# strongly_connected_components_recursive#

strongly_connected_components_recursive(G)[source]#

Generate nodes in strongly connected components of graph.

Deprecated since version 3.2: This function is deprecated and will be removed in a future version of NetworkX. Use `strongly_connected_components` instead.

Recursive version of algorithm.

Parameters:
GNetworkX Graph

A directed graph.

Returns:
compgenerator of sets

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

Raises:
NetworkXNotImplemented

If G is undirected.

Notes

Uses Tarjan’s algorithm[Re7cb971df765-1]_ with Nuutila’s modifications[Re7cb971df765-2]_.

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)..

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)]