Fix validation of datetime-formatted strings

CHANGELOG.md

@@ -4,8 +4,6 @@
 
 ### Enhancements
 - Add Data.set_data_io(), which allows for setting a `DataIO` to a data object after-the-fact. @bendichter and @CodyCBakerPhD [#1013](https://github.com/hdmf-dev/hdmf/pull/1013)
-
-### Enhancements
 - Added `add_ref_termset`, updated helper methods for `HERD`, revised `add_ref` to support validations prior to populating the tables
   and added `add_ref_container`.  @mavaylon1 [#968](https://github.com/hdmf-dev/hdmf/pull/968)
 - Use `stacklevel` in most warnings. @rly [#1027](https://github.com/hdmf-dev/hdmf/pull/1027)
@@ -19,8 +17,8 @@
 ### Bug fixes
 - Fixed issue with custom class generation when a spec has a `name`. @rly [#1006](https://github.com/hdmf-dev/hdmf/pull/1006)
 - Fixed issue with usage of deprecated `ruamel.yaml.safe_load` in `src/hdmf/testing/validate_spec.py`. @rly [#1008](https://github.com/hdmf-dev/hdmf/pull/1008)
-
 - Fixed issue where `ElementIdentifiers` data could be set to non-integer values. @rly [#1009](https://github.com/hdmf-dev/hdmf/pull/1009)
+- Fixed issue where string datasets/attributes with isodatetime-formatted values failed validation against a text spec. @rly [#1026](https://github.com/hdmf-dev/hdmf/pull/1026)
 
 ## HDMF 3.11.0 (October 30, 2023)
 

src/hdmf/validate/validator.py

@@ -42,7 +42,7 @@
 __allowable['numeric'] = set(chain.from_iterable(__allowable[k] for k in __allowable if 'int' in k or 'float' in k))
 
 
-def check_type(expected, received):
+def check_type(expected, received, string_format=None):
     '''
     *expected* should come from the spec
     *received* should come from the data
@@ -52,6 +52,12 @@
             raise ValueError('compound type shorter than expected')
         for i, exp in enumerate(DtypeHelper.simplify_cpd_type(expected)):
             rec = received[i]
+            if exp == "isodatetime":  # short circuit for isodatetime
+                sub_string_format = string_format[i]
+                return (
+                    rec in __allowable[exp] or
+                    rec in ("utf", "ascii") and sub_string_format == "isodatetime"
+                )
             if rec not in __allowable[exp]:
                 return False
         return True
@@ -71,6 +77,11 @@
                 received = received.name
         elif isinstance(received, type):
             received = received.__name__
+        if expected == "isodatetime":  # short circuit for isodatetime
+            return (
+                received in __allowable[expected] or
+                (received in ("utf", "ascii") and string_format == "isodatetime")
+            )
         if isinstance(expected, RefSpec):
             expected = expected.reftype
         elif isinstance(expected, type):
@@ -89,48 +100,58 @@
 _iso_re = get_iso8601_regex()
 
 
-def _check_isodatetime(s, default=None):
+def get_string_format(data):
+    """Return the string format of the given data. Possible outputs are "isodatetime" and None.
+    """
+    assert isinstance(data, (str, bytes))
     try:
-        if _iso_re.match(pystr(s)) is not None:
+        if _iso_re.match(pystr(data)) is not None:
             return 'isodatetime'
     except Exception:
         pass
-    return default
+    return None
 
 
 class EmptyArrayError(Exception):
     pass
 
 
-def get_type(data):
+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."""
     if isinstance(data, str):
-        return _check_isodatetime(data, 'utf')
+        return 'utf', get_string_format(data)
     elif isinstance(data, bytes):
-        return _check_isodatetime(data, 'ascii')
+        return 'ascii', get_string_format(data)
     elif isinstance(data, RegionBuilder):
-        return 'region'
+        return 'region', None
     elif isinstance(data, ReferenceBuilder):
-        return 'object'
+        return 'object', None
     elif isinstance(data, ReferenceResolver):
-        return data.dtype
+        return data.dtype, None
     elif isinstance(data, np.ndarray):
         if data.size == 0:
             raise EmptyArrayError()
-        return get_type(data[0])
+        return get_type(data[0], builder_dtype)
     elif isinstance(data, np.bool_):
-        return 'bool'
+        return 'bool', None
     if not hasattr(data, '__len__'):
-        return type(data).__name__
+        return type(data).__name__, None
     else:
+        if builder_dtype and isinstance(builder_dtype, list):  # compound dtype
+            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
         if hasattr(data, 'dtype'):
-            if isinstance(data.dtype, list):
-                return [get_type(data[0][i]) for i in range(len(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
+            return data.dtype, None
         if len(data) == 0:
             raise EmptyArrayError()
-        return get_type(data[0])
+        return get_type(data[0], builder_dtype)
 
