""" 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/`. """ import numpy as np import pytest from pandas.core.dtypes.common import is_extension_array_dtype import pandas as pd import pandas._testing as tm from pandas.api.types import is_float_dtype from pandas.core.arrays.floating import ( Float32Dtype, Float64Dtype, ) from pandas.tests.extension import base def make_data(): return ( list(np.arange(0.1, 0.9, 0.1)) + [pd.NA] + list(np.arange(1, 9.8, 0.1)) + [pd.NA] + [9.9, 10.0] ) @pytest.fixture(params=[Float32Dtype, Float64Dtype]) def dtype(request): return request.param() @pytest.fixture def data(dtype): return pd.array(make_data(), dtype=dtype) @pytest.fixture def data_for_twos(dtype): return pd.array(np.ones(100) * 2, dtype=dtype) @pytest.fixture def data_missing(dtype): return pd.array([pd.NA, 0.1], dtype=dtype) @pytest.fixture def data_for_sorting(dtype): return pd.array([0.1, 0.2, 0.0], dtype=dtype) @pytest.fixture def data_missing_for_sorting(dtype): return pd.array([0.1, pd.NA, 0.0], dtype=dtype) @pytest.fixture def na_cmp(): # we are pd.NA return lambda x, y: x is pd.NA and y is pd.NA @pytest.fixture def na_value(): return pd.NA @pytest.fixture def data_for_grouping(dtype): b = 0.1 a = 0.0 c = 0.2 na = pd.NA return pd.array([b, b, na, na, a, a, b, c], dtype=dtype) class TestDtype(base.BaseDtypeTests): pass class TestArithmeticOps(base.BaseArithmeticOpsTests): def check_opname(self, s, op_name, other, exc=None): # overwriting to indicate ops don't raise an error super().check_opname(s, op_name, other, exc=None) def _check_op(self, s, op, other, op_name, exc=NotImplementedError): if exc is None: sdtype = tm.get_dtype(s) if ( hasattr(other, "dtype") and not is_extension_array_dtype(other.dtype) and is_float_dtype(other.dtype) ): # other is np.float64 and would therefore always result in # upcasting, so keeping other as same numpy_dtype other = other.astype(sdtype.numpy_dtype) result = op(s, other) expected = self._combine(s, other, op) # combine method result in 'biggest' (float64) dtype expected = expected.astype(sdtype) self.assert_equal(result, expected) else: with pytest.raises(exc): op(s, other) def _check_divmod_op(self, s, op, other, exc=None): super()._check_divmod_op(s, op, other, None) class TestComparisonOps(base.BaseComparisonOpsTests): # TODO: share with IntegerArray? def _check_op(self, s, op, other, op_name, exc=NotImplementedError): if exc is None: result = op(s, other) # Override to do the astype to boolean expected = s.combine(other, op).astype("boolean") self.assert_series_equal(result, expected) else: with pytest.raises(exc): op(s, other) def check_opname(self, s, op_name, other, exc=None): super().check_opname(s, op_name, other, exc=None) def _compare_other(self, s, data, op, other): op_name = f"__{op.__name__}__" self.check_opname(s, op_name, other) class TestInterface(base.BaseInterfaceTests): pass class TestConstructors(base.BaseConstructorsTests): pass class TestReshaping(base.BaseReshapingTests): pass class TestGetitem(base.BaseGetitemTests): pass class TestSetitem(base.BaseSetitemTests): pass class TestIndex(base.BaseIndexTests): pass class TestMissing(base.BaseMissingTests): pass class TestMethods(base.BaseMethodsTests): pass class TestCasting(base.BaseCastingTests): pass class TestGroupby(base.BaseGroupbyTests): pass class TestNumericReduce(base.BaseNumericReduceTests): def check_reduce(self, s, op_name, skipna): # overwrite to ensure pd.NA is tested instead of np.nan # https://github.com/pandas-dev/pandas/issues/30958 result = getattr(s, op_name)(skipna=skipna) if not skipna and s.isna().any(): expected = pd.NA else: expected = getattr(s.dropna().astype(s.dtype.numpy_dtype), op_name)( skipna=skipna ) tm.assert_almost_equal(result, expected) @pytest.mark.skip(reason="Tested in tests/reductions/test_reductions.py") class TestBooleanReduce(base.BaseBooleanReduceTests): pass class TestPrinting(base.BasePrintingTests): pass class TestParsing(base.BaseParsingTests): pass class Test2DCompat(base.Dim2CompatTests): pass