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bfs_successors(G, source, depth_limit=None, sort_neighbors=None)

Notes

Based on http://www.ics.uci.edu/~eppstein/PADS/BFS.py by D. Eppstein, July 2004.The modifications to allow depth limits based on the Wikipedia article ":None:None:`Depth-limited-search`".

            <Unimplemented 'target' '.. _Depth-limited-search: https://en.wikipedia.org/wiki/Depth-limited_search'>
           

Parameters

G : NetworkX graph
source : node

Specify starting node for breadth-first search

depth_limit : int, optional(default=len(G))

Specify the maximum search depth

sort_neighbors : function

A function that takes the list of neighbors of given node as input, and returns an iterator over these neighbors but with custom ordering.

Returns

succ: iterator

(node, successors) iterator where successors is the non-empty list of successors of :None:None:`node` in a breadth first search from :None:None:`source`. To appear in the iterator, :None:None:`node` must have successors.

Returns an iterator of successors in breadth-first-search from source.

See Also

bfs_edges
bfs_tree
edge_bfs

Examples

>>> G = nx.path_graph(3)
... print(dict(nx.bfs_successors(G, 0))) {0: [1], 1: [2]}
>>> H = nx.Graph()
... H.add_edges_from([(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)])
... print(dict(nx.bfs_successors(H, 0))) {0: [1, 2], 1: [3, 4], 2: [5, 6]}
>>> G = nx.Graph()
... nx.add_path(G, [0, 1, 2, 3, 4, 5, 6])
... nx.add_path(G, [2, 7, 8, 9, 10])
... print(dict(nx.bfs_successors(G, source=1, depth_limit=3))) {1: [0, 2], 2: [3, 7], 3: [4], 7: [8]}
>>> G = nx.DiGraph()
... nx.add_path(G, [0, 1, 2, 3, 4, 5])
... print(dict(nx.bfs_successors(G, source=3))) {3: [4], 4: [5]}
See :

Back References

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

networkx.algorithms.traversal.breadth_first_search.bfs_successors

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/traversal/breadth_first_search.py#300
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