Bug#1004870: python-xarray: autopkgtest regression on s390x

[Graham Inggs]

Source: python-xarray
Version: 0.21.0-1
X-Debbugs-CC: debian-ci at lists.debian.org, debian-s390 at lists.debian.org
Severity: serious
User: debian-ci at lists.debian.org
Usertags: regression

Hi Maintainer

python-xarray's autopkgtests are failing on the big-endian s390x
architecture [1].
I've copied what I hope is the relevant part of the log below.

Regards
Graham


[1] https://ci.debian.net/packages/p/python-xarray/unstable/s390x/


=================================== FAILURES ===================================
_______________________ test_calendar_cftime_2D[365_day] _______________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.25602205, 0.47375523, 0.88418655, ..., 0.19579452,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: -259805407763208-03-07 00:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
_______________________ test_calendar_cftime_2D[360_day] _______________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.3348676 , 0.8813548 , 0.07158625, ..., 0.12469613,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: 768533895196513-09-16 16:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
_______________________ test_calendar_cftime_2D[julian] ________________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.05513783, 0.72362925, 0.78967474, ..., 0.8560986 ,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: 904522921033531-11-08 08:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
______________________ test_calendar_cftime_2D[all_leap] _______________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.02927022, 0.10328084, 0.12428704, ..., 0.83960594,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: -77577995854656-10-03 16:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
_______________________ test_calendar_cftime_2D[366_day] _______________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.32570151, 0.71143133, 0.43459037, ..., 0.14784034,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: 391106800438843-10-05 00:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
______________________ test_calendar_cftime_2D[gregorian] ______________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[0.91161183, 0.42436822, 0.53522578, ..., 0.36468928,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: -690921531052547-07-02 08:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
_________________ test_calendar_cftime_2D[proleptic_gregorian] _________________

data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)>
array([[[8.84930980e-01, 9.76547499e-01, 4.34131057e-01, ...,
...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0
  * time     (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00

    @requires_cftime
    def test_calendar_cftime_2D(data) -> None:
        # 2D np datetime:
>       data = xr.DataArray(
            np.random.randint(1, 1000000, size=(4,
5)).astype("<M8[h]"), dims=("x", "y")
        )

/usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__
    data = as_compatible_data(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:232: in
as_compatible_data
    data = _possibly_convert_objects(data)
/usr/lib/python3/dist-packages/xarray/core/variable.py:176: in
_possibly_convert_objects
    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)
/usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__
    data = sanitize_array(data, index, dtype, copy)
/usr/lib/python3/dist-packages/pandas/core/construction.py:545: in
sanitize_array
    subarr = _try_cast(data, dtype, copy, raise_cast_failure)
/usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast
    return sanitize_to_nanoseconds(arr, copy=copy)
/usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in
sanitize_to_nanoseconds
    values = conversion.ensure_datetime64ns(values)
pandas/_libs/tslibs/conversion.pyx:256: in
pandas._libs.tslibs.conversion.ensure_datetime64ns
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

>   ???
E   pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds
nanosecond timestamp: -67784665697082-12-03 00:00:00

pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime