mirror of
https://github.com/PiBrewing/craftbeerpi4.git
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152 lines
3.8 KiB
Python
152 lines
3.8 KiB
Python
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import string
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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import pandas as pd
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from pandas.core.arrays.string_ import StringDtype
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from pandas.core.arrays.string_arrow import ArrowStringDtype
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from pandas.tests.extension import base
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@pytest.fixture(
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params=[
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StringDtype,
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pytest.param(
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ArrowStringDtype, marks=td.skip_if_no("pyarrow", min_version="1.0.0")
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),
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]
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)
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def dtype(request):
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return request.param()
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@pytest.fixture
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def data(dtype):
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strings = np.random.choice(list(string.ascii_letters), size=100)
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while strings[0] == strings[1]:
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strings = np.random.choice(list(string.ascii_letters), size=100)
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return dtype.construct_array_type()._from_sequence(strings)
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@pytest.fixture
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def data_missing(dtype):
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"""Length 2 array with [NA, Valid]"""
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return dtype.construct_array_type()._from_sequence([pd.NA, "A"])
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@pytest.fixture
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def data_for_sorting(dtype):
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return dtype.construct_array_type()._from_sequence(["B", "C", "A"])
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@pytest.fixture
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def data_missing_for_sorting(dtype):
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return dtype.construct_array_type()._from_sequence(["B", pd.NA, "A"])
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@pytest.fixture
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def na_value():
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return pd.NA
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@pytest.fixture
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def data_for_grouping(dtype):
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return dtype.construct_array_type()._from_sequence(
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["B", "B", pd.NA, pd.NA, "A", "A", "B", "C"]
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)
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class TestDtype(base.BaseDtypeTests):
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pass
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class TestInterface(base.BaseInterfaceTests):
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def test_view(self, data, request):
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if isinstance(data.dtype, ArrowStringDtype):
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mark = pytest.mark.xfail(reason="not implemented")
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request.node.add_marker(mark)
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super().test_view(data)
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class TestConstructors(base.BaseConstructorsTests):
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pass
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class TestReshaping(base.BaseReshapingTests):
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def test_transpose(self, data, dtype, request):
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if isinstance(dtype, ArrowStringDtype):
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mark = pytest.mark.xfail(reason="not implemented")
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request.node.add_marker(mark)
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super().test_transpose(data)
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class TestGetitem(base.BaseGetitemTests):
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pass
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class TestSetitem(base.BaseSetitemTests):
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def test_setitem_preserves_views(self, data, dtype, request):
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if isinstance(dtype, ArrowStringDtype):
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mark = pytest.mark.xfail(reason="not implemented")
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request.node.add_marker(mark)
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super().test_setitem_preserves_views(data)
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class TestMissing(base.BaseMissingTests):
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pass
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class TestNoReduce(base.BaseNoReduceTests):
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@pytest.mark.parametrize("skipna", [True, False])
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def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):
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op_name = all_numeric_reductions
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if op_name in ["min", "max"]:
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return None
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s = pd.Series(data)
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with pytest.raises(TypeError):
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getattr(s, op_name)(skipna=skipna)
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class TestMethods(base.BaseMethodsTests):
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@pytest.mark.skip(reason="returns nullable")
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def test_value_counts(self, all_data, dropna):
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return super().test_value_counts(all_data, dropna)
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@pytest.mark.skip(reason="returns nullable")
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def test_value_counts_with_normalize(self, data):
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pass
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class TestCasting(base.BaseCastingTests):
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pass
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class TestComparisonOps(base.BaseComparisonOpsTests):
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def _compare_other(self, s, data, op_name, other):
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result = getattr(s, op_name)(other)
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expected = getattr(s.astype(object), op_name)(other).astype("boolean")
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self.assert_series_equal(result, expected)
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def test_compare_scalar(self, data, all_compare_operators):
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op_name = all_compare_operators
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s = pd.Series(data)
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self._compare_other(s, data, op_name, "abc")
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class TestParsing(base.BaseParsingTests):
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pass
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class TestPrinting(base.BasePrintingTests):
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pass
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class TestGroupBy(base.BaseGroupbyTests):
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pass
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