def test_dict_to_spark_row_field_validation_ndarrays():
    """Test various validations done on data types when converting a dictionary to a spark row"""
    TestSchema = Unischema('TestSchema', [
        UnischemaField('tensor3d', np.float32, (10, 20, 30), NdarrayCodec(), False),
    ])

    assert isinstance(dict_to_spark_row(TestSchema, {'tensor3d': np.zeros((10, 20, 30), dtype=np.float32)}), Row)

    # Null value into not nullable field
    with pytest.raises(ValueError):
        isinstance(dict_to_spark_row(TestSchema, {'string_field': None}), Row)

    # Wrong dimensions
    with pytest.raises(ValueError):
        isinstance(dict_to_spark_row(TestSchema, {'string_field': np.zeros((1, 2, 3), dtype=np.float32)}), Row)
Test various validations done on data types when converting a dictionary to a spark row
petastorm/tests/test_unischema.py