Struct aws_sdk_textract::Client

pub struct Client { /* private fields */ }

Client for Amazon Textract

Client for invoking operations on Amazon Textract. Each operation on Amazon Textract is a method on this this struct. .send() MUST be invoked on the generated operations to dispatch the request to the service.

Constructing a Client

A Config is required to construct a client. For most use cases, the aws-config crate should be used to automatically resolve this config using aws_config::load_from_env(), since this will resolve an SdkConfig which can be shared across multiple different AWS SDK clients. This config resolution process can be customized by calling aws_config::from_env() instead, which returns a ConfigLoader that uses the builder pattern to customize the default config.

In the simplest case, creating a client looks as follows:

let config = aws_config::load_from_env().await;
let client = aws_sdk_textract::Client::new(&config);

Occasionally, SDKs may have additional service-specific values that can be set on the Config that is absent from SdkConfig, or slightly different settings for a specific client may be desired. The Config struct implements From<&SdkConfig>, so setting these specific settings can be done as follows:

let sdk_config = ::aws_config::load_from_env().await;
let config = aws_sdk_textract::config::Builder::from(&sdk_config)
    .some_service_specific_setting("value")
    .build();

See the aws-config docs and Config for more information on customizing configuration.

Note: Client construction is expensive due to connection thread pool initialization, and should be done once at application start-up.

Using the Client

A client has a function for every operation that can be performed by the service. For example, the CreateAdapter operation has a Client::create_adapter, function which returns a builder for that operation. The fluent builder ultimately has a send() function that returns an async future that returns a result, as illustrated below:

let result = client.create_adapter()
    .adapter_name("example")
    .send()
    .await;

The underlying HTTP requests that get made by this can be modified with the customize_operation function on the fluent builder. See the customize module for more information.

Implementations

impl Client

pub fn analyze_document(&self) -> AnalyzeDocumentFluentBuilder

Constructs a fluent builder for the AnalyzeDocument operation.

• The fluent builder is configurable:
  • document(Document) / set_document(Option<Document>):
    required: true
    

    The input document as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Textract operations, you can’t pass image bytes. The document must be an image in JPEG, PNG, PDF, or TIFF format.

    If you’re using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes that are passed using the Bytes field.

    
    
  • feature_types(FeatureType) / set_feature_types(Option<Vec::<FeatureType>>):
    required: true
    

    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. Add SIGNATURES to return the locations of detected signatures. Add LAYOUT to the list to return information about the layout of the document. All lines and words detected in the document are included in the response (including text that isn’t related to the value of FeatureTypes).

    
    
  • human_loop_config(HumanLoopConfig) / set_human_loop_config(Option<HumanLoopConfig>):
    required: false
    

    Sets the configuration for the human in the loop workflow for analyzing documents.

    
    
  • queries_config(QueriesConfig) / set_queries_config(Option<QueriesConfig>):
    required: false
    

    Contains Queries and the alias for those Queries, as determined by the input.

    
    
  • adapters_config(AdaptersConfig) / set_adapters_config(Option<AdaptersConfig>):
    required: false
    

    Specifies the adapter to be used when analyzing a document.

    
    
• On success, responds with AnalyzeDocumentOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Metadata about the analyzed document. An example is the number of pages.

  • blocks(Option<Vec::<Block>>):

    The items that are detected and analyzed by AnalyzeDocument.

  • human_loop_activation_output(Option<HumanLoopActivationOutput>):

    Shows the results of the human in the loop evaluation.

  • analyze_document_model_version(Option<String>):

    The version of the model used to analyze the document.

• On failure, responds with SdkError<AnalyzeDocumentError>

impl Client

pub fn analyze_expense(&self) -> AnalyzeExpenseFluentBuilder

Constructs a fluent builder for the AnalyzeExpense operation.

• The fluent builder is configurable:
  • document(Document) / set_document(Option<Document>):
    required: true
    

    The input document, either as bytes or as an S3 object.

    You pass image bytes to an Amazon Textract API operation by using the Bytes property. For example, you would use the Bytes property to pass a document loaded from a local file system. Image bytes passed by using the Bytes property must be base64 encoded. Your code might not need to encode document file bytes if you’re using an AWS SDK to call Amazon Textract API operations.

