user_logging_tests.py 文件源码

def test_bad_val_in_column_descriptions():
    np.random.seed(0)

    df_titanic_train, df_titanic_test = utils.get_titanic_binary_classification_dataset()

    column_descriptions = {
        'survived': 'output'
        , 'embarked': 'categorical'
        , 'pclass': 'categorical'
        , 'fare': 'this_is_a_bad_value'
    }

    with warnings.catch_warnings(record=True) as w:

        ml_predictor = Predictor(type_of_estimator='classifier', column_descriptions=column_descriptions)
        print('we should be throwing a warning for the user to give them useful feedback')
        assert len(w) == 1