BFS is a workhorse! There are still many BFS-based algorithms still to do.

My main TODO is to benchmark these to give them a proper shakedown. I like to shake down most algorithms we add. Also, I wonder whether we should use A.T or AT in a couple places. I also wonder if we can come up with a heuristic to detect negative cycles.

It may be nice to know whether directed graphs are structurally symmetric. If we knew this, we could improve is_weakly_connected and other algorithms.

Also, there may be a couple NetworkX bugs to fix or behaviors to match.

Implemented:

• Components
  • is_connected
  • is_weakly_connected
  • node_connected_component
• Shortest Paths
  • all_pairs_shortest_path_length
  • negative_edge_cycle
  • single_source_shortest_path_length
  • single_target_shortest_path_length
• Traversal
  • bfs_layers
  • descendants_at_distance

I'm also not sure if these are the best algorithms for connected component-related functions. Connected components are an important class of algorithms that we should add soon (for example, we have an implementation of FastSV in a Jupyter notebook that we can port over), so perhaps we'll revisit these algorithms then.

Codecov Report

coverage: 87.71% and project coverage change: +2.46 🎉

Comparison is base (6de1fd6) 69.16% compared to head (029a639) 71.62%.

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Additional details and impacted files

@@            Coverage Diff             @@
##             main      #51      +/-   ##
==========================================
+ Coverage   69.16%   71.62%   +2.46%     
==========================================
  Files          77       89      +12     
  Lines        3152     3461     +309     
  Branches      602      642      +40     
==========================================
+ Hits         2180     2479     +299     
+ Misses        786      783       -3     
- Partials      186      199      +13     

Impacted Files	Coverage Δ
graphblas_algorithms/nxapi/_utils.py	57.47% <0.00%> (ø)
graphblas_algorithms/nxapi/cluster.py	85.55% <ø> (+7.55%)	⬆️
graphblas_algorithms/classes/nodeset.py	69.44% <42.85%> (-2.20%)	⬇️
...as_algorithms/algorithms/link_analysis/hits_alg.py	60.86% <50.00%> (ø)
...blas_algorithms/nxapi/shortest_paths/unweighted.py	62.50% <62.50%> (ø)
graphblas_algorithms/classes/nodemap.py	50.67% <75.00%> (+1.70%)	⬆️
...s_algorithms/algorithms/shortest_paths/weighted.py	31.36% <78.12%> (+11.21%)	⬆️
...algorithms/algorithms/shortest_paths/unweighted.py	78.57% <78.57%> (ø)
graphblas_algorithms/algorithms/dag.py	94.28% <81.81%> (+0.73%)	⬆️
...as_algorithms/algorithms/shortest_paths/generic.py	86.66% <92.30%> (+1.48%)	⬆️
... and 26 more

... and 1 file with indirect coverage changes

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Merging so we can do a release before PyConUS. May be able to benchmark and shakedown some algorithms later, but they're probably good enough.