    You pass images stored in an S3 bucket to an Amazon Textract API operation by using the S3Object property. Documents stored in an S3 bucket don’t need to be base64 encoded.

    The AWS Region for the S3 bucket that contains the S3 object must match the AWS Region that you use for Amazon Textract operations.

    If you use the AWS CLI to call Amazon Textract operations, passing image bytes using the Bytes property isn’t supported. You must first upload the document to an Amazon S3 bucket, and then call the operation using the S3Object property.

    For Amazon Textract to process an S3 object, the user must have permission to access the S3 object.

    
    
• On success, responds with AnalyzeExpenseOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about the input document.

  • expense_documents(Option<Vec::<ExpenseDocument>>):

    The expenses detected by Amazon Textract.

• On failure, responds with SdkError<AnalyzeExpenseError>

impl Client

pub fn analyze_id(&self) -> AnalyzeIDFluentBuilder

Constructs a fluent builder for the AnalyzeID operation.

• The fluent builder is configurable:
  • document_pages(Document) / set_document_pages(Option<Vec::<Document>>):
    required: true
    

    The document being passed to AnalyzeID.

    
    
• On success, responds with AnalyzeIdOutput with field(s):
  • identity_documents(Option<Vec::<IdentityDocument>>):

    The list of documents processed by AnalyzeID. Includes a number denoting their place in the list and the response structure for the document.

  • document_metadata(Option<DocumentMetadata>):

    Information about the input document.

  • analyze_id_model_version(Option<String>):

    The version of the AnalyzeIdentity API being used to process documents.

• On failure, responds with SdkError<AnalyzeIDError>

impl Client

pub fn create_adapter(&self) -> CreateAdapterFluentBuilder

Constructs a fluent builder for the CreateAdapter operation.

• The fluent builder is configurable:
  • adapter_name(impl Into<String>) / set_adapter_name(Option<String>):
    required: true
    

    The name to be assigned to the adapter being created.

    
    
  • client_request_token(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    Idempotent token is used to recognize the request. If the same token is used with multiple CreateAdapter requests, the same session is returned. This token is employed to avoid unintentionally creating the same session multiple times.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The description to be assigned to the adapter being created.

    
    
  • feature_types(FeatureType) / set_feature_types(Option<Vec::<FeatureType>>):
    required: true
    

    The type of feature that the adapter is being trained on. Currrenly, supported feature types are: QUERIES

    
    
  • auto_update(AutoUpdate) / set_auto_update(Option<AutoUpdate>):
    required: false
    

    Controls whether or not the adapter should automatically update.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    A list of tags to be added to the adapter.

    
    
• On success, responds with CreateAdapterOutput with field(s):
  • adapter_id(Option<String>):

    A string containing the unique ID for the adapter that has been created.

• On failure, responds with SdkError<CreateAdapterError>

impl Client

pub fn create_adapter_version(&self) -> CreateAdapterVersionFluentBuilder

Constructs a fluent builder for the CreateAdapterVersion operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string containing a unique ID for the adapter that will receive a new version.

    
    
  • client_request_token(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    Idempotent token is used to recognize the request. If the same token is used with multiple CreateAdapterVersion requests, the same session is returned. This token is employed to avoid unintentionally creating the same session multiple times.

    
    
  • dataset_config(AdapterVersionDatasetConfig) / set_dataset_config(Option<AdapterVersionDatasetConfig>):
    required: true
    

    Specifies a dataset used to train a new adapter version. Takes a ManifestS3Object as the value.

    
    
  • kms_key_id(impl Into<String>) / set_kms_key_id(Option<String>):
    required: false
    

    The identifier for your AWS Key Management Service key (AWS KMS key). Used to encrypt your documents.

    
    
  • output_config(OutputConfig) / set_output_config(Option<OutputConfig>):
    required: true
    

    Sets whether or not your output will go to a user created bucket. Used to set the name of the bucket, and the prefix on the output file.

    OutputConfig is an optional parameter which lets you adjust where your output will be placed. By default, Amazon Textract will store the results internally and can only be accessed by the Get API operations. With OutputConfig enabled, you can set the name of the bucket the output will be sent to the file prefix of the results where you can download your results. Additionally, you can set the KMSKeyID parameter to a customer master key (CMK) to encrypt your output. Without this parameter set Amazon Textract will encrypt server-side using the AWS managed CMK for Amazon S3.

