Handle uint in astype tests

pandas/tests/arrays/test_datetimes.py

@@ -53,6 +53,23 @@ def test_astype_to_same(self):
         result = arr.astype(DatetimeTZDtype(tz="US/Central"), copy=False)
         assert result is arr
 
+    @pytest.mark.parametrize("dtype", [
+        int, np.int32, np.int64, 'uint32', 'uint64',
+    ])
+    def test_astype_int(self, dtype):
+        arr = DatetimeArray._from_sequence([pd.Timestamp('2000'),
+                                            pd.Timestamp('2001')])
+        result = arr.astype(dtype)
+
+        if np.dtype(dtype).kind == 'u':
+            expected_dtype = np.dtype('uint64')
+        else:
+            expected_dtype = np.dtype('int64')
+        expected = arr.astype(expected_dtype)
+
+        assert result.dtype == expected_dtype
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_tz_setter_raises(self):
         arr = DatetimeArray._from_sequence(['2000'], tz='US/Central')
         with pytest.raises(AttributeError, match='tz_localize'):

pandas/tests/arrays/test_period.py

@@ -87,13 +87,19 @@ def test_take_raises():
         arr.take([0, -1], allow_fill=True, fill_value='foo')
 
 
-@pytest.mark.parametrize('dtype', [int, np.int32, np.int64, 'uint'])
+@pytest.mark.parametrize('dtype', [
+    int, np.int32, np.int64, 'uint32', 'uint64',
+])
 def test_astype(dtype):
     # We choose to ignore the sign and size of integers for
     # Period/Datetime/Timedelta astype
     arr = period_array(['2000', '2001', None], freq='D')
     result = arr.astype(dtype)
-    expected_dtype = np.dtype('int64')
+
+    if np.dtype(dtype).kind == 'u':
+        expected_dtype = np.dtype('uint64')
+    else:
+        expected_dtype = np.dtype('int64')
     expected = arr.astype(expected_dtype)
 
     assert result.dtype == expected_dtype

pandas/tests/arrays/test_timedeltas.py

@@ -55,3 +55,20 @@ def test_neg_freq(self):
 
         result = -arr
         tm.assert_timedelta_array_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", [
+        int, np.int32, np.int64, 'uint32', 'uint64',
+    ])
+    def test_astype_int(self, dtype):
+        arr = TimedeltaArray._from_sequence([pd.Timedelta('1H'),
+                                             pd.Timedelta('2H')])
+        result = arr.astype(dtype)
+
+        if np.dtype(dtype).kind == 'u':
+            expected_dtype = np.dtype('uint64')
+        else:
+            expected_dtype = np.dtype('int64')
+        expected = arr.astype(expected_dtype)
+
+        assert result.dtype == expected_dtype
+        tm.assert_numpy_array_equal(result, expected)