bfs_predecessors#

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

Returns an iterator of predecessors 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:
pred: iterator

(node, predecessor) iterator where predecessor is the predecessor of node in a breadth first search starting from source.

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_predecessors(G, 0))
{1: 0, 2: 1}
>>> H = nx.Graph()
>>> H.add_edges_from([(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)])
>>> dict(nx.bfs_predecessors(H, 0))
{1: 0, 2: 0, 3: 1, 4: 1, 5: 2, 6: 2}
>>> M = nx.Graph()
>>> nx.add_path(M, [0, 1, 2, 3, 4, 5, 6])
>>> nx.add_path(M, [2, 7, 8, 9, 10])
>>> sorted(nx.bfs_predecessors(M, source=1, depth_limit=3))
[(0, 1), (2, 1), (3, 2), (4, 3), (7, 2), (8, 7)]
>>> N = nx.DiGraph()
>>> nx.add_path(N, [0, 1, 2, 3, 4, 7])
>>> nx.add_path(N, [3, 5, 6, 7])
>>> sorted(nx.bfs_predecessors(N, source=2))
[(3, 2), (4, 3), (5, 3), (6, 5), (7, 4)]
----

Additional backends implement this function

cugraphGPU-accelerated backend.

sort_neighbors parameter is not yet supported.

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