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frispete opened this issue Mar 13, 2020 · 1 comment
Closed

Tests fail on 32bit archs with Python 3.8 and pandas 1.0.2 #32689

frispete opened this issue Mar 13, 2020 · 1 comment

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@frispete
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Apart from Test warnings noted here, we face plain test failures, that prevent packaging pandas for ix86 systems with Python 3.8.2 at least:

[ 1167s] =================================== FAILURES ===================================
[ 1167s] ______________ test_maybe_promote_int_with_int[int8-32768-int32] _______________
[ 1167s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1167s] 
[ 1167s] dtype = dtype('int8'), fill_value = 32768, expected_dtype = dtype('int32')
[ 1167s] 
[ 1167s]     @pytest.mark.parametrize(
[ 1167s]         "dtype, fill_value, expected_dtype",
[ 1167s]         [
[ 1167s]             # size 8
[ 1167s]             ("int8", 1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int8", -1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # keep signed-ness as long as possible
[ 1167s]             ("uint8", 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             # max of uint8 cannot be contained in int8
[ 1167s]             ("uint8", -1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 16
[ 1167s]             ("int16", 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int16", -1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint16", 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint16", -1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 32
[ 1167s]             ("int32", 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int32", -1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint32", 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint32", -1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 64
[ 1167s]             ("int64", 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int64", -1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint64", 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint64", -1, "object"),
[ 1167s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1167s]         ],
[ 1167s]     )
[ 1167s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1167s]         dtype = np.dtype(dtype)
[ 1167s]         expected_dtype = np.dtype(expected_dtype)
[ 1167s]     
[ 1167s]         # output is not a generic int, but corresponds to expected_dtype
[ 1167s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1167s]     
[ 1167s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1167s]     _assert_match(result_fill_value, expected_fill_value)
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] 
[ 1167s] result_fill_value = 32768, expected_fill_value = 32768
[ 1167s] 
[ 1167s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1167s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1167s]         res_type = type(result_fill_value)
[ 1167s]         ex_type = type(expected_fill_value)
[ 1167s]         if res_type.__name__ == "uint64":
[ 1167s]             # No idea why, but these (sometimes) do not compare as equal
[ 1167s]             assert ex_type.__name__ == "uint64"
[ 1167s]         elif res_type.__name__ == "ulonglong":
[ 1167s]             # On some builds we get this instead of np.uint64
[ 1167s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1167s]             assert res_type(0).itemsize == 8
[ 1167s]             assert ex_type == res_type or ex_type == np.uint64
[ 1167s]         else:
[ 1167s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1167s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1167s] E           AssertionError: assert (<class 'numpy.intc'> == <class 'numpy.int32'>
[ 1167s] E             -<class 'numpy.intc'>
[ 1167s] E             +<class 'numpy.int32'> or 'intc' == 'int32'
[ 1167s] E             - intc
[ 1167s] E             + int32)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1167s] _____________ test_maybe_promote_int_with_int[uint8-65536-uint32] ______________
[ 1167s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1167s] 
[ 1167s] dtype = dtype('uint8'), fill_value = 65536, expected_dtype = dtype('uint32')
[ 1167s] 
[ 1167s]     @pytest.mark.parametrize(
[ 1167s]         "dtype, fill_value, expected_dtype",
[ 1167s]         [
[ 1167s]             # size 8
[ 1167s]             ("int8", 1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int8", -1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # keep signed-ness as long as possible
[ 1167s]             ("uint8", 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             # max of uint8 cannot be contained in int8
[ 1167s]             ("uint8", -1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 16
[ 1167s]             ("int16", 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int16", -1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint16", 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint16", -1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 32
[ 1167s]             ("int32", 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int32", -1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint32", 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint32", -1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 64
