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())