Struct aws_sdk_comprehend::client::Client

pub struct Client<C = DynConnector, M = DefaultMiddleware, R = Standard> { /* private fields */ }

Client for Amazon Comprehend

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

Examples

Constructing a client and invoking an operation

    // create a shared configuration. This can be used & shared between multiple service clients.
    let shared_config = aws_config::load_from_env().await;
    let client = aws_sdk_comprehend::Client::new(&shared_config);
    // invoke an operation
    /* let rsp = client
        .<operation_name>().
        .<param>("some value")
        .send().await; */

Constructing a client with custom configuration

use aws_config::RetryConfig;
    let shared_config = aws_config::load_from_env().await;
    let config = aws_sdk_comprehend::config::Builder::from(&shared_config)
        .retry_config(RetryConfig::disabled())
        .build();
    let client = aws_sdk_comprehend::Client::from_conf(config);

Implementations

impl<C, M, R> Client<C, M, R>

pub fn with_config(client: Client<C, M, R>, conf: Config) -> Self

Creates a client with the given service configuration.

pub fn conf(&self) -> &Config

Returns the client’s configuration.

impl<C, M, R> Client<C, M, R> where
    C: SmithyConnector,
    M: SmithyMiddleware<C>,
    R: NewRequestPolicy, 

pub fn batch_detect_dominant_language(
    &self
) -> BatchDetectDominantLanguage<C, M, R>

Constructs a fluent builder for the BatchDetectDominantLanguage operation.

• The fluent builder is configurable:
  • text_list(Vec<String>) / set_text_list(Option<Vec<String>>):

    A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document should contain at least 20 characters and must contain fewer than 5,000 bytes of UTF-8 encoded characters.

• On success, responds with BatchDetectDominantLanguageOutput with field(s):
  • result_list(Option<Vec<BatchDetectDominantLanguageItemResult>>):

    A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.

  • error_list(Option<Vec<BatchItemError>>):

    A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.

• On failure, responds with SdkError<BatchDetectDominantLanguageError>

pub fn batch_detect_entities(&self) -> BatchDetectEntities<C, M, R>

Constructs a fluent builder for the BatchDetectEntities operation.

• The fluent builder is configurable:
  • text_list(Vec<String>) / set_text_list(Option<Vec<String>>):

    A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document must contain fewer than 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

• On success, responds with BatchDetectEntitiesOutput with field(s):
  • result_list(Option<Vec<BatchDetectEntitiesItemResult>>):

    A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.

  • error_list(Option<Vec<BatchItemError>>):

    A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.

• On failure, responds with SdkError<BatchDetectEntitiesError>

pub fn batch_detect_key_phrases(&self) -> BatchDetectKeyPhrases<C, M, R>

Constructs a fluent builder for the BatchDetectKeyPhrases operation.

• The fluent builder is configurable:
  • text_list(Vec<String>) / set_text_list(Option<Vec<String>>):

    A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

• On success, responds with BatchDetectKeyPhrasesOutput with field(s):
  • result_list(Option<Vec<BatchDetectKeyPhrasesItemResult>>):

    A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.

  • error_list(Option<Vec<BatchItemError>>):

    A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.

• On failure, responds with SdkError<BatchDetectKeyPhrasesError>

pub fn batch_detect_sentiment(&self) -> BatchDetectSentiment<C, M, R>

Constructs a fluent builder for the BatchDetectSentiment operation.

• The fluent builder is configurable:
  • text_list(Vec<String>) / set_text_list(Option<Vec<String>>):

    A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

• On success, responds with BatchDetectSentimentOutput with field(s):
  • result_list(Option<Vec<BatchDetectSentimentItemResult>>):

    A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.

  • error_list(Option<Vec<BatchItemError>>):

    A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.

• On failure, responds with SdkError<BatchDetectSentimentError>

pub fn batch_detect_syntax(&self) -> BatchDetectSyntax<C, M, R>

Constructs a fluent builder for the BatchDetectSyntax operation.

• The fluent builder is configurable:
  • text_list(Vec<String>) / set_text_list(Option<Vec<String>>):

    A list containing the text of the input documents. The list can contain a maximum of 25 documents. Each document must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(SyntaxLanguageCode) / set_language_code(Option<SyntaxLanguageCode>):

    The language of the input documents. You can specify any of the following languages supported by Amazon Comprehend: German (“de”), English (“en”), Spanish (“es”), French (“fr”), Italian (“it”), or Portuguese (“pt”). All documents must be in the same language.

• On success, responds with BatchDetectSyntaxOutput with field(s):
  • result_list(Option<Vec<BatchDetectSyntaxItemResult>>):

    A list of objects containing the results of the operation. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If all of the documents contain an error, the ResultList is empty.

  • error_list(Option<Vec<BatchItemError>>):

    A list containing one object for each document that contained an error. The results are sorted in ascending order by the Index field and match the order of the documents in the input list. If there are no errors in the batch, the ErrorList is empty.

• On failure, responds with SdkError<BatchDetectSyntaxError>

pub fn classify_document(&self) -> ClassifyDocument<C, M, R>

Constructs a fluent builder for the ClassifyDocument operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    The document text to be analyzed.

  • endpoint_arn(impl Into<String>) / set_endpoint_arn(Option<String>):

    The Amazon Resource Number (ARN) of the endpoint.

• On success, responds with ClassifyDocumentOutput with field(s):
  • classes(Option<Vec<DocumentClass>>):

    The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

  • labels(Option<Vec<DocumentLabel>>):

    The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

• On failure, responds with SdkError<ClassifyDocumentError>

pub fn contains_pii_entities(&self) -> ContainsPiiEntities<C, M, R>

Constructs a fluent builder for the ContainsPiiEntities operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    Creates a new document classification request to analyze a single document in real-time, returning personally identifiable information (PII) entity labels.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents.

• On success, responds with ContainsPiiEntitiesOutput with field(s):
  • labels(Option<Vec<EntityLabel>>):

    The labels used in the document being analyzed. Individual labels represent personally identifiable information (PII) entity types.

• On failure, responds with SdkError<ContainsPiiEntitiesError>

pub fn create_document_classifier(&self) -> CreateDocumentClassifier<C, M, R>

Constructs a fluent builder for the CreateDocumentClassifier operation.

• The fluent builder is configurable:
  • document_classifier_name(impl Into<String>) / set_document_classifier_name(Option<String>):

    The name of the document classifier.

  • version_name(impl Into<String>) / set_version_name(Option<String>):

    The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the account/AWS Region.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the document classifier being created. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

  • input_data_config(DocumentClassifierInputDataConfig) / set_input_data_config(Option<DocumentClassifierInputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(DocumentClassifierOutputDataConfig) / set_output_data_config(Option<DocumentClassifierOutputDataConfig>):

    Enables the addition of output results configuration parameters for custom classifier jobs.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the following languages supported by Amazon Comprehend: German (“de”), English (“en”), Spanish (“es”), French (“fr”), Italian (“it”), or Portuguese (“pt”). All documents must be in the same language.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see Amazon VPC.

  • mode(DocumentClassifierMode) / set_mode(Option<DocumentClassifierMode>):

    Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class mode, which identifies one and only one class for each document, or multi-label mode, which identifies one or more labels for each document. In multi-label mode, multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).

  • model_kms_key_id(impl Into<String>) / set_model_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

• On success, responds with CreateDocumentClassifierOutput with field(s):
  • document_classifier_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the document classifier.

• On failure, responds with SdkError<CreateDocumentClassifierError>

pub fn create_endpoint(&self) -> CreateEndpoint<C, M, R>

Constructs a fluent builder for the CreateEndpoint operation.

• The fluent builder is configurable:
  • endpoint_name(impl Into<String>) / set_endpoint_name(Option<String>):

    This is the descriptive suffix that becomes part of the EndpointArn used for all subsequent requests to this resource.

  • model_arn(impl Into<String>) / set_model_arn(Option<String>):

    The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.

  • desired_inference_units(i32) / set_desired_inference_units(Option<i32>):

    The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.

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

    An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a ResourceInUseException.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags associated with the endpoint being created. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with “Sales” as the key might be added to an endpoint to indicate its use by the sales department.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS identity and Access Management (IAM) role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).

• On success, responds with CreateEndpointOutput with field(s):
  • endpoint_arn(Option<String>):

    The Amazon Resource Number (ARN) of the endpoint being created.

• On failure, responds with SdkError<CreateEndpointError>

pub fn create_entity_recognizer(&self) -> CreateEntityRecognizer<C, M, R>

Constructs a fluent builder for the CreateEntityRecognizer operation.

• The fluent builder is configurable:
  • recognizer_name(impl Into<String>) / set_recognizer_name(Option<String>):

    The name given to the newly created recognizer. Recognizer names can be a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The name must be unique in the account/region.

  • version_name(impl Into<String>) / set_version_name(Option<String>):

    The version name given to the newly created recognizer. Version names can be a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same recognizer name in the account/ AWS Region.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM) role that grants Amazon Comprehend read access to your input data.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the entity recognizer being created. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

  • input_data_config(EntityRecognizerInputDataConfig) / set_input_data_config(Option<EntityRecognizerInputDataConfig>):

    Specifies the format and location of the input data. The S3 bucket containing the input data must be located in the same region as the entity recognizer being created.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    You can specify any of the following languages supported by Amazon Comprehend: English (“en”), Spanish (“es”), French (“fr”), Italian (“it”), German (“de”), or Portuguese (“pt”). All documents must be in the same language.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom entity recognizer. For more information, see Amazon VPC.

  • model_kms_key_id(impl Into<String>) / set_model_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

• On success, responds with CreateEntityRecognizerOutput with field(s):
  • entity_recognizer_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the entity recognizer.

• On failure, responds with SdkError<CreateEntityRecognizerError>

pub fn delete_document_classifier(&self) -> DeleteDocumentClassifier<C, M, R>

Constructs a fluent builder for the DeleteDocumentClassifier operation.

• The fluent builder is configurable:
  • document_classifier_arn(impl Into<String>) / set_document_classifier_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the document classifier.

• On success, responds with DeleteDocumentClassifierOutput
• On failure, responds with SdkError<DeleteDocumentClassifierError>

pub fn delete_endpoint(&self) -> DeleteEndpoint<C, M, R>

Constructs a fluent builder for the DeleteEndpoint operation.

• The fluent builder is configurable:
  • endpoint_arn(impl Into<String>) / set_endpoint_arn(Option<String>):

    The Amazon Resource Number (ARN) of the endpoint being deleted.

• On success, responds with DeleteEndpointOutput
• On failure, responds with SdkError<DeleteEndpointError>

pub fn delete_entity_recognizer(&self) -> DeleteEntityRecognizer<C, M, R>

Constructs a fluent builder for the DeleteEntityRecognizer operation.

• The fluent builder is configurable:
  • entity_recognizer_arn(impl Into<String>) / set_entity_recognizer_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the entity recognizer.

• On success, responds with DeleteEntityRecognizerOutput
• On failure, responds with SdkError<DeleteEntityRecognizerError>

pub fn describe_document_classification_job(
    &self
) -> DescribeDocumentClassificationJob<C, M, R>

Constructs a fluent builder for the DescribeDocumentClassificationJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribeDocumentClassificationJobOutput with field(s):
  • document_classification_job_properties(Option<DocumentClassificationJobProperties>):

    An object that describes the properties associated with the document classification job.

• On failure, responds with SdkError<DescribeDocumentClassificationJobError>

pub fn describe_document_classifier(
    &self
) -> DescribeDocumentClassifier<C, M, R>

Constructs a fluent builder for the DescribeDocumentClassifier operation.

• The fluent builder is configurable:
  • document_classifier_arn(impl Into<String>) / set_document_classifier_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the document classifier. The operation returns this identifier in its response.

• On success, responds with DescribeDocumentClassifierOutput with field(s):
  • document_classifier_properties(Option<DocumentClassifierProperties>):

    An object that contains the properties associated with a document classifier.

• On failure, responds with SdkError<DescribeDocumentClassifierError>

pub fn describe_dominant_language_detection_job(
    &self
) -> DescribeDominantLanguageDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeDominantLanguageDetectionJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribeDominantLanguageDetectionJobOutput with field(s):
  • dominant_language_detection_job_properties(Option<DominantLanguageDetectionJobProperties>):

    An object that contains the properties associated with a dominant language detection job.

• On failure, responds with SdkError<DescribeDominantLanguageDetectionJobError>

pub fn describe_endpoint(&self) -> DescribeEndpoint<C, M, R>

Constructs a fluent builder for the DescribeEndpoint operation.

• The fluent builder is configurable:
  • endpoint_arn(impl Into<String>) / set_endpoint_arn(Option<String>):

    The Amazon Resource Number (ARN) of the endpoint being described.

• On success, responds with DescribeEndpointOutput with field(s):
  • endpoint_properties(Option<EndpointProperties>):

    Describes information associated with the specific endpoint.

• On failure, responds with SdkError<DescribeEndpointError>

pub fn describe_entities_detection_job(
    &self
) -> DescribeEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeEntitiesDetectionJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribeEntitiesDetectionJobOutput with field(s):
  • entities_detection_job_properties(Option<EntitiesDetectionJobProperties>):

    An object that contains the properties associated with an entities detection job.

• On failure, responds with SdkError<DescribeEntitiesDetectionJobError>

pub fn describe_entity_recognizer(&self) -> DescribeEntityRecognizer<C, M, R>

Constructs a fluent builder for the DescribeEntityRecognizer operation.

• The fluent builder is configurable:
  • entity_recognizer_arn(impl Into<String>) / set_entity_recognizer_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the entity recognizer.

• On success, responds with DescribeEntityRecognizerOutput with field(s):
  • entity_recognizer_properties(Option<EntityRecognizerProperties>):

    Describes information associated with an entity recognizer.

• On failure, responds with SdkError<DescribeEntityRecognizerError>

pub fn describe_events_detection_job(
    &self
) -> DescribeEventsDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeEventsDetectionJob operation.

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

    The identifier of the events detection job.

• On success, responds with DescribeEventsDetectionJobOutput with field(s):
  • events_detection_job_properties(Option<EventsDetectionJobProperties>):

    An object that contains the properties associated with an event detection job.

• On failure, responds with SdkError<DescribeEventsDetectionJobError>

pub fn describe_key_phrases_detection_job(
    &self
) -> DescribeKeyPhrasesDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeKeyPhrasesDetectionJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribeKeyPhrasesDetectionJobOutput with field(s):
  • key_phrases_detection_job_properties(Option<KeyPhrasesDetectionJobProperties>):

    An object that contains the properties associated with a key phrases detection job.

• On failure, responds with SdkError<DescribeKeyPhrasesDetectionJobError>

pub fn describe_pii_entities_detection_job(
    &self
) -> DescribePiiEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the DescribePiiEntitiesDetectionJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribePiiEntitiesDetectionJobOutput with field(s):
  • pii_entities_detection_job_properties(Option<PiiEntitiesDetectionJobProperties>):

    Provides information about a PII entities detection job.

• On failure, responds with SdkError<DescribePiiEntitiesDetectionJobError>

pub fn describe_sentiment_detection_job(
    &self
) -> DescribeSentimentDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeSentimentDetectionJob operation.