    Decryption of Customer Content is necessary for processing of the documents by Amazon Textract. If your account is opted out under an AI services opt out policy then all unencrypted Customer Content is immediately and permanently deleted after the Customer Content has been processed by the service. No copy of of the output is retained by Amazon Textract. For information about how to opt out, see Managing AI services opt-out policy.

    For more information on data privacy, see the Data Privacy FAQ.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: false
    

    A set of tags (key-value pairs) that you want to attach to the adapter version.

    
    
• On success, responds with CreateAdapterVersionOutput with field(s):
  • adapter_id(Option<String>):

    A string containing the unique ID for the adapter that has received a new version.

  • adapter_version(Option<String>):

    A string describing the new version of the adapter.

• On failure, responds with SdkError<CreateAdapterVersionError>

impl Client

pub fn delete_adapter(&self) -> DeleteAdapterFluentBuilder

Constructs a fluent builder for the DeleteAdapter operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string containing a unique ID for the adapter to be deleted.

    
    
• On success, responds with DeleteAdapterOutput
• On failure, responds with SdkError<DeleteAdapterError>

impl Client

pub fn delete_adapter_version(&self) -> DeleteAdapterVersionFluentBuilder

Constructs a fluent builder for the DeleteAdapterVersion operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string containing a unique ID for the adapter version that will be deleted.

    
    
  • adapter_version(impl Into<String>) / set_adapter_version(Option<String>):
    required: true
    

    Specifies the adapter version to be deleted.

    
    
• On success, responds with DeleteAdapterVersionOutput
• On failure, responds with SdkError<DeleteAdapterVersionError>

impl Client

pub fn detect_document_text(&self) -> DetectDocumentTextFluentBuilder

Constructs a fluent builder for the DetectDocumentText operation.

• The fluent builder is configurable:
  • document(Document) / set_document(Option<Document>):
    required: true
    

    The input document as base64-encoded bytes or an Amazon S3 object. If you use the AWS CLI to call Amazon Textract operations, you can’t pass image bytes. The document must be an image in JPEG or PNG format.

    If you’re using an AWS SDK to call Amazon Textract, you might not need to base64-encode image bytes that are passed using the Bytes field.

    
    
• On success, responds with DetectDocumentTextOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Metadata about the document. It contains the number of pages that are detected in the document.

  • blocks(Option<Vec::<Block>>):

    An array of Block objects that contain the text that’s detected in the document.

  • detect_document_text_model_version(Option<String>):

• On failure, responds with SdkError<DetectDocumentTextError>

impl Client

pub fn get_adapter(&self) -> GetAdapterFluentBuilder

Constructs a fluent builder for the GetAdapter operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string containing a unique ID for the adapter.

    
    
• On success, responds with GetAdapterOutput with field(s):
  • adapter_id(Option<String>):

    A string identifying the adapter that information has been retrieved for.

  • adapter_name(Option<String>):

    The name of the requested adapter.

  • creation_time(Option<DateTime>):

    The date and time the requested adapter was created at.

  • description(Option<String>):

    The description for the requested adapter.

  • feature_types(Option<Vec::<FeatureType>>):

    List of the targeted feature types for the requested adapter.

  • auto_update(Option<AutoUpdate>):

    Binary value indicating if the adapter is being automatically updated or not.

  • tags(Option<HashMap::<String, String>>):

    A set of tags (key-value pairs) associated with the adapter that has been retrieved.

• On failure, responds with SdkError<GetAdapterError>

impl Client

pub fn get_adapter_version(&self) -> GetAdapterVersionFluentBuilder

Constructs a fluent builder for the GetAdapterVersion operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string specifying a unique ID for the adapter version you want to retrieve information for.

    
    
  • adapter_version(impl Into<String>) / set_adapter_version(Option<String>):
    required: true
    

    A string specifying the adapter version you want to retrieve information for.

    
    
• On success, responds with GetAdapterVersionOutput with field(s):
  • adapter_id(Option<String>):

    A string containing a unique ID for the adapter version being retrieved.

  • adapter_version(Option<String>):

    A string containing the adapter version that has been retrieved.

  • creation_time(Option<DateTime>):

    The time that the adapter version was created.