[ 1167s]             ("int64", 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int64", -1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint64", 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint64", -1, "object"),
[ 1167s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1167s]         ],
[ 1167s]     )
[ 1167s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1167s]         dtype = np.dtype(dtype)
[ 1167s]         expected_dtype = np.dtype(expected_dtype)
[ 1167s]     
[ 1167s]         # output is not a generic int, but corresponds to expected_dtype
[ 1167s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1167s]     
[ 1167s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1167s]     _assert_match(result_fill_value, expected_fill_value)
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] 
[ 1167s] result_fill_value = 65536, expected_fill_value = 65536
[ 1167s] 
[ 1167s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1167s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1167s]         res_type = type(result_fill_value)
[ 1167s]         ex_type = type(expected_fill_value)
[ 1167s]         if res_type.__name__ == "uint64":
[ 1167s]             # No idea why, but these (sometimes) do not compare as equal
[ 1167s]             assert ex_type.__name__ == "uint64"
[ 1167s]         elif res_type.__name__ == "ulonglong":
[ 1167s]             # On some builds we get this instead of np.uint64
[ 1167s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1167s]             assert res_type(0).itemsize == 8
[ 1167s]             assert ex_type == res_type or ex_type == np.uint64
[ 1167s]         else:
[ 1167s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1167s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1167s] E           AssertionError: assert (<class 'numpy.uintc'> == <class 'numpy.uint32'>
[ 1167s] E             -<class 'numpy.uintc'>
[ 1167s] E             +<class 'numpy.uint32'> or 'uintc' == 'uint32'
[ 1167s] E             - uintc
[ 1167s] E             + uint32)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1167s] ___________ test_maybe_promote_int_with_int[uint8-2147483648-uint32] ___________
[ 1167s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1167s] 
[ 1167s] dtype = dtype('uint8'), fill_value = 2147483648
[ 1167s] expected_dtype = dtype('uint32')
[ 1167s] 
[ 1167s]     @pytest.mark.parametrize(
[ 1167s]         "dtype, fill_value, expected_dtype",
[ 1167s]         [
[ 1167s]             # size 8
[ 1167s]             ("int8", 1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int8", -1, "int8"),
[ 1167s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # keep signed-ness as long as possible
[ 1167s]             ("uint8", 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1167s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             # max of uint8 cannot be contained in int8
[ 1167s]             ("uint8", -1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 16
[ 1167s]             ("int16", 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int16", -1, "int16"),
[ 1167s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1167s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint16", 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1167s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint16", -1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 32
[ 1167s]             ("int32", 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int32", -1, "int32"),
[ 1167s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1167s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint32", 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1167s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint32", -1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1167s]             # size 64
[ 1167s]             ("int64", 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1167s]             ("int64", -1, "int64"),
[ 1167s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1167s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1167s]             ("uint64", 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1167s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1167s]             ("uint64", -1, "object"),
[ 1167s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1167s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1167s]         ],
[ 1167s]     )
[ 1167s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1167s]         dtype = np.dtype(dtype)
[ 1167s]         expected_dtype = np.dtype(expected_dtype)
[ 1167s]     
[ 1167s]         # output is not a generic int, but corresponds to expected_dtype
[ 1167s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1167s]     
[ 1167s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1167s]     _assert_match(result_fill_value, expected_fill_value)
[ 1167s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1167s] 
[ 1167s] result_fill_value = 2147483648, expected_fill_value = 2147483648
[ 1167s] 
[ 1167s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1167s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1167s]         res_type = type(result_fill_value)
[ 1167s]         ex_type = type(expected_fill_value)
[ 1167s]         if res_type.__name__ == "uint64":
[ 1167s]             # No idea why, but these (sometimes) do not compare as equal
