get_vector_enrichment_job ¶

def get_vector_enrichment_job(
    self,
    arn: "capo_sagemaker_geospatial.types.vector_enrichment_job_arn.VectorEnrichmentJobArn",
    *,
    config_overrides: Optional[SageMakerGeospatialClientConfig] = None,
) -> "capo_sagemaker_geospatial.types.get_vector_enrichment_job_output.GetVectorEnrichmentJobOutput":
    """<p>Retrieves details of a Vector Enrichment Job for a given job Amazon Resource Name (ARN).</p>

    Args:
        arn: <p>The Amazon Resource Name (ARN) of the Vector Enrichment job.</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.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.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.get_vector_enrichment_job_input.GetVectorEnrichmentJobInput]",
    ) -> OperationResponse[
        "capo_sagemaker_geospatial.types.get_vector_enrichment_job_output.GetVectorEnrichmentJobOutput"
    ]:
        import capo_sagemaker_geospatial._operations.sage_maker_geospatial.get_vector_enrichment_job

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetVectorEnrichmentJob")
    )
    input_: capo_sagemaker_geospatial.types.get_vector_enrichment_job_input.GetVectorEnrichmentJobInput = {
        "arn": arn
    }

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