Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

# networkx.algorithms.components.strongly_connected_components_recursive¶

strongly_connected_components_recursive(G)[source]

Generate nodes in strongly connected components of graph.

Recursive version of algorithm.

Parameters

G (NetworkX Graph) – A directed graph.

Returns

comp – A generator of sets of nodes, one for each strongly connected component of G.

Return type

generator of sets

Raises

NetworkXNotImplemented – If G is undirected.

Examples

Generate a sorted list of strongly connected components, largest first.

>>> G = nx.cycle_graph(4, create_using=nx.DiGraph())
>>> [
...     len(c)
...     for c in sorted(
...         nx.strongly_connected_components_recursive(G), key=len, reverse=True
...     )
... ]
[4, 3]


If you only want the largest component, it’s more efficient to use max instead of sort.

>>> largest = max(nx.strongly_connected_components_recursive(G), key=len)


To create the induced subgraph of the components use: >>> S = [G.subgraph(c).copy() for c in nx.weakly_connected_components(G)]

Notes

Uses Tarjan’s algorithm[1]_ with Nuutila’s modifications[2]_.

References

1

Depth-first search and linear graph algorithms, R. Tarjan SIAM Journal of Computing 1(2):146-160, (1972).

2

On finding the strongly connected components in a directed graph. E. Nuutila and E. Soisalon-Soinen Information Processing Letters 49(1): 9-14, (1994)..