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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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freq = ser.dtype.freq |
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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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