def __eq__(self, other: Any) -> bool:
if isinstance(other, str):
if other.startswith("M8["):
other = "datetime64[" + other[3:]
return other == self.name
return (isinstance(other, DatetimeTZDtype) and self.unit == other.unit
and tz_compare(self.tz, other.tz))
def test_non_nano(self, unit, reso, dtype):
arr = np.arange(5, dtype=np.int64).view(f"M8[{unit}]")
dta = DatetimeArray._simple_new(arr, dtype=dtype)
assert dta.dtype == dtype
assert dta[0]._reso == reso
assert tz_compare(dta.tz, dta[0].tz)
assert (dta[0] == dta[:1]).all()
def test_maybe_promote_datetimetz_with_datetimetz(tz_aware_fixture, tz_aware_fixture2):
dtype = DatetimeTZDtype(tz=tz_aware_fixture)
fill_dtype = DatetimeTZDtype(tz=tz_aware_fixture2)
# create array of given dtype; casts "1" to correct dtype
fill_value = pd.Series([10 ** 9], dtype=fill_dtype)[0]
# filling datetimetz with datetimetz casts to object, unless tz matches
exp_val_for_scalar = fill_value
if tz_compare(dtype.tz, fill_dtype.tz):
expected_dtype = dtype
else:
expected_dtype = np.dtype(object)
_check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
