fix(python): fix ufunc for unlimited column args

py-polars/polars/expr/expr.py

@@ -6,7 +6,7 @@
 import os
 import warnings
 from datetime import timedelta
-from functools import partial, reduce
+from functools import reduce
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -66,7 +66,6 @@
 
 with contextlib.suppress(ImportError):  # Module not available when building docs
     from polars.polars import arg_where as py_arg_where
-    from polars.polars import reduce as pyreduce
 
 with contextlib.suppress(ImportError):  # Module not available when building docs
     from polars.polars import PyExpr
@@ -287,21 +286,29 @@ def __array_ufunc__(
         self, ufunc: Callable[..., Any], method: str, *inputs: Any, **kwargs: Any
     ) -> Self:
         """Numpy universal functions."""
+        if method != "__call__":
+            msg = f"Only call is implemented not {method}"
+            raise NotImplementedError(msg)
         is_custom_ufunc = ufunc.__class__ != np.ufunc
         num_expr = sum(isinstance(inp, Expr) for inp in inputs)
-        if num_expr > 1:
-            if num_expr < len(inputs):
-                msg = (
-                    "NumPy ufunc with more than one expression can only be used"
-                    " if all non-expression inputs are provided as keyword arguments only"
-                )
-                raise ValueError(msg)
-
-            exprs = parse_as_list_of_expressions(inputs)
-            return self._from_pyexpr(pyreduce(partial(ufunc, **kwargs), exprs))
+        exprs = [
+            (inp, Expr, i) if isinstance(inp, Expr) else (inp, None, i)
+            for i, inp in enumerate(inputs)
+        ]
+        if num_expr == 1:
+            root_expr = next(expr[0] for expr in exprs if expr[1] == Expr)
+        else:
+            root_expr = F.struct(expr[0] for expr in exprs if expr[1] == Expr)
 
         def function(s: Series) -> Series:  # pragma: no cover
-            args = [inp if not isinstance(inp, Expr) else s for inp in inputs]
+            args = []
+            for i, expr in enumerate(exprs):
+                if expr[1] == Expr and num_expr > 1:
+                    args.append(s.struct[i])
+                elif expr[1] == Expr:
+                    args.append(s)
+                else:
+                    args.append(expr[0])
             return ufunc(*args, **kwargs)
 
         if is_custom_ufunc is True:
@@ -316,8 +323,10 @@ def function(s: Series) -> Series:  # pragma: no cover
                 CustomUFuncWarning,
                 stacklevel=find_stacklevel(),
             )
-            return self.map_batches(function, is_elementwise=False)
-        return self.map_batches(function, is_elementwise=True)
+            return root_expr.map_batches(
+                function, is_elementwise=False
+            ).meta.undo_aliases()
+        return root_expr.map_batches(function, is_elementwise=True).meta.undo_aliases()
 
     @classmethod
     def from_json(cls, value: str) -> Self:

py-polars/tests/unit/operations/map/test_map_batches.py

@@ -77,3 +77,21 @@ def test_map_deprecated() -> None:
         pl.col("a").map(lambda x: x)
     with pytest.deprecated_call():
         pl.LazyFrame({"a": [1, 2]}).map(lambda x: x)
+
+
+def test_ufunc_args() -> None:
+    df = pl.DataFrame({"a": [1, 2, 3], "b": [2, 4, 6]})
+    result = df.select(
+        z=np.add(  # type: ignore[call-overload]
+            pl.col("a"), pl.col("b")
+        )
+    )
+    expected = pl.DataFrame({"z": [3, 6, 9]})
+    assert_frame_equal(result, expected)
+    result = df.select(
+        z=np.add(  # type: ignore[call-overload]
+            2, pl.col("a")
+        )
+    )
+    expected = pl.DataFrame({"z": [3, 4, 5]})
+    assert_frame_equal(result, expected)