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How to use test_check_not_equivalent method in pandera

Best Python code snippet using pandera_python

test_dtypes.py

...251    """Test that a pandas-compatible dtype can be validated by check()."""252    actual_dtype = pandas_engine.Engine.dtype(pd_dtype)253    expected_dtype = pandas_engine.Engine.dtype(dtype)254    assert actual_dtype.check(expected_dtype)255def test_check_not_equivalent(dtype: Any):256    """Test that check() rejects non-equivalent dtypes."""257    if str(pandas_engine.Engine.dtype(dtype)) == "object":258        actual_dtype = pandas_engine.Engine.dtype(int)259    else:260        actual_dtype = pandas_engine.Engine.dtype(object)261    expected_dtype = pandas_engine.Engine.dtype(dtype)262    assert actual_dtype.check(expected_dtype) is False263def test_coerce_no_cast(dtype: Any, pd_dtype: Any, data: List[Any]):264    """Test that dtypes can be coerced without casting."""265    expected_dtype = pandas_engine.Engine.dtype(dtype)266    series = pd.Series(data, dtype=pd_dtype)267    coerced_series = expected_dtype.coerce(series)268    assert series.equals(coerced_series)269    assert expected_dtype.check(...

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