  • feature_types(Option<Vec::<FeatureType>>):

    List of the targeted feature types for the requested adapter version.

  • status(Option<AdapterVersionStatus>):

    The status of the adapter version that has been requested.

  • status_message(Option<String>):

    A message that describes the status of the requested adapter version.

  • dataset_config(Option<AdapterVersionDatasetConfig>):

    Specifies a dataset used to train a new adapter version. Takes a ManifestS3Objec as the value.

  • kms_key_id(Option<String>):

    The identifier for your AWS Key Management Service key (AWS KMS key). Used to encrypt your documents.

  • output_config(Option<OutputConfig>):

    Sets whether or not your output will go to a user created bucket. Used to set the name of the bucket, and the prefix on the output file.

    OutputConfig is an optional parameter which lets you adjust where your output will be placed. By default, Amazon Textract will store the results internally and can only be accessed by the Get API operations. With OutputConfig enabled, you can set the name of the bucket the output will be sent to the file prefix of the results where you can download your results. Additionally, you can set the KMSKeyID parameter to a customer master key (CMK) to encrypt your output. Without this parameter set Amazon Textract will encrypt server-side using the AWS managed CMK for Amazon S3.

    Decryption of Customer Content is necessary for processing of the documents by Amazon Textract. If your account is opted out under an AI services opt out policy then all unencrypted Customer Content is immediately and permanently deleted after the Customer Content has been processed by the service. No copy of of the output is retained by Amazon Textract. For information about how to opt out, see Managing AI services opt-out policy.

    For more information on data privacy, see the Data Privacy FAQ.

  • evaluation_metrics(Option<Vec::<AdapterVersionEvaluationMetric>>):

    The evaluation metrics (F1 score, Precision, and Recall) for the requested version, grouped by baseline metrics and adapter version.

  • tags(Option<HashMap::<String, String>>):

    A set of tags (key-value pairs) that are associated with the adapter version.

• On failure, responds with SdkError<GetAdapterVersionError>

impl Client

pub fn get_document_analysis(&self) -> GetDocumentAnalysisFluentBuilder

Constructs a fluent builder for the GetDocumentAnalysis operation.

• The fluent builder is configurable:
  • job_id(impl Into<String>) / set_job_id(Option<String>):
    required: true
    

    A unique identifier for the text-detection job. The JobId is returned from StartDocumentAnalysis. A JobId value is only valid for 7 days.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return per paginated call. The largest value that you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.

    
    
• On success, responds with GetDocumentAnalysisOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about a document that Amazon Textract processed. DocumentMetadata is returned in every page of paginated responses from an Amazon Textract video operation.

  • job_status(Option<JobStatus>):

    The current status of the text detection job.

  • next_token(Option<String>):

    If the response is truncated, Amazon Textract returns this token. You can use this token in the subsequent request to retrieve the next set of text detection results.

  • blocks(Option<Vec::<Block>>):

    The results of the text-analysis operation.

  • warnings(Option<Vec::<Warning>>):

    A list of warnings that occurred during the document-analysis operation.

  • status_message(Option<String>):

    Returns if the detection job could not be completed. Contains explanation for what error occured.

  • analyze_document_model_version(Option<String>):

• On failure, responds with SdkError<GetDocumentAnalysisError>

impl Client

pub fn get_document_text_detection( &self, ) -> GetDocumentTextDetectionFluentBuilder

Constructs a fluent builder for the GetDocumentTextDetection operation.

• The fluent builder is configurable:
  • job_id(impl Into<String>) / set_job_id(Option<String>):
    required: true
    

    A unique identifier for the text detection job. The JobId is returned from StartDocumentTextDetection. A JobId value is only valid for 7 days.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return per paginated call. The largest value you can specify is 1,000. If you specify a value greater than 1,000, a maximum of 1,000 results is returned. The default value is 1,000.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.

    
    
• On success, responds with GetDocumentTextDetectionOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about a document that Amazon Textract processed. DocumentMetadata is returned in every page of paginated responses from an Amazon Textract video operation.

  • job_status(Option<JobStatus>):

    The current status of the text detection job.

  • next_token(Option<String>):

    If the response is truncated, Amazon Textract returns this token. You can use this token in the subsequent request to retrieve the next set of text-detection results.

