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single_source_shortest_path_length(G, source, cutoff=None)

Parameters

G : NetworkX graph
source : node

Starting node for path

cutoff : integer, optional

Depth to stop the search. Only paths of length <= cutoff are returned.

Returns

lengths : dict

Dict keyed by node to shortest path length to source.

Compute the shortest path lengths from source to all reachable nodes.

See Also

shortest_path_length

Examples

>>> G = nx.path_graph(5)
... length = nx.single_source_shortest_path_length(G, 0)
... length[4] 4
>>> for node in length:
...  print(f"{node}: {length[node]}") 0: 0 1: 1 2: 2 3: 3 4: 4
See :

Back References

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

networkx.algorithms.shortest_paths.unweighted.single_target_shortest_path_length networkx.algorithms.shortest_paths.generic.shortest_path_length networkx.algorithms.shortest_paths.unweighted.single_source_shortest_path_length

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


GitHub : /networkx/algorithms/shortest_paths/unweighted.py#18
type: <class 'function'>
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