chore: simplify definitions of rhs expressions, bump dask minimum to …

…2024.10 (#1720)

.github/workflows/extremes.yml

@@ -84,7 +84,7 @@ jobs:
   not_so_old_versions:
     strategy:
       matrix:
-        python-version: ["3.9"]
+        python-version: ["3.10"]
         os: [ubuntu-latest]
     runs-on: ${{ matrix.os }}
     steps:
@@ -99,7 +99,7 @@ jobs:
           cache-suffix: ${{ matrix.python-version }}
           cache-dependency-glob: "pyproject.toml"
       - name: install-not-so-old-versions
-        run: uv pip install tox virtualenv setuptools pandas==2.0.3 polars==0.20.8 numpy==1.24.4 pyarrow==14.0.0 "pyarrow-stubs<17" pyspark==3.4.0 scipy==1.8.0 scikit-learn==1.3.0 dask[dataframe]==2024.7 tzdata --system
+        run: uv pip install tox virtualenv setuptools pandas==2.0.3 polars==0.20.8 numpy==1.24.4 pyarrow==15.0.0 "pyarrow-stubs<17" pyspark==3.4.0 scipy==1.8.0 scikit-learn==1.3.0 dask[dataframe]==2024.10 tzdata --system
       - name: install-reqs
         run: uv pip install -e ".[dev]" --system
       - name: show-deps
@@ -110,11 +110,11 @@ jobs:
           echo "$DEPS" | grep 'pandas==2.0.3'
           echo "$DEPS" | grep 'polars==0.20.8'
           echo "$DEPS" | grep 'numpy==1.24.4'
-          echo "$DEPS" | grep 'pyarrow==14.0.0'
+          echo "$DEPS" | grep 'pyarrow==15.0.0'
           echo "$DEPS" | grep 'pyspark==3.4.0'
           echo "$DEPS" | grep 'scipy==1.8.0'
           echo "$DEPS" | grep 'scikit-learn==1.3.0'
-          echo "$DEPS" | grep 'dask==2024.7'
+          echo "$DEPS" | grep 'dask==2024.10'
       - name: Run pytest
         run: pytest tests --cov=narwhals --cov=tests --cov-fail-under=50 --runslow --constructors=pandas,pyarrow,polars[eager],polars[lazy],dask
 

.github/workflows/pytest.yml

@@ -59,7 +59,7 @@ jobs:
   pytest-full-coverage:
     strategy:
       matrix:
-        python-version: ["3.9", "3.11", "3.13"]
+        python-version: ["3.11", "3.13"]
         os: [ubuntu-latest]
     runs-on: ${{ matrix.os }}
     steps:
@@ -78,7 +78,7 @@ jobs:
       - name: install pyspark
         run: uv pip install -e ".[pyspark]" --system
         # PySpark is not yet available on Python3.12+
-        if: matrix.python-version == '3.9' || matrix.python-version == '3.11'
+        if: matrix.python-version != '3.13'
       - name: install ibis
         run: uv pip install -e ".[ibis]" --system
         # Ibis puts upper bounds on dependencies, and requires Python3.10+,

narwhals/_arrow/expr.py

@@ -163,66 +163,30 @@ def __lt__(self: Self, other: ArrowExpr | Any) -> Self:
     def __and__(self: Self, other: ArrowExpr | bool | Any) -> Self:
         return reuse_series_implementation(self, "__and__", other=other)
 
-    def __rand__(self: Self, other: ArrowExpr | bool | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__and__(self)  # type: ignore[return-value]
-
     def __or__(self: Self, other: ArrowExpr | bool | Any) -> Self:
         return reuse_series_implementation(self, "__or__", other=other)
 
-    def __ror__(self: Self, other: ArrowExpr | bool | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__or__(self)  # type: ignore[return-value]
-
     def __add__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__add__", other=other)
 
-    def __radd__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__add__(self)  # type: ignore[return-value]
-
     def __sub__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__sub__", other=other)
 
-    def __rsub__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__sub__(self)  # type: ignore[return-value]
-
     def __mul__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__mul__", other=other)
 
-    def __rmul__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__mul__(self)  # type: ignore[return-value]
-
     def __pow__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__pow__", other=other)
 
-    def __rpow__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__pow__(self)  # type: ignore[return-value]
-
     def __floordiv__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__floordiv__", other=other)
 
-    def __rfloordiv__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__floordiv__(self)  # type: ignore[return-value]
-
     def __truediv__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__truediv__", other=other)
 
-    def __rtruediv__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__truediv__(self)  # type: ignore[return-value]
-
     def __mod__(self: Self, other: ArrowExpr | Any) -> Self:
         return reuse_series_implementation(self, "__mod__", other=other)
 
-    def __rmod__(self: Self, other: ArrowExpr | Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__mod__(self)  # type: ignore[return-value]
-
     def __invert__(self: Self) -> Self:
         return reuse_series_implementation(self, "__invert__")
 