  • blocks(Option<Vec::<Block>>):

    The results of the text-detection operation.

  • warnings(Option<Vec::<Warning>>):

    A list of warnings that occurred during the text-detection operation for the document.

  • status_message(Option<String>):

    Returns if the detection job could not be completed. Contains explanation for what error occured.

  • detect_document_text_model_version(Option<String>):

• On failure, responds with SdkError<GetDocumentTextDetectionError>

impl Client

pub fn get_expense_analysis(&self) -> GetExpenseAnalysisFluentBuilder

Constructs a fluent builder for the GetExpenseAnalysis operation.

• The fluent builder is configurable:
  • job_id(impl Into<String>) / set_job_id(Option<String>):
    required: true
    

    A unique identifier for the text detection job. The JobId is returned from StartExpenseAnalysis. A JobId value is only valid for 7 days.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return per paginated call. The largest value you can specify is 20. If you specify a value greater than 20, a maximum of 20 results is returned. The default value is 20.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there are more blocks to retrieve), Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of blocks.

    
    
• On success, responds with GetExpenseAnalysisOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about a document that Amazon Textract processed. DocumentMetadata is returned in every page of paginated responses from an Amazon Textract operation.

  • job_status(Option<JobStatus>):

    The current status of the text detection job.

  • next_token(Option<String>):

    If the response is truncated, Amazon Textract returns this token. You can use this token in the subsequent request to retrieve the next set of text-detection results.

  • expense_documents(Option<Vec::<ExpenseDocument>>):

    The expenses detected by Amazon Textract.

  • warnings(Option<Vec::<Warning>>):

    A list of warnings that occurred during the text-detection operation for the document.

  • status_message(Option<String>):

    Returns if the detection job could not be completed. Contains explanation for what error occured.

  • analyze_expense_model_version(Option<String>):

    The current model version of AnalyzeExpense.

• On failure, responds with SdkError<GetExpenseAnalysisError>

impl Client

pub fn get_lending_analysis(&self) -> GetLendingAnalysisFluentBuilder

Constructs a fluent builder for the GetLendingAnalysis operation.

• The fluent builder is configurable:
  • job_id(impl Into<String>) / set_job_id(Option<String>):
    required: true
    

    A unique identifier for the lending or text-detection job. The JobId is returned from StartLendingAnalysis. A JobId value is only valid for 7 days.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return per paginated call. The largest value that you can specify is 30. If you specify a value greater than 30, a maximum of 30 results is returned. The default value is 30.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete, Amazon Textract returns a pagination token in the response. You can use this pagination token to retrieve the next set of lending results.

    
    
• On success, responds with GetLendingAnalysisOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about the input document.

  • job_status(Option<JobStatus>):

    The current status of the lending analysis job.

  • next_token(Option<String>):

    If the response is truncated, Amazon Textract returns this token. You can use this token in the subsequent request to retrieve the next set of lending results.

  • results(Option<Vec::<LendingResult>>):

    Holds the information returned by one of AmazonTextract’s document analysis operations for the pinstripe.

  • warnings(Option<Vec::<Warning>>):

    A list of warnings that occurred during the lending analysis operation.

  • status_message(Option<String>):

    Returns if the lending analysis job could not be completed. Contains explanation for what error occurred.

  • analyze_lending_model_version(Option<String>):

    The current model version of the Analyze Lending API.

• On failure, responds with SdkError<GetLendingAnalysisError>

impl Client

pub fn get_lending_analysis_summary( &self, ) -> GetLendingAnalysisSummaryFluentBuilder

Constructs a fluent builder for the GetLendingAnalysisSummary operation.

• The fluent builder is configurable:
  • job_id(impl Into<String>) / set_job_id(Option<String>):
    required: true
    

    A unique identifier for the lending or text-detection job. The JobId is returned from StartLendingAnalysis. A JobId value is only valid for 7 days.

    
    
• On success, responds with GetLendingAnalysisSummaryOutput with field(s):
  • document_metadata(Option<DocumentMetadata>):

    Information about the input document.

  • job_status(Option<JobStatus>):

    The current status of the lending analysis job.

  • summary(Option<LendingSummary>):

    Contains summary information for documents grouped by type.

  • warnings(Option<Vec::<Warning>>):

    A list of warnings that occurred during the lending analysis operation.

