From 6055393b215c62809a7248094a5848253121651e Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>
Date: Thu, 31 Oct 2024 13:42:23 -0700
Subject: [PATCH] Fix binop with LHS numpy datetimelike scalar (#17226)

closes #17087

For binops, cudf tries to convert a 0D numpy array to a numpy scalar via `.dtype.type(value)`, but `.dtype.type` requires other parameters if its a `numpy.datetime64` or `numpy.timedelta64`. Indexing via `[()]` will perform this conversion correctly.

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - Vyas Ramasubramani (https://github.com/vyasr)

URL: https://github.com/rapidsai/cudf/pull/17226
---
 python/cudf/cudf/core/column/column.py |  4 ++--
 python/cudf/cudf/tests/test_binops.py  | 13 +++++++++++++
 2 files changed, 15 insertions(+), 2 deletions(-)

diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index d2cd6e8ac8f..d2f9d208c77 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -580,8 +580,8 @@ def _wrap_binop_normalization(self, other):
         if cudf.utils.utils.is_na_like(other):
             return cudf.Scalar(other, dtype=self.dtype)
         if isinstance(other, np.ndarray) and other.ndim == 0:
-            # Try and maintain the dtype
-            other = other.dtype.type(other.item())
+            # Return numpy scalar
+            other = other[()]
         return self.normalize_binop_value(other)
 
     def _scatter_by_slice(
diff --git a/python/cudf/cudf/tests/test_binops.py b/python/cudf/cudf/tests/test_binops.py
index 949fa909b5b..71b6bbd688d 100644
--- a/python/cudf/cudf/tests/test_binops.py
+++ b/python/cudf/cudf/tests/test_binops.py
@@ -3431,3 +3431,16 @@ def test_binop_eq_ne_index_series(data1, data2):
     expected = gi.to_pandas() != gs.to_pandas()
 
     assert_eq(expected, actual)
+
+
+@pytest.mark.parametrize("scalar", [np.datetime64, np.timedelta64])
+def test_binop_lhs_numpy_datetimelike_scalar(scalar):
+    slr1 = scalar(1, "ms")
+    slr2 = scalar(1, "ns")
+    result = slr1 < cudf.Series([slr2])
+    expected = slr1 < pd.Series([slr2])
+    assert_eq(result, expected)
+
+    result = slr2 < cudf.Series([slr1])
+    expected = slr2 < pd.Series([slr1])
+    assert_eq(result, expected)