in validation, add check for if a varlen datasets is empty

CHANGELOG.md

@@ -13,6 +13,7 @@
 - Update `get_key` to return all the keys if there are multiple within a `HERD` instance. @mavaylon1 [#999](https://github.com/hdmf-dev/hdmf/pull/999)
 - Improve HTML rendering of tables. @bendichter [#998](https://github.com/hdmf-dev/hdmf/pull/998)
 - Improved issue and PR templates. @rly [#1004](https://github.com/hdmf-dev/hdmf/pull/1004)
+- Added check during validation for if a variable length dataset is empty. @bendichter, @oruebel [#789](https://github.com/hdmf-dev/hdmf/pull/789)
 
 ### Bug fixes
 - Fixed issue with custom class generation when a spec has a `name`. @rly [#1006](https://github.com/hdmf-dev/hdmf/pull/1006)

src/hdmf/validate/validator.py

@@ -118,40 +118,65 @@ class EmptyArrayError(Exception):
 
 def get_type(data, builder_dtype=None):
     """Return a tuple of (the string representation of the type, the format of the string data) for the given data."""
+    # String data
     if isinstance(data, str):
         return 'utf', get_string_format(data)
+    # Bytes data
     elif isinstance(data, bytes):
         return 'ascii', get_string_format(data)
+    # RegionBuilder data
     elif isinstance(data, RegionBuilder):
         return 'region', None
+    # ReferenceBuilder data
     elif isinstance(data, ReferenceBuilder):
         return 'object', None
+    # ReferenceResolver data
     elif isinstance(data, ReferenceResolver):
         return data.dtype, None
+    # Numpy nd-array data
     elif isinstance(data, np.ndarray):
-        if data.size == 0:
+        if data.size > 0:
+            return get_type(data[0], builder_dtype)
+        else:
             raise EmptyArrayError()
-        return get_type(data[0], builder_dtype)
+    # Numpy bool data
     elif isinstance(data, np.bool_):
         return 'bool', None
     if not hasattr(data, '__len__'):
         return type(data).__name__, None
+    # Case for h5py.Dataset and other I/O specific array types
     else:
-        if builder_dtype and isinstance(builder_dtype, list):  # compound dtype
+        # Compound dtype
+        if builder_dtype and isinstance(builder_dtype, list):
             dtypes = []
             string_formats = []
             for i in range(len(builder_dtype)):
                 dtype, string_format = get_type(data[0][i])
                 dtypes.append(dtype)
                 string_formats.append(string_format)
             return dtypes, string_formats
+        # Object has 'dtype' attribute, e.g., an h5py.Dataset
         if hasattr(data, 'dtype'):
             if data.dtype.metadata is not None and data.dtype.metadata.get('vlen') is not None:
-                return get_type(data[0])
-            return data.dtype, None
-        if len(data) == 0:
+                # Try to determine dtype from the first array element
+                if len(data) > 0:
+                    return get_type(data[0], builder_dtype)
+                # Empty array
+                else:
+                    # Empty string array
+                    if data.dtype.metadata["vlen"] == str:
+                        return "utf", None
+                    # Undetermined variable length data type.
+                    else:                        # pragma: no cover
+                        raise EmptyArrayError()  # pragma: no cover
+            # Standard data type (i.e., not compound or vlen)
+            else:
+                return data.dtype, None
+        # If all else has failed, try to determine the datatype from the first element of the array
+        if len(data) > 0:
+            return get_type(data[0], builder_dtype)
+        else:
             raise EmptyArrayError()
-        return get_type(data[0], builder_dtype)
 
 
 def check_shape(expected, received):