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

    The identifier that Amazon Comprehend generated for the job. The operation returns this identifier in its response.

• On success, responds with DescribeSentimentDetectionJobOutput with field(s):
  • sentiment_detection_job_properties(Option<SentimentDetectionJobProperties>):

    An object that contains the properties associated with a sentiment detection job.

• On failure, responds with SdkError<DescribeSentimentDetectionJobError>

pub fn describe_topics_detection_job(
    &self
) -> DescribeTopicsDetectionJob<C, M, R>

Constructs a fluent builder for the DescribeTopicsDetectionJob operation.

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

    The identifier assigned by the user to the detection job.

• On success, responds with DescribeTopicsDetectionJobOutput with field(s):
  • topics_detection_job_properties(Option<TopicsDetectionJobProperties>):

    The list of properties for the requested job.

• On failure, responds with SdkError<DescribeTopicsDetectionJobError>

pub fn detect_dominant_language(&self) -> DetectDominantLanguage<C, M, R>

Constructs a fluent builder for the DetectDominantLanguage operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 text string. Each string should contain at least 20 characters and must contain fewer that 5,000 bytes of UTF-8 encoded characters.

• On success, responds with DetectDominantLanguageOutput with field(s):
  • languages(Option<Vec<DominantLanguage>>):

    The languages that Amazon Comprehend detected in the input text. For each language, the response returns the RFC 5646 language code and the level of confidence that Amazon Comprehend has in the accuracy of its inference. For more information about RFC 5646, see Tags for Identifying Languages on the IETF Tools web site.

• On failure, responds with SdkError<DetectDominantLanguageError>

pub fn detect_entities(&self) -> DetectEntities<C, M, R>

Constructs a fluent builder for the DetectEntities operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

    If your request includes the endpoint for a custom entity recognition model, Amazon Comprehend uses the language of your custom model, and it ignores any language code that you specify here.

  • endpoint_arn(impl Into<String>) / set_endpoint_arn(Option<String>):

    The Amazon Resource Name of an endpoint that is associated with a custom entity recognition model. Provide an endpoint if you want to detect entities by using your own custom model instead of the default model that is used by Amazon Comprehend.

    If you specify an endpoint, Amazon Comprehend uses the language of your custom model, and it ignores any language code that you provide in your request.

• On success, responds with DetectEntitiesOutput with field(s):
  • entities(Option<Vec<Entity>>):

    A collection of entities identified in the input text. For each entity, the response provides the entity text, entity type, where the entity text begins and ends, and the level of confidence that Amazon Comprehend has in the detection.

    If your request uses a custom entity recognition model, Amazon Comprehend detects the entities that the model is trained to recognize. Otherwise, it detects the default entity types. For a list of default entity types, see how-entities.

• On failure, responds with SdkError<DetectEntitiesError>

pub fn detect_key_phrases(&self) -> DetectKeyPhrases<C, M, R>

Constructs a fluent builder for the DetectKeyPhrases operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

• On success, responds with DetectKeyPhrasesOutput with field(s):
  • key_phrases(Option<Vec<KeyPhrase>>):

    A collection of key phrases that Amazon Comprehend identified in the input text. For each key phrase, the response provides the text of the key phrase, where the key phrase begins and ends, and the level of confidence that Amazon Comprehend has in the accuracy of the detection.

• On failure, responds with SdkError<DetectKeyPhrasesError>

pub fn detect_pii_entities(&self) -> DetectPiiEntities<C, M, R>

Constructs a fluent builder for the DetectPiiEntities operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents.

• On success, responds with DetectPiiEntitiesOutput with field(s):
  • entities(Option<Vec<PiiEntity>>):

    A collection of PII entities identified in the input text. For each entity, the response provides the entity type, where the entity text begins and ends, and the level of confidence that Amazon Comprehend has in the detection.

• On failure, responds with SdkError<DetectPiiEntitiesError>

pub fn detect_sentiment(&self) -> DetectSentiment<C, M, R>

Constructs a fluent builder for the DetectSentiment operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 text string. Each string must contain fewer that 5,000 bytes of UTF-8 encoded characters.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

• On success, responds with DetectSentimentOutput with field(s):
  • sentiment(Option<SentimentType>):

    The inferred sentiment that Amazon Comprehend has the highest level of confidence in.

  • sentiment_score(Option<SentimentScore>):

    An object that lists the sentiments, and their corresponding confidence levels.

• On failure, responds with SdkError<DetectSentimentError>

pub fn detect_syntax(&self) -> DetectSyntax<C, M, R>

Constructs a fluent builder for the DetectSyntax operation.

• The fluent builder is configurable:
  • text(impl Into<String>) / set_text(Option<String>):

    A UTF-8 string. Each string must contain fewer that 5,000 bytes of UTF encoded characters.

  • language_code(SyntaxLanguageCode) / set_language_code(Option<SyntaxLanguageCode>):

    The language code of the input documents. You can specify any of the following languages supported by Amazon Comprehend: German (“de”), English (“en”), Spanish (“es”), French (“fr”), Italian (“it”), or Portuguese (“pt”).

