Fix handling of read h5py string datasets (#1189)

CHANGELOG.md

@@ -1,5 +1,11 @@
 # HDMF Changelog
 
+## HDMF 3.14.5 (September 6, 2024)
+
+### Bug fixes
+- Fixed bug in writing of string arrays to an HDF5 file that were read from an HDF5 file that was introduced in 3.14.4. @rly @stephprince
+  [#1189](https://github.com/hdmf-dev/hdmf/pull/1189)
+
 ## HDMF 3.14.4 (September 4, 2024)
 
 ### Enhancements

src/hdmf/build/objectmapper.py

@@ -602,7 +602,10 @@ def __get_data_type(cls, spec):
     def __convert_string(self, value, spec):
         """Convert string types to the specified dtype."""
         def __apply_string_type(value, string_type):
-            if isinstance(value, (list, tuple, np.ndarray, DataIO)):
+            # NOTE: if a user passes a h5py.Dataset that is not wrapped with a hdmf.utils.StrDataset,
+            # then this conversion may not be correct. Users should unpack their string h5py.Datasets
+            # into a numpy array (or wrap them in StrDataset) before passing them to a container object.
+            if hasattr(value, '__iter__') and not isinstance(value, (str, bytes)):
                 return [__apply_string_type(item, string_type) for item in value]
             else:
                 return string_type(value)

src/hdmf/utils.py

@@ -1140,7 +1140,7 @@ def update(self, other):
 
 @docval_macro('array_data')
 class StrDataset(h5py.Dataset):
-    """Wrapper to decode strings on reading the dataset"""
+    """Wrapper to decode strings on reading the dataset. Use only for h5py 3+."""
     def __init__(self, dset, encoding, errors='strict'):
         self.dset = dset
         if encoding is None:

tests/unit/build_tests/test_io_map.py

@@ -1,4 +1,4 @@
-from hdmf.utils import docval, getargs
+from hdmf.utils import StrDataset, docval, getargs
 from hdmf import Container, Data
 from hdmf.backends.hdf5 import H5DataIO
 from hdmf.build import (GroupBuilder, DatasetBuilder, ObjectMapper, BuildManager, TypeMap, LinkBuilder,
@@ -7,12 +7,15 @@
 from hdmf.spec import (GroupSpec, AttributeSpec, DatasetSpec, SpecCatalog, SpecNamespace, NamespaceCatalog, RefSpec,
                        LinkSpec)
 from hdmf.testing import TestCase
+import h5py
 from abc import ABCMeta, abstractmethod
 import unittest
 import numpy as np
 
 from tests.unit.helpers.utils import CORE_NAMESPACE, create_test_type_map
 
+H5PY_3 = h5py.__version__.startswith('3')
+
 
 class Bar(Container):
 
@@ -460,6 +463,132 @@ def test_build_3d_ndarray(self):
         np.testing.assert_array_equal(builder.get('data').data, str_array_3d)
         np.testing.assert_array_equal(builder.get('attr_array'), str_array_3d)
 
