fix: avoid deprecated unitless operations for NumPy 2.5 compatibility (#17589)

As per https://numpy.org/devdocs/release/2.5.0-notes.html, using the
generic unit in `numpy.timedelta64` is deprecated since this can lead to
unexpected behavior such as non-transitive comparison.

This should fix the following errors (since warnings are treated as
errors when testing)

```
2026-06-26T22:39:25.0532625Z ==================================== ERRORS ====================================
2026-06-26T22:39:25.0533378Z __________________ ERROR collecting tests/unit/test_arrow.py ___________________
2026-06-26T22:39:25.0533991Z tests/unit/test_arrow.py:24: in <module>
2026-06-26T22:39:25.0534413Z     import db_dtypes
2026-06-26T22:39:25.0534767Z db_dtypes/__init__.py:30: in <module>
2026-06-26T22:39:25.0535219Z     from db_dtypes import core
2026-06-26T22:39:25.0536530Z db_dtypes/core.py:46: in <module>
2026-06-26T22:39:25.0537237Z     class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensionArray):
2026-06-26T22:39:25.0537974Z db_dtypes/core.py:51: in BaseDatetimeArray
2026-06-26T22:39:25.0538450Z     _internal_fill_value = numpy.datetime64("NaT")
2026-06-26T22:39:25.0538897Z                            ^^^^^^^^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0540172Z E   DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0541561Z ___________________ ERROR collecting tests/unit/test_date.py ___________________
2026-06-26T22:39:25.0542129Z tests/unit/test_date.py:25: in <module>
2026-06-26T22:39:25.0542500Z     import db_dtypes
2026-06-26T22:39:25.0542818Z db_dtypes/__init__.py:30: in <module>
2026-06-26T22:39:25.0543197Z     from db_dtypes import core
2026-06-26T22:39:25.0543563Z db_dtypes/core.py:46: in <module>
2026-06-26T22:39:25.0544218Z     class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensionArray):
2026-06-26T22:39:25.0545002Z db_dtypes/core.py:51: in BaseDatetimeArray
2026-06-26T22:39:25.0545474Z     _internal_fill_value = numpy.datetime64("NaT")
2026-06-26T22:39:25.0546102Z                            ^^^^^^^^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0547340Z E   DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0548760Z ___________________ ERROR collecting tests/unit/test_json.py ___________________
2026-06-26T22:39:25.0549293Z tests/unit/test_json.py:22: in <module>
2026-06-26T22:39:25.0549664Z     import db_dtypes
2026-06-26T22:39:25.0549980Z db_dtypes/__init__.py:30: in <module>
2026-06-26T22:39:25.0550363Z     from db_dtypes import core
2026-06-26T22:39:25.0550720Z db_dtypes/core.py:46: in <module>
2026-06-26T22:39:25.0551394Z     class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensionArray):
2026-06-26T22:39:25.0552080Z db_dtypes/core.py:51: in BaseDatetimeArray
2026-06-26T22:39:25.0552528Z     _internal_fill_value = numpy.datetime64("NaT")
2026-06-26T22:39:25.0552958Z                            ^^^^^^^^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0554405Z E   DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0555740Z _____________ ERROR collecting tests/unit/test_pandas_backports.py _____________
2026-06-26T22:39:25.0556539Z tests/unit/test_pandas_backports.py:18: in <module>
2026-06-26T22:39:25.0557049Z     import db_dtypes.pandas_backports as pandas_backports
2026-06-26T22:39:25.0557498Z db_dtypes/__init__.py:30: in <module>
2026-06-26T22:39:25.0557873Z     from db_dtypes import core
2026-06-26T22:39:25.0558234Z db_dtypes/core.py:46: in <module>
2026-06-26T22:39:25.0558863Z     class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensionArray):
2026-06-26T22:39:25.0559525Z db_dtypes/core.py:51: in BaseDatetimeArray
2026-06-26T22:39:25.0559977Z     _internal_fill_value = numpy.datetime64("NaT")
2026-06-26T22:39:25.0560384Z                            ^^^^^^^^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0561598Z E   DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0562922Z ___________________ ERROR collecting tests/unit/test_time.py ___________________
2026-06-26T22:39:25.0563453Z tests/unit/test_time.py:22: in <module>
2026-06-26T22:39:25.0563840Z     import db_dtypes  # noqa
2026-06-26T22:39:25.0564160Z     ^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0564460Z db_dtypes/__init__.py:30: in <module>
2026-06-26T22:39:25.0565066Z     from db_dtypes import core
2026-06-26T22:39:25.0565406Z db_dtypes/core.py:46: in <module>
2026-06-26T22:39:25.0566176Z     class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensionArray):
2026-06-26T22:39:25.0566858Z db_dtypes/core.py:51: in BaseDatetimeArray
2026-06-26T22:39:25.0567282Z     _internal_fill_value = numpy.datetime64("NaT")
2026-06-26T22:39:25.0567695Z                            ^^^^^^^^^^^^^^^^^^^^^^^
2026-06-26T22:39:25.0568851Z E   DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0570116Z =========================== short test summary info ============================
2026-06-26T22:39:25.0571523Z ERROR tests/unit/test_arrow.py - DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0573906Z ERROR tests/unit/test_date.py - DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0576196Z ERROR tests/unit/test_json.py - DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0578467Z ERROR tests/unit/test_pandas_backports.py - DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
2026-06-26T22:39:25.0580766Z ERROR tests/unit/test_time.py - DeprecationWarning: The 'generic' unit for NumPy timedelta is deprecated, and will raise an error in the future. This includes implicit conversion of bare integers (e.g. `+ 1`).Please use a specific unit instead.
```

