adjacency(self)

For directed graphs, only outgoing neighbors/adjacencies are included.

Returns

adj_iter : iterator

An iterator over (node, adjacency dictionary) for all nodes in the graph.

Returns an iterator over (node, adjacency dict) tuples for all nodes.

Examples

>>> G = nx.path_graph(4)  # or DiGraph, MultiGraph, MultiDiGraph, etc
... [(n, nbrdict) for n, nbrdict in G.adjacency()]
[(0, {1: {}}), (1, {0: {}, 2: {}}), (2, {1: {}, 3: {}}), (3, {2: {}})]

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.classes.multidigraph.MultiDiGraph networkx.classes.digraph.DiGraph networkx.classes.graph.Graph networkx.classes.multigraph.MultiGraph networkx.classes.graph.Graph.adjacency

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/classes/graph.py#1359
type: <class 'function'>
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