[ 1167s]             assert ex_type.__name__ == "uint64"
[ 1167s]         elif res_type.__name__ == "ulonglong":
[ 1167s]             # On some builds we get this instead of np.uint64
[ 1167s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1167s]             assert res_type(0).itemsize == 8
[ 1167s]             assert ex_type == res_type or ex_type == np.uint64
[ 1167s]         else:
[ 1167s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1167s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1167s] E           AssertionError: assert (<class 'numpy.uintc'> == <class 'numpy.uint32'>
[ 1167s] E             -<class 'numpy.uintc'>
[ 1167s] E             +<class 'numpy.uint32'> or 'uintc' == 'uint32'
[ 1167s] E             - uintc
[ 1167s] E             + uint32)
[ 1167s] 
[ 1167s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1168s] ______________ test_maybe_promote_int_with_int[int16-32768-int32] ______________
[ 1168s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1168s] 
[ 1168s] dtype = dtype('int16'), fill_value = 32768, expected_dtype = dtype('int32')
[ 1168s] 
[ 1168s]     @pytest.mark.parametrize(
[ 1168s]         "dtype, fill_value, expected_dtype",
[ 1168s]         [
[ 1168s]             # size 8
[ 1168s]             ("int8", 1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int8", -1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # keep signed-ness as long as possible
[ 1168s]             ("uint8", 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             # max of uint8 cannot be contained in int8
[ 1168s]             ("uint8", -1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 16
[ 1168s]             ("int16", 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int16", -1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint16", 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint16", -1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 32
[ 1168s]             ("int32", 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int32", -1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint32", 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint32", -1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 64
[ 1168s]             ("int64", 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int64", -1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint64", 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint64", -1, "object"),
[ 1168s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1168s]         ],
[ 1168s]     )
[ 1168s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1168s]         dtype = np.dtype(dtype)
[ 1168s]         expected_dtype = np.dtype(expected_dtype)
[ 1168s]     
[ 1168s]         # output is not a generic int, but corresponds to expected_dtype
[ 1168s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1168s]     
[ 1168s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1168s]     _assert_match(result_fill_value, expected_fill_value)
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] 
[ 1168s] result_fill_value = 32768, expected_fill_value = 32768
[ 1168s] 
[ 1168s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1168s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1168s]         res_type = type(result_fill_value)
[ 1168s]         ex_type = type(expected_fill_value)
[ 1168s]         if res_type.__name__ == "uint64":
[ 1168s]             # No idea why, but these (sometimes) do not compare as equal
[ 1168s]             assert ex_type.__name__ == "uint64"
[ 1168s]         elif res_type.__name__ == "ulonglong":
[ 1168s]             # On some builds we get this instead of np.uint64
[ 1168s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1168s]             assert res_type(0).itemsize == 8
[ 1168s]             assert ex_type == res_type or ex_type == np.uint64
[ 1168s]         else:
[ 1168s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1168s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1168s] E           AssertionError: assert (<class 'numpy.intc'> == <class 'numpy.int32'>
[ 1168s] E             -<class 'numpy.intc'>
[ 1168s] E             +<class 'numpy.int32'> or 'intc' == 'int32'
[ 1168s] E             - intc
[ 1168s] E             + int32)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1168s] _____________ test_maybe_promote_int_with_int[uint16-65536-uint32] _____________
[ 1168s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1168s] 
[ 1168s] dtype = dtype('uint16'), fill_value = 65536, expected_dtype = dtype('uint32')
[ 1168s] 
[ 1168s]     @pytest.mark.parametrize(
[ 1168s]         "dtype, fill_value, expected_dtype",
[ 1168s]         [
[ 1168s]             # size 8
[ 1168s]             ("int8", 1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int8", -1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # keep signed-ness as long as possible
[ 1168s]             ("uint8", 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             # max of uint8 cannot be contained in int8
[ 1168s]             ("uint8", -1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 16
[ 1168s]             ("int16", 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int16", -1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint16", 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint16", -1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 32