• On success, responds with DetectSyntaxOutput with field(s):
  • syntax_tokens(Option<Vec<SyntaxToken>>):

    A collection of syntax tokens describing the text. For each token, the response provides the text, the token type, where the text begins and ends, and the level of confidence that Amazon Comprehend has that the token is correct. For a list of token types, see how-syntax.

• On failure, responds with SdkError<DetectSyntaxError>

pub fn list_document_classification_jobs(
    &self
) -> ListDocumentClassificationJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(DocumentClassificationJobFilter) / set_filter(Option<DocumentClassificationJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their names, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListDocumentClassificationJobsOutput with field(s):
  • document_classification_job_properties_list(Option<Vec<DocumentClassificationJobProperties>>):

    A list containing the properties of each job returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListDocumentClassificationJobsError>

pub fn list_document_classifiers(&self) -> ListDocumentClassifiers<C, M, R>

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

• The fluent builder is configurable:
  • filter(DocumentClassifierFilter) / set_filter(Option<DocumentClassifierFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListDocumentClassifiersOutput with field(s):
  • document_classifier_properties_list(Option<Vec<DocumentClassifierProperties>>):

    A list containing the properties of each job returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListDocumentClassifiersError>

pub fn list_document_classifier_summaries(
    &self
) -> ListDocumentClassifierSummaries<C, M, R>

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

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):

    Identifies the next page of results to return.

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

    The maximum number of results to return on each page. The default is 100.

• On success, responds with ListDocumentClassifierSummariesOutput with field(s):
  • document_classifier_summaries_list(Option<Vec<DocumentClassifierSummary>>):

    The list of summaries of document classifiers.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListDocumentClassifierSummariesError>

pub fn list_dominant_language_detection_jobs(
    &self
) -> ListDominantLanguageDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(DominantLanguageDetectionJobFilter) / set_filter(Option<DominantLanguageDetectionJobFilter>):

    Filters that jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListDominantLanguageDetectionJobsOutput with field(s):
  • dominant_language_detection_job_properties_list(Option<Vec<DominantLanguageDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListDominantLanguageDetectionJobsError>

pub fn list_endpoints(&self) -> ListEndpoints<C, M, R>

Constructs a fluent builder for the ListEndpoints operation.

• The fluent builder is configurable:
  • filter(EndpointFilter) / set_filter(Option<EndpointFilter>):

    Filters the endpoints that are returned. You can filter endpoints on their name, model, status, or the date and time that they were created. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListEndpointsOutput with field(s):
  • endpoint_properties_list(Option<Vec<EndpointProperties>>):

    Displays a list of endpoint properties being retrieved by the service in response to the request.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListEndpointsError>

pub fn list_entities_detection_jobs(&self) -> ListEntitiesDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(EntitiesDetectionJobFilter) / set_filter(Option<EntitiesDetectionJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListEntitiesDetectionJobsOutput with field(s):
  • entities_detection_job_properties_list(Option<Vec<EntitiesDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListEntitiesDetectionJobsError>

pub fn list_entity_recognizers(&self) -> ListEntityRecognizers<C, M, R>

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

• The fluent builder is configurable:
  • filter(EntityRecognizerFilter) / set_filter(Option<EntityRecognizerFilter>):

    Filters the list of entities returned. You can filter on Status, SubmitTimeBefore, or SubmitTimeAfter. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return on each page. The default is 100.

• On success, responds with ListEntityRecognizersOutput with field(s):
  • entity_recognizer_properties_list(Option<Vec<EntityRecognizerProperties>>):

    The list of properties of an entity recognizer.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListEntityRecognizersError>

pub fn list_entity_recognizer_summaries(
    &self
) -> ListEntityRecognizerSummaries<C, M, R>

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

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):

    Identifies the next page of results to return.

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

    The maximum number of results to return on each page. The default is 100.

• On success, responds with ListEntityRecognizerSummariesOutput with field(s):
  • entity_recognizer_summaries_list(Option<Vec<EntityRecognizerSummary>>):

    The list entity recognizer summaries.

  • next_token(Option<String>):

    The list entity recognizer summaries.

• On failure, responds with SdkError<ListEntityRecognizerSummariesError>

pub fn list_events_detection_jobs(&self) -> ListEventsDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(EventsDetectionJobFilter) / set_filter(Option<EventsDetectionJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page.

• On success, responds with ListEventsDetectionJobsOutput with field(s):
  • events_detection_job_properties_list(Option<Vec<EventsDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListEventsDetectionJobsError>

pub fn list_key_phrases_detection_jobs(
    &self
) -> ListKeyPhrasesDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(KeyPhrasesDetectionJobFilter) / set_filter(Option<KeyPhrasesDetectionJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListKeyPhrasesDetectionJobsOutput with field(s):
  • key_phrases_detection_job_properties_list(Option<Vec<KeyPhrasesDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListKeyPhrasesDetectionJobsError>

pub fn list_pii_entities_detection_jobs(
    &self
) -> ListPiiEntitiesDetectionJobs<C, M, R>

Constructs a fluent builder for the ListPiiEntitiesDetectionJobs operation.