  • status_message(Option<String>):

    Returns if the lending analysis could not be completed. Contains explanation for what error occurred.

  • analyze_lending_model_version(Option<String>):

    The current model version of the Analyze Lending API.

• On failure, responds with SdkError<GetLendingAnalysisSummaryError>

impl Client

pub fn list_adapter_versions(&self) -> ListAdapterVersionsFluentBuilder

Constructs a fluent builder for the ListAdapterVersions operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: false
    

    A string containing a unique ID for the adapter to match for when listing adapter versions.

    
    
  • after_creation_time(DateTime) / set_after_creation_time(Option<DateTime>):
    required: false
    

    Specifies the lower bound for the ListAdapterVersions operation. Ensures ListAdapterVersions returns only adapter versions created after the specified creation time.

    
    
  • before_creation_time(DateTime) / set_before_creation_time(Option<DateTime>):
    required: false
    

    Specifies the upper bound for the ListAdapterVersions operation. Ensures ListAdapterVersions returns only adapter versions created after the specified creation time.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return when listing adapter versions.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    Identifies the next page of results to return when listing adapter versions.

    
    
• On success, responds with ListAdapterVersionsOutput with field(s):
  • adapter_versions(Option<Vec::<AdapterVersionOverview>>):

    Adapter versions that match the filtering criteria specified when calling ListAdapters.

  • next_token(Option<String>):

    Identifies the next page of results to return when listing adapter versions.

• On failure, responds with SdkError<ListAdapterVersionsError>

impl Client

pub fn list_adapters(&self) -> ListAdaptersFluentBuilder

Constructs a fluent builder for the ListAdapters operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • after_creation_time(DateTime) / set_after_creation_time(Option<DateTime>):
    required: false
    

    Specifies the lower bound for the ListAdapters operation. Ensures ListAdapters returns only adapters created after the specified creation time.

    
    
  • before_creation_time(DateTime) / set_before_creation_time(Option<DateTime>):
    required: false
    

    Specifies the upper bound for the ListAdapters operation. Ensures ListAdapters returns only adapters created before the specified creation time.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of results to return when listing adapters.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    Identifies the next page of results to return when listing adapters.

    
    
• On success, responds with ListAdaptersOutput with field(s):
  • adapters(Option<Vec::<AdapterOverview>>):

    A list of adapters that matches the filtering criteria specified when calling ListAdapters.

  • next_token(Option<String>):

    Identifies the next page of results to return when listing adapters.

• On failure, responds with SdkError<ListAdaptersError>

impl Client

pub fn list_tags_for_resource(&self) -> ListTagsForResourceFluentBuilder

Constructs a fluent builder for the ListTagsForResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) that specifies the resource to list tags for.

    
    
• On success, responds with ListTagsForResourceOutput with field(s):
  • tags(Option<HashMap::<String, String>>):

    A set of tags (key-value pairs) that are part of the requested resource.

• On failure, responds with SdkError<ListTagsForResourceError>

impl Client

pub fn start_document_analysis(&self) -> StartDocumentAnalysisFluentBuilder

Constructs a fluent builder for the StartDocumentAnalysis operation.

• The fluent builder is configurable:
  • document_location(DocumentLocation) / set_document_location(Option<DocumentLocation>):
    required: true
    

    The location of the document to be processed.

    
    
  • feature_types(FeatureType) / set_feature_types(Option<Vec::<FeatureType>>):
    required: true
    

    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(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    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(impl Into<String>) / set_job_tag(Option<String>):
    required: false
    

    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(NotificationChannel) / set_notification_channel(Option<NotificationChannel>):
    required: false
    

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

    
    
  • output_config(OutputConfig) / set_output_config(Option<OutputConfig>):
    required: false
    

    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(impl Into<String>) / set_kms_key_id(Option<String>):
    required: false
    

    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(QueriesConfig) / set_queries_config(Option<QueriesConfig>):
    required: false
    
    
    
  • adapters_config(AdaptersConfig) / set_adapters_config(Option<AdaptersConfig>):
    required: false
    

    Specifies the adapter to be used when analyzing a document.

    
    
• On success, responds with StartDocumentAnalysisOutput with field(s):
  • job_id(Option<String>):

    The identifier for the document text detection job. Use JobId to identify the job in a subsequent call to GetDocumentAnalysis. A JobId value is only valid for 7 days.

