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

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

anndata/_core/index.py

@@ -123,12 +123,14 @@ def _subset(a: np.ndarray, subset_idx: Index):
         subset_idx = np.ix_(*subset_idx)
     return a[subset_idx]
 
+
 @_subset.register(ZarrArray)
 def _subset_zarr(a: ZarrArray, subset_idx: Index):
     if all(isinstance(x, cabc.Iterable) for x in subset_idx):
         subset_idx = np.ix_(*subset_idx)
     return a.oindex[subset_idx]
 
+
 @_subset.register(DaskArray)
 def _subset_dask(a: DaskArray, subset_idx: Index):
     if isinstance(subset_idx, slice):

anndata/experimental/read_backed/lazy_arrays.py

@@ -38,7 +38,7 @@ class LazyCategoricalArray(MaskedArrayMixIn):
         "_categories",
         "_categories_cache",
         "group",
-        "_drop_unused_cats"
+        "_drop_unused_cats",
     )
 
     def __init__(self, codes, categories, attrs, _drop_unused_cats, *args, **kwargs):
@@ -54,7 +54,7 @@ def __init__(self, codes, categories, attrs, _drop_unused_cats, *args, **kwargs)
         self._categories = categories
         self._categories_cache = None
         self.attrs = dict(attrs)
-        self._drop_unused_cats = _drop_unused_cats # obsm/varm do not drop, but obs and var do.  TODO: Should fix in normal AnnData?
+        self._drop_unused_cats = _drop_unused_cats  # obsm/varm do not drop, but obs and var do.  TODO: Should fix in normal AnnData?
 
     @property
     def categories(self):  # __slots__ and cached_property are incompatible

anndata/experimental/read_backed/read_backed.py

@@ -223,7 +223,6 @@ def _normalize_indices(self, index: Optional[Index]) -> Tuple[slice, slice]:
         )
 
     def to_memory(self, exclude=[]):
-
         # nullable and categoricals need special handling because xarray will convert them to numpy arrays first with dtype object
         def get_nullable_and_categorical_cols(ds):
             cols = []
@@ -252,7 +251,7 @@ def to_df(ds, exclude_vars=[]):
             if len(exclude_vars) == 0:
                 df = df[list(ds.keys())]
             return df
-        
+
         # handling for AxisArrays
         def backed_dict_to_memory(d, prefix):
             res = {}
@@ -534,8 +533,12 @@ def callback(func, elem_name: str, elem, iospec):
                     d_with_xr[k] = v
             return Dataset2D(d_with_xr)
         elif iospec.encoding_type == "categorical":
-            drop_unused_cats = not (elem_name.startswith('/obsm') or elem_name.startswith('/varm'))
-            return LazyCategoricalArray(elem["codes"], elem["categories"], elem.attrs, drop_unused_cats)
+            drop_unused_cats = not (
+                elem_name.startswith("/obsm") or elem_name.startswith("/varm")
+            )
+            return LazyCategoricalArray(
+                elem["codes"], elem["categories"], elem.attrs, drop_unused_cats
+            )
         elif "nullable" in iospec.encoding_type:
             return LazyMaskedArray(
                 elem["values"],

anndata/experimental/read_backed/xarray.py

@@ -2,23 +2,32 @@
 from anndata._core.index import Index, _subset
 from anndata._core.views import as_view
 
+
 def get_index_dim(ds):
-    assert len(ds.dims) == 1, f"xarray Dataset should not have more than 1 dims, found {len(ds)}"
+    assert (
+        len(ds.dims) == 1
+    ), f"xarray Dataset should not have more than 1 dims, found {len(ds)}"
     return list(ds.dims.keys())[0]
 
-class Dataset2D(xr.Dataset):
 
+class Dataset2D(xr.Dataset):
     @property
-    def shape(self): # aligned mapping classes look for this for DataFrames so this ensures usability with e.g., obsm
+    def shape(
+        self,
+    ):  # aligned mapping classes look for this for DataFrames so this ensures usability with e.g., obsm
         return [self.dims[get_index_dim(self)], len(self)]
-
+
+
 @_subset.register(Dataset2D)
 def _(a: xr.DataArray, subset_idx: Index):
     key = get_index_dim(a)
-    if isinstance(subset_idx, tuple) and len(subset_idx) == 1: # xarray seems to have some code looking for a second entry in tuples
-        return a.isel(**{ key:subset_idx[0] })
-    return a.isel(**{ key:subset_idx })
+    if (
+        isinstance(subset_idx, tuple) and len(subset_idx) == 1
+    ):  # xarray seems to have some code looking for a second entry in tuples
+        return a.isel(**{key: subset_idx[0]})
+    return a.isel(**{key: subset_idx})
+
 
 @as_view.register(Dataset2D)
 def _(a: Dataset2D, view_args):
-    return a
+    return a

anndata/tests/test_read_backed_experimental.py

@@ -398,8 +398,8 @@ def test_nullable_boolean_array_subset_subset(nullable_boolean_lazy_arr):
 
 
 def test_nullable_boolean_array_no_mask_equality(nullable_boolean_lazy_arr_no_mask):
-    assert nullable_boolean_lazy_arr_no_mask[0] == True
-    assert (nullable_boolean_lazy_arr_no_mask[3:5] == False).all()
+    assert nullable_boolean_lazy_arr_no_mask[0] is True
+    assert (nullable_boolean_lazy_arr_no_mask[3:5] is False).all()
     assert (nullable_boolean_lazy_arr_no_mask[5:7] == np.array([True, False])).all()