• The fluent builder is configurable:
  • filter(PiiEntitiesDetectionJobFilter) / set_filter(Option<PiiEntitiesDetectionJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page.

• On success, responds with ListPiiEntitiesDetectionJobsOutput with field(s):
  • pii_entities_detection_job_properties_list(Option<Vec<PiiEntitiesDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListPiiEntitiesDetectionJobsError>

pub fn list_sentiment_detection_jobs(
    &self
) -> ListSentimentDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(SentimentDetectionJobFilter) / set_filter(Option<SentimentDetectionJobFilter>):

    Filters the jobs that are returned. You can filter jobs on their name, status, or the date and time that they were submitted. You can only set one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListSentimentDetectionJobsOutput with field(s):
  • sentiment_detection_job_properties_list(Option<Vec<SentimentDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListSentimentDetectionJobsError>

pub fn list_tags_for_resource(&self) -> ListTagsForResource<C, M, R>

Constructs a fluent builder for the ListTagsForResource operation.

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

    The Amazon Resource Name (ARN) of the given Amazon Comprehend resource you are querying.

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

    The Amazon Resource Name (ARN) of the given Amazon Comprehend resource you are querying.

  • tags(Option<Vec<Tag>>):

    Tags associated with the Amazon Comprehend resource being queried. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

• On failure, responds with SdkError<ListTagsForResourceError>

pub fn list_topics_detection_jobs(&self) -> ListTopicsDetectionJobs<C, M, R>

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

• The fluent builder is configurable:
  • filter(TopicsDetectionJobFilter) / set_filter(Option<TopicsDetectionJobFilter>):

    Filters the jobs that are returned. Jobs can be filtered on their name, status, or the date and time that they were submitted. You can set only one filter at a time.

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

    Identifies the next page of results to return.

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

    The maximum number of results to return in each page. The default is 100.

• On success, responds with ListTopicsDetectionJobsOutput with field(s):
  • topics_detection_job_properties_list(Option<Vec<TopicsDetectionJobProperties>>):

    A list containing the properties of each job that is returned.

  • next_token(Option<String>):

    Identifies the next page of results to return.

• On failure, responds with SdkError<ListTopicsDetectionJobsError>

pub fn start_document_classification_job(
    &self
) -> StartDocumentClassificationJob<C, M, R>

Constructs a fluent builder for the StartDocumentClassificationJob operation.

• The fluent builder is configurable:
  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • document_classifier_arn(impl Into<String>) / set_document_classifier_arn(Option<String>):

    The Amazon Resource Name (ARN) of the document classifier to use to process the job.

  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.

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

    A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your document classification job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the document classification job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of the job, use this identifier with the operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the document classification job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :document-classification-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:document-classification-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job:

    • SUBMITTED - The job has been received and queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. For details, use the operation.

    • STOP_REQUESTED - Amazon Comprehend has received a stop request for the job and is processing the request.

    • STOPPED - The job was successfully stopped without completing.

• On failure, responds with SdkError<StartDocumentClassificationJobError>

pub fn start_dominant_language_detection_job(
    &self
) -> StartDominantLanguageDetectionJob<C, M, R>

Constructs a fluent builder for the StartDominantLanguageDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    An identifier for the job.

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

    A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your dominant language detection job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the dominant language detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of a job, use this identifier with the operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the dominant language detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :dominant-language-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:dominant-language-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job.

    • SUBMITTED - The job has been received and is queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. To get details, use the operation.

• On failure, responds with SdkError<StartDominantLanguageDetectionJobError>

pub fn start_entities_detection_job(&self) -> StartEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the StartEntitiesDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • entity_recognizer_arn(impl Into<String>) / set_entity_recognizer_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the specific entity recognizer to be used by the StartEntitiesDetectionJob. This ARN is optional and is only used for a custom entity recognition job.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. All documents must be in the same language. You can specify any of the languages supported by Amazon Comprehend. If custom entities recognition is used, this parameter is ignored and the language used for training the model is used instead.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your entity detection job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the entities detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of job, use this identifier with the operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the entities detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :entities-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:entities-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job.

    • SUBMITTED - The job has been received and is queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. To get details, use the operation.

    • STOP_REQUESTED - Amazon Comprehend has received a stop request for the job and is processing the request.

    • STOPPED - The job was successfully stopped without completing.

• On failure, responds with SdkError<StartEntitiesDetectionJobError>

pub fn start_events_detection_job(&self) -> StartEventsDetectionJob<C, M, R>

Constructs a fluent builder for the StartEventsDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the events detection job.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language code of the input documents.

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

    An unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • target_event_types(Vec<String>) / set_target_event_types(Option<Vec<String>>):

    The types of events to detect in the input documents.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the events detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    An unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the events detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :events-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:events-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the events detection job.

• On failure, responds with SdkError<StartEventsDetectionJobError>

pub fn start_key_phrases_detection_job(
    &self
) -> StartKeyPhrasesDetectionJob<C, M, R>

Constructs a fluent builder for the StartKeyPhrasesDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your key phrases detection job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the key phrases detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of a job, use this identifier with the operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the key phrase detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :key-phrases-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:key-phrases-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job.

