Add should_run policy for when nodes is None

nx_parallel/algorithms/cluster.py

@@ -80,7 +80,7 @@ def _compute_clustering_chunk(node_iter_chunk):
     return clustering
 
 
-@nxp._configure_if_nx_active()
+@nxp._configure_if_nx_active(should_run=nxp.should_run_if_nodes_none)
 def triangles(G, nodes=None, get_chunks="chunks"):
     """The nodes are chunked into `node_chunks` and for all `node_chunks`
     the number of triangles that include a node as one vertex is computed

nx_parallel/tests/test_should_run.py

@@ -52,6 +52,19 @@ def dummy_if_large(G):
     assert dummy_if_large.should_run(largeG)
 
 
+def test_should_run_if_nodes_none():
+    @nxp._configure_if_nx_active(should_run=nxp.should_run_if_nodes_none)
+    def dummy_nodes_none(G, nodes=None):
+        pass
+
+    G = nx.fast_gnp_random_graph(20, 0.6, seed=42)
+    assert (
+        dummy_nodes_none.should_run(G, nodes=[1, 3])
+        == "`nodes` should be None for parallel execution"
+    )
+    assert dummy_nodes_none.should_run(G)
+
+
 def test_should_run_if_sparse():
     @nxp._configure_if_nx_active(should_run=nxp.should_run_if_sparse)
     def dummy_if_sparse(G):

nx_parallel/utils/should_run_policies.py

@@ -5,6 +5,7 @@
     "default_should_run",
     "should_skip_parallel",
     "should_run_if_large",
+    "should_run_if_nodes_none",
     "should_run_if_sparse",
 ]
 
@@ -27,6 +28,12 @@ def default_should_run(*_):
     return True
 
 
+def should_run_if_nodes_none(G, nodes=None, *_):
+    if nodes is None:
+        return True
+    return "`nodes` should be None for parallel execution"
+
+
 def should_run_if_sparse(G, *args, threshold=0.3, **kwargs):
     if hasattr(G, "graph_object"):
         G = G.graph_object