ci: bump ruff==0.15.0

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ ci:
 repos:
 - repo: https://github.com/astral-sh/ruff-pre-commit
   # Ruff version.
-  rev: 'v0.14.14'
+  rev: 'v0.15.0'
   hooks:
     # Run the formatter.
     - id: ruff-format

narwhals/_dask/expr.py

@@ -235,7 +235,7 @@ def _with_alias_output_names(self, func: AliasNames | None, /) -> Self:
     def _with_binary(
         self, call: Callable[[dx.Series, Any], dx.Series], other: Any
     ) -> Self:
-        return self._with_callable(lambda expr, other: call(expr, other), other=other)
+        return self._with_callable(call, other=other)
 
     def _binary_op(self, op_name: str, other: Any) -> Self:
         return self._with_binary(lambda expr, other: getattr(expr, op_name)(other), other)

narwhals/_dask/expr_dt.py

@@ -71,9 +71,11 @@ def to_string(self, format: str) -> DaskExpr:
 
     def replace_time_zone(self, time_zone: str | None) -> DaskExpr:
         return self.compliant._with_callable(
-            lambda expr: expr.dt.tz_localize(None).dt.tz_localize(time_zone)
-            if time_zone is not None
-            else expr.dt.tz_localize(None)
+            lambda expr: (
+                expr.dt.tz_localize(None).dt.tz_localize(time_zone)
+                if time_zone is not None
+                else expr.dt.tz_localize(None)
+            )
         )
 
     def convert_time_zone(self, time_zone: str) -> DaskExpr:

narwhals/_duckdb/expr_dt.py

@@ -58,20 +58,26 @@ def total_minutes(self) -> DuckDBExpr:
 
     def total_seconds(self) -> DuckDBExpr:
         return self.compliant._with_elementwise(
-            lambda expr: lit(SECONDS_PER_MINUTE) * F("datepart", lit("minute"), expr)
-            + F("datepart", lit("second"), expr)
+            lambda expr: (
+                lit(SECONDS_PER_MINUTE) * F("datepart", lit("minute"), expr)
+                + F("datepart", lit("second"), expr)
+            )
         )
 
     def total_milliseconds(self) -> DuckDBExpr:
         return self.compliant._with_elementwise(
-            lambda expr: lit(MS_PER_MINUTE) * F("datepart", lit("minute"), expr)
-            + F("datepart", lit("millisecond"), expr)
+            lambda expr: (
+                lit(MS_PER_MINUTE) * F("datepart", lit("minute"), expr)
+                + F("datepart", lit("millisecond"), expr)
+            )
         )
 
     def total_microseconds(self) -> DuckDBExpr:
         return self.compliant._with_elementwise(
-            lambda expr: lit(US_PER_MINUTE) * F("datepart", lit("minute"), expr)
-            + F("datepart", lit("microsecond"), expr)
+            lambda expr: (
+                lit(US_PER_MINUTE) * F("datepart", lit("minute"), expr)
+                + F("datepart", lit("microsecond"), expr)
+            )
         )
 
     def truncate(self, every: str) -> DuckDBExpr:

tests/dtypes/dtypes_test.py

@@ -9,7 +9,13 @@
 
 import narwhals as nw
 from narwhals.exceptions import InvalidOperationError, PerformanceWarning
-from tests.utils import PANDAS_VERSION, POLARS_VERSION, PYARROW_VERSION, pyspark_session
+from tests.utils import (
+    PANDAS_VERSION,
+    POLARS_VERSION,
+    PYARROW_VERSION,
+    assert_equal_hash,
+    pyspark_session,
+)
 
 if TYPE_CHECKING:
     from collections.abc import Iterable
@@ -68,7 +74,7 @@ def test_list_valid() -> None:
     assert dtype == nw.List(nw.List(nw.Int64))
     assert dtype == nw.List
     assert dtype != nw.List(nw.List(nw.Float32))
-    assert dtype in {nw.List(nw.List(nw.Int64))}
+    assert_equal_hash(dtype, nw.List(nw.List(nw.Int64)))
 
