ForecastService / Client / describe_explainability

describe_explainability

ForecastService.Client.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