export_vector_enrichment_job ¶

def export_vector_enrichment_job(
    self,
    arn: "capo_sagemaker_geospatial.types.vector_enrichment_job_arn.VectorEnrichmentJobArn",
    execution_role_arn: "capo_sagemaker_geospatial.types.execution_role_arn.ExecutionRoleArn",
    output_config: "capo_sagemaker_geospatial.types.export_vector_enrichment_job_output_config.ExportVectorEnrichmentJobOutputConfig",
    *,
    config_overrides: Optional[SageMakerGeospatialClientConfig] = None,
    client_token: Optional[str] = None,
) -> "capo_sagemaker_geospatial.types.export_vector_enrichment_job_output.ExportVectorEnrichmentJobOutput":
    """<p>Use this operation to copy results of a Vector Enrichment job to an Amazon S3 location.</p>

    Args:
        arn: <p>The Amazon Resource Name (ARN) of the Vector Enrichment job.</p>
        client_token: <p>A unique token that guarantees that the call to this API is idempotent.</p>
        execution_role_arn: <p>The Amazon Resource Name (ARN) of the IAM rolewith permission to upload to the location in OutputConfig.</p>
        output_config: <p>Output location information for exporting Vector Enrichment Job results. </p>

    Raises:
        capo_sagemaker_geospatial.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_sagemaker_geospatial.errors.conflict_exception.ConflictException: <p>Updating or deleting a resource can cause an inconsistent state.</p>
        capo_sagemaker_geospatial.errors.internal_server_exception.InternalServerException: <p>The request processing has failed because of an unknown error, exception, or failure.</p>
        capo_sagemaker_geospatial.errors.resource_not_found_exception.ResourceNotFoundException: <p>The request references a resource which does not exist.</p>
        capo_sagemaker_geospatial.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have exceeded the service quota.</p>
        capo_sagemaker_geospatial.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_sagemaker_geospatial.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_sagemaker_geospatial.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker_geospatial.types.export_vector_enrichment_job_input.ExportVectorEnrichmentJobInput]",
    ) -> OperationResponse[
        "capo_sagemaker_geospatial.types.export_vector_enrichment_job_output.ExportVectorEnrichmentJobOutput"
    ]:
        import capo_sagemaker_geospatial._operations.sage_maker_geospatial.export_vector_enrichment_job

        output, http_response = (
            capo_sagemaker_geospatial._operations.sage_maker_geospatial.export_vector_enrichment_job.export_vector_enrichment_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ExportVectorEnrichmentJob")
    )
    input_: capo_sagemaker_geospatial.types.export_vector_enrichment_job_input.ExportVectorEnrichmentJobInput = {
        "arn": arn,
        "execution_role_arn": execution_role_arn,
        "output_config": output_config,
    }
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output