 
 def test_array_valid() -> None:
@@ -83,7 +89,7 @@ def test_array_valid() -> None:
     assert dtype == nw.Array(nw.Array(nw.Int64, 2), 2)
     assert dtype == nw.Array
     assert dtype != nw.Array(nw.Array(nw.Float32, 2), 2)
-    assert dtype in {nw.Array(nw.Array(nw.Int64, 2), 2)}
+    assert_equal_hash(dtype, nw.Array(nw.Array(nw.Int64, 2), 2))
 
     with pytest.raises(TypeError, match="invalid input for shape"):
         nw.Array(nw.Int64(), shape=None)  # type: ignore[arg-type]
@@ -105,7 +111,7 @@ def test_struct_valid() -> None:
     assert dtype.to_schema() == nw.Struct({"a": nw.Int64, "b": nw.String}).to_schema()
     assert dtype == nw.Struct
     assert dtype != nw.Struct({"a": nw.Int32, "b": nw.String})
-    assert dtype in {nw.Struct({"a": nw.Int64, "b": nw.String})}
+    assert_equal_hash(dtype, nw.Struct({"a": nw.Int64, "b": nw.String}))
 
 
 def test_struct_reverse() -> None:
@@ -535,8 +541,10 @@ def test_enum_repr() -> None:
 
 
 def test_enum_hash() -> None:
-    assert nw.Enum(["a", "b"]) in {nw.Enum(["a", "b"])}
-    assert nw.Enum(["a", "b"]) not in {nw.Enum(["a", "b", "c"])}
+    dtype = nw.Enum(["a", "b"])
+    assert_equal_hash(dtype, nw.Enum(["a", "b"]))
+    with pytest.raises(AssertionError):
+        assert_equal_hash(dtype, nw.Enum(["a", "b", "c"]))
 
 
 @pytest.mark.xfail(

tests/stable_api_test.py

@@ -30,7 +30,7 @@ def test_stable_api_completeness() -> None:
 def test_stable_api_docstrings() -> None:
     main_namespace_api = nw.__all__
     for item in main_namespace_api:
-        if item in {"from_dict"}:
+        if item == "from_dict":
             # We keep `native_namespace` around in the main namespace
             # until at least hierarchical forecast make a release
             continue

tests/utils.py

@@ -166,6 +166,14 @@ def assert_equal_series(
     assert_equal_data(result.to_frame(), {name: expected})
 
 
+def assert_equal_hash(left: Any, right: Any) -> None:
+    """Assert that the left and right produce identical hash values."""
+    __tracebackhide__ = True
+    assert left in {right}, (  # noqa: FURB171
+        f"inputs do not compare equal by `__hash__`\n[left]: {left}\n[right]: {right}"
+    )
+
+
 def sqlframe_session() -> DuckDBSession:
     from sqlframe.duckdb import DuckDBSession
 

tests/v1_test.py

@@ -39,6 +39,7 @@
     Constructor,
     ConstructorEager,
     assert_equal_data,
+    assert_equal_hash,
     assert_equal_series,
 )
 
@@ -531,10 +532,10 @@ def test_dtypes() -> None:
         pd.DataFrame({"a": [1], "b": [datetime(2020, 1, 1)], "c": [timedelta(1)]})
     )
     dtype = df.collect_schema()["b"]
-    assert dtype in {nw_v1.Datetime}
+    assert_equal_hash(dtype, nw_v1.Datetime)
     assert isinstance(dtype, nw_v1.Datetime)
     dtype = df.lazy().schema["c"]
-    assert dtype in {nw_v1.Duration}
+    assert_equal_hash(dtype, nw_v1.Duration)
     assert isinstance(dtype, nw_v1.Duration)