要停止在关闭Sagemaker时持续使用DataWrangler，应该确保已经合理地终止DataWrangler会话。

以下是如何终止DataWrangler会话的示例代码：

import boto3
sm_session = boto3.Session(region_name='us-west-2')
sm = sm_session.client('sagemaker')

# Replace with your DataWragler Flow Amazon Resource Name (ARN)
flow_arn = "arn:aws:sagemaker:us-west-2:123456789012:data-flow/my-flow"

# Create processing job
processing_job_arn = sm.create_processing_job(
    ProcessingInputs=[
        {
            "InputName": "input_path",
            "AppManaged": False,
            "S3Input": {
                "S3Uri": "s3://path/to/input/data",
                "LocalPath": "/opt/ml/processing/input"
            }
        }
    ],
    ProcessingOutputConfig={
        "Outputs": [
            {
                "OutputName": "output",
                "AppManaged": False,
                "S3Output": {
                    "S3Uri": "s3://path/to/output/data",
                    "LocalPath": "/opt/ml/processing/output",
                    "S3UploadMode": "EndOfJob"
                }
            }
        ]
    },
    ProcessingJobName="my-processing-job",
    ProcessingResources={
        "ClusterConfig": {
            "InstanceCount": 1,
            "InstanceType": "ml.m5.large",
            "VolumeSizeInGB": 30
        }
    },
    StoppingCondition={
        "MaxRuntimeInSeconds": 300
    },
    AppSpecification={
        "ImageUri": "874736623134.dkr.ecr.us-west-2.amazonaws.com/sagemaker-data-wrangler-container:1.0",
        "ContainerEntrypoint": [
            "/opt/ml/processing/input/code/data_wrangler_processing.py"
        ],
        "ContainerArguments": [
            "--s3_input_path",
            "/opt/ml/processing/input",
            "--s3_output_path",
            "/opt/ml/processing/output",
            "--flow_id",
            flow_arn.split('/')[-1]
        ]
    },
    NetworkConfig={
        "EnableNetworkIsolation