[ 1168s]             ("int32", 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int32", -1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint32", 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint32", -1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 64
[ 1168s]             ("int64", 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int64", -1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint64", 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint64", -1, "object"),
[ 1168s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1168s]         ],
[ 1168s]     )
[ 1168s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1168s]         dtype = np.dtype(dtype)
[ 1168s]         expected_dtype = np.dtype(expected_dtype)
[ 1168s]     
[ 1168s]         # output is not a generic int, but corresponds to expected_dtype
[ 1168s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1168s]     
[ 1168s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1168s]     _assert_match(result_fill_value, expected_fill_value)
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] 
[ 1168s] result_fill_value = 65536, expected_fill_value = 65536
[ 1168s] 
[ 1168s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1168s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1168s]         res_type = type(result_fill_value)
[ 1168s]         ex_type = type(expected_fill_value)
[ 1168s]         if res_type.__name__ == "uint64":
[ 1168s]             # No idea why, but these (sometimes) do not compare as equal
[ 1168s]             assert ex_type.__name__ == "uint64"
[ 1168s]         elif res_type.__name__ == "ulonglong":
[ 1168s]             # On some builds we get this instead of np.uint64
[ 1168s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1168s]             assert res_type(0).itemsize == 8
[ 1168s]             assert ex_type == res_type or ex_type == np.uint64
[ 1168s]         else:
[ 1168s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1168s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1168s] E           AssertionError: assert (<class 'numpy.uintc'> == <class 'numpy.uint32'>
[ 1168s] E             -<class 'numpy.uintc'>
[ 1168s] E             +<class 'numpy.uint32'> or 'uintc' == 'uint32'
[ 1168s] E             - uintc
[ 1168s] E             + uint32)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1168s] __________ test_maybe_promote_int_with_int[uint16-2147483648-uint32] ___________
[ 1168s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1168s] 
[ 1168s] dtype = dtype('uint16'), fill_value = 2147483648
[ 1168s] expected_dtype = dtype('uint32')
[ 1168s] 
[ 1168s]     @pytest.mark.parametrize(
[ 1168s]         "dtype, fill_value, expected_dtype",
[ 1168s]         [
[ 1168s]             # size 8
[ 1168s]             ("int8", 1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int8", -1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # keep signed-ness as long as possible
[ 1168s]             ("uint8", 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             # max of uint8 cannot be contained in int8
[ 1168s]             ("uint8", -1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 16
[ 1168s]             ("int16", 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int16", -1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint16", 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint16", -1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 32
[ 1168s]             ("int32", 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int32", -1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint32", 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint32", -1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 64
[ 1168s]             ("int64", 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int64", -1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint64", 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint64", -1, "object"),
[ 1168s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1168s]         ],
[ 1168s]     )
[ 1168s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1168s]         dtype = np.dtype(dtype)
[ 1168s]         expected_dtype = np.dtype(expected_dtype)
[ 1168s]     
[ 1168s]         # output is not a generic int, but corresponds to expected_dtype
[ 1168s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1168s]     
[ 1168s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1168s]     _assert_match(result_fill_value, expected_fill_value)
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] 
[ 1168s] result_fill_value = 2147483648, expected_fill_value = 2147483648
[ 1168s] 
[ 1168s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1168s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1168s]         res_type = type(result_fill_value)
[ 1168s]         ex_type = type(expected_fill_value)
[ 1168s]         if res_type.__name__ == "uint64":
[ 1168s]             # No idea why, but these (sometimes) do not compare as equal
[ 1168s]             assert ex_type.__name__ == "uint64"
[ 1168s]         elif res_type.__name__ == "ulonglong":
[ 1168s]             # On some builds we get this instead of np.uint64
[ 1168s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1168s]             assert res_type(0).itemsize == 8
