cleanups

xarray/core/groupers.py

@@ -360,7 +360,6 @@ def _get_index_and_items(self) -> tuple[pd.Index, pd.Series, np.ndarray]:
 
     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.group_as_index, CFTimeIndex):
             return self.index_grouper.first_items(
@@ -375,8 +374,6 @@ def first_items(self) -> tuple[pd.Series, np.ndarray]:
             # So for _flox_reduce we avoid one reindex and copy by avoiding
             # _maybe_restore_empty_groups
             codes = np.repeat(np.arange(len(first_items)), counts)
-            if self.loffset is not None:
-                _apply_loffset(self.loffset, first_items)
             return first_items, codes
 
     def factorize(self, group: T_Group) -> EncodedGroups:

xarray/tests/test_groupby.py

@@ -2351,25 +2351,6 @@ def test_resample_drop_nondim_coords(self) -> None:
         actual = ds.resample(time="1h").interpolate("linear")
         assert "tc" not in actual.coords
 
-    def test_resample_old_api(self) -> None:
-        times = pd.date_range("2000-01-01", freq="6h", periods=10)
-        ds = Dataset(
-            {
-                "foo": (["time", "x", "y"], np.random.randn(10, 5, 3)),
-                "bar": ("time", np.random.randn(10), {"meta": "data"}),
-                "time": times,
-            }
-        )
-
-        with pytest.raises(TypeError, match=r"resample\(\) no longer supports"):
-            ds.resample("1D", "time")  # type: ignore[arg-type]
-
-        with pytest.raises(TypeError, match=r"resample\(\) no longer supports"):
-            ds.resample("1D", dim="time", how="mean")  # type: ignore[arg-type]
-
-        with pytest.raises(TypeError, match=r"resample\(\) no longer supports"):
-            ds.resample("1D", dim="time")  # type: ignore[arg-type]
-
     def test_resample_ds_da_are_the_same(self) -> None:
         time = pd.date_range("2000-01-01", freq="6h", periods=365 * 4)
         ds = xr.Dataset(