list_explainabilities

ForecastService.Client.list_explainabilities(**kwargs)

Returns a list of Explainability resources created using the CreateExplainability operation. This operation returns a summary for each Explainability. You can filter the list using an array of Filter objects.

To retrieve the complete set of properties for a particular Explainability resource, use the ARN with the DescribeExplainability operation.

See also: AWS API Documentation

Request Syntax

response = client.list_explainabilities(
    NextToken='string',
    MaxResults=123,
    Filters=[
        {
            'Key': 'string',
            'Value': 'string',
            'Condition': 'IS'|'IS_NOT'
        },
    ]
)

Parameters

• NextToken (string) -- If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.
• MaxResults (integer) -- The number of items returned in the response.
• Filters (list) --

  An array of filters. For each filter, provide a condition and a match statement. The condition is either IS or IS_NOT , which specifies whether to include or exclude the resources that match the statement from the list. The match statement consists of a key and a value.

  Filter properties

  • Condition - The condition to apply. Valid values are IS and IS_NOT .
  • Key - The name of the parameter to filter on. Valid values are ResourceArn and Status .
  • Value - The value to match.
  • (dict) --

    Describes a filter for choosing a subset of objects. Each filter consists of a condition and a match statement. The condition is either IS or IS_NOT , which specifies whether to include or exclude the objects that match the statement, respectively. The match statement consists of a key and a value.

    • Key (string) -- [REQUIRED]

      The name of the parameter to filter on.

    • Value (string) -- [REQUIRED]

      The value to match.

    • Condition (string) -- [REQUIRED]

      The condition to apply. To include the objects that match the statement, specify IS . To exclude matching objects, specify IS_NOT .

Return type

dict

Returns

Response Syntax

{
    'Explainabilities': [
        {
            'ExplainabilityArn': 'string',
            'ExplainabilityName': 'string',
            'ResourceArn': 'string',
            'ExplainabilityConfig': {
                'TimeSeriesGranularity': 'ALL'|'SPECIFIC',
                'TimePointGranularity': 'ALL'|'SPECIFIC'
            },
            'Status': 'string',
            'Message': 'string',
            'CreationTime': datetime(2015, 1, 1),
            'LastModificationTime': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

• (dict) --

  • Explainabilities (list) --

    An array of objects that summarize the properties of each Explainability resource.

    • (dict) --

      Provides a summary of the Explainability properties used in the ListExplainabilities operation. To get a complete set of properties, call the DescribeExplainability operation, and provide the listed ExplainabilityArn .

      • 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.

      • 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.

      • Status (string) --

        The status of the Explainability. States include:

        • ACTIVE
        • CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
        • CREATE_STOPPING , CREATE_STOPPED
        • DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED

      • Message (string) --

        Information about any errors that may have occurred during the Explainability creation process.

      • CreationTime (datetime) --

        When the Explainability 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.

  • NextToken (string) --

    Returns this token if the response is truncated. To retrieve the next set of results, use the token in the next request.

Exceptions

• ForecastService.Client.exceptions.InvalidNextTokenException
• ForecastService.Client.exceptions.InvalidInputException