    • SUBMITTED - The job has been received and is queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. To get details, use the operation.

• On failure, responds with SdkError<StartKeyPhrasesDetectionJobError>

pub fn start_pii_entities_detection_job(
    &self
) -> StartPiiEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the StartPiiEntitiesDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    The input properties for a PII entities detection job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Provides configuration parameters for the output of PII entity detection jobs.

  • mode(PiiEntitiesDetectionMode) / set_mode(Option<PiiEntitiesDetectionMode>):

    Specifies whether the output provides the locations (offsets) of PII entities or a file in which PII entities are redacted.

  • redaction_config(RedactionConfig) / set_redaction_config(Option<RedactionConfig>):

    Provides configuration parameters for PII entity redaction.

    This parameter is required if you set the Mode parameter to ONLY_REDACTION. In that case, you must provide a RedactionConfig definition that includes the PiiEntityTypes parameter.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the PII entities detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the PII entity detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :pii-entities-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:pii-entities-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job.

• On failure, responds with SdkError<StartPiiEntitiesDetectionJobError>

pub fn start_sentiment_detection_job(
    &self
) -> StartSentimentDetectionJob<C, M, R>

Constructs a fluent builder for the StartSentimentDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files.

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • language_code(LanguageCode) / set_language_code(Option<LanguageCode>):

    The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. All documents must be in the same language.

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

    A unique identifier for the request. If you don’t set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your sentiment detection job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the sentiment detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of a job, use this identifier with the operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the sentiment detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :sentiment-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:sentiment-detection-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job.

    • SUBMITTED - The job has been received and is queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. To get details, use the operation.

• On failure, responds with SdkError<StartSentimentDetectionJobError>

pub fn start_topics_detection_job(&self) -> StartTopicsDetectionJob<C, M, R>

Constructs a fluent builder for the StartTopicsDetectionJob operation.

• The fluent builder is configurable:
  • input_data_config(InputDataConfig) / set_input_data_config(Option<InputDataConfig>):

    Specifies the format and location of the input data for the job.

  • output_data_config(OutputDataConfig) / set_output_data_config(Option<OutputDataConfig>):

    Specifies where to send the output files. The output is a compressed archive with two files, topic-terms.csv that lists the terms associated with each topic, and doc-topics.csv that lists the documents associated with each topic

  • data_access_role_arn(impl Into<String>) / set_data_access_role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.

  • job_name(impl Into<String>) / set_job_name(Option<String>):

    The identifier of the job.

  • number_of_topics(i32) / set_number_of_topics(Option<i32>):

    The number of topics to detect.

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

    A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.

  • volume_kms_key_id(impl Into<String>) / set_volume_kms_key_id(Option<String>):

    ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:

    • KMS Key ID: “1234abcd-12ab-34cd-56ef-1234567890ab”

    • Amazon Resource Name (ARN) of a KMS Key: “arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”

  • vpc_config(VpcConfig) / set_vpc_config(Option<VpcConfig>):

    Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your topic detection job. For more information, see Amazon VPC.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags to be associated with the topics detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.

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

    The identifier generated for the job. To get the status of the job, use this identifier with the DescribeTopicDetectionJob operation.

  • job_arn(Option<String>):

    The Amazon Resource Name (ARN) of the topics detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:

    arn: :comprehend: : :topics-detection-job/

    The following is an example job ARN:

    arn:aws:comprehend:us-west-2:111122223333:document-classification-job/1234abcd12ab34cd56ef1234567890ab

  • job_status(Option<JobStatus>):

    The status of the job:

    • SUBMITTED - The job has been received and is queued for processing.

    • IN_PROGRESS - Amazon Comprehend is processing the job.

    • COMPLETED - The job was successfully completed and the output is available.

    • FAILED - The job did not complete. To get details, use the DescribeTopicDetectionJob operation.

• On failure, responds with SdkError<StartTopicsDetectionJobError>

pub fn stop_dominant_language_detection_job(
    &self
) -> StopDominantLanguageDetectionJob<C, M, R>

Constructs a fluent builder for the StopDominantLanguageDetectionJob operation.

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

    The identifier of the dominant language detection job to stop.

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

    The identifier of the dominant language detection job to stop.

  • job_status(Option<JobStatus>):

    Either STOP_REQUESTED if the job is currently running, or STOPPED if the job was previously stopped with the StopDominantLanguageDetectionJob operation.

• On failure, responds with SdkError<StopDominantLanguageDetectionJobError>

pub fn stop_entities_detection_job(&self) -> StopEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the StopEntitiesDetectionJob operation.

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

    The identifier of the entities detection job to stop.

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

    The identifier of the entities detection job to stop.

  • job_status(Option<JobStatus>):

    Either STOP_REQUESTED if the job is currently running, or STOPPED if the job was previously stopped with the StopEntitiesDetectionJob operation.

• On failure, responds with SdkError<StopEntitiesDetectionJobError>

pub fn stop_events_detection_job(&self) -> StopEventsDetectionJob<C, M, R>

Constructs a fluent builder for the StopEventsDetectionJob operation.

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

    The identifier of the events detection job to stop.