+    @unittest.skipIf(not H5PY_3, "Use StrDataset only for h5py 3+")
+    def test_build_1d_h5py_3_dataset(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(
+                    doc='an example dataset',
+                    dtype='text',
+                    name='data',
+                    shape=(None, ),
+                    attributes=[AttributeSpec(name='attr2', doc='an example integer attribute', dtype='int')],
+                )
+            ],
+            attributes=[AttributeSpec(name='attr_array', doc='an example array attribute', dtype='text',
+                                      shape=(None, ))],
+        )
+        type_map = self.customSetUp(bar_spec)
+        type_map.register_map(Bar, BarMapper)
+        # create in-memory hdf5 file that is discarded after closing
+        with h5py.File("test.h5", "w", driver="core", backing_store=False) as f:
+            str_array_1d = np.array(
+                ['aa', 'bb', 'cc', 'dd'],
+                dtype=h5py.special_dtype(vlen=str)
+            )
+            # wrap the dataset in a StrDataset to mimic how HDF5IO would read this dataset with h5py 3+
+            dataset = StrDataset(f.create_dataset('data', data=str_array_1d), None)
+            bar_inst = Bar('my_bar', dataset, 'value1', 10, attr_array=dataset)
+            builder = type_map.build(bar_inst)
+            np.testing.assert_array_equal(builder.get('data').data, dataset[:])
+            np.testing.assert_array_equal(builder.get('attr_array'), dataset[:])
+
+    @unittest.skipIf(not H5PY_3, "Use StrDataset only for h5py 3+")
+    def test_build_3d_h5py_3_dataset(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(
+                    doc='an example dataset',
+                    dtype='text',
+                    name='data',
+                    shape=(None, None, None),
+                    attributes=[AttributeSpec(name='attr2', doc='an example integer attribute', dtype='int')],
+                )
+            ],
+            attributes=[AttributeSpec(name='attr_array', doc='an example array attribute', dtype='text',
+                                      shape=(None, None, None))],
+        )
+        type_map = self.customSetUp(bar_spec)
+        type_map.register_map(Bar, BarMapper)
+        # create in-memory hdf5 file that is discarded after closing
+        with h5py.File("test.h5", "w", driver="core", backing_store=False) as f:
+            str_array_3d = np.array(
+                [[['aa', 'bb'], ['cc', 'dd']], [['ee', 'ff'], ['gg', 'hh']]],
+                dtype=h5py.special_dtype(vlen=str)
+            )
+            # wrap the dataset in a StrDataset to mimic how HDF5IO would read this dataset with h5py 3+
+            dataset = StrDataset(f.create_dataset('data', data=str_array_3d), None)
+            bar_inst = Bar('my_bar', dataset, 'value1', 10, attr_array=dataset)
+            builder = type_map.build(bar_inst)
+            np.testing.assert_array_equal(builder.get('data').data, dataset[:])
+            np.testing.assert_array_equal(builder.get('attr_array'), dataset[:])
+
+    @unittest.skipIf(H5PY_3, "Create dataset differently for h5py < 3")
+    def test_build_1d_h5py_2_dataset(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(
+                    doc='an example dataset',
+                    dtype='text',
+                    name='data',
+                    shape=(None, ),
+                    attributes=[AttributeSpec(name='attr2', doc='an example integer attribute', dtype='int')],
+                )
+            ],
+            attributes=[AttributeSpec(name='attr_array', doc='an example array attribute', dtype='text',
+                                      shape=(None, ))],
+        )
+        type_map = self.customSetUp(bar_spec)
+        type_map.register_map(Bar, BarMapper)
+        # create in-memory hdf5 file that is discarded after closing
+        with h5py.File("test.h5", "w", driver="core", backing_store=False) as f:
+            str_array_1d = np.array(
+                ['aa', 'bb', 'cc', 'dd'],
+                dtype=h5py.special_dtype(vlen=str)
+            )
+            dataset = f.create_dataset('data', data=str_array_1d)
+            bar_inst = Bar('my_bar', dataset, 'value1', 10, attr_array=dataset)
+            builder = type_map.build(bar_inst)
+            np.testing.assert_array_equal(builder.get('data').data, dataset[:])
+            np.testing.assert_array_equal(builder.get('attr_array'), dataset[:])
+
+    @unittest.skipIf(H5PY_3, "Create dataset differently for h5py < 3")
+    def test_build_3d_h5py_2_dataset(self):
+        bar_spec = GroupSpec(
+            doc='A test group specification with a data type',
+            data_type_def='Bar',
+            datasets=[
+                DatasetSpec(
+                    doc='an example dataset',
+                    dtype='text',
+                    name='data',
+                    shape=(None, None, None),
+                    attributes=[AttributeSpec(name='attr2', doc='an example integer attribute', dtype='int')],
+                )
+            ],
+            attributes=[AttributeSpec(name='attr_array', doc='an example array attribute', dtype='text',
+                                      shape=(None, None, None))],
+        )
+        type_map = self.customSetUp(bar_spec)
+        type_map.register_map(Bar, BarMapper)
+        # create in-memory hdf5 file that is discarded after closing
+        with h5py.File("test.h5", "w", driver="core", backing_store=False) as f:
+            str_array_3d = np.array(
+                [[['aa', 'bb'], ['cc', 'dd']], [['ee', 'ff'], ['gg', 'hh']]],
+                dtype=h5py.special_dtype(vlen=str)
+            )
+            dataset = f.create_dataset('data', data=str_array_3d)
+            bar_inst = Bar('my_bar', dataset, 'value1', 10, attr_array=dataset)
+            builder = type_map.build(bar_inst)
+            np.testing.assert_array_equal(builder.get('data').data, dataset[:])
+            np.testing.assert_array_equal(builder.get('attr_array'), dataset[:])
+
     def test_build_dataio(self):
         bar_spec = GroupSpec('A test group specification with a data type',
                              data_type_def='Bar',