create_context

create_context(**kwargs)

Creates a context . A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.

See also: AWS API Documentation

Request Syntax

response = client.create_context(
    ContextName='string',
    Source={
        'SourceUri': 'string',
        'SourceType': 'string',
        'SourceId': 'string'
    },
    ContextType='string',
    Description='string',
    Properties={
        'string': 'string'
    },
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
)

Parameters

• ContextName (string) --

  [REQUIRED]

  The name of the context. Must be unique to your account in an Amazon Web Services Region.

• Source (dict) --

  [REQUIRED]

  The source type, ID, and URI.

  • SourceUri (string) -- [REQUIRED]

    The URI of the source.

  • SourceType (string) --

    The type of the source.

  • SourceId (string) --

    The ID of the source.

• ContextType (string) --

  [REQUIRED]

  The context type.

• Description (string) -- The description of the context.
• Properties (dict) --

  A list of properties to add to the context.

  • (string) --
    • (string) --
• Tags (list) --

  A list of tags to apply to the context.

  • (dict) --

    A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

    You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.

    For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.

    • Key (string) -- [REQUIRED]

      The tag key. Tag keys must be unique per resource.

    • Value (string) -- [REQUIRED]

      The tag value.

Return type

dict

Returns

Response Syntax

{
    'ContextArn': 'string'
}

Response Structure

• (dict) --

  • ContextArn (string) --

    The Amazon Resource Name (ARN) of the context.

Exceptions

• SageMaker.Client.exceptions.ResourceLimitExceeded