number_weakly_connected_components

number_weakly_connected_components(G)

Returns the number of weakly connected components in G.

Parameters:

GNetworkX graph

A directed graph.

Returns:

ninteger

Number of weakly connected components

Raises:

NetworkXNotImplemented

If G is undirected.

See also

weakly_connected_components

number_connected_components

number_strongly_connected_components

Notes

For directed graphs only.

Examples

>>> G = nx.DiGraph([(0, 1), (2, 1), (3, 4)])
>>> nx.number_weakly_connected_components(G)
2
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Additional backends implement this function

cugraph : GPU-accelerated backend.

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 weakly 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 weakly connected components as input and returns an iterable component_chunks. The default chunking is done by slicing the list of weakly connected components into n_jobs number of chunks.

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