• On failure, responds with SdkError<StartDocumentAnalysisError>

impl Client

pub fn start_document_text_detection( &self, ) -> StartDocumentTextDetectionFluentBuilder

Constructs a fluent builder for the StartDocumentTextDetection operation.

• The fluent builder is configurable:
  • document_location(DocumentLocation) / set_document_location(Option<DocumentLocation>):
    required: true
    

    The location of the document to be processed.

    
    
  • client_request_token(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    The idempotent token that’s used to identify the start request. If you use the same token with multiple StartDocumentTextDetection 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(impl Into<String>) / set_job_tag(Option<String>):
    required: false
    

    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(NotificationChannel) / set_notification_channel(Option<NotificationChannel>):
    required: false
    

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

    
    
  • output_config(OutputConfig) / set_output_config(Option<OutputConfig>):
    required: false
    

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

    
    
  • kms_key_id(impl Into<String>) / set_kms_key_id(Option<String>):
    required: false
    

    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.

    
    
• On success, responds with StartDocumentTextDetectionOutput with field(s):
  • job_id(Option<String>):

    The identifier of the text detection job for the document. Use JobId to identify the job in a subsequent call to GetDocumentTextDetection. A JobId value is only valid for 7 days.

• On failure, responds with SdkError<StartDocumentTextDetectionError>

impl Client

pub fn start_expense_analysis(&self) -> StartExpenseAnalysisFluentBuilder

Constructs a fluent builder for the StartExpenseAnalysis operation.

• The fluent builder is configurable:
  • document_location(DocumentLocation) / set_document_location(Option<DocumentLocation>):
    required: true
    

    The location of the document to be processed.

    
    
  • client_request_token(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    The idempotent token that’s used to identify the start request. If you use the same token with multiple StartDocumentTextDetection 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(impl Into<String>) / set_job_tag(Option<String>):
    required: false
    

    An identifier 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(NotificationChannel) / set_notification_channel(Option<NotificationChannel>):
    required: false
    

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

    
    
  • output_config(OutputConfig) / set_output_config(Option<OutputConfig>):
    required: false
    

    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 GetExpenseAnalysis operation.

    
    
  • kms_key_id(impl Into<String>) / set_kms_key_id(Option<String>):
    required: false
    

    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.

    
    
• On success, responds with StartExpenseAnalysisOutput with field(s):
  • job_id(Option<String>):

    A unique identifier for the text detection job. The JobId is returned from StartExpenseAnalysis. A JobId value is only valid for 7 days.

• On failure, responds with SdkError<StartExpenseAnalysisError>

impl Client

pub fn start_lending_analysis(&self) -> StartLendingAnalysisFluentBuilder

Constructs a fluent builder for the StartLendingAnalysis operation.

• The fluent builder is configurable:
  • document_location(DocumentLocation) / set_document_location(Option<DocumentLocation>):
    required: true
    

    The Amazon S3 bucket that contains the document to be processed. It’s used by asynchronous operations.

    The input document can be an image file in JPEG or PNG format. It can also be a file in PDF format.

    
    
  • client_request_token(impl Into<String>) / set_client_request_token(Option<String>):
    required: false
    

    The idempotent token that you use to identify the start request. If you use the same token with multiple StartLendingAnalysis 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(impl Into<String>) / set_job_tag(Option<String>):
    required: false
    

    An identifier that you specify to be 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(NotificationChannel) / set_notification_channel(Option<NotificationChannel>):
    required: false
    

    The Amazon Simple Notification Service (Amazon SNS) topic to which Amazon Textract publishes the completion status of an asynchronous document operation.

    
    
  • output_config(OutputConfig) / set_output_config(Option<OutputConfig>):
    required: false
    

    Sets whether or not your output will go to a user created bucket. Used to set the name of the bucket, and the prefix on the output file.

    OutputConfig is an optional parameter which lets you adjust where your output will be placed. By default, Amazon Textract will store the results internally and can only be accessed by the Get API operations. With OutputConfig enabled, you can set the name of the bucket the output will be sent to the file prefix of the results where you can download your results. Additionally, you can set the KMSKeyID parameter to a customer master key (CMK) to encrypt your output. Without this parameter set Amazon Textract will encrypt server-side using the AWS managed CMK for Amazon S3.

