craftbeerpi4-pione/venv/lib/python3.8/site-packages/pandas/tests/extension/test_string.py

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import string
import numpy as np
import pytest
import pandas.util._test_decorators as td
import pandas as pd
from pandas.core.arrays.string_ import StringDtype
from pandas.core.arrays.string_arrow import ArrowStringDtype
from pandas.tests.extension import base
@pytest.fixture(
params=[
StringDtype,
pytest.param(
ArrowStringDtype, marks=td.skip_if_no("pyarrow", min_version="1.0.0")
),
]
)
def dtype(request):
return request.param()
@pytest.fixture
def data(dtype):
strings = np.random.choice(list(string.ascii_letters), size=100)
while strings[0] == strings[1]:
strings = np.random.choice(list(string.ascii_letters), size=100)
return dtype.construct_array_type()._from_sequence(strings)
@pytest.fixture
def data_missing(dtype):
"""Length 2 array with [NA, Valid]"""
return dtype.construct_array_type()._from_sequence([pd.NA, "A"])
@pytest.fixture
def data_for_sorting(dtype):
return dtype.construct_array_type()._from_sequence(["B", "C", "A"])
@pytest.fixture
def data_missing_for_sorting(dtype):
return dtype.construct_array_type()._from_sequence(["B", pd.NA, "A"])
@pytest.fixture
def na_value():
return pd.NA
@pytest.fixture
def data_for_grouping(dtype):
return dtype.construct_array_type()._from_sequence(
["B", "B", pd.NA, pd.NA, "A", "A", "B", "C"]
)
class TestDtype(base.BaseDtypeTests):
pass
class TestInterface(base.BaseInterfaceTests):
def test_view(self, data, request):
if isinstance(data.dtype, ArrowStringDtype):
mark = pytest.mark.xfail(reason="not implemented")
request.node.add_marker(mark)
super().test_view(data)
class TestConstructors(base.BaseConstructorsTests):
pass
class TestReshaping(base.BaseReshapingTests):
def test_transpose(self, data, dtype, request):
if isinstance(dtype, ArrowStringDtype):
mark = pytest.mark.xfail(reason="not implemented")
request.node.add_marker(mark)
super().test_transpose(data)
class TestGetitem(base.BaseGetitemTests):
pass
class TestSetitem(base.BaseSetitemTests):
def test_setitem_preserves_views(self, data, dtype, request):
if isinstance(dtype, ArrowStringDtype):
mark = pytest.mark.xfail(reason="not implemented")
request.node.add_marker(mark)
super().test_setitem_preserves_views(data)
class TestMissing(base.BaseMissingTests):
pass
class TestNoReduce(base.BaseNoReduceTests):
@pytest.mark.parametrize("skipna", [True, False])
def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):
op_name = all_numeric_reductions
if op_name in ["min", "max"]:
return None
s = pd.Series(data)
with pytest.raises(TypeError):
getattr(s, op_name)(skipna=skipna)
class TestMethods(base.BaseMethodsTests):
@pytest.mark.skip(reason="returns nullable")
def test_value_counts(self, all_data, dropna):
return super().test_value_counts(all_data, dropna)
@pytest.mark.skip(reason="returns nullable")
def test_value_counts_with_normalize(self, data):
pass
class TestCasting(base.BaseCastingTests):
pass
class TestComparisonOps(base.BaseComparisonOpsTests):
def _compare_other(self, s, data, op_name, other):
result = getattr(s, op_name)(other)
expected = getattr(s.astype(object), op_name)(other).astype("boolean")
self.assert_series_equal(result, expected)
def test_compare_scalar(self, data, all_compare_operators):
op_name = all_compare_operators
s = pd.Series(data)
self._compare_other(s, data, op_name, "abc")
class TestParsing(base.BaseParsingTests):
pass
class TestPrinting(base.BasePrintingTests):
pass
class TestGroupBy(base.BaseGroupbyTests):
pass