Enforce ruff/flake8-pie rules (PIE)

asv_bench/benchmarks/dataset_io.py

@@ -712,7 +712,7 @@ def load(self) -> tuple:
                         dims=("time",),
                         fastpath=True,
                     )
-                    for v in range(0, n_variables)
+                    for v in range(n_variables)
                 }
                 attributes = {}
 

pyproject.toml

@@ -246,6 +246,7 @@ ignore = [
   "E731",
   "UP007",
   "PERF20",
+  "PIE790",  # unnecessary pass statement
   "RUF001",
   "RUF002",
   "RUF003",
@@ -260,6 +261,7 @@ extend-select = [
   "TID", # flake8-tidy-imports (absolute imports)
   "I", # isort
   "PERF", # Perflint
+  "PIE", # flake8-pie
   "PGH", # pygrep-hooks
   "RUF",
   "UP", # Pyupgrade

xarray/plot/facetgrid.py

@@ -495,14 +495,14 @@ def map_plot1d(
         if self._single_group:
             full = tuple(
                 {self._single_group: x}
-                for x in range(0, self.data[self._single_group].size)
+                for x in range(self.data[self._single_group].size)
             )
             empty = tuple(None for x in range(self._nrow * self._ncol - len(full)))
             name_d = full + empty
         else:
             rowcols = itertools.product(
-                range(0, self.data[self._row_var].size),
-                range(0, self.data[self._col_var].size),
+                range(self.data[self._row_var].size),
+                range(self.data[self._col_var].size),
             )
             name_d = tuple({self._row_var: r, self._col_var: c} for r, c in rowcols)
         name_dicts = np.array(name_d).reshape(self._nrow, self._ncol)

xarray/tests/test_computation.py

@@ -1561,7 +1561,7 @@ def arrays():
     )
 
     return [
-        da.isel(time=range(0, 18)),
+        da.isel(time=range(18)),
         da.isel(time=range(2, 20)).rolling(time=3, center=True).mean(),
         xr.DataArray([[1, 2], [1, np.nan]], dims=["x", "time"]),
         xr.DataArray([[1, 2], [np.nan, np.nan]], dims=["x", "time"]),

xarray/tests/test_concat.py

@@ -394,7 +394,7 @@ def concat_var_names() -> Callable:
     def get_varnames(var_cnt: int = 10, list_cnt: int = 10) -> list[list[str]]:
         orig = [f"d{i:02d}" for i in range(var_cnt)]
         var_names = []
-        for _i in range(0, list_cnt):
+        for _i in range(list_cnt):
             l1 = orig.copy()
             var_names.append(l1)
         return var_names

xarray/tests/test_groupby.py

@@ -1273,7 +1273,7 @@ def test_groupby_iter(self) -> None:
 
     def test_groupby_properties(self) -> None:
         grouped = self.da.groupby("abc")
-        expected_groups = {"a": range(0, 9), "c": [9], "b": range(10, 20)}
+        expected_groups = {"a": range(9), "c": [9], "b": range(10, 20)}
         assert expected_groups.keys() == grouped.groups.keys()
         for key in expected_groups:
             expected_group = expected_groups[key]
@@ -1936,7 +1936,7 @@ def test_resample_bad_resample_dim(self) -> None:
         times = pd.date_range("2000-01-01", freq="6h", periods=10)
         array = DataArray(np.arange(10), [("__resample_dim__", times)])
         with pytest.raises(ValueError, match=r"Proxy resampling dimension"):
-            array.resample(**{"__resample_dim__": "1D"}).first()  # type: ignore[arg-type]
+            array.resample(__resample_dim__="1D").first()
 
     @requires_scipy
     def test_resample_drop_nondim_coords(self) -> None:

xarray/tests/test_interp.py

@@ -889,7 +889,7 @@ def test_decompose(method: InterpOptions) -> None:
         (data_ndim, interp_ndim, nscalar)
         for data_ndim in range(1, 4)
         for interp_ndim in range(1, data_ndim + 1)
-        for nscalar in range(0, interp_ndim + 1)
+        for nscalar in range(interp_ndim + 1)
     ],
 )
 def test_interpolate_chunk_1d(

xarray/tests/test_units.py

@@ -3934,7 +3934,7 @@ def test_grouped_operations(self, func, variant, dtype, compute_backend):
         data_array = xr.DataArray(
             data=array, coords={"x": x, "y": y, "u": ("x", u)}, dims=("x", "y")
         )
-        units = {**extract_units(data_array), **{"z": unit_registry.s, "q": None}}
+        units = {**extract_units(data_array), "z": unit_registry.s, "q": None}
 
         stripped_kwargs = {
             key: (