ForecastService / Client / list_explainabilities

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