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bfs_edges(G, source, reverse=False, depth_limit=None, sort_neighbors=None)

Notes

The naming of this function is very similar to ~networkx.algorithms.traversal.edgebfs.edge_bfs . The difference is that edge_bfs yields edges even if they extend back to an already explored node while this generator yields the edges of the tree that results from a breadth-first-search (BFS) so no edges are reported if they extend to already explored nodes. That means edge_bfs reports all edges while bfs_edges only reports those traversed by a node-based BFS. Yet another description is that bfs_edges reports the edges traversed during BFS while edge_bfs reports all edges in the order they are explored.

Based on the breadth-first search implementation in PADS by D. Eppstein, July 2004; with modifications to allow depth limits as described in .

Parameters

G : NetworkX graph
source : node: Specify starting node for breadth-first search; this function iterates over only those edges in the component reachable from this node.
reverse : bool, optional: If True traverse a directed graph in the reverse direction
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.

Iterate over edges in a breadth-first-search starting at source.

Yields

edge: 2-tuple of nodes: Yields edges resulting from the breadth-first search.

Examples

>>> G = nx.path_graph(3)
>>> list(nx.bfs_edges(G, 0))
[(0, 1), (1, 2)]
>>> list(nx.bfs_edges(G, source=0, depth_limit=1))
[(0, 1)]

>>> G = nx.path_graph(3)
>>> root = 2
>>> edges = nx.bfs_edges(G, root)
>>> nodes = [root] + [v for u, v in edges]
>>> nodes
[2, 1, 0]

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_predecessors networkx.algorithms.traversal.depth_first_search.dfs_edges networkx.algorithms.traversal.breadth_first_search.bfs_successors networkx.algorithms.traversal.edgebfs.edge_bfs networkx.algorithms.traversal.breadth_first_search.bfs_tree networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes networkx.algorithms.traversal.breadth_first_search.generic_bfs_edges

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