 
 def check_shape(expected, received):
@@ -310,7 +331,7 @@
                 if not isinstance(value, BaseBuilder):
                     expected = '%s reference' % spec.dtype.reftype
                     try:
-                        value_type = get_type(value)
+                        value_type, _ = get_type(value)
                         ret.append(DtypeError(self.get_spec_loc(spec), expected, value_type))
                     except EmptyArrayError:
                         # do not validate dtype of empty array. HDMF does not yet set dtype when writing a list/tuple
@@ -323,8 +344,8 @@
                         ret.append(IncorrectDataType(self.get_spec_loc(spec), spec.dtype.target_type, data_type))
             else:
                 try:
-                    dtype = get_type(value)
-                    if not check_type(spec.dtype, dtype):
+                    dtype, string_format = get_type(value)
+                    if not check_type(spec.dtype, dtype, string_format):
                         ret.append(DtypeError(self.get_spec_loc(spec), spec.dtype, dtype))
                 except EmptyArrayError:
                     # do not validate dtype of empty array. HDMF does not yet set dtype when writing a list/tuple
@@ -385,14 +406,17 @@
         data = builder.data
         if self.spec.dtype is not None:
             try:
-                dtype = get_type(data)
-                if not check_type(self.spec.dtype, dtype):
+                dtype, string_format = get_type(data, builder.dtype)
+                if not check_type(self.spec.dtype, dtype, string_format):
                     ret.append(DtypeError(self.get_spec_loc(self.spec), self.spec.dtype, dtype,
                                           location=self.get_builder_loc(builder)))
             except EmptyArrayError:
                 # do not validate dtype of empty array. HDMF does not yet set dtype when writing a list/tuple
                 pass
-        shape = get_data_shape(data)
+        if isinstance(builder.dtype, list):
+            shape = (len(builder.data), )  # only 1D datasets with compound types are supported
+        else:
+            shape = get_data_shape(data)
         if not check_shape(self.spec.shape, shape):
             if shape is None:
                 ret.append(ExpectedArrayError(self.get_spec_loc(self.spec), self.spec.shape, str(data),

tests/unit/validator_tests/test_validate.py

@@ -116,7 +116,18 @@ def getSpecs(self):
                 ),
                 DatasetSpec('an example time dataset', 'isodatetime', name='datetime'),
                 DatasetSpec('an example time dataset', 'isodatetime', name='date', quantity='?'),
-                DatasetSpec('an array of times', 'isodatetime', name='time_array', dims=('num_times',), shape=(None,))
+                DatasetSpec('an array of times', 'isodatetime', name='time_array', dims=('num_times',), shape=(None,)),
+                DatasetSpec(
+                    doc='an array with compound dtype that includes an isodatetime',
+                    dtype=[
+                        DtypeSpec('x', doc='x', dtype='int'),
+                        DtypeSpec('y', doc='y', dtype='isodatetime'),
+                    ],
+                    name='cpd_array',
+                    dims=('num_times',),
+                    shape=(None,),
+                    quantity="?",
+                ),
             ],
             attributes=[AttributeSpec('attr1', 'an example string attribute', 'text')])
         return ret,
@@ -129,7 +140,15 @@ def test_valid_isodatetime(self):
                 DatasetBuilder('data', 100, attributes={'attr2': 10}),
                 DatasetBuilder('datetime', datetime(2017, 5, 1, 12, 0, 0)),
                 DatasetBuilder('date', date(2017, 5, 1)),
-                DatasetBuilder('time_array', [datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())])
+                DatasetBuilder('time_array', [datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())]),
+                DatasetBuilder(
+                    name='cpd_array',
+                    data=[(1, datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal()))],
+                    dtype=[
+                        DtypeSpec('x', doc='x', dtype='int'),
+                        DtypeSpec('y', doc='y', dtype='isodatetime'),
+                    ],
+                ),
             ]
         )
         validator = self.vmap.get_validator('Bar')
@@ -143,7 +162,7 @@ def test_invalid_isodatetime(self):
             datasets=[
                 DatasetBuilder('data', 100, attributes={'attr2': 10}),
                 DatasetBuilder('datetime', 100),
-                DatasetBuilder('time_array', [datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())])
+                DatasetBuilder('time_array', [datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())]),
             ]
         )
         validator = self.vmap.get_validator('Bar')
@@ -152,18 +171,44 @@ def test_invalid_isodatetime(self):
         self.assertValidationError(result[0], DtypeError, name='Bar/datetime')
 
