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113 lines
3.2 KiB
113 lines
3.2 KiB
import numpy as np
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import pytest
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from pandas.compat import (
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is_ci_environment,
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is_platform_windows,
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)
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import pandas as pd
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import pandas._testing as tm
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from pandas.api.types import is_bool_dtype
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from pandas.tests.extension import base
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pytest.importorskip("pyarrow", minversion="1.0.1")
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from pandas.tests.extension.arrow.arrays import ( # isort:skip
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ArrowBoolArray,
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ArrowBoolDtype,
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)
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@pytest.fixture
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def dtype():
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return ArrowBoolDtype()
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@pytest.fixture
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def data():
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values = np.random.randint(0, 2, size=100, dtype=bool)
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values[1] = ~values[0]
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return ArrowBoolArray.from_scalars(values)
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@pytest.fixture
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def data_missing():
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return ArrowBoolArray.from_scalars([None, True])
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def test_basic_equals(data):
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# https://github.com/pandas-dev/pandas/issues/34660
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assert pd.Series(data).equals(pd.Series(data))
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class BaseArrowTests:
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pass
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class TestDtype(BaseArrowTests, base.BaseDtypeTests):
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pass
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class TestInterface(BaseArrowTests, base.BaseInterfaceTests):
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def test_copy(self, data):
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# __setitem__ does not work, so we only have a smoke-test
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data.copy()
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def test_view(self, data):
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# __setitem__ does not work, so we only have a smoke-test
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data.view()
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@pytest.mark.xfail(
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raises=AssertionError,
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reason="Doesn't recognize data._na_value as NA",
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)
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def test_contains(self, data, data_missing):
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super().test_contains(data, data_missing)
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class TestConstructors(BaseArrowTests, base.BaseConstructorsTests):
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# seems like some bug in isna on empty BoolArray returning floats.
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@pytest.mark.xfail(reason="bad is-na for empty data")
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def test_from_sequence_from_cls(self, data):
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super().test_from_sequence_from_cls(data)
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@pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
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def test_series_constructor_no_data_with_index(self, dtype, na_value):
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# pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
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super().test_series_constructor_no_data_with_index(dtype, na_value)
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@pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
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def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
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# pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
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super().test_series_constructor_scalar_na_with_index(dtype, na_value)
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@pytest.mark.xfail(reason="ufunc 'invert' not supported for the input types")
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def test_construct_empty_dataframe(self, dtype):
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super().test_construct_empty_dataframe(dtype)
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@pytest.mark.xfail(reason="_from_sequence ignores dtype keyword")
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def test_empty(self, dtype):
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super().test_empty(dtype)
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class TestReduce(base.BaseNoReduceTests):
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def test_reduce_series_boolean(self):
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pass
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@pytest.mark.skipif(
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is_ci_environment() and is_platform_windows(),
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reason="Causes stack overflow on Windows CI",
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)
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class TestReduceBoolean(base.BaseBooleanReduceTests):
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pass
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def test_is_bool_dtype(data):
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assert is_bool_dtype(data)
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assert pd.core.common.is_bool_indexer(data)
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s = pd.Series(range(len(data)))
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result = s[data]
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expected = s[np.asarray(data)]
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tm.assert_series_equal(result, expected)
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