Check for dataset type compatibility when creating execution butler

python/lsst/pipe/base/executionButlerBuilder.py

@@ -28,6 +28,7 @@
 from typing import Callable, DefaultDict, Iterable, List, Mapping, Optional, Set, Tuple, Union
 
 from lsst.daf.butler import Butler, Config, DataCoordinate, DatasetRef, DatasetType
+from lsst.daf.butler.registry import ConflictingDefinitionError
 from lsst.daf.butler.core.repoRelocation import BUTLER_ROOT_TAG
 from lsst.daf.butler.transfers import RepoExportContext
 from lsst.resources import ResourcePath, ResourcePathExpression
@@ -218,7 +219,22 @@ def _import(
 
     # Register datasets to be produced and insert them into the registry
     for dsType, dataIds in inserts.items():
-        newButler.registry.registerDatasetType(dsType)
+        # There may be inconsistencies with storage class definitions
+        # so those differences must be checked.
+        try:
+            newButler.registry.registerDatasetType(dsType)
+        except ConflictingDefinitionError:
+            # We do not at this point know whether the dataset type is
+            # an intermediate (and so must be able to support conversion
+            # from the registry storage class to an input) or solely an output
+            # dataset type. Test both compatibilities.
+            registryDsType = newButler.registry.getDatasetType(dsType.name)
+            if registryDsType.is_compatible_with(dsType) and dsType.is_compatible_with(registryDsType):
+                pass
+            else:
+                # Not compatible to re-raise the original exception.
+                raise
+
         newButler.registry.insertDatasets(dsType, dataIds, run)
 
     return newButler