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我开始在一个项目中使用远大期望。我正在尝试以编程方式创建一个具有远大期望的期望套件。我有一个 GCS 数据源（由 2 个 csv 文件组成），定义如下great_expectations.yml：

datasources:
  GCS_Data:
    class_name: Datasource
    data_connectors:
      default_inferred_data_connector_name:
        class_name: InferredAssetFilesystemDataConnector
        default_regex:
          group_names:
            - data_asset_name
          pattern: (.*)
        base_directory: gs://mybucket/GCS_datasource
        module_name: great_expectations.datasource.data_connector
      default_runtime_data_connector_name:
        class_name: RuntimeDataConnector
        module_name: great_expectations.datasource.data_connector
        assets:
          my_runtime_asset_name:
            class_name: Asset
            module_name: great_expectations.datasource.data_connector.asset
            batch_identifiers:
              - runtime_batch_identifier_name
    execution_engine:
      class_name: PandasExecutionEngine
      module_name: great_expectations.execution_engine
    module_name: great_expectations.datasource
config_variables_file_path: uncommitted/config_variables.yml

当我尝试创建期望套件时，我运行：

   
import great_expectations as ge
from great_expectations.core.batch import BatchRequest
from great_expectations.checkpoint import SimpleCheckpoint #needed?
from great_expectations.exceptions import DataContextError

context = ge.data_context.DataContext()

# Note that if you modify this batch request, …