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

    The identifier of the events detection job to stop.

  • job_status(Option<JobStatus>):

    The status of the events detection job.

• On failure, responds with SdkError<StopEventsDetectionJobError>

pub fn stop_key_phrases_detection_job(
    &self
) -> StopKeyPhrasesDetectionJob<C, M, R>

Constructs a fluent builder for the StopKeyPhrasesDetectionJob operation.

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

    The identifier of the key phrases detection job to stop.

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

    The identifier of the key phrases detection job to stop.

  • job_status(Option<JobStatus>):

    Either STOP_REQUESTED if the job is currently running, or STOPPED if the job was previously stopped with the StopKeyPhrasesDetectionJob operation.

• On failure, responds with SdkError<StopKeyPhrasesDetectionJobError>

pub fn stop_pii_entities_detection_job(
    &self
) -> StopPiiEntitiesDetectionJob<C, M, R>

Constructs a fluent builder for the StopPiiEntitiesDetectionJob operation.

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

    The identifier of the PII entities detection job to stop.

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

    The identifier of the PII entities detection job to stop.

  • job_status(Option<JobStatus>):

    The status of the PII entities detection job.

• On failure, responds with SdkError<StopPiiEntitiesDetectionJobError>

pub fn stop_sentiment_detection_job(&self) -> StopSentimentDetectionJob<C, M, R>

Constructs a fluent builder for the StopSentimentDetectionJob operation.

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

    The identifier of the sentiment detection job to stop.

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

    The identifier of the sentiment detection job to stop.

  • job_status(Option<JobStatus>):

    Either STOP_REQUESTED if the job is currently running, or STOPPED if the job was previously stopped with the StopSentimentDetectionJob operation.

• On failure, responds with SdkError<StopSentimentDetectionJobError>

pub fn stop_training_document_classifier(
    &self
) -> StopTrainingDocumentClassifier<C, M, R>

Constructs a fluent builder for the StopTrainingDocumentClassifier operation.

• The fluent builder is configurable:
  • document_classifier_arn(impl Into<String>) / set_document_classifier_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the document classifier currently being trained.

• On success, responds with StopTrainingDocumentClassifierOutput
• On failure, responds with SdkError<StopTrainingDocumentClassifierError>

pub fn stop_training_entity_recognizer(
    &self
) -> StopTrainingEntityRecognizer<C, M, R>

Constructs a fluent builder for the StopTrainingEntityRecognizer operation.

• The fluent builder is configurable:
  • entity_recognizer_arn(impl Into<String>) / set_entity_recognizer_arn(Option<String>):

    The Amazon Resource Name (ARN) that identifies the entity recognizer currently being trained.

• On success, responds with StopTrainingEntityRecognizerOutput
• On failure, responds with SdkError<StopTrainingEntityRecognizerError>

pub fn tag_resource(&self) -> TagResource<C, M, R>

Constructs a fluent builder for the TagResource operation.

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

    The Amazon Resource Name (ARN) of the given Amazon Comprehend resource to which you want to associate the tags.

  • tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):

    Tags being associated with a specific Amazon Comprehend resource. There can be a maximum of 50 tags (both existing and pending) associated with a specific resource.

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

pub fn untag_resource(&self) -> UntagResource<C, M, R>

Constructs a fluent builder for the UntagResource operation.

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

    The Amazon Resource Name (ARN) of the given Amazon Comprehend resource from which you want to remove the tags.

  • tag_keys(Vec<String>) / set_tag_keys(Option<Vec<String>>):

    The initial part of a key-value pair that forms a tag being removed from a given resource. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department. Keys must be unique and cannot be duplicated for a particular resource.

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

pub fn update_endpoint(&self) -> UpdateEndpoint<C, M, R>

Constructs a fluent builder for the UpdateEndpoint operation.

• The fluent builder is configurable:
  • endpoint_arn(impl Into<String>) / set_endpoint_arn(Option<String>):

    The Amazon Resource Number (ARN) of the endpoint being updated.

  • desired_model_arn(impl Into<String>) / set_desired_model_arn(Option<String>):

    The ARN of the new model to use when updating an existing endpoint.

  • desired_inference_units(i32) / set_desired_inference_units(Option<i32>):

    The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.

  • desired_data_access_role_arn(impl Into<String>) / set_desired_data_access_role_arn(Option<String>):

    Data access role ARN to use in case the new model is encrypted with a customer CMK.

• On success, responds with UpdateEndpointOutput
• On failure, responds with SdkError<UpdateEndpointError>

impl<C> Client<C, DefaultMiddleware, Standard>

pub fn from_conf_conn(conf: Config, conn: C) -> Self

Creates a client with the given service config and connector override.

impl Client<DynConnector, DefaultMiddleware, Standard>

pub fn new(config: &Config) -> Self

Creates a new client from a shared config.

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Trait Implementations

impl<C, M, R> Clone for Client<C, M, R>

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<C: Debug, M: Debug, R: Debug> Debug for Client<C, M, R>

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

Formats the value using the given formatter.

impl<C, M, R> From<Client<C, M, R>> for Client<C, M, R>

fn from(client: Client<C, M, R>) -> Self

Performs the conversion.