Merge branch 'dev' into warn_extra_args_spec

CHANGELOG.md

@@ -1,9 +1,10 @@
 # HDMF Changelog
 
-## HDMF 3.14.2 (???)
+## HDMF 3.14.2 (Upcoming)
 
 ### Enhancements
 - Warn when unexpected keys are present in specs. @rly [#1134](https://github.com/hdmf-dev/hdmf/pull/1134)
+- Support appending to zarr arrays. @mavaylon1 [#1136](https://github.com/hdmf-dev/hdmf/pull/1136)
 
 ### Bug fixes
 - Fix iterator increment causing an extra +1 added after the end of completion. @CodyCBakerPhD [#1128](https://github.com/hdmf-dev/hdmf/pull/1128)

pyproject.toml

@@ -36,12 +36,12 @@ dependencies = [
     "pandas>=1.0.5",
     "ruamel.yaml>=0.16",
     "scipy>=1.4",
+    "zarr >= 2.12.0",
     "importlib-resources; python_version < '3.9'",  # TODO: remove when minimum python version is 3.9
 ]
 dynamic = ["version"]
 
 [project.optional-dependencies]
-zarr = ["zarr>=2.12.0"]
 tqdm = ["tqdm>=4.41.0"]
 termset = ["linkml-runtime>=1.5.5; python_version >= '3.9'",
            "schemasheets>=0.1.23; python_version >= '3.9'",
@@ -117,7 +117,7 @@ omit = [
 # force-exclude = "src/hdmf/common/hdmf-common-schema|docs/gallery"
 
 [tool.ruff]
-select = ["E", "F", "T100", "T201", "T203"]
+lint.select = ["E", "F", "T100", "T201", "T203"]
 exclude = [
   ".git",
   ".tox",
@@ -132,11 +132,11 @@ exclude = [
 ]
 line-length = 120
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 "docs/gallery/*" = ["E402", "T201"]
 "src/*/__init__.py" = ["F401"]
 "setup.py" = ["T201"]
 "test_gallery.py" = ["T201"]
 
-[tool.ruff.mccabe]
+[tool.ruff.lint.mccabe]
 max-complexity = 17

src/hdmf/backends/hdf5/h5tools.py

@@ -728,7 +728,7 @@ def __read_dataset(self, h5obj, name=None):
     def _check_str_dtype(self, h5obj):
         dtype = h5obj.dtype
         if dtype.kind == 'O':
-            if dtype.metadata.get('vlen') == str and H5PY_3:
+            if dtype.metadata.get('vlen') is str and H5PY_3:
                 return StrDataset(h5obj, None)
         return h5obj
 

src/hdmf/build/objectmapper.py

@@ -1164,7 +1164,7 @@ def __get_subspec_values(self, builder, spec, manager):
             if not isinstance(builder, DatasetBuilder):  # pragma: no cover
                 raise ValueError("__get_subspec_values - must pass DatasetBuilder with DatasetSpec")
             if (spec.shape is None and getattr(builder.data, 'shape', None) == (1,) and
-                    type(builder.data[0]) != np.void):
+                    type(builder.data[0]) is not np.void):
                 # if a scalar dataset is expected and a 1-element non-compound dataset is given, then read the dataset
                 builder['data'] = builder.data[0]  # use dictionary reference instead of .data to bypass error
             ret[spec] = self.__check_ref_resolver(builder.data)

src/hdmf/data_utils.py

@@ -5,17 +5,20 @@
 from warnings import warn
 from typing import Tuple
 from itertools import product, chain
+from zarr import Array as ZarrArray
 
 import h5py
 import numpy as np
 
 from .utils import docval, getargs, popargs, docval_macro, get_data_shape
 
-
 def append_data(data, arg):
     if isinstance(data, (list, DataIO)):
         data.append(arg)
         return data
+    elif isinstance(data, ZarrArray):
+        data.append([arg], axis=0)
+        return data
     elif type(data).__name__ == 'TermSetWrapper': # circular import
         data.append(arg)
         return data

src/hdmf/testing/testcase.py

@@ -174,7 +174,7 @@ def _assert_array_equal(self,
         :param message: custom additional message to show when assertions as part of this assert are failing
         """
         array_data_types = tuple([i for i in get_docval_macro('array_data')
-                                  if (i != list and i != tuple and i != AbstractDataChunkIterator)])
+                                  if (i is not list and i is not tuple and i is not AbstractDataChunkIterator)])
         # We construct array_data_types this way to avoid explicit dependency on h5py, Zarr and other
         # I/O backends. Only list and tuple do not support [()] slicing, and AbstractDataChunkIterator
         # should never occur here. The effective value of array_data_types is then:

src/hdmf/validate/validator.py

@@ -164,7 +164,7 @@ def get_type(data, builder_dtype=None):
                 # Empty array
                 else:
                     # Empty string array
-                    if data.dtype.metadata["vlen"] == str:
+                    if data.dtype.metadata["vlen"] is str:
                         return "utf", None
                     # Undetermined variable length data type.
                     else:                        # pragma: no cover

tests/unit/utils_test/test_data_utils.py

@@ -0,0 +1,14 @@
+from hdmf.data_utils import append_data
+from hdmf.testing import TestCase
+
+import numpy as np
+from numpy.testing import assert_array_equal
+import zarr
+
+class TestAppendData(TestCase):
+
+    def test_append_data_zarr(self):
+        zarr_array = zarr.array([1,2,3])
+        new = append_data(zarr_array, 4)
+
+        assert_array_equal(new[:], np.array([1,2,3,4]))