This documents the development version of NetworkX. Documentation for the current release can be found here.
networkx.classes.graphviews.subgraph_view¶

subgraph_view
(G, filter_node=<function no_filter>, filter_edge=<function no_filter>)[source]¶ View of
G
applying a filter on nodes and edges.subgraph_view
provides a readonly view of the input graph that excludes nodes and edges based on the outcome of two filter functionsfilter_node
andfilter_edge
.The
filter_node
function takes one argument — the node — and returnsTrue
if the node should be included in the subgraph, andFalse
if it should not be included.The
filter_edge
function takes two (or three arguments ifG
is a multigraph) — the nodes describing an edge, plus the edgekey if parallel edges are possible — and returnsTrue
if the edge should be included in the subgraph, andFalse
if it should not be included.Both node and edge filter functions are called on graph elements as they are queried, meaning there is no upfront cost to creating the view.
 Parameters
 Gnetworkx.Graph
A directed/undirected graph/multigraph
 filter_nodecallable, optional
A function taking a node as input, which returns
True
if the node should appear in the view. filter_edgecallable, optional
A function taking as input the two nodes describing an edge (plus the edgekey if
G
is a multigraph), which returnsTrue
if the edge should appear in the view.
 Returns
 graphnetworkx.Graph
A readonly graph view of the input graph.
Examples
>>> G = nx.path_graph(6)
Filter functions operate on the node, and return
True
if the node should appear in the view:>>> def filter_node(n1): ... return n1 != 5 ... >>> view = nx.subgraph_view(G, filter_node=filter_node) >>> view.nodes() NodeView((0, 1, 2, 3, 4))
We can use a closure pattern to filter graph elements based on additional data — for example, filtering on edge data attached to the graph:
>>> G[3][4]["cross_me"] = False >>> def filter_edge(n1, n2): ... return G[n1][n2].get("cross_me", True) ... >>> view = nx.subgraph_view(G, filter_edge=filter_edge) >>> view.edges() EdgeView([(0, 1), (1, 2), (2, 3), (4, 5)])
>>> view = nx.subgraph_view(G, filter_node=filter_node, filter_edge=filter_edge,) >>> view.nodes() NodeView((0, 1, 2, 3, 4)) >>> view.edges() EdgeView([(0, 1), (1, 2), (2, 3)])