def validator_with_titanic_1911_asset(
titanic_pandas_multibatch_data_context_v3):
class ExpectNothing(Expectation):
success_keys = ("expectation_argument", )
def _validate(
self,
configuration: ExpectationConfiguration,
metrics: Dict,
runtime_configuration: dict = None,
execution_engine: ExecutionEngine = None,
):
expectation_argument = configuration.kwargs.get(
"expectation_argument")
return {
"success": True,
"result": {
"details": {
"expectation_argument": expectation_argument
}
},
}
register_expectation(ExpectNothing)
titanic_pandas_multibatch_data_context_v3.create_expectation_suite(
expectation_suite_name="titanic_1911_suite")
batch_request = BatchRequest(
datasource_name="titanic_multi_batch",
data_connector_name="my_data_connector",
data_asset_name="Titanic_1911",
)
return titanic_pandas_multibatch_data_context_v3.get_validator(
batch_request=batch_request,
expectation_suite_name="titanic_1911_suite")
def __new__(cls, clsname, bases, attrs):
newclass = super().__new__(cls, clsname, bases, attrs)
if not isabstract(newclass):
newclass.expectation_type = camel_to_snake(clsname)
register_expectation(newclass)
newclass._register_renderer_functions()
default_kwarg_values = dict()
for base in reversed(bases):
default_kwargs = getattr(base, "default_kwarg_values", dict())
default_kwarg_values = nested_update(default_kwarg_values, default_kwargs)
newclass.default_kwarg_values = nested_update(
default_kwarg_values, attrs.get("default_kwarg_values", dict())
)
return newclass