189 lines
4.9 KiB
Python
189 lines
4.9 KiB
Python
"""
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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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import numpy as np
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import pytest
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from pandas.core.dtypes.dtypes import IntervalDtype
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from pandas import (
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Interval,
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Series,
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)
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from pandas.core.arrays import IntervalArray
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from pandas.tests.extension import base
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def make_data():
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N = 100
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left_array = np.random.uniform(size=N).cumsum()
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right_array = left_array + np.random.uniform(size=N)
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return [Interval(left, right) for left, right in zip(left_array, right_array)]
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@pytest.fixture
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def dtype():
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return IntervalDtype()
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@pytest.fixture
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def data():
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"""Length-100 PeriodArray for semantics test."""
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return IntervalArray(make_data())
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@pytest.fixture
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def data_missing():
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"""Length 2 array with [NA, Valid]"""
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return IntervalArray.from_tuples([None, (0, 1)])
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@pytest.fixture
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def data_for_sorting():
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return IntervalArray.from_tuples([(1, 2), (2, 3), (0, 1)])
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@pytest.fixture
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def data_missing_for_sorting():
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return IntervalArray.from_tuples([(1, 2), None, (0, 1)])
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@pytest.fixture
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def na_value():
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return np.nan
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@pytest.fixture
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def data_for_grouping():
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a = (0, 1)
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b = (1, 2)
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c = (2, 3)
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return IntervalArray.from_tuples([b, b, None, None, a, a, b, c])
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class BaseInterval:
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pass
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class TestDtype(BaseInterval, base.BaseDtypeTests):
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pass
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class TestCasting(BaseInterval, base.BaseCastingTests):
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pass
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class TestConstructors(BaseInterval, base.BaseConstructorsTests):
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pass
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class TestGetitem(BaseInterval, base.BaseGetitemTests):
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pass
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class TestIndex(base.BaseIndexTests):
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pass
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class TestGrouping(BaseInterval, base.BaseGroupbyTests):
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pass
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class TestInterface(BaseInterval, base.BaseInterfaceTests):
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pass
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class TestReduce(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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ser = Series(data)
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if op_name in ["min", "max"]:
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# IntervalArray *does* implement these
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assert getattr(ser, op_name)(skipna=skipna) in data
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assert getattr(data, op_name)(skipna=skipna) in data
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return
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super().test_reduce_series_numeric(data, all_numeric_reductions, skipna)
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class TestMethods(BaseInterval, base.BaseMethodsTests):
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@pytest.mark.xfail(reason="addition is not defined for intervals")
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def test_combine_add(self, data_repeated):
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super().test_combine_add(data_repeated)
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@pytest.mark.xfail(
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reason="Raises with incorrect message bc it disallows *all* listlikes "
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"instead of just wrong-length listlikes"
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)
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def test_fillna_length_mismatch(self, data_missing):
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super().test_fillna_length_mismatch(data_missing)
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class TestMissing(BaseInterval, base.BaseMissingTests):
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# Index.fillna only accepts scalar `value`, so we have to xfail all
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# non-scalar fill tests.
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unsupported_fill = pytest.mark.xfail(
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reason="Unsupported fillna option for Interval."
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)
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@unsupported_fill
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def test_fillna_limit_pad(self):
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super().test_fillna_limit_pad()
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@unsupported_fill
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def test_fillna_series_method(self):
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super().test_fillna_series_method()
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@unsupported_fill
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def test_fillna_limit_backfill(self):
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super().test_fillna_limit_backfill()
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@unsupported_fill
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def test_fillna_no_op_returns_copy(self):
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super().test_fillna_no_op_returns_copy()
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@unsupported_fill
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def test_fillna_series(self):
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super().test_fillna_series()
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def test_fillna_non_scalar_raises(self, data_missing):
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msg = "can only insert Interval objects and NA into an IntervalArray"
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with pytest.raises(TypeError, match=msg):
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data_missing.fillna([1, 1])
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class TestReshaping(BaseInterval, base.BaseReshapingTests):
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pass
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class TestSetitem(BaseInterval, base.BaseSetitemTests):
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pass
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class TestPrinting(BaseInterval, base.BasePrintingTests):
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@pytest.mark.xfail(reason="Interval has custom repr")
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def test_array_repr(self, data, size):
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super().test_array_repr()
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class TestParsing(BaseInterval, base.BaseParsingTests):
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@pytest.mark.parametrize("engine", ["c", "python"])
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def test_EA_types(self, engine, data):
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expected_msg = r".*must implement _from_sequence_of_strings.*"
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with pytest.raises(NotImplementedError, match=expected_msg):
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super().test_EA_types(engine, data)
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