number_strongly_connected_components#

number_strongly_connected_components(G)[source]#

Returns number of strongly connected components in graph.

Parameters:

GNetworkX graph: A directed graph.

Returns:

ninteger: Number of strongly connected components

Raises:

NetworkXNotImplemented: If G is undirected.

See also

strongly_connected_components
number_connected_components
number_weakly_connected_components

Notes

For directed graphs only.

Examples

>>> G = nx.DiGraph(
...     [(0, 1), (1, 2), (2, 0), (2, 3), (4, 5), (3, 4), (5, 6), (6, 3), (6, 7)]
... )
>>> nx.number_strongly_connected_components(G)
3
----

Additional backends implement this function

parallelA networkx backend that uses joblib to run graph algorithms in parallel. Find the nx-parallel’s configuration guide here

The parallel computation is implemented by dividing the list of strongly connected components into chunks and then finding the length of each chunk in parallel and then adding all the lengths at the end.

Additional parameters:

get_chunksstr, function (default = “chunks”): A function that takes in a list of strongly connected components as input and returns an iterable component_chunks. The default chunking is done by slicing the list of strongly connected components into n_jobs number of chunks.

[Source]