allow a datetime.date object to be used instead of datetime.datetime for isodatetime data (#874)

Co-authored-by: Ryan Ly <[email protected]>

Author: bendichter

CHANGELOG.md

@@ -4,8 +4,9 @@
 
 ### New features and minor improvements
 - Updated `ExternalResources` to have EntityKeyTable with updated tests/documentation and minor bug fix to ObjectKeyTable. @mavaylon1 [#872](https://github.com/hdmf-dev/hdmf/pull/872)
-- Added warning for DynamicTableRegion links that are not added to the same parent as the original container object. @mavaylon1 [#891](https://github.com/hdmf-dev/hdmf/pull/891)
+- Added warning for `DynamicTableRegion` links that are not added to the same parent as the original container object. @mavaylon1 [#891](https://github.com/hdmf-dev/hdmf/pull/891)
 - Added the `TermSet` class along with integrated validation methods for any child of `AbstractContainer`, e.g., `VectorData`, `Data`, `DynamicTable`. @mavaylon1 [#880](https://github.com/hdmf-dev/hdmf/pull/880)
+- Allow for `datetime.date` to be used instead of `datetime.datetime`. @bendichter [#874](https://github.com/hdmf-dev/hdmf/pull/874)
 - Updated `HDMFIO` and `HDF5IO` to support `ExternalResources`. @mavaylon1 [#895](https://github.com/hdmf-dev/hdmf/pull/895)
 - Dropped Python 3.7 support. @rly [#897](https://github.com/hdmf-dev/hdmf/pull/897)
 

src/hdmf/build/builders.py

@@ -3,7 +3,7 @@
 import posixpath as _posixpath
 from abc import ABCMeta
 from collections.abc import Iterable
-from datetime import datetime
+from datetime import datetime, date
 
 import numpy as np
 from h5py import RegionReference
@@ -318,7 +318,7 @@ class DatasetBuilder(BaseBuilder):
 
     @docval({'name': 'name', 'type': str, 'doc': 'The name of the dataset.'},
             {'name': 'data',
-             'type': ('array_data', 'scalar_data', 'data', 'DatasetBuilder', 'RegionBuilder', Iterable, datetime),
+             'type': ('array_data', 'scalar_data', 'data', 'DatasetBuilder', 'RegionBuilder', Iterable, datetime, date),
              'doc': 'The data in this dataset.', 'default': None},
             {'name': 'dtype', 'type': (type, np.dtype, str, list),
              'doc': 'The datatype of this dataset.', 'default': None},

src/hdmf/build/classgenerator.py

@@ -1,5 +1,5 @@
 from copy import deepcopy
-from datetime import datetime
+from datetime import datetime, date
 
 import numpy as np
 
@@ -126,8 +126,8 @@ def __new__(cls, *args, **kwargs):  # pragma: no cover
         'ascii': bytes,
         'bytes': bytes,
         'bool': (bool, np.bool_),
-        'isodatetime': datetime,
-        'datetime': datetime
+        'isodatetime': (datetime, date),
+        'datetime': (datetime, date)
     }
 
     @classmethod

src/hdmf/build/objectmapper.py

@@ -3,7 +3,6 @@
 import warnings
 from collections import OrderedDict
 from copy import copy
-from datetime import datetime
 
 import numpy as np
 
@@ -611,7 +610,8 @@ def __convert_string(self, value, spec):
                 elif 'ascii' in spec.dtype:
                     string_type = bytes
                 elif 'isodatetime' in spec.dtype:
-                    string_type = datetime.isoformat
+                    def string_type(x):
+                        return x.isoformat()  # method works for both date and datetime
                 if string_type is not None:
                     if spec.shape is not None or spec.dims is not None:
                         ret = list(map(string_type, value))

src/hdmf/spec/spec.py

@@ -41,7 +41,7 @@ class DtypeHelper:
         'object': ['object'],
         'region': ['region'],
         'numeric': ['numeric'],
-        'isodatetime': ["isodatetime", "datetime"]
+        'isodatetime': ["isodatetime", "datetime", "date"]
     }
 
