Multiple imports for an import name (#10743)

Author: DimitriPapadopoulos

xarray/backends/api.py

@@ -77,7 +77,6 @@
         ErrorOptionsWithWarn,
         JoinOptions,
         NestedSequence,
-        ReadBuffer,
         T_Chunks,
         ZarrStoreLike,
     )

xarray/computation/apply_ufunc.py

@@ -715,7 +715,7 @@ def apply_variable_ufunc(
 ) -> Variable | tuple[Variable, ...]:
     """Apply a ndarray level function over Variable and/or ndarray objects."""
     from xarray.core.formatting import short_array_repr
-    from xarray.core.variable import Variable, as_compatible_data
+    from xarray.core.variable import as_compatible_data
 
     dim_sizes = unified_dim_sizes(
         (a for a in args if hasattr(a, "dims")), exclude_dims=exclude_dims

xarray/core/dataset.py

@@ -8465,8 +8465,6 @@ def integrate(
         return result
 
     def _integrate_one(self, coord, datetime_unit=None, cumulative=False):
-        from xarray.core.variable import Variable
-
         if coord not in self.variables and coord not in self.dims:
             variables_and_dims = tuple(set(self.variables.keys()).union(self.dims))
             raise ValueError(

xarray/core/groupby.py

@@ -390,7 +390,6 @@ def _parse_group_and_groupers(
     eagerly_compute_group: Literal[False] | None,
 ) -> tuple[ResolvedGrouper, ...]:
     from xarray.core.dataarray import DataArray
-    from xarray.core.variable import Variable
     from xarray.groupers import Grouper, UniqueGrouper
 
     if group is not None and groupers:

xarray/groupers.py

@@ -547,9 +547,6 @@ def _get_index_and_items(self) -> tuple[pd.Index, pd.Series, np.ndarray]:
         return full_index, first_items, codes
 
     def first_items(self) -> tuple[pd.Series, np.ndarray]:
-        from xarray.coding.cftimeindex import CFTimeIndex
-        from xarray.core.resample_cftime import CFTimeGrouper
-
         if isinstance(self.index_grouper, CFTimeGrouper):
             return self.index_grouper.first_items(
                 cast(CFTimeIndex, self.group_as_index)
@@ -605,8 +602,6 @@ def compute_chunks(self, variable: Variable, *, dim: Hashable) -> tuple[int, ...
         tuple[int, ...]
             A tuple of chunk sizes for the dimension.
         """
-        from xarray.core.dataarray import DataArray
-
         if not _contains_datetime_like_objects(variable):
             raise ValueError(
                 f"Computing chunks with {type(self)!r} only supported for datetime variables. "
@@ -1050,8 +1045,6 @@ def compute_chunks(self, variable: Variable, *, dim: Hashable) -> tuple[int, ...
         tuple[int, ...]
             A tuple of chunk sizes for the dimension.
         """
-        from xarray.core.dataarray import DataArray
-
         if not _contains_datetime_like_objects(variable):
             raise ValueError(
                 f"Computing chunks with {type(self)!r} only supported for datetime variables. "

xarray/structure/alignment.py

@@ -30,7 +30,6 @@
     from xarray.core.dataset import Dataset
     from xarray.core.types import (
         Alignable,
-        JoinOptions,
         T_DataArray,
         T_Dataset,
         T_DuckArray,

xarray/tests/test_backends.py

@@ -192,7 +192,6 @@ def _check_compression_codec_available(codec: str | None) -> bool:
 
     try:
         import os
-        import tempfile
 
         import netCDF4
 
@@ -5304,11 +5303,9 @@ def test_open_mfdataset_list_attr() -> None:
     """
     Case when an attribute of type list differs across the multiple files
     """
-    from netCDF4 import Dataset
-
     with create_tmp_files(2) as nfiles:
         for i in range(2):
-            with Dataset(nfiles[i], "w") as f:
+            with nc4.Dataset(nfiles[i], "w") as f:
                 f.createDimension("x", 3)
                 vlvar = f.createVariable("test_var", np.int32, ("x"))
                 # here create an attribute as a list
@@ -7269,8 +7266,6 @@ def test_zarr_closing_internal_zip_store():
 @requires_zarr
 @pytest.mark.parametrize("create_default_indexes", [True, False])
 def test_zarr_create_default_indexes(tmp_path, create_default_indexes) -> None:
-    from xarray.core.indexes import PandasIndex
-
     store_path = tmp_path / "tmp.zarr"
     original_ds = xr.Dataset({"data": ("x", np.arange(3))}, coords={"x": [-1, 0, 1]})
     original_ds.to_zarr(store_path, mode="w")