Nightly Hypothesis tests failed

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Python 3.12 Test Summary

properties/test_index_manipulation.py::DatasetTest::runTest: hypothesis.errors.FlakyFailure: Inconsistent results: An example failed on the first run but now succeeds (or fails with another error, or is for some reason not runnable). (1 sub-exception)
Falsifying example:
state = DatasetStateMachine()
state.init_ds(var=Variable(
    data=array([6.97735636e+16]),
    dims=['żzåäH'],
    attrs={'ŵāºŻŋ': {'': None, 'ĺſÍĂł': False},
     'óžŅſÒ': {'ŻOÀĜ': array([['}\x9fÉt\x0b', 'x)\U000ae574vu'],
             ['¶\x85Ê |', '\U000e8a69\U000c7509{`÷']], dtype='<U5'),
      'čØŽÞo': None,
      'nàM': 'Ō'},
     'ĭ': {'īLIř': None,
      'őOÇİ6': None,
      'żžĠéĆ': 'Yï',
      'ŻōŅ4r': 'ąĸ',
      '': array([           -inf, -2.41930698e+16]),
      'ſŻĮ': None,
      'ų': '1À',
      'ŃĀD': 'ðżŔ',
      'Þſìćû': True}},
))
state.assert_invariants()
Draw 1: ['żzåäH']
> stacking ['żzåäH'] as ſ1
state.stack(create_index=False, data=data(...), newname='ſ1')
state.assert_invariants()
adding dimension coordinate йŶ
state.add_dim_coord(var=Variable(
    data=array(['1969-12-31T23:59:56.242924246', '1970-01-01T00:00:00.000024524',
           '1969-12-31T23:59:59.999946357', '1970-01-01T00:00:00.000000215',
           '2005-12-20T07:21:30.571963408', '1969-12-31T23:59:59.999968231'],
          dtype='datetime64[ns]'),
    dims=['йŶ'],
    attrs={'ÐżĔdŒ': True, '': False},
))
state.assert_invariants()
Draw 2: ['йŶ']
> stacking ['йŶ'] as š³Żh
state.stack(create_index=False, data=data(...), newname='š³Żh')
state.assert_invariants()
adding dimension coordinate ă
state.add_dim_coord(var=Variable(
    data=array([                 238,                33549,  9223372036854775807,
                          33437, -5672900794703796655,  8457639148380062172],
          dtype='timedelta64[ns]'),
    dims=['ă'],
    attrs={},
))
state.assert_invariants()
Draw 3: ['ă']
> stacking ['ă'] as ťĖ
state.stack(create_index=False, data=data(...), newname='ťĖ')
state.assert_invariants()
adding dimension coordinate 7óŸŻç
state.add_dim_coord(var=Variable(
    data=array([4157794707,        371, 2440091218,       5774,         53,
                16806], dtype=uint32),
    dims=['7óŸŻç'],
    attrs={'çhŁ': {'V': True, '': array([[6.10351562e-05-2.22507386e-313j],
             [1.40129846e-45-3.33333333e-001j]]), 'EÉ': 'ŽÁþH', 'Ŧ': None, 'Ġĩ': False, 'žŝŬŻø': False, 'ſfą': None, 'ðQŤĩ': array([['ú\U000d2b93\U00044bab', ''],
             ['\x96£5ü', '']], dtype='<U4'), 'ųŽÅ': array([b'\xc5', b';'], dtype='|S2'), 'ijŻŁŻã': 'ăıż', 'ð': array([['', ''],
             ['', '\x9d']], dtype='>U3'), 'ŤŒ': 'WáŶʾ'}},
))
state.assert_invariants()
Draw 4: ['7óŸŻç']
> stacking ['7óŸŻç'] as 1ôŇĆ
state.stack(create_index=False, data=data(...), newname='1ôŇĆ')
state.assert_invariants()
adding dimension coordinate ŸĸÂqſ
state.add_dim_coord(var=Variable(
    data=array([              -5456,               51517, 8787776349668474847,
                         43576], dtype='timedelta64[ns]'),
    dims=['ŸĸÂqſ'],
    attrs={},
))
state.assert_invariants()
adding dimension coordinate ª
state.add_dim_coord(var=Variable(
    data=array([     18392, 4260466259,      22621, 3303341823], dtype=uint32),
    dims=['ª'],
    attrs={'íŻÚŸœ': 'ÂĪßĵſ', 'ćŻė': None, 'ÚrÄſņ': array([[65523, 20189],
            [54688,  4286]], dtype=uint16)},
))
state.assert_invariants()
adding dimension coordinate ķŘÀōú
state.add_dim_coord(var=Variable(
    data=array(['', '\x9a\x84>\U000781caO'], dtype='<U14'),
    dims=['ķŘÀōú'],
    attrs={'ÕŕŸz2': {'2ĐſRª': 'żſężĤ', 'ČſŰÑÉ': None, 'ŇJiõŞ': 'ŷ', '': 'ż'}},
))
state.assert_invariants()
assign_coords: žſa
state.assign_coords(var=Variable(
    data=array(['', 'Éi\x8ajz\U000d8bfaÀ', ',1J^À\U0003b229\U001094c0\uddd7',
           'N\U0010e27eX\x13\x03ìf0', 'í'], dtype='<U8'),
    dims=['žſa'],
    attrs={},
))
state.assert_invariants()
Draw 5: ['ķŘÀōú']
> drop_indexes: ['ķŘÀōú']
state.drop_indexes(data=data(...))
state.assert_invariants()
adding dimension coordinate Îr
state.add_dim_coord(var=Variable(
    data=array(['\U0006a7dc¸!', '\U001028a8&5ç'], dtype='<U15'),
    dims=['Îr'],
    attrs={'ÿŝfźö': {'ŽġžžŨ': 'O', 'SŢijìō': None}},
))
state.assert_invariants()
adding dimension coordinate ŽŃêńŢ
state.add_dim_coord(var=Variable(
    data=array([18446744073709551614,                54242,                59560],
          dtype=uint64),
    dims=['ŽŃêńŢ'],
    attrs={},
))
state.assert_invariants()
assign_coords: Q
state.assign_coords(var=Variable(
    data=array(['2253-06-01T23:30:19.684719259', '1970-01-01T00:00:00.000000245',
           '1969-12-31T23:59:59.999983953', '1970-01-01T00:00:00.000053418',
           '1970-01-01T00:00:00.000000229', '1970-01-01T00:00:00.000062968'],
          dtype='datetime64[ns]'),
    dims=['Q'],
    attrs={'gTſ': {'oVUļg': False, '': '', 'íÌŤZ': None},
     'ŽſŻŲŻ': {},
     'ĸĩL': {}},
))
state.assert_invariants()
adding dimension coordinate Ūʼn
state.add_dim_coord(var=Variable(data=array([-51867485], dtype=int32), dims=['Ūʼn'], attrs={}))
state.assert_invariants()
Draw 6: ['Ūʼn']
> stacking ['Ūʼn'] as ňŔvjſ
state.stack(create_index=True, data=data(...), newname='ňŔvjſ')
state.assert_invariants()
Draw 7: ['ŽŃêńŢ', 'žſa', 'Q']
> stacking ['ŽŃêńŢ', 'žſa', 'Q'] as cê
state.stack(create_index=True, data=data(...), newname='cê')
state.assert_invariants()
Draw 8: 'cê'
> unstacking cê
state.unstack(data=data(...))
state.assert_invariants()
state.teardown()

You can reproduce this example by temporarily adding @reproduce_failure('6.115.0', b'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') as a decorator on your test case