Fix imports and use is_chunked_array instead of _chunkedarrayfunction…

…_or_api

xarray/backends/common.py

@@ -13,8 +13,8 @@
 from xarray.conventions import cf_encoder
 from xarray.core import indexing
 from xarray.core.utils import FrozenDict, NdimSizeLenMixin, is_remote_uri
-from xarray.namedarray._typing import _chunkedarrayfunction_or_api
 from xarray.namedarray.parallelcompat import get_chunked_array_type
+from xarray.namedarray.pycompat import is_chunked_array
 
 if TYPE_CHECKING:
     from io import BufferedIOBase
@@ -232,7 +232,7 @@ def __init__(self, lock=None):
         self.lock = lock
 
     def add(self, source, target, region=None):
-        if isinstance(source, _chunkedarrayfunction_or_api):
+        if is_chunked_array(source):
             self.sources.append(source)
             self.targets.append(target)
             self.regions.append(region)

xarray/coding/variables.py

@@ -163,7 +163,7 @@ def lazy_elemwise_func(array, func: Callable, dtype: np.typing.DTypeLike):
     if is_chunked_array(array):
         chunkmanager = get_chunked_array_type(array)
 
-        return chunkmanager.map_blocks(func, array, dtype=dtype)  # type: ignore
+        return chunkmanager.map_blocks(func, array, dtype=dtype)  # type: ignore[arg-type]
     else:
         return _ElementwiseFunctionArray(array, func, dtype)
 

xarray/core/duck_array_ops.py

@@ -17,17 +17,17 @@
 import pandas as pd
 from numpy import all as array_all  # noqa
 from numpy import any as array_any  # noqa
-from numpy import (
+from numpy import (  # noqa
     around,  # noqa
     full_like,
-    gradient,  # noqa
+    gradient,
     isclose,
-    isin,  # noqa
+    isin,
     isnat,
-    take,  # noqa
-    tensordot,  # noqa
-    transpose,  # noqa
-    unravel_index,  # noqa
+    take,
+    tensordot,
+    transpose,
+    unravel_index,
 )
 from numpy import concatenate as _concatenate
 from numpy.lib.stride_tricks import sliding_window_view  # noqa