Fix for ruff 0.4.3

ci/min_deps_check.py

@@ -133,7 +133,7 @@ def process_pkg(
     - publication date of version suggested by policy (YYYY-MM-DD)
     - status ("<", "=", "> (!)")
     """
-    print("Analyzing %s..." % pkg)
+    print(f"Analyzing {pkg}...")
     versions = query_conda(pkg)
 
     try:

xarray/datatree_/datatree/__init__.py

@@ -1,7 +1,6 @@
 # import public API
 from xarray.core.treenode import InvalidTreeError, NotFoundInTreeError
 
-
 __all__ = (
     "InvalidTreeError",
     "NotFoundInTreeError",

xarray/datatree_/datatree/common.py

@@ -6,8 +6,9 @@
 """
 
 import warnings
+from collections.abc import Hashable, Iterable, Mapping
 from contextlib import suppress
-from typing import Any, Hashable, Iterable, List, Mapping
+from typing import Any
 
 
 class TreeAttrAccessMixin:
@@ -83,16 +84,14 @@ def __setattr__(self, name: str, value: Any) -> None:
         except AttributeError as e:
             # Don't accidentally shadow custom AttributeErrors, e.g.
             # DataArray.dims.setter
-            if str(e) != "{!r} object has no attribute {!r}".format(
-                type(self).__name__, name
-            ):
+            if str(e) != f"{type(self).__name__!r} object has no attribute {name!r}":
                 raise
             raise AttributeError(
                 f"cannot set attribute {name!r} on a {type(self).__name__!r} object. Use __setitem__ style"
                 "assignment (e.g., `ds['name'] = ...`) instead of assigning variables."
             ) from e
 
-    def __dir__(self) -> List[str]:
+    def __dir__(self) -> list[str]:
         """Provide method name lookup and completion. Only provide 'public'
         methods.
         """

xarray/tests/test_dataset.py

@@ -284,7 +284,7 @@ def test_repr(self) -> None:
             Dimensions:  (dim2: 9, dim3: 10, time: 20, dim1: 8)
             Coordinates:
               * dim2     (dim2) float64 72B 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
-              * dim3     (dim3) %s 40B 'a' 'b' 'c' 'd' 'e' 'f' 'g' 'h' 'i' 'j'
+              * dim3     (dim3) {} 40B 'a' 'b' 'c' 'd' 'e' 'f' 'g' 'h' 'i' 'j'
               * time     (time) datetime64[ns] 160B 2000-01-01 2000-01-02 ... 2000-01-20
                 numbers  (dim3) int64 80B 0 1 2 0 0 1 1 2 2 3
             Dimensions without coordinates: dim1
@@ -293,8 +293,9 @@ def test_repr(self) -> None:
                 var2     (dim1, dim2) float64 576B 1.162 -1.097 -2.123 ... 1.267 0.3328
                 var3     (dim3, dim1) float64 640B 0.5565 -0.2121 0.4563 ... -0.2452 -0.3616
             Attributes:
-                foo:      bar"""
-            % data["dim3"].dtype
+                foo:      bar""".format(
+                data["dim3"].dtype
+            )
         )
         actual = "\n".join(x.rstrip() for x in repr(data).split("\n"))
         print(actual)

xarray/tests/test_groupby.py

@@ -577,8 +577,8 @@ def test_da_groupby_assign_coords() -> None:
 def test_groupby_repr(obj, dim) -> None:
     actual = repr(obj.groupby(dim))
     expected = f"{obj.__class__.__name__}GroupBy"
-    expected += ", grouped over %r" % dim
-    expected += "\n%r groups with labels " % (len(np.unique(obj[dim])))
+    expected += f", grouped over {dim!r}"
+    expected += f"\n{len(np.unique(obj[dim]))!r} groups with labels "
     if dim == "x":
         expected += "1, 2, 3, 4, 5."
     elif dim == "y":
@@ -595,7 +595,7 @@ def test_groupby_repr_datetime(obj) -> None:
     actual = repr(obj.groupby("t.month"))
     expected = f"{obj.__class__.__name__}GroupBy"
     expected += ", grouped over 'month'"
-    expected += "\n%r groups with labels " % (len(np.unique(obj.t.dt.month)))
+    expected += f"\n{len(np.unique(obj.t.dt.month))!r} groups with labels "
     expected += "1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12."
     assert actual == expected
 

xarray/tests/test_rolling.py

@@ -254,7 +254,7 @@ def test_rolling_reduce(
         rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods)
 
         # add nan prefix to numpy methods to get similar # behavior as bottleneck
-        actual = rolling_obj.reduce(getattr(np, "nan%s" % name))
+        actual = rolling_obj.reduce(getattr(np, f"nan{name}"))
         expected = getattr(rolling_obj, name)()
         assert_allclose(actual, expected)
         assert actual.sizes == expected.sizes
@@ -276,7 +276,7 @@ def test_rolling_reduce_nonnumeric(
         rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods)
 
         # add nan prefix to numpy methods to get similar behavior as bottleneck
-        actual = rolling_obj.reduce(getattr(np, "nan%s" % name))
+        actual = rolling_obj.reduce(getattr(np, f"nan{name}"))
         expected = getattr(rolling_obj, name)()
         assert_allclose(actual, expected)
         assert actual.sizes == expected.sizes
@@ -741,7 +741,7 @@ def test_rolling_reduce(self, ds, center, min_periods, window, name) -> None:
         rolling_obj = ds.rolling(time=window, center=center, min_periods=min_periods)
 
         # add nan prefix to numpy methods to get similar behavior as bottleneck
-        actual = rolling_obj.reduce(getattr(np, "nan%s" % name))
+        actual = rolling_obj.reduce(getattr(np, f"nan{name}"))
         expected = getattr(rolling_obj, name)()
         assert_allclose(actual, expected)
         assert ds.sizes == actual.sizes