我的数据源配置如下所示:
datasource_config = {
"name": "example_datasource",
"class_name": "Datasource",
"module_name": "great_expectations.datasource",
"execution_engine": {
"module_name": "great_expectations.execution_engine",
"class_name": "PandasExecutionEngine",
},
"data_connectors": {
"default_runtime_data_connector_name": {
"class_name": "RuntimeDataConnector",
"module_name": "great_expectations.datasource.data_connector",
"batch_identifiers": ["default_identifier_name"],
},
},
}
context.add_datasource(**datasource_config)
我的Pandas Dataframe 和batch_requests已通过以下命令成功创建:
...
df = read_csv_pandas(file_path="../done/my_file.txt",
sep="|",
header=0,
quoting=csv.QUOTE_ALL)
batch_request = RuntimeBatchRequest(
datasource_name="example_datasource",
data_connector_name="default_runtime_data_connector_name",
data_asset_name="MyDataAsset",
runtime_parameters={"batch_data": df},
batch_identifiers={"default_identifier_name": "default_identifier"}
)
我的期望套件:
expectation_suite_name = "My_validations"
suite = context.create_expectation_suite(expectation_suite_name, overwrite_existing=True)
然后创建验证程序。
validator = context.get_validator(
batch_request=batch_request, expectation_suite_name=expectation_suite_name
)
validator.head(2)
最后一个命令成功打印了我的 Dataframe 的2行。
那我就给我的套房增加了期待。
validator.expect_table_columns_to_match_ordered_list(['last_name', 'first_name', 'sex'])
validator.expect_column_values_to_be_in_set("sex", ["male", "female", "other", "unknown"])
validator.save_expectation_suite(discard_failed_expectations=False)
然后生成数据文档:
suite_identifier = ExpectationSuiteIdentifier(expectation_suite_name=expectation_suite_name)
context.build_data_docs(resource_identifiers=[suite_identifier])
context.open_data_docs(resource_identifier=suite_identifier)
我的检查点如下所示:
name: my_checkpoint_2
config_version: 1
class_name: SimpleCheckpoint
validations:
- batch_request:
datasource_name: example_datasource
data_connector_name: default_runtime_data_connector_name
data_asset_name: MyDataAsset
runtime_parameters:
batch_data: {df}
batch_identifiers:
default_identifier_name: default_identifier
expectation_suite_name: My_validations
但这个命令
context.run_checkpoint(checkpoint_name="my_checkpoint_2")
产生错误:
ValueError: RuntimeDataBatchSpec must provide a Pandas DataFrame or PandasBatchData object.
1条答案
按热度按时间ozxc1zmp1#
Great Expectations具有多个执行引擎。您正在指定PandasExecutionEngine。执行引擎应更改为SparkDFExecutionEngine,或者您应将 Dataframe 转换为Pandas。