     # List of recommended primary dtype strings. These are the keys of primary_dtype_string_synonyms

src/hdmf/utils.py

@@ -599,8 +599,7 @@ def dec(func):
                            'expected {})'.format(a['name'], [type(x) for x in a['enum']], a['type']))
                     raise Exception(msg)
             if a.get('allow_none', False) and 'default' not in a:
-                msg = ('docval for {}: allow_none=True can only be set if a default value is provided.').format(
-                    a['name'])
+                msg = 'docval for {}: allow_none=True can only be set if a default value is provided.'.format(a['name'])
                 raise Exception(msg)
             if 'default' in a:
                 kw.append(a)

src/hdmf/validate/validator.py

@@ -79,8 +79,10 @@ def check_type(expected, received):
 
 
 def get_iso8601_regex():
-    isodate_re = (r'^(-?(?:[1-9][0-9]*)?[0-9]{4})-(1[0-2]|0[1-9])-(3[01]|0[1-9]|[12][0-9])T(2[0-3]|[01][0-9]):'
-                  r'([0-5][0-9]):([0-5][0-9])(\.[0-9]+)?(Z|[+-](?:2[0-3]|[01][0-9]):[0-5][0-9])?$')
+    isodate_re = (
+        r'^(-?(?:[1-9][0-9]*)?[0-9]{4})-(1[0-2]|0[1-9])-(3[01]|0[1-9]|[12][0-9])'  # date
+        r'(T(2[0-3]|[01][0-9]):([0-5][0-9]):([0-5][0-9])(\.[0-9]+)?(Z|[+-](?:2[0-3]|[01][0-9]):[0-5][0-9])?)?$'  # time
+    )
     return re.compile(isodate_re)
 
 

tests/unit/build_tests/mapper_tests/test_build_datetime.py

@@ -0,0 +1,85 @@
+from hdmf.utils import docval, getargs
+from hdmf import Container
+from hdmf.spec import GroupSpec, DatasetSpec
+from hdmf.testing import TestCase
+from datetime import datetime, date
+
+from tests.unit.helpers.utils import create_test_type_map
+
+
+class Bar(Container):
+
+    @docval({'name': 'name', 'type': str, 'doc': 'the name of this Bar'},
+            {'name': 'data', 'type': ('data', 'array_data', datetime, date), 'doc': 'some data'})
+    def __init__(self, **kwargs):
+        name, data = getargs('name', 'data', kwargs)
+        super().__init__(name=name)
+        self.__data = data
+
+    @property
+    def data_type(self):
+        return 'Bar'
+
+    @property
+    def data(self):
+        return self.__data
+
+
+class TestBuildDatasetDateTime(TestCase):
+    """Test that building a dataset with dtype isodatetime works with datetime and date objects."""
+
+    def test_datetime_scalar(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[DatasetSpec(doc='an example dataset', name='data', dtype='isodatetime')],
+        )
+        type_map = create_test_type_map([bar_spec], {'Bar': Bar})
+
+        bar_inst = Bar(name='my_bar', data=datetime(2023, 7, 9))
+        builder = type_map.build(bar_inst)
+        ret = builder.get('data')
+        assert ret.data == b'2023-07-09T00:00:00'
+        assert ret.dtype == 'ascii'
+
+    def test_date_scalar(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[DatasetSpec(doc='an example dataset', name='data', dtype='isodatetime')],
+        )
+        type_map = create_test_type_map([bar_spec], {'Bar': Bar})
+
+        bar_inst = Bar(name='my_bar', data=date(2023, 7, 9))
+        builder = type_map.build(bar_inst)
+        ret = builder.get('data')
+        assert ret.data == b'2023-07-09'
+        assert ret.dtype == 'ascii'
+
+    def test_datetime_array(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[DatasetSpec(doc='an example dataset', name='data', dtype='isodatetime', dims=(None,))],
+        )
+        type_map = create_test_type_map([bar_spec], {'Bar': Bar})
+
+        bar_inst = Bar(name='my_bar', data=[datetime(2023, 7, 9), datetime(2023, 7, 10)])
+        builder = type_map.build(bar_inst)
+        ret = builder.get('data')
+        assert ret.data == [b'2023-07-09T00:00:00', b'2023-07-10T00:00:00']
+        assert ret.dtype == 'ascii'
+
+    def test_date_array(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[DatasetSpec(doc='an example dataset', name='data', dtype='isodatetime', dims=(None,))],
+        )
+        type_map = create_test_type_map([bar_spec], {'Bar': Bar})
+
+        bar_inst = Bar(name='my_bar', data=[date(2023, 7, 9), date(2023, 7, 10)])
+        builder = type_map.build(bar_inst)
+        ret = builder.get('data')
+        assert ret.data == [b'2023-07-09', b'2023-07-10']
+        assert ret.dtype == 'ascii'

