def test_validator_default_expectation_args__pandas(basic_datasource): df = pd.DataFrame({"a": [1, 5, 22, 3, 5, 10], "b": [1, 2, 3, 4, 5, None]}) batch = basic_datasource.get_single_batch_from_batch_request( BatchRequest( **{ "datasource_name": "my_datasource", "data_connector_name": "test_runtime_data_connector", "data_asset_name": "IN_MEMORY_DATA_ASSET", "batch_data": df, "partition_request": PartitionRequest( **{ "batch_identifiers": { "pipeline_stage_name": 0, "airflow_run_id": 0, "custom_key_0": 0, } }), })) my_validator = Validator(execution_engine=PandasExecutionEngine(), batches=[batch]) print(my_validator.get_default_expectation_arguments())
def test_validator_default_expectation_args__pandas(basic_datasource): df = pd.DataFrame({"a": [1, 5, 22, 3, 5, 10], "b": [1, 2, 3, 4, 5, None]}) expectationConfiguration = ExpectationConfiguration( expectation_type="expect_column_value_z_scores_to_be_less_than", kwargs={ "column": "b", "mostly": 0.9, "threshold": 4, "double_sided": True, }, ) batch = basic_datasource.get_single_batch_from_batch_request( BatchRequest( **{ "datasource_name": "my_datasource", "data_connector_name": "test_runtime_data_connector", "batch_data": df, "partition_request": PartitionRequest( **{ "partition_identifiers": { "pipeline_stage_name": 0, "run_id": 0, "custom_key_0": 0, } } ), } ) ) my_validator = Validator(execution_engine=PandasExecutionEngine(), batches=[batch]) print(my_validator.get_default_expectation_arguments())