Fix comparison between Datetime/Timedelta columns and NULL scalars (#7504)

Fixes #6897

Authors:
  - @brandon-b-miller

Approvers:
  - GALI PREM SAGAR (@galipremsagar)
  - Ram (Ramakrishna Prabhu) (@rgsl888prabhu)

URL: #7504

Author: brandon-b-miller

python/cudf/cudf/core/column/datetime.py

@@ -178,6 +178,8 @@ def normalize_binop_value(self, other: DatetimeLikeScalar) -> ScalarLike:
                 return cudf.Scalar(None, dtype=other.dtype)
 
             return cudf.Scalar(other)
+        elif other is None:
+            return cudf.Scalar(other, dtype=self.dtype)
         else:
             raise TypeError(f"cannot normalize {type(other)}")
 

python/cudf/cudf/core/column/timedelta.py

@@ -275,6 +275,8 @@ def normalize_binop_value(self, other) -> BinaryOperand:
             return cudf.Scalar(other)
         elif np.isscalar(other):
             return cudf.Scalar(other)
+        elif other is None:
+            return cudf.Scalar(other, dtype=self.dtype)
         else:
             raise TypeError(f"cannot normalize {type(other)}")
 

python/cudf/cudf/tests/test_binops.py

@@ -1773,6 +1773,51 @@ def decimal_series(input, dtype):
     utils.assert_eq(expect, got)
 
 
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        "uint8",
+        "uint16",
+        "uint32",
+        "uint64",
+        "int8",
+        "int16",
+        "int32",
+        "int64",
+        "float32",
+        "float64",
+        "str",
+        "datetime64[ns]",
+        "datetime64[us]",
+        "datetime64[ms]",
+        "datetime64[s]",
+        "timedelta64[ns]",
+        "timedelta64[us]",
+        "timedelta64[ms]",
+        "timedelta64[s]",
+    ],
+)
+@pytest.mark.parametrize("null_scalar", [None, cudf.NA, np.datetime64("NaT")])
+@pytest.mark.parametrize("cmpop", _cmpops)
+def test_column_null_scalar_comparison(dtype, null_scalar, cmpop):
+    # This test is meant to validate that comparing
+    # a series of any dtype with a null scalar produces
+    # a new series where all the elements are <NA>.
+
+    if isinstance(null_scalar, np.datetime64):
+        if np.dtype(dtype).kind not in "mM":
+            pytest.skip()
+        null_scalar = null_scalar.astype(dtype)
+
+    dtype = np.dtype(dtype)
+
+    data = [1, 2, 3, 4, 5]
+    sr = cudf.Series(data, dtype=dtype)
+    result = cmpop(sr, null_scalar)
+
+    assert result.isnull().all()
+
+
 @pytest.mark.parametrize("fn", ["eq", "ne", "lt", "gt", "le", "ge"])
 def test_equality_ops_index_mismatch(fn):
     a = cudf.Series(