[ENH] Workflow connect performance

.zenodo.json

@@ -157,6 +157,11 @@
       "name": "De La Vega, Alejandro",
       "orcid": "0000-0001-9062-3778"
     },
+    {
+      "affiliation": "Charite Universitatsmedizin Berlin, Germany",
+      "name": "Waller, Lea",
+      "orcid": "0000-0002-3239-6957"
+    },
     {
       "affiliation": "MIT",
       "name": "Kaczmarzyk, Jakub",

nipype/pipeline/engine/workflows.py

@@ -770,16 +770,46 @@ def _check_nodes(self, nodes):
     def _has_attr(self, parameter, subtype="in"):
         """Checks if a parameter is available as an input or output
         """
+        hierarchy = parameter.split(".")
+        attrname = hierarchy.pop()
+        nodename = hierarchy.pop()
+
+        targetworkflow = self
+        for workflowname in hierarchy:
+            workflow = None
+            for node in targetworkflow._graph.nodes():
+                if node.name == workflowname:
+                    if isinstance(node, Workflow):
+                        workflow = node
+                        break
+            if workflow is None:
+                return False
+            targetworkflow = workflow
+
+        targetnode = None
+        for node in targetworkflow._graph.nodes():
+            if node.name == nodename:
+                if isinstance(node, Workflow):
+                    return False
+                else:
+                    targetnode = node
+                    break
+        if targetnode is None:
+            return False
+
         if subtype == "in":
-            subobject = self.inputs
+            if not hasattr(targetnode.inputs, attrname):
+                return False
         else:
-            subobject = self.outputs
-        attrlist = parameter.split(".")
-        cur_out = subobject
-        for attr in attrlist:
-            if not hasattr(cur_out, attr):
+            if not hasattr(targetnode.outputs, attrname):
                 return False
-            cur_out = getattr(cur_out, attr)
+
+        if subtype == "in":
+            for _, _, d in targetworkflow._graph.in_edges(nbunch=targetnode, data=True):
+                for cd in d["connect"]:
+                    if attrname == cd[1]:
+                        return False
+
         return True
 
     def _get_parameter_node(self, parameter, subtype="in"):