tests/unit/validator_tests/test_validate.py

@@ -1118,3 +1118,102 @@ def test_round_trip_validation_of_compound_dtype_with_reference(self):
             attributes={'data_type': 'Foo'}
         )
         self.runBuilderRoundTrip(foo)
+
+
+class TestEmptyDataRoundTrip(ValidatorTestBase):
+    """
+    Test the special case of empty string datasets and attributes during validation
+    """
+    def setUp(self):
+        self.filename = 'test_ref_dataset.h5'
+        super().setUp()
+
+    def tearDown(self):
+        remove_test_file(self.filename)
+        super().tearDown()
+
+    def getSpecs(self):
+        ret = GroupSpec('A test group specification with a data type',
+                        data_type_def='Bar',
+                        datasets=[DatasetSpec(name='data',
+                                              doc='an example dataset',
+                                              dtype='text',
+                                              attributes=[AttributeSpec(
+                                                  name='attr2',
+                                                  doc='an example integer attribute',
+                                                  dtype='int',
+                                                  shape=(None,))]),
+                                  DatasetSpec(name='dataInt',
+                                              doc='an example int dataset',
+                                              dtype='int',
+                                              attributes=[])
+                                  ],
+                        attributes=[AttributeSpec(name='attr1',
+                                                  doc='an example string attribute',
+                                                  dtype='text',
+                                                  shape=(None,))])
+        return (ret,)
+
+    def runBuilderRoundTrip(self, builder):
+        """Executes a round-trip test for a builder
+
+        1. First writes the builder to file,
+        2. next reads a new builder from disk
+        3. and finally runs the builder through the validator.
+        The test is successful if there are no validation errors."""
+        ns_catalog = NamespaceCatalog()
+        ns_catalog.add_namespace(self.namespace.name, self.namespace)
+        typemap = TypeMap(ns_catalog)
+        self.manager = BuildManager(typemap)
+
+        with HDF5IO(self.filename, manager=self.manager, mode='w') as write_io:
+            write_io.write_builder(builder)
+
+        with HDF5IO(self.filename, manager=self.manager, mode='r') as read_io:
+            read_builder = read_io.read_builder()
+            errors = self.vmap.validate(read_builder)
+            self.assertEqual(len(errors), 0, errors)
+
+    def test_empty_string_attribute(self):
+        """Verify that we can determine dtype for empty string attribute during validation"""
+        builder = GroupBuilder('my_bar',
+                               attributes={'data_type': 'Bar', 'attr1': []},  # <-- Empty string attribute
+                               datasets=[DatasetBuilder(name='data', data=['text1', 'text2'],
+                                                        attributes={'attr2': [10, ]}),
+                                         DatasetBuilder(name='dataInt', data=[5, ])
+                                         ])
+        self.runBuilderRoundTrip(builder)
+
+    def test_empty_string_dataset(self):
+        """Verify that we can determine dtype for empty string dataset during validation"""
+        builder = GroupBuilder('my_bar',
+                               attributes={'data_type': 'Bar', 'attr1': ['text1', 'text2']},
+                               datasets=[DatasetBuilder(name='data',    # <-- Empty string dataset
+                                                        data=[],
+                                                        dtype='text',
+                                                        attributes={'attr2': [10, ]}),
+                                         DatasetBuilder(name='dataInt', data=[5, ])
+                                         ])
+        self.runBuilderRoundTrip(builder)
+
+    def test_empty_int_attribute(self):
+        """Verify that we can determine dtype for empty integer attribute  during validation"""
+        builder = GroupBuilder('my_bar',
+                               attributes={'data_type': 'Bar', 'attr1': ['text1', 'text2']},
+                               datasets=[DatasetBuilder(name='data', data=['text1', 'text2'],
+                                                        attributes={'attr2': []}  # <-- Empty integer attribute
+                                                        ),
+                                         DatasetBuilder(name='dataInt', data=[5, ])
+                                         ])
+        self.runBuilderRoundTrip(builder)
+
+    def test_empty_int_dataset(self):
+        """Verify that a dataset builder containing an array of references passes
+        validation after a round trip"""
+        builder = GroupBuilder('my_bar',
+                               attributes={'data_type': 'Bar', 'attr1': ['text1', 'text2']},
+                               datasets=[DatasetBuilder(name='data', data=['text1', 'text2'],
+                                                        attributes={'attr2': [10, ]}),
+                                         DatasetBuilder(name='dataInt', data=[], dtype='int')  # <-- Empty int dataset
+                                         ])
+        self.runBuilderRoundTrip(builder)