[ 1168s]             assert ex_type == res_type or ex_type == np.uint64
[ 1168s]         else:
[ 1168s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1168s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1168s] E           AssertionError: assert (<class 'numpy.uintc'> == <class 'numpy.uint32'>
[ 1168s] E             -<class 'numpy.uintc'>
[ 1168s] E             +<class 'numpy.uint32'> or 'uintc' == 'uint32'
[ 1168s] E             - uintc
[ 1168s] E             + uint32)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1168s] _______________ test_maybe_promote_int_with_int[uint16--1-int32] _______________
[ 1168s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1168s] 
[ 1168s] dtype = dtype('uint16'), fill_value = -1, expected_dtype = dtype('int32')
[ 1168s] 
[ 1168s]     @pytest.mark.parametrize(
[ 1168s]         "dtype, fill_value, expected_dtype",
[ 1168s]         [
[ 1168s]             # size 8
[ 1168s]             ("int8", 1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int8", -1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # keep signed-ness as long as possible
[ 1168s]             ("uint8", 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             # max of uint8 cannot be contained in int8
[ 1168s]             ("uint8", -1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 16
[ 1168s]             ("int16", 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int16", -1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint16", 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint16", -1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 32
[ 1168s]             ("int32", 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int32", -1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint32", 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint32", -1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 64
[ 1168s]             ("int64", 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int64", -1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint64", 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint64", -1, "object"),
[ 1168s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1168s]         ],
[ 1168s]     )
[ 1168s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1168s]         dtype = np.dtype(dtype)
[ 1168s]         expected_dtype = np.dtype(expected_dtype)
[ 1168s]     
[ 1168s]         # output is not a generic int, but corresponds to expected_dtype
[ 1168s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1168s]     
[ 1168s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1168s]     _assert_match(result_fill_value, expected_fill_value)
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] 
[ 1168s] result_fill_value = -1, expected_fill_value = -1
[ 1168s] 
[ 1168s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1168s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1168s]         res_type = type(result_fill_value)
[ 1168s]         ex_type = type(expected_fill_value)
[ 1168s]         if res_type.__name__ == "uint64":
[ 1168s]             # No idea why, but these (sometimes) do not compare as equal
[ 1168s]             assert ex_type.__name__ == "uint64"
[ 1168s]         elif res_type.__name__ == "ulonglong":
[ 1168s]             # On some builds we get this instead of np.uint64
[ 1168s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1168s]             assert res_type(0).itemsize == 8
[ 1168s]             assert ex_type == res_type or ex_type == np.uint64
[ 1168s]         else:
[ 1168s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1168s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1168s] E           AssertionError: assert (<class 'numpy.intc'> == <class 'numpy.int32'>
[ 1168s] E             -<class 'numpy.intc'>
[ 1168s] E             +<class 'numpy.int32'> or 'intc' == 'int32'
[ 1168s] E             - intc
[ 1168s] E             + int32)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:111: AssertionError
[ 1168s] ______________ test_maybe_promote_int_with_int[uint16--129-int32] ______________
[ 1168s] [gw7] linux -- Python 3.8.2 /usr/bin/python3
[ 1168s] 
[ 1168s] dtype = dtype('uint16'), fill_value = -129, expected_dtype = dtype('int32')
[ 1168s] 
[ 1168s]     @pytest.mark.parametrize(
[ 1168s]         "dtype, fill_value, expected_dtype",
[ 1168s]         [
[ 1168s]             # size 8
[ 1168s]             ("int8", 1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int8", -1, "int8"),
[ 1168s]             ("int8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # keep signed-ness as long as possible
[ 1168s]             ("uint8", 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("int8").max + 1, "uint8"),
[ 1168s]             ("uint8", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint8", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint8", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint8", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             # max of uint8 cannot be contained in int8
[ 1168s]             ("uint8", -1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("uint8", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint8", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint8", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 16
