bfs_successors#

bfs_successors(G, source, depth_limit=None, sort_neighbors=None)[source]#

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

Parameters:
GNetworkX graph
sourcenode

Specify starting node for breadth-first search

depth_limitint, optional(default=len(G))

Specify the maximum search depth

sort_neighborsfunction (default=None)

A function that takes an iterator over nodes as the input, and returns an iterable of the same nodes with a custom ordering. For example, sorted will sort the nodes in increasing order.

Returns:
succ: iterator

(node, successors) iterator where successors is the non-empty list of successors of node in a breadth first search from source. To appear in the iterator, node must have successors.

See also

bfs_tree
bfs_edges
edge_bfs

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 “Depth-limited-search”.

Examples

>>> G = nx.path_graph(3)
>>> 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)])
>>> 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])
>>> 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])
>>> dict(nx.bfs_successors(G, source=3))
{3: [4], 4: [5]}
----

Additional backends implement this function

cugraphGPU-accelerated backend.

sort_neighbors parameter is not yet supported.

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