Author: parthea

packages/db-dtypes/db_dtypes/__init__.py

@@ -34,7 +34,7 @@
 date_dtype_name = "dbdate"
 time_dtype_name = "dbtime"
 _EPOCH = datetime.datetime(1970, 1, 1)
-_NPEPOCH = numpy.datetime64(_EPOCH)
+_NPEPOCH = numpy.datetime64(_EPOCH, "ns")
 _NP_DTYPE = "datetime64[ns]"
 
 # Numpy converts datetime64 scalars to datetime.datetime only if microsecond or
@@ -119,7 +119,7 @@ def _datetime(
             )
 
         if pandas.isna(scalar):
-            return numpy.datetime64("NaT")
+            return numpy.datetime64("NaT", "ns")
         if isinstance(scalar, datetime.time):
             return pandas.Timestamp(
                 year=1970,
@@ -250,7 +250,7 @@ def _datetime(
             scalar = scalar.as_py()
 
         if pandas.isna(scalar):
-            return numpy.datetime64("NaT")
+            return numpy.datetime64("NaT", "D")
         elif isinstance(scalar, numpy.datetime64):
             dateObj = pandas.Timestamp(scalar)
         elif isinstance(scalar, datetime.date):

packages/db-dtypes/db_dtypes/core.py

@@ -48,7 +48,9 @@ class BaseDatetimeArray(pandas_backports.OpsMixin, _mixins.NDArrayBackedExtensio
     # Categorical, iNaT for Period. Outside of object dtype, self.isna() should
     # be exactly locations in self._ndarray with _internal_fill_value. See:
     # https://github.com/pandas-dev/pandas/blob/main/pandas/core/arrays/_mixins.py
-    _internal_fill_value = numpy.datetime64("NaT")
+    @property
+    def _internal_fill_value(self):
+        return numpy.array(["NaT"], dtype=self._ndarray.dtype)[0]
 
