feat: dask expr __invert__, is_null, n_unique methods

narwhals/_dask/expr.py

@@ -334,6 +334,13 @@ def __ror__(self, other: DaskExpr) -> Self:  # pragma: no cover
             returns_scalar=False,
         )
 
+    def __invert__(self: Self) -> Self:
+        return self._from_call(
+            lambda _input: _input.__invert__(),
+            "__invert__",
+            returns_scalar=False,
+        )
+
     def mean(self) -> Self:
         return self._from_call(
             lambda _input: _input.mean(),
@@ -473,6 +480,20 @@ def clip(
             returns_scalar=False,
         )
 
+    def n_unique(self: Self) -> Self:
+        return self._from_call(
+            lambda _input: _input.nunique(dropna=False),
+            "n_unique",
+            returns_scalar=True,
+        )
+
+    def is_null(self: Self) -> Self:
+        return self._from_call(
+            lambda _input: _input.isna(),
+            "is_null",
+            returns_scalar=False,
+        )
+
     @property
     def str(self: Self) -> DaskExprStringNamespace:
         return DaskExprStringNamespace(self)

tests/expr_and_series/is_null_test.py

@@ -0,0 +1,22 @@
+from typing import Any
+
+import narwhals.stable.v1 as nw
+from tests.utils import compare_dicts
+
+
+def test_null(constructor: Any) -> None:
+    data_na = {"a": [None, 3, 2], "z": [7.0, None, None]}
+    expected = {"a": [True, False, False], "z": [True, False, False]}
+    df = nw.from_native(constructor(data_na))
+    result = df.select(nw.col("a").is_null(), ~nw.col("z").is_null())
+
+    compare_dicts(result, expected)
+
+
+def test_null_series(constructor_eager: Any) -> None:
+    data_na = {"a": [None, 3, 2], "z": [7.0, None, None]}
+    expected = {"a": [True, False, False], "z": [True, False, False]}
+    df = nw.from_native(constructor_eager(data_na), eager_only=True)
+    result = {"a": df["a"].is_null(), "z": ~df["z"].is_null()}
+
+    compare_dicts(result, expected)

tests/expr_and_series/n_unique_test.py

@@ -1,7 +1,5 @@
 from typing import Any
 
-import pytest
-
 import narwhals.stable.v1 as nw
 from tests.utils import compare_dicts
 
@@ -11,9 +9,7 @@
 }
 
 
-def test_n_unique(constructor: Any, request: Any) -> None:
-    if "dask" in str(constructor):
-        request.applymarker(pytest.mark.xfail)
+def test_n_unique(constructor: Any) -> None:
     df = nw.from_native(constructor(data))
     result = df.select(nw.all().n_unique())
     expected = {"a": [3], "b": [4]}