From 0c2c7a1dc4a556722a3bd28c9188f4fdc84d229f Mon Sep 17 00:00:00 2001
From: Vyas Ramasubramani <vyasr@nvidia.com>
Date: Tue, 27 Apr 2021 12:46:12 -0700
Subject: [PATCH] Add missing __cuda_array_interface__ for datetime objects.

---
 python/cudf/cudf/core/column/datetime.py | 31 +++++++++++++++++++++++-
 1 file changed, 30 insertions(+), 1 deletion(-)

diff --git a/python/cudf/cudf/core/column/datetime.py b/python/cudf/cudf/core/column/datetime.py
index b9d42c031c7..d86a54e6970 100644
--- a/python/cudf/cudf/core/column/datetime.py
+++ b/python/cudf/cudf/core/column/datetime.py
@@ -2,10 +2,12 @@
 
 from __future__ import annotations
 
+import builtins
 import datetime as dt
 import re
 from numbers import Number
-from typing import Any, Sequence, Union, cast
+from types import SimpleNamespace
+from typing import Any, Mapping, Sequence, Union, cast
 
 import numpy as np
 import pandas as pd
@@ -199,6 +201,33 @@ def as_numerical(self) -> "cudf.core.column.NumericalColumn":
             ),
         )
 
+    @property
+    def __cuda_array_interface__(self) -> Mapping[builtins.str, Any]:
+        output = {
+            "shape": (len(self),),
+            "strides": (self.dtype.itemsize,),
+            "typestr": self.dtype.str,
+            "data": (self.data_ptr, False),
+            "version": 1,
+        }
+
+        if self.nullable and self.has_nulls:
+
+            # Create a simple Python object that exposes the
+            # `__cuda_array_interface__` attribute here since we need to modify
+            # some of the attributes from the numba device array
+            mask = SimpleNamespace(
+                __cuda_array_interface__={
+                    "shape": (len(self),),
+                    "typestr": "<t1",
+                    "data": (self.mask_ptr, True),
+                    "version": 1,
+                }
+            )
+            output["mask"] = mask
+
+        return output
+
     def as_datetime_column(self, dtype: Dtype, **kwargs) -> DatetimeColumn:
         dtype = np.dtype(dtype)
         if dtype == self.dtype: