Struct CreateExplainabilityInput

#[non_exhaustive]
pub struct CreateExplainabilityInput {
    pub explainability_name: Option<String>,
    pub resource_arn: Option<String>,
    pub explainability_config: Option<ExplainabilityConfig>,
    pub data_source: Option<DataSource>,
    pub schema: Option<Schema>,
    pub enable_visualization: Option<bool>,
    pub start_date_time: Option<String>,
    pub end_date_time: Option<String>,
    pub tags: Option<Vec<Tag>>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

explainability_name: Option<String>

A unique name for the Explainability.

resource_arn: Option<String>

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

explainability_config: Option<ExplainabilityConfig>

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

data_source: Option<DataSource>

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.

schema: Option<Schema>

Defines the fields of a dataset.

enable_visualization: Option<bool>

Create an Explainability visualization that is viewable within the Amazon Web Services console.

start_date_time: Option<String>

If TimePointGranularity is set to SPECIFIC, define the first point for the Explainability.

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)

end_date_time: Option<String>

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

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)

tags: Option<Vec<Tag>>

Optional metadata to help you categorize and organize your resources. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

The following restrictions apply to tags:

• For each resource, each tag key must be unique and each tag key must have one value.

• Maximum number of tags per resource: 50.

• Maximum key length: 128 Unicode characters in UTF-8.

• Maximum value length: 256 Unicode characters in UTF-8.

• Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

• Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit. You cannot edit or delete tag keys with this prefix.

Implementations

impl CreateExplainabilityInput

pub fn explainability_name(&self) -> Option<&str>

A unique name for the Explainability.

pub fn resource_arn(&self) -> Option<&str>

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

pub fn explainability_config(&self) -> Option<&ExplainabilityConfig>

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

pub fn data_source(&self) -> Option<&DataSource>

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.

pub fn schema(&self) -> Option<&Schema>

Defines the fields of a dataset.

pub fn enable_visualization(&self) -> Option<bool>

Create an Explainability visualization that is viewable within the Amazon Web Services console.

pub fn start_date_time(&self) -> Option<&str>

If TimePointGranularity is set to SPECIFIC, define the first point for the Explainability.

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)

pub fn end_date_time(&self) -> Option<&str>

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

Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)

pub fn tags(&self) -> &[Tag]

Optional metadata to help you categorize and organize your resources. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

The following restrictions apply to tags:

• For each resource, each tag key must be unique and each tag key must have one value.

• Maximum number of tags per resource: 50.

• Maximum key length: 128 Unicode characters in UTF-8.

• Maximum value length: 256 Unicode characters in UTF-8.

• Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

• Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit. You cannot edit or delete tag keys with this prefix.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .tags.is_none().

impl CreateExplainabilityInput

pub fn builder() -> CreateExplainabilityInputBuilder

Creates a new builder-style object to manufacture CreateExplainabilityInput.

Trait Implementations

impl Clone for CreateExplainabilityInput

fn clone(&self) -> CreateExplainabilityInput

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateExplainabilityInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateExplainabilityInput

fn eq(&self, other: &CreateExplainabilityInput) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateExplainabilityInput