Struct aws_sdk_frauddetector::Client

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pub struct Client { /* private fields */ }

Expand description

Client for Amazon Fraud Detector

Client for invoking operations on Amazon Fraud Detector. Each operation on Amazon Fraud Detector 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_frauddetector::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_frauddetector::config::Builder::from(&shared_config)
  .retry_config(RetryConfig::disabled())
  .build();
let client = aws_sdk_frauddetector::Client::from_conf(config);

Implementations

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impl Client

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pub fn with_config(
client: Client<DynConnector, DynMiddleware<DynConnector>>,
conf: Config
) -> Self

Creates a client with the given service configuration.

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pub fn conf(&self) -> &Config

Returns the client’s configuration.

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impl Client

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pub fn batch_create_variable(&self) -> BatchCreateVariable

Constructs a fluent builder for the BatchCreateVariable operation.

The fluent builder is configurable:
- variable_entries(Vec<VariableEntry>) / set_variable_entries(Option<Vec<VariableEntry>>):
 The list of variables for the batch create variable request.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with BatchCreateVariableOutput with field(s):
- errors(Option<Vec<BatchCreateVariableError>>):
 Provides the errors for the BatchCreateVariable request.
On failure, responds with SdkError<BatchCreateVariableError>

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pub fn batch_get_variable(&self) -> BatchGetVariable

Constructs a fluent builder for the BatchGetVariable operation.

The fluent builder is configurable:
- names(Vec<String>) / set_names(Option<Vec<String>>):
 The list of variable names to get.
On success, responds with BatchGetVariableOutput with field(s):
- variables(Option<Vec<Variable>>):
 The returned variables.
- errors(Option<Vec<BatchGetVariableError>>):
 The errors from the request.
On failure, responds with SdkError<BatchGetVariableError>

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pub fn cancel_batch_import_job(&self) -> CancelBatchImportJob

Constructs a fluent builder for the CancelBatchImportJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of an in-progress batch import job to cancel.
 
 Amazon Fraud Detector will throw an error if the batch import job is in FAILED, CANCELED, or COMPLETED state.
On success, responds with CancelBatchImportJobOutput
On failure, responds with SdkError<CancelBatchImportJobError>

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pub fn cancel_batch_prediction_job(&self) -> CancelBatchPredictionJob

Constructs a fluent builder for the CancelBatchPredictionJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch prediction job to cancel.
On success, responds with CancelBatchPredictionJobOutput
On failure, responds with SdkError<CancelBatchPredictionJobError>

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pub fn create_batch_import_job(&self) -> CreateBatchImportJob

Constructs a fluent builder for the CreateBatchImportJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch import job. The ID cannot be of a past job, unless the job exists in CREATE_FAILED state.
- input_path(impl Into<String>) / set_input_path(Option<String>):
 The URI that points to the Amazon S3 location of your data file.
- output_path(impl Into<String>) / set_output_path(Option<String>):
 The URI that points to the Amazon S3 location for storing your results.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
- iam_role_arn(impl Into<String>) / set_iam_role_arn(Option<String>):
 The ARN of the IAM role created for Amazon S3 bucket that holds your data file. The IAM role must have read and write permissions to both input and output S3 buckets.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key-value pairs associated with this request.
On success, responds with CreateBatchImportJobOutput
On failure, responds with SdkError<CreateBatchImportJobError>

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pub fn create_batch_prediction_job(&self) -> CreateBatchPredictionJob

Constructs a fluent builder for the CreateBatchPredictionJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch prediction job.
- input_path(impl Into<String>) / set_input_path(Option<String>):
 The Amazon S3 location of your training file.
- output_path(impl Into<String>) / set_output_path(Option<String>):
 The Amazon S3 location of your output file.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
- detector_name(impl Into<String>) / set_detector_name(Option<String>):
 The name of the detector.
- detector_version(impl Into<String>) / set_detector_version(Option<String>):
 The detector version.
- iam_role_arn(impl Into<String>) / set_iam_role_arn(Option<String>):
 The ARN of the IAM role to use for this job request.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateBatchPredictionJobOutput
On failure, responds with SdkError<CreateBatchPredictionJobError>

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pub fn create_detector_version(&self) -> CreateDetectorVersion

Constructs a fluent builder for the CreateDetectorVersion operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The ID of the detector under which you want to create a new version.
- description(impl Into<String>) / set_description(Option<String>):
 The description of the detector version.
- external_model_endpoints(Vec<String>) / set_external_model_endpoints(Option<Vec<String>>):
 The Amazon Sagemaker model endpoints to include in the detector version.
- rules(Vec<Rule>) / set_rules(Option<Vec<Rule>>):
 The rules to include in the detector version.
- model_versions(Vec<ModelVersion>) / set_model_versions(Option<Vec<ModelVersion>>):
 The model versions to include in the detector version.
- rule_execution_mode(RuleExecutionMode) / set_rule_execution_mode(Option<RuleExecutionMode>):
 The rule execution mode for the rules included in the detector version.
 
 You can define and edit the rule mode at the detector version level, when it is in draft status.
 
 If you specify FIRST_MATCHED, Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.
 
 If you specifiy ALL_MATCHED, Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules.
 
 The default behavior is FIRST_MATCHED.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateDetectorVersionOutput with field(s):
- detector_id(Option<String>):
 The ID for the created version’s parent detector.
- detector_version_id(Option<String>):
 The ID for the created detector.
- status(Option<DetectorVersionStatus>):
 The status of the detector version.
On failure, responds with SdkError<CreateDetectorVersionError>

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pub fn create_model(&self) -> CreateModel

Constructs a fluent builder for the CreateModel operation.

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type.
- description(impl Into<String>) / set_description(Option<String>):
 The model description.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateModelOutput
On failure, responds with SdkError<CreateModelError>

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pub fn create_model_version(&self) -> CreateModelVersion

Constructs a fluent builder for the CreateModelVersion operation.

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type.
- training_data_source(TrainingDataSourceEnum) / set_training_data_source(Option<TrainingDataSourceEnum>):
 The training data source location in Amazon S3.
- training_data_schema(TrainingDataSchema) / set_training_data_schema(Option<TrainingDataSchema>):
 The training data schema.
- external_events_detail(ExternalEventsDetail) / set_external_events_detail(Option<ExternalEventsDetail>):
 Details of the external events data used for model version training. Required if trainingDataSource is EXTERNAL_EVENTS.
- ingested_events_detail(IngestedEventsDetail) / set_ingested_events_detail(Option<IngestedEventsDetail>):
 Details of the ingested events data used for model version training. Required if trainingDataSource is INGESTED_EVENTS.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateModelVersionOutput with field(s):
- model_id(Option<String>):
 The model ID.
- model_type(Option<ModelTypeEnum>):
 The model type.
- model_version_number(Option<String>):
 The model version number of the model version created.
- status(Option<String>):
 The model version status.
On failure, responds with SdkError<CreateModelVersionError>

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pub fn create_rule(&self) -> CreateRule

Constructs a fluent builder for the CreateRule operation.

The fluent builder is configurable:
- rule_id(impl Into<String>) / set_rule_id(Option<String>):
 The rule ID.
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID for the rule’s parent detector.
- description(impl Into<String>) / set_description(Option<String>):
 The rule description.
- expression(impl Into<String>) / set_expression(Option<String>):
 The rule expression.
- language(Language) / set_language(Option<Language>):
 The language of the rule.
- outcomes(Vec<String>) / set_outcomes(Option<Vec<String>>):
 The outcome or outcomes returned when the rule expression matches.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateRuleOutput with field(s):
- rule(Option<Rule>):
 The created rule.
On failure, responds with SdkError<CreateRuleError>

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pub fn create_variable(&self) -> CreateVariable

Constructs a fluent builder for the CreateVariable operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the variable.
- data_type(DataType) / set_data_type(Option<DataType>):
 The data type.
- data_source(DataSource) / set_data_source(Option<DataSource>):
 The source of the data.
- default_value(impl Into<String>) / set_default_value(Option<String>):
 The default value for the variable when no value is received.
- description(impl Into<String>) / set_description(Option<String>):
 The description.
- variable_type(impl Into<String>) / set_variable_type(Option<String>):
 The variable type. For more information see Variable types.
 
 Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with CreateVariableOutput
On failure, responds with SdkError<CreateVariableError>

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pub fn delete_batch_import_job(&self) -> DeleteBatchImportJob

Constructs a fluent builder for the DeleteBatchImportJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch import job to delete.
On success, responds with DeleteBatchImportJobOutput
On failure, responds with SdkError<DeleteBatchImportJobError>

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pub fn delete_batch_prediction_job(&self) -> DeleteBatchPredictionJob

Constructs a fluent builder for the DeleteBatchPredictionJob operation.

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch prediction job to delete.
On success, responds with DeleteBatchPredictionJobOutput
On failure, responds with SdkError<DeleteBatchPredictionJobError>

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pub fn delete_detector(&self) -> DeleteDetector

Constructs a fluent builder for the DeleteDetector operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The ID of the detector to delete.
On success, responds with DeleteDetectorOutput
On failure, responds with SdkError<DeleteDetectorError>

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pub fn delete_detector_version(&self) -> DeleteDetectorVersion

Constructs a fluent builder for the DeleteDetectorVersion operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The ID of the parent detector for the detector version to delete.
- detector_version_id(impl Into<String>) / set_detector_version_id(Option<String>):
 The ID of the detector version to delete.
On success, responds with DeleteDetectorVersionOutput
On failure, responds with SdkError<DeleteDetectorVersionError>

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pub fn delete_entity_type(&self) -> DeleteEntityType

Constructs a fluent builder for the DeleteEntityType operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the entity type to delete.
On success, responds with DeleteEntityTypeOutput
On failure, responds with SdkError<DeleteEntityTypeError>

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pub fn delete_event(&self) -> DeleteEvent

Constructs a fluent builder for the DeleteEvent operation.

The fluent builder is configurable:
- event_id(impl Into<String>) / set_event_id(Option<String>):
 The ID of the event to delete.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
- delete_audit_history(bool) / set_delete_audit_history(Option<bool>):
 Specifies whether or not to delete any predictions associated with the event.
On success, responds with DeleteEventOutput
On failure, responds with SdkError<DeleteEventError>

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pub fn delete_events_by_event_type(&self) -> DeleteEventsByEventType

Constructs a fluent builder for the DeleteEventsByEventType operation.

The fluent builder is configurable:
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
On success, responds with DeleteEventsByEventTypeOutput with field(s):
- event_type_name(Option<String>):
 Name of event type for which to delete the events.
- events_deletion_status(Option<String>):
 The status of the delete request.
On failure, responds with SdkError<DeleteEventsByEventTypeError>

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pub fn delete_event_type(&self) -> DeleteEventType

Constructs a fluent builder for the DeleteEventType operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the event type to delete.
On success, responds with DeleteEventTypeOutput
On failure, responds with SdkError<DeleteEventTypeError>

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pub fn delete_external_model(&self) -> DeleteExternalModel

Constructs a fluent builder for the DeleteExternalModel operation.

The fluent builder is configurable:
- model_endpoint(impl Into<String>) / set_model_endpoint(Option<String>):
 The endpoint of the Amazon Sagemaker model to delete.
On success, responds with DeleteExternalModelOutput
On failure, responds with SdkError<DeleteExternalModelError>

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pub fn delete_label(&self) -> DeleteLabel

Constructs a fluent builder for the DeleteLabel operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the label to delete.
On success, responds with DeleteLabelOutput
On failure, responds with SdkError<DeleteLabelError>

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pub fn delete_model(&self) -> DeleteModel

Constructs a fluent builder for the DeleteModel operation.

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID of the model to delete.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type of the model to delete.
On success, responds with DeleteModelOutput
On failure, responds with SdkError<DeleteModelError>

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pub fn delete_model_version(&self) -> DeleteModelVersion

Constructs a fluent builder for the DeleteModelVersion operation.

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID of the model version to delete.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type of the model version to delete.
- model_version_number(impl Into<String>) / set_model_version_number(Option<String>):
 The model version number of the model version to delete.
On success, responds with DeleteModelVersionOutput
On failure, responds with SdkError<DeleteModelVersionError>

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pub fn delete_outcome(&self) -> DeleteOutcome

Constructs a fluent builder for the DeleteOutcome operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the outcome to delete.
On success, responds with DeleteOutcomeOutput
On failure, responds with SdkError<DeleteOutcomeError>

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pub fn delete_rule(&self) -> DeleteRule

Constructs a fluent builder for the DeleteRule operation.

The fluent builder is configurable:
- rule(Rule) / set_rule(Option<Rule>):
 A rule.
On success, responds with DeleteRuleOutput
On failure, responds with SdkError<DeleteRuleError>

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pub fn delete_variable(&self) -> DeleteVariable

Constructs a fluent builder for the DeleteVariable operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the variable to delete.
On success, responds with DeleteVariableOutput
On failure, responds with SdkError<DeleteVariableError>

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pub fn describe_detector(&self) -> DescribeDetector

Constructs a fluent builder for the DescribeDetector operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token from the previous response.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of results to return for the request.
On success, responds with DescribeDetectorOutput with field(s):
- detector_id(Option<String>):
 The detector ID.
- detector_version_summaries(Option<Vec<DetectorVersionSummary>>):
 The status and description for each detector version.
- next_token(Option<String>):
 The next token to be used for subsequent requests.
- arn(Option<String>):
 The detector ARN.
On failure, responds with SdkError<DescribeDetectorError>

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pub fn describe_model_versions(&self) -> DescribeModelVersions

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

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID.
- model_version_number(impl Into<String>) / set_model_version_number(Option<String>):
 The model version number.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token from the previous results.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of results to return.
On success, responds with DescribeModelVersionsOutput with field(s):
- model_version_details(Option<Vec<ModelVersionDetail>>):
 The model version details.
- next_token(Option<String>):
 The next token.
On failure, responds with SdkError<DescribeModelVersionsError>

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pub fn get_batch_import_jobs(&self) -> GetBatchImportJobs

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

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The ID of the batch import job to get.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for request.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token from the previous request.
On success, responds with GetBatchImportJobsOutput with field(s):
- batch_imports(Option<Vec<BatchImport>>):
 An array containing the details of each batch import job.
- next_token(Option<String>):
 The next token for the subsequent resquest.
On failure, responds with SdkError<GetBatchImportJobsError>

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pub fn get_batch_prediction_jobs(&self) -> GetBatchPredictionJobs

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

The fluent builder is configurable:
- job_id(impl Into<String>) / set_job_id(Option<String>):
 The batch prediction job for which to get the details.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token from the previous request.
On success, responds with GetBatchPredictionJobsOutput with field(s):
- batch_predictions(Option<Vec<BatchPrediction>>):
 An array containing the details of each batch prediction job.
- next_token(Option<String>):
 The next token for the subsequent request.
On failure, responds with SdkError<GetBatchPredictionJobsError>

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pub fn get_delete_events_by_event_type_status(
&self
) -> GetDeleteEventsByEventTypeStatus

Constructs a fluent builder for the GetDeleteEventsByEventTypeStatus operation.

The fluent builder is configurable:
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 Name of event type for which to get the deletion status.
On success, responds with GetDeleteEventsByEventTypeStatusOutput with field(s):
- event_type_name(Option<String>):
 The event type name.
- events_deletion_status(Option<AsyncJobStatus>):
 The deletion status.
On failure, responds with SdkError<GetDeleteEventsByEventTypeStatusError>

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pub fn get_detectors(&self) -> GetDetectors

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

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token for the subsequent request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetDetectorsOutput with field(s):
- detectors(Option<Vec<Detector>>):
 The detectors.
- next_token(Option<String>):
 The next page token.
On failure, responds with SdkError<GetDetectorsError>

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pub fn get_detector_version(&self) -> GetDetectorVersion

Constructs a fluent builder for the GetDetectorVersion operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- detector_version_id(impl Into<String>) / set_detector_version_id(Option<String>):
 The detector version ID.
On success, responds with GetDetectorVersionOutput with field(s):
- detector_id(Option<String>):
 The detector ID.
- detector_version_id(Option<String>):
 The detector version ID.
- description(Option<String>):
 The detector version description.
- external_model_endpoints(Option<Vec<String>>):
 The Amazon SageMaker model endpoints included in the detector version.
- model_versions(Option<Vec<ModelVersion>>):
 The model versions included in the detector version.
- rules(Option<Vec<Rule>>):
 The rules included in the detector version.
- status(Option<DetectorVersionStatus>):
 The status of the detector version.
- last_updated_time(Option<String>):
 The timestamp when the detector version was last updated.
- created_time(Option<String>):
 The timestamp when the detector version was created.
- rule_execution_mode(Option<RuleExecutionMode>):
 The execution mode of the rule in the dectector
 
 FIRST_MATCHED indicates that Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.
 
 ALL_MATCHED indicates that Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules. You can define and edit the rule mode at the detector version level, when it is in draft status.
- arn(Option<String>):
 The detector version ARN.
On failure, responds with SdkError<GetDetectorVersionError>

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pub fn get_entity_types(&self) -> GetEntityTypes

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

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token for the subsequent request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetEntityTypesOutput with field(s):
- entity_types(Option<Vec<EntityType>>):
 An array of entity types.
- next_token(Option<String>):
 The next page token.
On failure, responds with SdkError<GetEntityTypesError>

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pub fn get_event(&self) -> GetEvent

Constructs a fluent builder for the GetEvent operation.

The fluent builder is configurable:
- event_id(impl Into<String>) / set_event_id(Option<String>):
 The ID of the event to retrieve.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The event type of the event to retrieve.
On success, responds with GetEventOutput with field(s):
- event(Option<Event>):
 The details of the event.
On failure, responds with SdkError<GetEventError>

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pub fn get_event_prediction(&self) -> GetEventPrediction

Constructs a fluent builder for the GetEventPrediction operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- detector_version_id(impl Into<String>) / set_detector_version_id(Option<String>):
 The detector version ID.
- event_id(impl Into<String>) / set_event_id(Option<String>):
 The unique ID used to identify the event.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The event type associated with the detector specified for the prediction.
- entities(Vec<Entity>) / set_entities(Option<Vec<Entity>>):
 The entity type (associated with the detector’s event type) and specific entity ID representing who performed the event. If an entity id is not available, use “UNKNOWN.”
- event_timestamp(impl Into<String>) / set_event_timestamp(Option<String>):
 Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO 8601 standard in UTC.
- event_variables(HashMap<String, String>) / set_event_variables(Option<HashMap<String, String>>):
 Names of the event type’s variables you defined in Amazon Fraud Detector to represent data elements and their corresponding values for the event you are sending for evaluation.
 
 You must provide at least one eventVariable
 
 To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
 
 For Amazon Fraud Detector trained models:
 
 If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
 
 For imported SageMaker models:
 
 If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
- external_model_endpoint_data_blobs(HashMap<String, ModelEndpointDataBlob>) / set_external_model_endpoint_data_blobs(Option<HashMap<String, ModelEndpointDataBlob>>):
 The Amazon SageMaker model endpoint input data blobs.
On success, responds with GetEventPredictionOutput with field(s):
- model_scores(Option<Vec<ModelScores>>):
 The model scores. Amazon Fraud Detector generates model scores between 0 and 1000, where 0 is low fraud risk and 1000 is high fraud risk. Model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate.
- rule_results(Option<Vec<RuleResult>>):
 The results from the rules.
- external_model_outputs(Option<Vec<ExternalModelOutputs>>):
 The model scores for Amazon SageMaker models.
On failure, responds with SdkError<GetEventPredictionError>

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pub fn get_event_prediction_metadata(&self) -> GetEventPredictionMetadata

Constructs a fluent builder for the GetEventPredictionMetadata operation.

The fluent builder is configurable:
- event_id(impl Into<String>) / set_event_id(Option<String>):
 The event ID.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The event type associated with the detector specified for the prediction.
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- detector_version_id(impl Into<String>) / set_detector_version_id(Option<String>):
 The detector version ID.
- prediction_timestamp(impl Into<String>) / set_prediction_timestamp(Option<String>):
 The timestamp that defines when the prediction was generated. The timestamp must be specified using ISO 8601 standard in UTC.
 
 We recommend calling ListEventPredictions first, and using the predictionTimestamp value in the response to provide an accurate prediction timestamp value.
On success, responds with GetEventPredictionMetadataOutput with field(s):
- event_id(Option<String>):
 The event ID.
- event_type_name(Option<String>):
 The event type associated with the detector specified for this prediction.
- entity_id(Option<String>):
 The entity ID.
- entity_type(Option<String>):
 The entity type.
- event_timestamp(Option<String>):
 The timestamp for when the prediction was generated for the associated event ID.
- detector_id(Option<String>):
 The detector ID.
- detector_version_id(Option<String>):
 The detector version ID.
- detector_version_status(Option<String>):
 The status of the detector version.
- event_variables(Option<Vec<EventVariableSummary>>):
 A list of event variables that influenced the prediction scores.
- rules(Option<Vec<EvaluatedRule>>):
 List of rules associated with the detector version that were used for evaluating variable values.
- rule_execution_mode(Option<RuleExecutionMode>):
 The execution mode of the rule used for evaluating variable values.
- outcomes(Option<Vec<String>>):
 The outcomes of the matched rule, based on the rule execution mode.
- evaluated_model_versions(Option<Vec<EvaluatedModelVersion>>):
 Model versions that were evaluated for generating predictions.
- evaluated_external_models(Option<Vec<EvaluatedExternalModel>>):
 External (Amazon SageMaker) models that were evaluated for generating predictions.
- prediction_timestamp(Option<String>):
 The timestamp that defines when the prediction was generated.
On failure, responds with SdkError<GetEventPredictionMetadataError>

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pub fn get_event_types(&self) -> GetEventTypes

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

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token for the subsequent request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetEventTypesOutput with field(s):
- event_types(Option<Vec<EventType>>):
 An array of event types.
- next_token(Option<String>):
 The next page token.
On failure, responds with SdkError<GetEventTypesError>

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pub fn get_external_models(&self) -> GetExternalModels

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

The fluent builder is configurable:
- model_endpoint(impl Into<String>) / set_model_endpoint(Option<String>):
 The Amazon SageMaker model endpoint.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next page token for the request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetExternalModelsOutput with field(s):
- external_models(Option<Vec<ExternalModel>>):
 Gets the Amazon SageMaker models.
- next_token(Option<String>):
 The next page token to be used in subsequent requests.
On failure, responds with SdkError<GetExternalModelsError>

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pub fn get_kms_encryption_key(&self) -> GetKMSEncryptionKey

Constructs a fluent builder for the GetKMSEncryptionKey operation.

The fluent builder takes no input, just send it.
On success, responds with GetKmsEncryptionKeyOutput with field(s):
- kms_key(Option<KmsKey>):
 The KMS encryption key.
On failure, responds with SdkError<GetKMSEncryptionKeyError>

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pub fn get_labels(&self) -> GetLabels

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

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the label or labels to get.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token for the subsequent request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetLabelsOutput with field(s):
- labels(Option<Vec<Label>>):
 An array of labels.
- next_token(Option<String>):
 The next page token.
On failure, responds with SdkError<GetLabelsError>

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pub fn get_models(&self) -> GetModels

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

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token for the subsequent request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetModelsOutput with field(s):
- next_token(Option<String>):
 The next page token to be used in subsequent requests.
- models(Option<Vec<Model>>):
 The array of models.
On failure, responds with SdkError<GetModelsError>

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pub fn get_model_version(&self) -> GetModelVersion

Constructs a fluent builder for the GetModelVersion operation.

The fluent builder is configurable:
- model_id(impl Into<String>) / set_model_id(Option<String>):
 The model ID.
- model_type(ModelTypeEnum) / set_model_type(Option<ModelTypeEnum>):
 The model type.
- model_version_number(impl Into<String>) / set_model_version_number(Option<String>):
 The model version number.
On success, responds with GetModelVersionOutput with field(s):
- model_id(Option<String>):
 The model ID.
- model_type(Option<ModelTypeEnum>):
 The model type.
- model_version_number(Option<String>):
 The model version number.
- training_data_source(Option<TrainingDataSourceEnum>):
 The training data source.
- training_data_schema(Option<TrainingDataSchema>):
 The training data schema.
- external_events_detail(Option<ExternalEventsDetail>):
 The details of the external events data used for training the model version. This will be populated if the trainingDataSource is EXTERNAL_EVENTS
- ingested_events_detail(Option<IngestedEventsDetail>):
 The details of the ingested events data used for training the model version. This will be populated if the trainingDataSource is INGESTED_EVENTS.
- status(Option<String>):
 The model version status.
 
 Possible values are:
 - TRAINING_IN_PROGRESS
 - TRAINING_COMPLETE
 - ACTIVATE_REQUESTED
 - ACTIVATE_IN_PROGRESS
 - ACTIVE
 - INACTIVATE_REQUESTED
 - INACTIVATE_IN_PROGRESS
 - INACTIVE
 - ERROR
- arn(Option<String>):
 The model version ARN.
On failure, responds with SdkError<GetModelVersionError>

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pub fn get_outcomes(&self) -> GetOutcomes

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

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the outcome or outcomes to get.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next page token for the request.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with GetOutcomesOutput with field(s):
- outcomes(Option<Vec<Outcome>>):
 The outcomes.
- next_token(Option<String>):
 The next page token for subsequent requests.
On failure, responds with SdkError<GetOutcomesError>

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pub fn get_rules(&self) -> GetRules

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

The fluent builder is configurable:
- rule_id(impl Into<String>) / set_rule_id(Option<String>):
 The rule ID.
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- rule_version(impl Into<String>) / set_rule_version(Option<String>):
 The rule version.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next page token.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of rules to return for the request.
On success, responds with GetRulesOutput with field(s):
- rule_details(Option<Vec<RuleDetail>>):
 The details of the requested rule.
- next_token(Option<String>):
 The next page token to be used in subsequent requests.
On failure, responds with SdkError<GetRulesError>

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pub fn get_variables(&self) -> GetVariables

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

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the variable.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next page token of the get variable request.
- max_results(i32) / set_max_results(Option<i32>):
 The max size per page determined for the get variable request.
On success, responds with GetVariablesOutput with field(s):
- variables(Option<Vec<Variable>>):
 The names of the variables returned.
- next_token(Option<String>):
 The next page token to be used in subsequent requests.
On failure, responds with SdkError<GetVariablesError>

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pub fn list_event_predictions(&self) -> ListEventPredictions

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

The fluent builder is configurable:
- event_id(FilterCondition) / set_event_id(Option<FilterCondition>):
 The event ID.
- event_type(FilterCondition) / set_event_type(Option<FilterCondition>):
 The event type associated with the detector.
- detector_id(FilterCondition) / set_detector_id(Option<FilterCondition>):
 The detector ID.
- detector_version_id(FilterCondition) / set_detector_version_id(Option<FilterCondition>):
 The detector version ID.
- prediction_time_range(PredictionTimeRange) / set_prediction_time_range(Option<PredictionTimeRange>):
 The time period for when the predictions were generated.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 Identifies the next page of results to return. Use the token to make the call again to retrieve the next page. Keep all other arguments unchanged. Each pagination token expires after 24 hours.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of predictions to return for the request.
On success, responds with ListEventPredictionsOutput with field(s):
- event_prediction_summaries(Option<Vec<EventPredictionSummary>>):
 The summary of the past predictions.
- next_token(Option<String>):
 Identifies the next page of results to return. Use the token to make the call again to retrieve the next page. Keep all other arguments unchanged. Each pagination token expires after 24 hours.
On failure, responds with SdkError<ListEventPredictionsError>

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pub fn list_tags_for_resource(&self) -> ListTagsForResource

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

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 The ARN that specifies the resource whose tags you want to list.
- next_token(impl Into<String>) / set_next_token(Option<String>):
 The next token from the previous results.
- max_results(i32) / set_max_results(Option<i32>):
 The maximum number of objects to return for the request.
On success, responds with ListTagsForResourceOutput with field(s):
- tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
- next_token(Option<String>):
 The next token for subsequent requests.
On failure, responds with SdkError<ListTagsForResourceError>

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pub fn put_detector(&self) -> PutDetector

Constructs a fluent builder for the PutDetector operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The detector ID.
- description(impl Into<String>) / set_description(Option<String>):
 The description of the detector.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The name of the event type.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with PutDetectorOutput
On failure, responds with SdkError<PutDetectorError>

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pub fn put_entity_type(&self) -> PutEntityType

Constructs a fluent builder for the PutEntityType operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the entity type.
- description(impl Into<String>) / set_description(Option<String>):
 The description.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with PutEntityTypeOutput
On failure, responds with SdkError<PutEntityTypeError>

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pub fn put_event_type(&self) -> PutEventType

Constructs a fluent builder for the PutEventType operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name.
- description(impl Into<String>) / set_description(Option<String>):
 The description of the event type.
- event_variables(Vec<String>) / set_event_variables(Option<Vec<String>>):
 The event type variables.
- labels(Vec<String>) / set_labels(Option<Vec<String>>):
 The event type labels.
- entity_types(Vec<String>) / set_entity_types(Option<Vec<String>>):
 The entity type for the event type. Example entity types: customer, merchant, account.
- event_ingestion(EventIngestion) / set_event_ingestion(Option<EventIngestion>):
 Specifies if ingenstion is enabled or disabled.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with PutEventTypeOutput
On failure, responds with SdkError<PutEventTypeError>

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pub fn put_external_model(&self) -> PutExternalModel

Constructs a fluent builder for the PutExternalModel operation.

The fluent builder is configurable:
- model_endpoint(impl Into<String>) / set_model_endpoint(Option<String>):
 The model endpoints name.
- model_source(ModelSource) / set_model_source(Option<ModelSource>):
 The source of the model.
- invoke_model_endpoint_role_arn(impl Into<String>) / set_invoke_model_endpoint_role_arn(Option<String>):
 The IAM role used to invoke the model endpoint.
- input_configuration(ModelInputConfiguration) / set_input_configuration(Option<ModelInputConfiguration>):
 The model endpoint input configuration.
- output_configuration(ModelOutputConfiguration) / set_output_configuration(Option<ModelOutputConfiguration>):
 The model endpoint output configuration.
- model_endpoint_status(ModelEndpointStatus) / set_model_endpoint_status(Option<ModelEndpointStatus>):
 The model endpoint’s status in Amazon Fraud Detector.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with PutExternalModelOutput
On failure, responds with SdkError<PutExternalModelError>

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pub fn put_kms_encryption_key(&self) -> PutKMSEncryptionKey

Constructs a fluent builder for the PutKMSEncryptionKey operation.

