added parallel implementations for number_ algorithms

[akshitasure12]

added parallel implementations for

• number_attracting_components
• number_connected_components
• number_strongly_connected_components
• number_weakly_connected_components

These algorithms involve lightweight computations (e.g., simple summations), limiting their performance. Their behaviour should be analysed in context of PR #79.

[edit]: added the should_run parameter discussed in issue #77.

[akshitasure12]

A few observations:

I ran the following with NETWORKX_BACKEND_PRIORITY_ALGOS=parallel NETWORKX_FALLBACK_TO_NX=False:

python3 test_should_run.py

Contents of test_should_run.py :

import networkx as nx
import logging

nxl = logging.getLogger("networkx")
nxl.addHandler(logging.StreamHandler())
nxl.setLevel(logging.DEBUG)

G = nx.empty_graph(5)
print(nx.number_of_isolates(G))

Output:

Call to 'number_of_isolates' has inputs from {'networkx'} backends, and will try to use backends in the following order: ['parallel', 'networkx']
Backend 'parallel' shouldn't run `number_of_isolates` with arguments: (G=<networkx.classes.graph.Graph object at 0x1055fb6e0>), because: Fast algorithm; not worth converting
Trying next backend: 'networkx'
Call to 'isolates' has inputs from {'networkx'} backends, and will try to use backends in the following order: ['parallel', 'networkx']
Backend 'parallel' does not implement 'isolates'
Trying next backend: 'networkx'
5

Note: Despite setting NETWORKX_FALLBACK_TO_NX=False, the call still proceeds to use the networkx backend.

[dschult]

I am pretty sure the fallback_to_networkx flag applies to the case when you call the function with a graph input that is the backend graph type. That is, "fallback" means we have to convert the backend graph to a NetworkX graph and then call networkx. Perhaps there is a better name for this option. But I think that is why you are still getting the number of isolates. Your input is a NetworkX graph. So it will use the networkx version of the function whatever the value of "fallback_to_networkx" is.