[ aws . forecast ]

list-explainabilities

Description

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

See ‘aws help’ for descriptions of global parameters.

Synopsis

  list-explainabilities
[--next-token <value>]
[--max-results <value>]
[--filters <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--next-token (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.

--max-results (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.

(structure)

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)

The name of the parameter to filter on.

Value -> (string)

The value to match.

Condition -> (string)

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

Shorthand Syntax:

Key=string,Value=string,Condition=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string",
    "Condition": "IS"|"IS_NOT"
  }
  ...
]

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See ‘aws help’ for descriptions of global parameters.

Output

Explainabilities -> (list)

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

(structure)

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 -> (structure)

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 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 -> (timestamp)

When the Explainability was created.

LastModificationTime -> (timestamp)

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.