describe_explainability

describe_explainability(**kwargs)

Describes an Explainability resource created using the CreateExplainability operation.

See also: AWS API Documentation

Request Syntax

response = client.describe_explainability(
    ExplainabilityArn='string'
)

Parameters

ExplainabilityArn (string) --

[REQUIRED]

The Amazon Resource Name (ARN) of the Explaianability to describe.

Return type

dict

Returns

Response Syntax

{
    'ExplainabilityArn': 'string',
    'ExplainabilityName': 'string',
    'ResourceArn': 'string',
    'ExplainabilityConfig': {
        'TimeSeriesGranularity': 'ALL'|'SPECIFIC',
        'TimePointGranularity': 'ALL'|'SPECIFIC'
    },
    'EnableVisualization': True|False,
    'DataSource': {
        'S3Config': {
            'Path': 'string',
            'RoleArn': 'string',
            'KMSKeyArn': 'string'
        }
    },
    'Schema': {
        'Attributes': [
            {
                'AttributeName': 'string',
                'AttributeType': 'string'|'integer'|'float'|'timestamp'|'geolocation'
            },
        ]
    },
    'StartDateTime': 'string',
    'EndDateTime': 'string',
    'EstimatedTimeRemainingInMinutes': 123,
    'Message': 'string',
    'Status': 'string',
    'CreationTime': datetime(2015, 1, 1),
    'LastModificationTime': datetime(2015, 1, 1)
}

Response Structure

• (dict) --
  • ExplainabilityArn (string) --

    The Amazon Resource Name (ARN) of the Explainability.

  • ExplainabilityName (string) --

    The name of the Explainability.

  • ResourceArn (string) --

    The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability resource.

  • ExplainabilityConfig (dict) --

    The configuration settings that define the granularity of time series and time points for the Explainability.

    • TimeSeriesGranularity (string) --

      To create an Explainability for all time series in your datasets, use ALL . To create an Explainability for specific time series in your datasets, use SPECIFIC .

      Specify time series by uploading a CSV or Parquet file to an Amazon S3 bucket and set the location within the DataDestination data type.

    • TimePointGranularity (string) --

      To create an Explainability for all time points in your forecast horizon, use ALL . To create an Explainability for specific time points in your forecast horizon, use SPECIFIC .

      Specify time points with the StartDateTime and EndDateTime parameters within the CreateExplainability operation.

  • EnableVisualization (boolean) --

    Whether the visualization was enabled for the Explainability resource.

  • DataSource (dict) --

    The source of your data, an Identity and Access Management (IAM) role that allows Amazon Forecast to access the data and, optionally, an Key Management Service (KMS) key.

    • S3Config (dict) --

      The path to the data stored in an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the data.

      • Path (string) --

        The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket.

      • RoleArn (string) --

        The ARN of the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket or files. If you provide a value for the KMSKeyArn key, the role must allow access to the key.

        Passing a role across Amazon Web Services accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.

      • KMSKeyArn (string) --

        The Amazon Resource Name (ARN) of an Key Management Service (KMS) key.

  • Schema (dict) --

    Defines the fields of a dataset.

    • Attributes (list) --

      An array of attributes specifying the name and type of each field in a dataset.

      • (dict) --

        An attribute of a schema, which defines a dataset field. A schema attribute is required for every field in a dataset. The Schema object contains an array of SchemaAttribute objects.

        • AttributeName (string) --

          The name of the dataset field.

        • AttributeType (string) --

          The data type of the field.

          For a related time series dataset, other than date, item_id, and forecast dimensions attributes, all attributes should be of numerical type (integer/float).

  • StartDateTime (string) --

    If TimePointGranularity is set to SPECIFIC , the first time point in the Explainability.

  • EndDateTime (string) --

    If TimePointGranularity is set to SPECIFIC , the last time point in the Explainability.

  • EstimatedTimeRemainingInMinutes (integer) --

    The estimated time remaining in minutes for the CreateExplainability job to complete.

  • Message (string) --

    If an error occurred, a message about the error.

  • Status (string) --

    The status of the Explainability resource. States include:

    • ACTIVE
    • CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
    • CREATE_STOPPING , CREATE_STOPPED
    • DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
  • CreationTime (datetime) --

    When the Explainability resource was created.

  • LastModificationTime (datetime) --

    The last time the resource was modified. The timestamp depends on the status of the job:

    • CREATE_PENDING - The CreationTime .
    • CREATE_IN_PROGRESS - The current timestamp.
    • CREATE_STOPPING - The current timestamp.
    • CREATE_STOPPED - When the job stopped.
    • ACTIVE or CREATE_FAILED - When the job finished or failed.

Exceptions

• ForecastService.Client.exceptions.InvalidInputException
• ForecastService.Client.exceptions.ResourceNotFoundException