[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

src/anndata/_io/specs/methods.py

@@ -1137,7 +1137,14 @@ def write_hdf5_scalar(
 ):
     # Can’t compress scalars, error is thrown
     dataset_kwargs = dict(dataset_kwargs)
-    for arg in ("compression", "compression_opts", "chunks", "shuffle", "fletcher32", "scaleoffset"):
+    for arg in (
+        "compression",
+        "compression_opts",
+        "chunks",
+        "shuffle",
+        "fletcher32",
+        "scaleoffset",
+    ):
         dataset_kwargs.pop(arg, None)
     f.create_dataset(key, data=np.array(value), **dataset_kwargs)
 

src/anndata/_io/utils.py

@@ -15,9 +15,9 @@
     from collections.abc import Callable, Mapping
     from typing import Literal
 
-    from .specs.registry import Writer
-    from .._types import StorageType, _WriteInternal, ContravariantRWAble
+    from .._types import ContravariantRWAble, StorageType, _WriteInternal
     from ..compat import H5Group, ZarrGroup
+    from .specs.registry import Writer
 
     Storage = StorageType | BaseCompressedSparseDataset
 
@@ -294,7 +294,14 @@ def zero_dim_array_as_scalar(func: _WriteInternal):
     """
 
     @wraps(func, assigned=WRAPPER_ASSIGNMENTS + ("__defaults__", "__kwdefaults__"))
-    def func_wrapper(f: StorageType, k: str, elem: ContravariantRWAble, *, _writer: Writer, dataset_kwargs: Mapping[str, Any]):
+    def func_wrapper(
+        f: StorageType,
+        k: str,
+        elem: ContravariantRWAble,
+        *,
+        _writer: Writer,
+        dataset_kwargs: Mapping[str, Any],
+    ):
         if elem.shape == ():
             _writer.write_elem(f, k, elem[()], dataset_kwargs=dataset_kwargs)
         else:

tests/test_io_elementwise.py

@@ -208,6 +208,7 @@ def test_io_spec(store, value, encoding_type):
     assert_equal(value, from_disk)
     assert get_spec(store[key]) == _REGISTRY.get_spec(value)
 
+
 @pytest.mark.parametrize(
     ("value", "encoding_type"),
     [
@@ -219,13 +220,16 @@ def test_io_spec(store, value, encoding_type):
 )
 def test_io_spec_compressed_scalars(store: G, value: np.ndarray, encoding_type: str):
     key = f"key_for_{encoding_type}"
-    write_elem(store, key, value, dataset_kwargs={"compression": "gzip", "compression_opts": 5})
+    write_elem(
+        store, key, value, dataset_kwargs={"compression": "gzip", "compression_opts": 5}
+    )
 
     assert encoding_type == _read_attr(store[key].attrs, "encoding-type")
 
     from_disk = read_elem(store[key])
     assert_equal(value, from_disk)
 
+
 # Can't instantiate cupy types at the top level, so converting them within the test
 @pytest.mark.gpu
 @pytest.mark.parametrize(