Struct aws_sdk_textract::operation::start_document_analysis::StartDocumentAnalysisInput

#[non_exhaustive]
pub struct StartDocumentAnalysisInput {
    pub document_location: Option<DocumentLocation>,
    pub feature_types: Option<Vec<FeatureType>>,
    pub client_request_token: Option<String>,
    pub job_tag: Option<String>,
    pub notification_channel: Option<NotificationChannel>,
    pub output_config: Option<OutputConfig>,
    pub kms_key_id: Option<String>,
    pub queries_config: Option<QueriesConfig>,
    pub adapters_config: Option<AdaptersConfig>,
}

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.

document_location: Option<DocumentLocation>

The location of the document to be processed.

feature_types: Option<Vec<FeatureType>>

A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to FeatureTypes. All lines and words detected in the document are included in the response (including text that isn't related to the value of FeatureTypes).

client_request_token: Option<String>

The idempotent token that you use to identify the start request. If you use the same token with multiple StartDocumentAnalysis requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations.

job_tag: Option<String>

An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).

notification_channel: Option<NotificationChannel>

The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.

output_config: Option<OutputConfig>

Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.

kms_key_id: Option<String>

The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.

queries_config: Option<QueriesConfig>

adapters_config: Option<AdaptersConfig>

Specifies the adapter to be used when analyzing a document.

Implementations

impl StartDocumentAnalysisInput

pub fn document_location(&self) -> Option<&DocumentLocation>

The location of the document to be processed.

pub fn feature_types(&self) -> &[FeatureType]

A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to FeatureTypes. All lines and words detected in the document are included in the response (including text that isn't related to the value of FeatureTypes).

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

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

The idempotent token that you use to identify the start request. If you use the same token with multiple StartDocumentAnalysis requests, the same JobId is returned. Use ClientRequestToken to prevent the same job from being accidentally started more than once. For more information, see Calling Amazon Textract Asynchronous Operations.

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

An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use JobTag to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).

pub fn notification_channel(&self) -> Option<&NotificationChannel>

The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.

pub fn output_config(&self) -> Option<&OutputConfig>

Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.

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

The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.

pub fn queries_config(&self) -> Option<&QueriesConfig>

pub fn adapters_config(&self) -> Option<&AdaptersConfig>

Specifies the adapter to be used when analyzing a document.

impl StartDocumentAnalysisInput

pub fn builder() -> StartDocumentAnalysisInputBuilder

Creates a new builder-style object to manufacture StartDocumentAnalysisInput.

Trait Implementations

impl Clone for StartDocumentAnalysisInput

fn clone(&self) -> StartDocumentAnalysisInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for StartDocumentAnalysisInput

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

Formats the value using the given formatter.

impl PartialEq for StartDocumentAnalysisInput

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for StartDocumentAnalysisInput