tz = tz_naive_fixture
if freq == "YE" and not IS64 and isinstance(tz, tzlocal):
request.applymarker(
- pytest.mark.xfail(reason="OverflowError inside tzlocal past 2038")
+ pytest.mark.xfail(reason="OverflowError inside tzlocal past 2038", strict=False)
)
idx = date_range(start="2013-04-01", periods=30, freq=freq, tz=tz)
import pandas._testing as tm
from pandas.io.sas.sas7bdat import SAS7BDATReader
+import platform
+import re
+is_platform_x86_32 = bool(re.match("i.?86|x86", platform.uname()[4])) and not IS64
@pytest.fixture
res = df0["DateTimeHi"].astype("M8[us]").dt.round("ms")
df0["DateTimeHi"] = res.astype("M8[ms]")
- if not IS64:
+ if is_platform_x86_32:
# No good reason for this, just what we get on the CI
df0.loc[0, "DateTimeHi"] += np.timedelta64(1, "ms")
df0.loc[[2, 3], "DateTimeHi"] -= np.timedelta64(1, "ms")
columns=["text", "dt_as_float", "dt_as_dt", "date_as_float", "date_as_date"],
)
- if not IS64:
+ if is_platform_x86_32:
# No good reason for this, just what we get on the CI
expected.loc[:, "dt_as_dt"] -= np.timedelta64(1, "ms")
columns=col_order,
),
]
- if not IS64:
+ if is_platform_x86_32:
# No good reason for this, just what we get on the CI
expected[0].loc[0, "dt_as_dt"] -= np.timedelta64(1, "ms")
expected[1].loc[0, "dt_as_dt"] -= np.timedelta64(1, "ms")
),
},
)
- if not IS64:
+ if is_platform_x86_32:
# No good reason for this, just what we get on the CI
expected.loc[0, "datetimecol"] -= np.timedelta64(1, "ms")
tm.assert_frame_equal(df, expected)
actual = to_timedelta([val])
assert actual[0]._value == np.timedelta64("NaT").astype("int64")
- @pytest.mark.xfail(not IS64, reason="Floating point error")
+ @pytest.mark.xfail(not IS64, reason="Floating point error", strict=False)
def test_to_timedelta_float(self):
# https://github.com/pandas-dev/pandas/issues/25077
arr = np.arange(0, 1, 1e-6)[-10:]