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