     def test_invalid_isodatetime_array(self):
-        builder = GroupBuilder('my_bar',
-                               attributes={'data_type': 'Bar', 'attr1': 'a string attribute'},
-                               datasets=[DatasetBuilder('data', 100, attributes={'attr2': 10}),
-                                         DatasetBuilder('datetime',
-                                                        datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())),
-                                         DatasetBuilder('time_array',
-                                                        datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal()))])
+        builder = GroupBuilder(
+            'my_bar',
+            attributes={'data_type': 'Bar', 'attr1': 'a string attribute'},
+            datasets=[
+                DatasetBuilder('data', 100, attributes={'attr2': 10}),
+                DatasetBuilder('datetime', datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())),
+                DatasetBuilder('time_array', datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())),
+            ],
+        )
         validator = self.vmap.get_validator('Bar')
         result = validator.validate(builder)
         self.assertEqual(len(result), 1)
         self.assertValidationError(result[0], ExpectedArrayError, name='Bar/time_array')
 
+    def test_invalid_cpd_isodatetime_array(self):
+        builder = GroupBuilder(
+            'my_bar',
+            attributes={'data_type': 'Bar', 'attr1': 'a string attribute'},
+            datasets=[
+                DatasetBuilder('data', 100, attributes={'attr2': 10}),
+                DatasetBuilder('datetime', datetime(2017, 5, 1, 12, 0, 0)),
+                DatasetBuilder('date', date(2017, 5, 1)),
+                DatasetBuilder('time_array', [datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())]),
+                DatasetBuilder(
+                    name='cpd_array',
+                    data=[(1, "wrong")],
+                    dtype=[
+                        DtypeSpec('x', doc='x', dtype='int'),
+                        DtypeSpec('y', doc='y', dtype='isodatetime'),
+                    ],
+                ),
+            ],
+        )
+        validator = self.vmap.get_validator('Bar')
+        result = validator.validate(builder)
+        self.assertEqual(len(result), 1)
+        self.assertValidationError(result[0], DtypeError, name='Bar/cpd_array')
+
 
 class TestNestedTypes(ValidatorTestBase):
 
@@ -508,6 +553,58 @@ def test_empty_nparray(self):
     # TODO test shape validation more completely
 
 
+class TestStringDatetime(TestCase):
+
+    def test_str_coincidental_isodatetime(self):
+        """Test validation of a text spec allows a string that coincidentally matches the isodatetime format."""
+        spec_catalog = SpecCatalog()
+        spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(doc='an example scalar dataset', dtype="text", name='data1'),
+                DatasetSpec(doc='an example 1D dataset', dtype="text", name='data2', shape=(None, )),
+                DatasetSpec(
+                    doc='an example 1D compound dtype dataset',
+                    dtype=[
+                        DtypeSpec('x', doc='x', dtype='int'),
+                        DtypeSpec('y', doc='y', dtype='text'),
+                    ],
+                    name='data3',
+                    shape=(None, ),
+                ),
+            ],
+            attributes=[
+                AttributeSpec(name='attr1', doc='an example scalar attribute', dtype="text"),
+                AttributeSpec(name='attr2', doc='an example 1D attribute', dtype="text", shape=(None, )),
+            ]
+        )
+        spec_catalog.register_spec(spec, 'test.yaml')
+        namespace = SpecNamespace(
+            'a test namespace', CORE_NAMESPACE, [{'source': 'test.yaml'}], version='0.1.0', catalog=spec_catalog
+        )
+        vmap = ValidatorMap(namespace)
+
+        bar_builder = GroupBuilder(
+            name='my_bar',
+            attributes={'data_type': 'Bar', 'attr1': "2023-01-01", 'attr2': ["2023-01-01"]},
+            datasets=[
+                DatasetBuilder(name='data1', data="2023-01-01"),
+                DatasetBuilder(name='data2', data=["2023-01-01"]),
+                DatasetBuilder(
+                    name='data3',
+                    data=[(1, "2023-01-01")],
+                    dtype=[
+                        DtypeSpec('x', doc='x', dtype='int'),
+                        DtypeSpec('y', doc='y', dtype='text'),
+                    ],
+                ),
+            ],
+        )
+        results = vmap.validate(bar_builder)
+        self.assertEqual(len(results), 0)
+
+
 class TestLinkable(TestCase):
 
     def set_up_spec(self):