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dfs_edges(G, source=None, depth_limit=None)

Perform a depth-first-search over the nodes of G and yield the edges in order. This may not generate all edges in G (see ~networkx.algorithms.traversal.edgedfs.edge_dfs ).

Notes

If a source is not specified then a source is chosen arbitrarily and repeatedly until all components in the graph are searched.

The implementation of this function is adapted from David Eppstein's depth-first search function in PADS , with modifications to allow depth limits based on the Wikipedia article "Depth-limited search" .

Parameters

G : NetworkX graph
source : node, optional: Specify starting node for depth-first search and yield edges in the component reachable from source.
depth_limit : int, optional (default=len(G)): Specify the maximum search depth.

Iterate over edges in a depth-first-search (DFS).

Yields

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

Examples

>>> G = nx.path_graph(5)
... list(nx.dfs_edges(G, source=0))
[(0, 1), (1, 2), (2, 3), (3, 4)]

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

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_edges networkx.algorithms.traversal.edgedfs.edge_dfs networkx.algorithms.traversal.depth_first_search.dfs_edges networkx.algorithms.traversal.depth_first_search.dfs_labeled_edges networkx.algorithms.traversal.depth_first_search.dfs_postorder_nodes networkx.algorithms.traversal.depth_first_search.dfs_preorder_nodes

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