[ 1168s]             ("int16", 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").max + 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int16", -1, "int16"),
[ 1168s]             ("int16", np.iinfo("int8").min - 1, "int16"),
[ 1168s]             ("int16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint16", 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint8").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("int16").max + 1, "uint16"),
[ 1168s]             ("uint16", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint16", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint16", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint16", -1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("uint16", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint16", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 32
[ 1168s]             ("int32", 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").max + 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int32", -1, "int32"),
[ 1168s]             ("int32", np.iinfo("int8").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int16").min - 1, "int32"),
[ 1168s]             ("int32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint32", 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint8").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint16").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("int32").max + 1, "uint32"),
[ 1168s]             ("uint32", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint32", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint32", -1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("uint32", np.iinfo("int64").min - 1, "object"),
[ 1168s]             # size 64
[ 1168s]             ("int64", 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").max + 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").max + 1, "object"),
[ 1168s]             ("int64", -1, "int64"),
[ 1168s]             ("int64", np.iinfo("int8").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int16").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int32").min - 1, "int64"),
[ 1168s]             ("int64", np.iinfo("int64").min - 1, "object"),
[ 1168s]             ("uint64", 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint8").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint16").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint32").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("int64").max + 1, "uint64"),
[ 1168s]             ("uint64", np.iinfo("uint64").max + 1, "object"),
[ 1168s]             ("uint64", -1, "object"),
[ 1168s]             ("uint64", np.iinfo("int8").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int16").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int32").min - 1, "object"),
[ 1168s]             ("uint64", np.iinfo("int64").min - 1, "object"),
[ 1168s]         ],
[ 1168s]     )
[ 1168s]     def test_maybe_promote_int_with_int(dtype, fill_value, expected_dtype):
[ 1168s]         dtype = np.dtype(dtype)
[ 1168s]         expected_dtype = np.dtype(expected_dtype)
[ 1168s]     
[ 1168s]         # output is not a generic int, but corresponds to expected_dtype
[ 1168s]         exp_val_for_scalar = np.array([fill_value], dtype=expected_dtype)[0]
[ 1168s]     
[ 1168s] >       _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
[ 1168s] 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:237: 
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] ../../BUILDROOT/python-pandas-1.0.2-37.1.i386/usr/lib/python3.8/site-packages/pandas/tests/dtypes/cast/test_promote.py:94: in _check_promote
[ 1168s]     _assert_match(result_fill_value, expected_fill_value)
[ 1168s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[ 1168s] 
[ 1168s] result_fill_value = -129, expected_fill_value = -129
[ 1168s] 
[ 1168s]     def _assert_match(result_fill_value, expected_fill_value):
[ 1168s]         # GH#23982/25425 require the same type in addition to equality/NA-ness
[ 1168s]         res_type = type(result_fill_value)
[ 1168s]         ex_type = type(expected_fill_value)
[ 1168s]         if res_type.__name__ == "uint64":
[ 1168s]             # No idea why, but these (sometimes) do not compare as equal
[ 1168s]             assert ex_type.__name__ == "uint64"
[ 1168s]         elif res_type.__name__ == "ulonglong":
[ 1168s]             # On some builds we get this instead of np.uint64
[ 1168s]             # Note: cant check res_type.dtype.itemsize directly on numpy 1.18
[ 1168s]             assert res_type(0).itemsize == 8
[ 1168s]             assert ex_type == res_type or ex_type == np.uint64
[ 1168s]         else:
[ 1168s]             # On some builds, type comparison fails, e.g. np.int32 != np.int32
[ 1168s] >           assert res_type == ex_type or res_type.__name__ == ex_type.__name__
[ 1168s] E           AssertionError: assert (<class 'numpy.intc'> == <class 'numpy.int32'>
[ 1168s] E             -<class 'numpy.intc'>
[ 1168s] E             +<class 'numpy.int32'> or 'intc' == 'int32'
[ 1168s] E             - intc
[ 1168s] E             + int32)

You can find the full build log here
@TomAugspurger
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Duplicate of #31856 I think. If you're able to provide any guidance there we'd appreciate it. None of the devs is on a 32-bit machine.

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@frispete @TomAugspurger