The fluent builder is configurable:
- kms_encryption_key_arn(impl Into<String>) / set_kms_encryption_key_arn(Option<String>):
 The KMS encryption key ARN.
On success, responds with PutKmsEncryptionKeyOutput
On failure, responds with SdkError<PutKMSEncryptionKeyError>

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pub fn put_label(&self) -> PutLabel

Constructs a fluent builder for the PutLabel operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The label name.
- description(impl Into<String>) / set_description(Option<String>):
 The label description.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
On success, responds with PutLabelOutput
On failure, responds with SdkError<PutLabelError>

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pub fn put_outcome(&self) -> PutOutcome

Constructs a fluent builder for the PutOutcome operation.

The fluent builder is configurable:
- name(impl Into<String>) / set_name(Option<String>):
 The name of the outcome.
- description(impl Into<String>) / set_description(Option<String>):
 The outcome description.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 A collection of key and value pairs.
On success, responds with PutOutcomeOutput
On failure, responds with SdkError<PutOutcomeError>

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pub fn send_event(&self) -> SendEvent

Constructs a fluent builder for the SendEvent operation.

The fluent builder is configurable:
- event_id(impl Into<String>) / set_event_id(Option<String>):
 The event ID to upload.
- event_type_name(impl Into<String>) / set_event_type_name(Option<String>):
 The event type name of the event.
- event_timestamp(impl Into<String>) / set_event_timestamp(Option<String>):
 The timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO 8601 standard in UTC.
- event_variables(HashMap<String, String>) / set_event_variables(Option<HashMap<String, String>>):
 Names of the event type’s variables you defined in Amazon Fraud Detector to represent data elements and their corresponding values for the event you are sending for evaluation.
- assigned_label(impl Into<String>) / set_assigned_label(Option<String>):
 The label to associate with the event. Required if specifying labelTimestamp.
- label_timestamp(impl Into<String>) / set_label_timestamp(Option<String>):
 The timestamp associated with the label. Required if specifying assignedLabel.
- entities(Vec<Entity>) / set_entities(Option<Vec<Entity>>):
 An array of entities.
On success, responds with SendEventOutput
On failure, responds with SdkError<SendEventError>

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pub fn tag_resource(&self) -> TagResource

Constructs a fluent builder for the TagResource operation.

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 The resource ARN.
- tags(Vec<Tag>) / set_tags(Option<Vec<Tag>>):
 The tags to assign to the resource.
On success, responds with TagResourceOutput
On failure, responds with SdkError<TagResourceError>

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pub fn untag_resource(&self) -> UntagResource

Constructs a fluent builder for the UntagResource operation.

The fluent builder is configurable:
- resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
 The ARN of the resource from which to remove the tag.
- tag_keys(Vec<String>) / set_tag_keys(Option<Vec<String>>):
 The resource ARN.
On success, responds with UntagResourceOutput
On failure, responds with SdkError<UntagResourceError>

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pub fn update_detector_version(&self) -> UpdateDetectorVersion

Constructs a fluent builder for the UpdateDetectorVersion operation.

The fluent builder is configurable:
- detector_id(impl Into<String>) / set_detector_id(Option<String>):
 The parent detector ID for the detector version you want to update.
- detector_version_id(impl Into<String>) / set_detector_version_id(Option<String>):
 The detector version ID.
- external_model_endpoints(Vec<String>) / set_external_model_endpoints(Option<Vec<String>>):
 The Amazon SageMaker model endpoints to include in the detector version.
- rules(Vec<Rule>) / set_rules(Option<Vec<Rule>>):
 The rules to include in the detector version.
- description(impl Into<String>) / set_description(Option<String>):
 The detector version description.
- model_versions(Vec<ModelVersion>) / set_model_versions(Option<Vec<ModelVersion>>):
 The model versions to include in the detector version.
- rule_execution_mode(RuleExecutionMode) / set_rule_execution_mode(Option<RuleExecutionMode>):
 The rule execution mode to add to the detector.
 
 If you specify FIRST_MATCHED, Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule.
 
 If you specifiy ALL_MATCHED, Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules. You can define and edit the rule mode at the detector version level, when it is in draft status.
 
 The default behavior is FIRST_MATCHED.
On success, responds with UpdateDetectorVersionOutput
On failure, responds with SdkError<UpdateDetectorVersionError>