SageMaker / Client / describe_studio_lifecycle_config

describe_studio_lifecycle_config

SageMaker.Client.describe_studio_lifecycle_config(**kwargs)

Describes the Amazon SageMaker AI Studio Lifecycle Configuration.

See also: AWS API Documentation

Request Syntax

response = client.describe_studio_lifecycle_config(
    StudioLifecycleConfigName='string'
)

Parameters:

StudioLifecycleConfigName (string) –

[REQUIRED]

The name of the Amazon SageMaker AI Studio Lifecycle Configuration to describe.

Return type:

dict

Returns:

Response Syntax

{
    'StudioLifecycleConfigArn': 'string',
    'StudioLifecycleConfigName': 'string',
    'CreationTime': datetime(2015, 1, 1),
    'LastModifiedTime': datetime(2015, 1, 1),
    'StudioLifecycleConfigContent': 'string',
    'StudioLifecycleConfigAppType': 'JupyterServer'|'KernelGateway'|'CodeEditor'|'JupyterLab'
}

Response Structure

• (dict) –

  • StudioLifecycleConfigArn (string) –

    The ARN of the Lifecycle Configuration to describe.

  • StudioLifecycleConfigName (string) –

    The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is described.

  • CreationTime (datetime) –

    The creation time of the Amazon SageMaker AI Studio Lifecycle Configuration.

  • LastModifiedTime (datetime) –

    This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.

  • StudioLifecycleConfigContent (string) –

    The content of your Amazon SageMaker AI Studio Lifecycle Configuration script.

  • StudioLifecycleConfigAppType (string) –

    The App type that the Lifecycle Configuration is attached to.

Exceptions

• SageMaker.Client.exceptions.ResourceNotFound