Merge pull request #1904 from braingram/datatype_validator_fix

Datatype validator fix

Author: braingram

asdf/_tests/tags/core/tests/test_ndarray.py

@@ -99,7 +99,11 @@ def with_custom_extension():
         datatype: int16
       - name: b
         datatype: ['ascii', 16]
-    exact_datatype: true""",
+    exact_datatype: true
+  e:
+    anyOf:
+      - type: "null"
+      - datatype: int16""",
                 "http://nowhere.org/schemas/custom/ndim-1.0.0": """%YAML 1.1
 ---
 $schema: "http://stsci.edu/schemas/asdf/asdf-schema-1.1.0"
@@ -803,6 +807,15 @@ def test_datatype_validation(tmp_path):
     ):
         pass
 
+    content = """
+obj: !<tag:nowhere.org:custom/datatype-1.0.0>
+    e: null
+    """
+    buff = helpers.yaml_to_asdf(content)
+
+    with asdf.open(buff):
+        pass
+
 
 @with_custom_extension()
 def test_structured_datatype_validation(tmp_path):

asdf/tags/core/ndarray.py

@@ -528,12 +528,14 @@ def validate_datatype(validator, datatype, instance, schema):
             in_datatype, _ = numpy_dtype_to_asdf_datatype(array.dtype)
         else:
             msg = "Not an array"
-            raise ValidationError(msg)
+            yield ValidationError(msg)
+            return
     elif isinstance(instance, (np.ndarray, NDArrayType)):
         in_datatype, _ = numpy_dtype_to_asdf_datatype(instance.dtype)
     else:
         msg = "Not an array"
-        raise ValidationError(msg)
+        yield ValidationError(msg)
+        return
 
     # We are only concerned with some fields from the datatype
     # object in the schema so if the schema datatype is structured
@@ -547,23 +549,28 @@ def validate_datatype(validator, datatype, instance, schema):
 
     if schema.get("exact_datatype", False):
         yield ValidationError(f"Expected datatype '{datatype}', got '{in_datatype}'")
+        return
 
     np_datatype = asdf_datatype_to_numpy_dtype(datatype)
     np_in_datatype = asdf_datatype_to_numpy_dtype(in_datatype)
 
     if not np_datatype.fields:
         if np_in_datatype.fields:
             yield ValidationError(f"Expected scalar datatype '{datatype}', got '{in_datatype}'")
+            return
 
         if not np.can_cast(np_in_datatype, np_datatype, "safe"):
             yield ValidationError(f"Can not safely cast from '{in_datatype}' to '{datatype}' ")
+            return
 
     else:
         if not np_in_datatype.fields:
             yield ValidationError(f"Expected structured datatype '{datatype}', got '{in_datatype}'")
+            return
 
         if len(np_in_datatype.fields) != len(np_datatype.fields):
             yield ValidationError(f"Mismatch in number of columns: Expected {len(datatype)}, got {len(in_datatype)}")
+            return
 
         for i in range(len(np_datatype.fields)):
             in_type = np_in_datatype[i]
@@ -574,3 +581,4 @@ def validate_datatype(validator, datatype, instance, schema):
                     f"Expected {numpy_dtype_to_asdf_datatype(out_type)[0]}, "
                     f"got {numpy_dtype_to_asdf_datatype(in_type)[0]}",
                 )
+                return

changes/1904.bugfix.rst

@@ -0,0 +1 @@
+yield instead of raise ValidationError in validate_datatype to allow use in schema combiners