tests/unit/build_tests/test_convert_dtype.py

@@ -1,4 +1,4 @@
-from datetime import datetime
+from datetime import datetime, date
 
 import numpy as np
 from hdmf.backends.hdf5 import H5DataIO
@@ -534,8 +534,20 @@ def test_isodatetime_spec(self):
 
         # NOTE: datetime.isoformat is called on all values with a datetime spec before conversion
         # see ObjectMapper.get_attr_value
-        value = datetime.isoformat(datetime(2020, 11, 10))
+        value = datetime(2020, 11, 10).isoformat()
         ret, ret_dtype = ObjectMapper.convert_dtype(spec, value)
         self.assertEqual(ret, b'2020-11-10T00:00:00')
         self.assertIs(type(ret), bytes)
         self.assertEqual(ret_dtype, 'ascii')
+
+    def test_isodate_spec(self):
+        spec_type = 'isodatetime'
+        spec = DatasetSpec('an example dataset', spec_type, name='data')
+
+        # NOTE: datetime.isoformat is called on all values with a datetime spec before conversion
+        # see ObjectMapper.get_attr_value
+        value = date(2020, 11, 10).isoformat()
+        ret, ret_dtype = ObjectMapper.convert_dtype(spec, value)
+        self.assertEqual(ret, b'2020-11-10')
+        self.assertIs(type(ret), bytes)
+        self.assertEqual(ret_dtype, 'ascii')

tests/unit/validator_tests/test_validate.py

@@ -1,5 +1,5 @@
 from abc import ABCMeta, abstractmethod
-from datetime import datetime
+from datetime import datetime, date
 from unittest import mock, skip
 
 import numpy as np
@@ -104,46 +104,58 @@ def test_valid(self):
 class TestDateTimeInSpec(ValidatorTestBase):
 
     def getSpecs(self):
-        ret = GroupSpec('A test group specification with a data type',
-                        data_type_def='Bar',
-                        datasets=[DatasetSpec('an example dataset', 'int', name='data',
-                                              attributes=[AttributeSpec(
-                                                  'attr2', 'an example integer attribute', 'int')]),
-                                  DatasetSpec('an example time dataset', 'isodatetime', name='time'),
-                                  DatasetSpec('an array of times', 'isodatetime', name='time_array',
-                                              dims=('num_times',), shape=(None,))],
-                        attributes=[AttributeSpec('attr1', 'an example string attribute', 'text')])
-        return (ret,)
+        ret = GroupSpec(
+            'A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(
+                    'an example dataset',
+                    'int',
+                    name='data',
+                    attributes=[AttributeSpec('attr2', 'an example integer attribute', 'int')]
+                ),
+                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,))
+            ],
+            attributes=[AttributeSpec('attr1', 'an example string attribute', 'text')])
+        return ret,
 
     def test_valid_isodatetime(self):
-        builder = GroupBuilder('my_bar',
-                               attributes={'data_type': 'Bar', 'attr1': 'a string attribute'},
-                               datasets=[DatasetBuilder('data', 100, attributes={'attr2': 10}),
-                                         DatasetBuilder('time',
-                                                        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)),
+                DatasetBuilder('date', date(2017, 5, 1)),
+                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), 0)
 
     def test_invalid_isodatetime(self):
-        builder = GroupBuilder('my_bar',
-                               attributes={'data_type': 'Bar', 'attr1': 'a string attribute'},
-                               datasets=[DatasetBuilder('data', 100, attributes={'attr2': 10}),
-                                         DatasetBuilder('time', 100),
-                                         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', 100),
+                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], DtypeError, name='Bar/time')
+        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('time',
+                                         DatasetBuilder('datetime',
                                                         datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())),
                                          DatasetBuilder('time_array',
                                                         datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal()))])