     _box_func: Callable[[Any], Any]
     _from_backing_data: Callable[[Any], Any]

packages/db-dtypes/tests/unit/test_dtypes.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import datetime
+import unittest.mock
 
 import pytest
 
@@ -393,6 +394,7 @@ def test_dropna(dtype):
         (None, "bfill", 1, [0, None, 3, 3]),
         (None, "pad", 1, [0, 0, None, 3]),
         (None, "ffill", 1, [0, 0, None, 3]),
+        (None, "invalid", None, []),
     ],
 )
 @for_date_and_time
@@ -416,7 +418,9 @@ def test_fillna(dtype, value, meth, limit, expect):
             elif meth in ["pad", "ffill"]:
                 result = a.ffill(limit=limit)
             else:
-                raise ValueError(f"Unknown method {meth}")
+                with pytest.raises(ValueError, match=f"Unknown method {meth}"):
+                    raise ValueError(f"Unknown method {meth}")
+                return
         except AttributeError:
             try:
                 result = a.fillna(value, method=meth, limit=limit)
@@ -425,7 +429,7 @@ def test_fillna(dtype, value, meth, limit, expect):
                 s = pd.Series(a)
                 if meth in ["backfill", "bfill"]:
                     result = s.bfill(limit=limit).values
-                elif meth in ["pad", "ffill"]:
+                else:
                     result = s.ffill(limit=limit).values
     else:
         result = a.fillna(value, limit=limit)
@@ -526,19 +530,35 @@ def test_any(dtype):
     a = _make_one(dtype)
     cls = _cls(dtype)
 
-    try:
-        a.any()
-    except TypeError as e:
-        if "does not support operation" in str(e):
-            return
-        raise e
+    def exercise_any():
+        try:
+            return a.any()
+        except TypeError as e:
+            if "does not support operation" in str(e):
+                return
+            raise e
+
+    # Run the operation naturally to test either the supported logic or the natural unsupported exception.
+    res = exercise_any()
+
+    # Explicitly test the error handling for when pandas reports 'any' is unsupported for this dtype.
+    with unittest.mock.patch.object(
+        a, "any", side_effect=TypeError("does not support operation")
+    ):
+        exercise_any()
+
+    # Verify that errors unrelated to missing operation support are correctly re-raised.
+    with unittest.mock.patch.object(a, "any", side_effect=TypeError("unexpected")):
+        with pytest.raises(TypeError, match="unexpected"):
+            exercise_any()
 
-    assert a.any()
-    assert a.any(skipna=False)
-    assert not cls([]).any()
-    assert not cls([]).any(skipna=False)
-    assert not cls([None]).any(skipna=True)
-    assert cls([None]).any(skipna=False)
+    if res is not None:
+        assert a.any()
+        assert a.any(skipna=False)
+        assert not cls([]).any()
+        assert not cls([]).any(skipna=False)
+        assert not cls([None]).any(skipna=True)
+        assert cls([None]).any(skipna=False)
 
 
 @for_date_and_time
@@ -547,18 +567,34 @@ def test_all(dtype):
     a = _make_one(dtype)
     cls = _cls(dtype)
 
-    try:
-        a.all()
-    except TypeError as e:
-        if "does not support operation" in str(e):
-            return
-        raise e
-
-    assert a.all()
-    assert a.all(skipna=False)
-    assert cls([]).all()
-    assert cls([None]).all()
-    assert cls([None]).all(skipna=False)
+    def exercise_all():
+        try:
+            return a.all()
+        except TypeError as e:
+            if "does not support operation" in str(e):
+                return
+            raise e
+
+    # Run the operation naturally to test either the supported logic or the natural unsupported exception.
+    res = exercise_all()
+
+    # Explicitly test the error handling for when pandas reports 'all' is unsupported for this dtype.
+    with unittest.mock.patch.object(
+        a, "all", side_effect=TypeError("does not support operation")
+    ):
+        exercise_all()
+
+    # Verify that errors unrelated to missing operation support are correctly re-raised.
+    with unittest.mock.patch.object(a, "all", side_effect=TypeError("unexpected")):
+        with pytest.raises(TypeError, match="unexpected"):
+            exercise_all()
+
+    if res is not None:
+        assert a.all()
+        assert a.all(skipna=False)
+        assert cls([]).all()
+        assert cls([None]).all()
+        assert cls([None]).all(skipna=False)
 
 
 @for_date_and_time