Bug#1142515: marked as done (apache-arrow: fails tests with pandas 3.0)

[Debian Bug Tracking System]

Your message dated Fri, 31 Jul 2026 23:33:54 +0000
with message-id <e1wpwji-0000000cz8g-2...@fasolo.debian.org>
and subject line Bug#1142515: fixed in apache-arrow 25.0.0-1
has caused the Debian Bug report #1142515,
regarding apache-arrow: fails tests with pandas 3.0
to be marked as done.

This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.

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-- 
1142515: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1142515
Debian Bug Tracking System
Contact ow...@bugs.debian.org with problems

--- Begin Message ---

Source: apache-arrow
Version: 23.0.1-11
Control: block 1141694 by -1

apache-arrow fails autopkgtests with pandas 3.0 (in experimental):

https://ci.debian.net/packages/a/apache-arrow/unstable/amd64/73190584/

I haven't tried the newer apache-arrow in experimental.

I'm not sure exactly what the problem is but it looks datetime-related.
Upstream release notes: https://pandas.pydata.org/docs/whatsnew/v3.0.0.html


204s

204s
204s resolution = 's', tz = 'America/New_York'
204s dt = datetime.datetime(1553, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s
204s resolution = 'ms', tz = 'America/New_York'
204s dt = datetime.datetime(1553, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s
204s resolution = 'us', tz = 'America/New_York'
204s dt = datetime.datetime(1553, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s
204s resolution = 's', tz = 'America/New_York'
204s dt = datetime.datetime(2020, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s
204s resolution = 'ms', tz = 'America/New_York'
204s dt = datetime.datetime(2020, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s
204s resolution = 'us', tz = 'America/New_York'
204s dt = datetime.datetime(2020, 1, 1, 0, 0)
204s
204s     @pytest.mark.parametrize("resolution", ["s", "ms", "us"])
204s     @pytest.mark.parametrize("tz", [None, "America/New_York"])

204s     def test_timestamp_as_object_non_nanosecond(resolution, tz, dt):

204s         # of information if the timestamp_as_object option is True.
204s         arr = pa.array([dt], type=pa.timestamp(resolution, tz=tz))
204s         table = pa.table({'a': arr})
204s
204s         for result in [
204s             arr.to_pandas(timestamp_as_object=True),
204s             table.to_pandas(timestamp_as_object=True)['a']
204s         ]:
204s             assert result.dtype == object
204s             assert isinstance(result[0], datetime)
204s             if tz:
204s                 assert result[0].tzinfo is not None
204s >               expected = result[0].tzinfo.fromutc(dt)
204s                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
204s E               ValueError: fromutc: dt.tzinfo is not self
204s

204s =================================== FAILURES =================================== 204s _______ test_timestamp_as_object_non_nanosecond[dt0-America/New_York-s] ________ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError 204s _______ test_timestamp_as_object_non_nanosecond[dt0-America/New_York-ms] _______ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError 204s _______ test_timestamp_as_object_non_nanosecond[dt0-America/New_York-us] _______ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError 204s _______ test_timestamp_as_object_non_nanosecond[dt1-America/New_York-s] ________ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError 204s _______ test_timestamp_as_object_non_nanosecond[dt1-America/New_York-ms] _______ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError 204s _______ test_timestamp_as_object_non_nanosecond[dt1-America/New_York-us] _______ 204s # One datetime outside nanosecond range, one inside nanosecond range: 204s @pytest.mark.parametrize("dt", [datetime(1553, 1, 1), datetime(2020, 1, 1)]) 204s # Timestamps can be converted Arrow and reloaded into Pandas with no loss 204s /usr/lib/python3/dist-packages/pyarrow/tests/test_pandas.py:4970: ValueError
--- End Message ---

--- Begin Message ---

Source: apache-arrow
Source-Version: 25.0.0-1
Done: Dominique Belhachemi <domi...@debian.org>

We believe that the bug you reported is fixed in the latest version of
apache-arrow, which is due to be installed in the Debian FTP archive.

A summary of the changes between this version and the previous one is
attached.

Thank you for reporting the bug, which will now be closed.  If you
have further comments please address them to 1142...@bugs.debian.org,
and the maintainer will reopen the bug report if appropriate.

Debian distribution maintenance software
pp.
Dominique Belhachemi <domi...@debian.org> (supplier of updated apache-arrow 
package)

(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing ftpmas...@ftp-master.debian.org)


-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA512

Format: 1.8
Date: Fri, 31 Jul 2026 22:40:46 +0000
Source: apache-arrow
Architecture: source
Version: 25.0.0-1
Distribution: unstable
Urgency: medium
Maintainer: Debian Science Maintainers 
<debian-science-maintain...@lists.alioth.debian.org>
Changed-By: Dominique Belhachemi <domi...@debian.org>
Closes: 1142515
Changes:
 apache-arrow (25.0.0-1) unstable; urgency=medium
 .
   [ Rene Engelhard ]
   * drop r-4.6.diff, applied upstream
 .
   [ Dominique Belhachemi ]
   * New upstream version 25.0.0
   * switch to soname 2500
   * refresh use-debian-mimalloc.patch, restore DEP-3 header
   * debian/control: add pybuild-plugin-pyproject and python3-scikit-build-core
     to Build-Depends
   * switch pybuild from the distutils plugin to the pyproject plugin
   * pyarrow now builds with scikit-build-core instead of setup.py
   * debian/python3-pyarrow.install: .egg-info -> .dist-info
   * debian/copyright: drop ci/conan stanzas, removed upstream
   * Standards-Version: 4.7.4 (no changes needed)
   * debian/control: drop redundant Priority field from the source stanza
   * add new patch build-sse4.2-kernels.patch, keeps SIMD dispatch with the
     x86-64-v1 baseline
   * fixes autopkgtest failures with pandas 3.0 (Closes: #1142515)
   * debian/tests/control: add python3-pytz
   * drop the duplicate python bridge-lib copies
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