120 lines
3.4 KiB
Python
120 lines
3.4 KiB
Python
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"""
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This file contains a minimal set of tests for compliance with the extension
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array interface test suite, and should contain no other tests.
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The test suite for the full functionality of the array is located in
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`pandas/tests/arrays/`.
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The tests in this file are inherited from the BaseExtensionTests, and only
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minimal tweaks should be applied to get the tests passing (by overwriting a
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parent method).
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Additional tests should either be added to one of the BaseExtensionTests
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classes (if they are relevant for the extension interface for all dtypes), or
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be added to the array-specific tests in `pandas/tests/arrays/`.
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"""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import numpy as np
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import pytest
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from pandas._libs import (
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Period,
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iNaT,
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)
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from pandas.compat import is_platform_windows
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from pandas.compat.numpy import np_version_gte1p24
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from pandas.core.dtypes.dtypes import PeriodDtype
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import pandas._testing as tm
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from pandas.core.arrays import PeriodArray
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from pandas.tests.extension import base
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if TYPE_CHECKING:
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import pandas as pd
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@pytest.fixture(params=["D", "2D"])
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def dtype(request):
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return PeriodDtype(freq=request.param)
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@pytest.fixture
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def data(dtype):
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return PeriodArray(np.arange(1970, 2070), dtype=dtype)
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@pytest.fixture
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def data_for_sorting(dtype):
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return PeriodArray([2018, 2019, 2017], dtype=dtype)
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@pytest.fixture
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def data_missing(dtype):
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return PeriodArray([iNaT, 2017], dtype=dtype)
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@pytest.fixture
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def data_missing_for_sorting(dtype):
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return PeriodArray([2018, iNaT, 2017], dtype=dtype)
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@pytest.fixture
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def data_for_grouping(dtype):
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B = 2018
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NA = iNaT
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A = 2017
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C = 2019
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return PeriodArray([B, B, NA, NA, A, A, B, C], dtype=dtype)
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class TestPeriodArray(base.ExtensionTests):
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def _get_expected_exception(self, op_name, obj, other):
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if op_name in ("__sub__", "__rsub__"):
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return None
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return super()._get_expected_exception(op_name, obj, other)
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def _supports_accumulation(self, ser, op_name: str) -> bool:
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return op_name in ["cummin", "cummax"]
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def _supports_reduction(self, obj, op_name: str) -> bool:
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return op_name in ["min", "max", "median"]
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def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):
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if op_name == "median":
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res_op = getattr(ser, op_name)
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alt = ser.astype("int64")
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exp_op = getattr(alt, op_name)
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result = res_op(skipna=skipna)
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expected = exp_op(skipna=skipna)
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# error: Item "dtype[Any]" of "dtype[Any] | ExtensionDtype" has no
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# attribute "freq"
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freq = ser.dtype.freq # type: ignore[union-attr]
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expected = Period._from_ordinal(int(expected), freq=freq)
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tm.assert_almost_equal(result, expected)
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else:
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return super().check_reduce(ser, op_name, skipna)
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@pytest.mark.parametrize("periods", [1, -2])
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def test_diff(self, data, periods):
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if is_platform_windows() and np_version_gte1p24:
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with tm.assert_produces_warning(RuntimeWarning, check_stacklevel=False):
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super().test_diff(data, periods)
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else:
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super().test_diff(data, periods)
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@pytest.mark.parametrize("na_action", [None, "ignore"])
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def test_map(self, data, na_action):
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result = data.map(lambda x: x, na_action=na_action)
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tm.assert_extension_array_equal(result, data)
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class Test2DCompat(base.NDArrayBacked2DTests):
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pass
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