narwhals/_dask/expr.py

@@ -210,14 +210,6 @@ def __add__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __radd__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__radd__(other),
-            "__radd__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __sub__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__sub__(other),
@@ -226,14 +218,6 @@ def __sub__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rsub__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rsub__(other),
-            "__rsub__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __mul__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__mul__(other),
@@ -242,14 +226,6 @@ def __mul__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rmul__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rmul__(other),
-            "__rmul__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __truediv__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__truediv__(other),
@@ -258,14 +234,6 @@ def __truediv__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rtruediv__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rtruediv__(other),
-            "__rtruediv__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __floordiv__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__floordiv__(other),
@@ -274,14 +242,6 @@ def __floordiv__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rfloordiv__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rfloordiv__(other),
-            "__rfloordiv__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __pow__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__pow__(other),
@@ -290,14 +250,6 @@ def __pow__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rpow__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rpow__(other),
-            "__rpow__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __mod__(self, other: Any) -> Self:
         return self._from_call(
             lambda _input, other: _input.__mod__(other),
@@ -306,14 +258,6 @@ def __mod__(self, other: Any) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rmod__(self, other: Any) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rmod__(other),
-            "__rmod__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __eq__(self, other: DaskExpr) -> Self:  # type: ignore[override]
         return self._from_call(
             lambda _input, other: _input.__eq__(other),
@@ -370,14 +314,6 @@ def __and__(self, other: DaskExpr) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __rand__(self, other: DaskExpr) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__rand__(other),
-            "__rand__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __or__(self, other: DaskExpr) -> Self:
         return self._from_call(
             lambda _input, other: _input.__or__(other),
@@ -386,14 +322,6 @@ def __or__(self, other: DaskExpr) -> Self:
             returns_scalar=binary_operation_returns_scalar(self, other),
         )
 
-    def __ror__(self, other: DaskExpr) -> Self:
-        return self._from_call(
-            lambda _input, other: _input.__ror__(other),
-            "__ror__",
-            other=other,
-            returns_scalar=binary_operation_returns_scalar(self, other),
-        ).alias("literal")
-
     def __invert__(self: Self) -> Self:
         return self._from_call(
             lambda _input: _input.__invert__(),

narwhals/_dask/namespace.py

@@ -66,26 +66,30 @@ def nth(self, *column_indices: int) -> DaskExpr:
         )
 
     def lit(self, value: Any, dtype: DType | None) -> DaskExpr:
-        def convert_if_dtype(
-            series: dask_expr.Series, dtype: DType | type[DType]
-        ) -> dask_expr.Series:
-            return (
-                series.astype(narwhals_to_native_dtype(dtype, self._version))
-                if dtype
-                else series
-            )
+        import dask.dataframe as dd
+        import pandas as pd
 
-        return DaskExpr(
-            lambda df: [
-                df._native_frame.assign(literal=value)["literal"].pipe(
-                    convert_if_dtype, dtype
+        def func(df: DaskLazyFrame) -> list[dask_expr.Series]:
+            return [
+                dd.from_pandas(
+                    pd.Series(
+                        [value],
+                        dtype=narwhals_to_native_dtype(dtype, self._version)
+                        if dtype is not None
+                        else None,
+                        name="literal",
+                    ),
+                    npartitions=df._native_frame.npartitions,
                 )
-            ],
+            ]
+
+        return DaskExpr(
+            func,
             depth=0,
             function_name="lit",
             root_names=None,
             output_names=["literal"],
-            returns_scalar=False,
+            returns_scalar=True,
             backend_version=self._backend_version,
             version=self._version,
             kwargs={},
@@ -414,6 +418,9 @@ def __call__(self, df: DaskLazyFrame) -> Sequence[dask_expr.Series]:
             # `self._otherwise_value` is a scalar and can't be converted to an expression
             return [value_series.where(condition, self._otherwise_value)]
         otherwise_series = otherwise_expr(df)[0]
+
+        if otherwise_expr._returns_scalar:  # type: ignore[attr-defined]
+            return [value_series.where(condition, otherwise_series[0])]
         validate_comparand(condition, otherwise_series)
         return [value_series.where(condition, otherwise_series)]
 

narwhals/_dask/utils.py

@@ -31,7 +31,8 @@ def maybe_evaluate(df: DaskLazyFrame, obj: Any) -> Any:
             msg = "Multi-output expressions (e.g. `nw.all()` or `nw.col('a', 'b')`) not supported in this context"
             raise NotImplementedError(msg)
         result = results[0]
-        validate_comparand(df._native_frame, result)
+        if not obj._returns_scalar:
+            validate_comparand(df._native_frame, result)
         if obj._returns_scalar:
             # Return scalar, let Dask do its broadcasting
             return result[0]

narwhals/_pandas_like/expr.py

@@ -179,68 +179,31 @@ def __lt__(self, other: PandasLikeExpr | Any) -> Self:
     def __and__(self, other: PandasLikeExpr | bool | Any) -> Self:
         return reuse_series_implementation(self, "__and__", other=other)
 
-    def __rand__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__and__(self)  # type: ignore[no-any-return]
-
     def __or__(self, other: PandasLikeExpr | bool | Any) -> Self:
         return reuse_series_implementation(self, "__or__", other=other)
 
-    def __ror__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__or__(self)  # type: ignore[no-any-return]
-
     def __add__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__add__", other=other)
 
-    def __radd__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__add__(self)  # type: ignore[no-any-return]
-
     def __sub__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__sub__", other=other)
 
-    def __rsub__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__sub__(self)  # type: ignore[no-any-return]
-
     def __mul__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__mul__", other=other)
 
-    def __rmul__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__mul__(self)  # type: ignore[no-any-return]
-
     def __truediv__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__truediv__", other=other)
 
-    def __rtruediv__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__truediv__(self)  # type: ignore[no-any-return]
-
     def __floordiv__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__floordiv__", other=other)
 
-    def __rfloordiv__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__floordiv__(self)  # type: ignore[no-any-return]
-
     def __pow__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__pow__", other=other)
 
-    def __rpow__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__pow__(self)  # type: ignore[no-any-return]
-
     def __mod__(self, other: PandasLikeExpr | Any) -> Self:
         return reuse_series_implementation(self, "__mod__", other=other)
 
-    def __rmod__(self, other: Any) -> Self:
-        other = self.__narwhals_namespace__().lit(other, dtype=None)
-        return other.__mod__(self)  # type: ignore[no-any-return]
-
     # Unary
-
     def __invert__(self) -> Self:
         return reuse_series_implementation(self, "__invert__")