    Decryption of Customer Content is necessary for processing of the documents by Amazon Textract. If your account is opted out under an AI services opt out policy then all unencrypted Customer Content is immediately and permanently deleted after the Customer Content has been processed by the service. No copy of of the output is retained by Amazon Textract. For information about how to opt out, see Managing AI services opt-out policy.

    For more information on data privacy, see the Data Privacy FAQ.

    
    
  • kms_key_id(impl Into<String>) / set_kms_key_id(Option<String>):
    required: false
    

    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.

    
    
• On success, responds with StartLendingAnalysisOutput with field(s):
  • job_id(Option<String>):

    A unique identifier for the lending or text-detection job. The JobId is returned from StartLendingAnalysis. A JobId value is only valid for 7 days.

• On failure, responds with SdkError<StartLendingAnalysisError>

impl Client

pub fn tag_resource(&self) -> TagResourceFluentBuilder

Constructs a fluent builder for the TagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) that specifies the resource to be tagged.

    
    
  • tags(impl Into<String>, impl Into<String>) / set_tags(Option<HashMap::<String, String>>):
    required: true
    

    A set of tags (key-value pairs) that you want to assign to the resource.

    
    
• On success, responds with TagResourceOutput
• On failure, responds with SdkError<TagResourceError>

impl Client

pub fn untag_resource(&self) -> UntagResourceFluentBuilder

Constructs a fluent builder for the UntagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) that specifies the resource to be untagged.

    
    
  • tag_keys(impl Into<String>) / set_tag_keys(Option<Vec::<String>>):
    required: true
    

    Specifies the tags to be removed from the resource specified by the ResourceARN.

    
    
• On success, responds with UntagResourceOutput
• On failure, responds with SdkError<UntagResourceError>

impl Client

pub fn update_adapter(&self) -> UpdateAdapterFluentBuilder

Constructs a fluent builder for the UpdateAdapter operation.

• The fluent builder is configurable:
  • adapter_id(impl Into<String>) / set_adapter_id(Option<String>):
    required: true
    

    A string containing a unique ID for the adapter that will be updated.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    The new description to be applied to the adapter.

    
    
  • adapter_name(impl Into<String>) / set_adapter_name(Option<String>):
    required: false
    

    The new name to be applied to the adapter.

    
    
  • auto_update(AutoUpdate) / set_auto_update(Option<AutoUpdate>):
    required: false
    

    The new auto-update status to be applied to the adapter.

    
    
• On success, responds with UpdateAdapterOutput with field(s):
  • adapter_id(Option<String>):

    A string containing a unique ID for the adapter that has been updated.

  • adapter_name(Option<String>):

    A string containing the name of the adapter that has been updated.

  • creation_time(Option<DateTime>):

    An object specifying the creation time of the the adapter that has been updated.

  • description(Option<String>):

    A string containing the description of the adapter that has been updated.

  • feature_types(Option<Vec::<FeatureType>>):

    List of the targeted feature types for the updated adapter.

  • auto_update(Option<AutoUpdate>):

    The auto-update status of the adapter that has been updated.

• On failure, responds with SdkError<UpdateAdapterError>

impl Client

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Panics

This method will panic in the following cases:

• Retries or timeouts are enabled without a sleep_impl configured.
• Identity caching is enabled without a sleep_impl and time_source configured.
• No behavior_version is provided.

The panic message for each of these will have instructions on how to resolve them.

pub fn config(&self) -> &Config

Returns the client’s configuration.

impl Client

pub fn new(sdk_config: &SdkConfig) -> Self

Creates a new client from an SDK Config.

Panics

• This method will panic if the sdk_config is missing an async sleep implementation. If you experience this panic, set the sleep_impl on the Config passed into this function to fix it.
• This method will panic if the sdk_config is missing an HTTP connector. If you experience this panic, set the http_connector on the Config passed into this function to fix it.
• This method will panic if no BehaviorVersion is provided. If you experience this panic, set behavior_version on the Config or enable the behavior-version-latest Cargo feature.

Trait Implementations

impl Clone for Client

fn clone(&self) -> Client

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Client

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

Formats the value using the given formatter.