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batch_get_worker

batch_get_worker(
    identifiers: BatchGetWorkerIdentifiers,
    *,
    config_overrides: Optional[deadlineClientConfig] = None,
) -> BatchGetWorkerResponse

Retrieves multiple workers in a single request. This is a batch version of the GetWorker API.

The result of getting each worker is reported individually in the response. Because the batch request can result in a combination of successful and unsuccessful actions, you should check for batch errors even when the call returns an HTTP status code of 200.

Parameters:

  • identifiers (BatchGetWorkerIdentifiers) –

    The list of worker identifiers to retrieve. You can specify up to 100 identifiers per request.

Raises:

Examples:

Get multiple workers in a single request

>>> client.batch_get_worker(identifiers=[{'farmId': 'farm-1234567890abcdef1234567890abcdef', 'fleetId': 'fleet-1234567890abcdef1234567890abcdef', 'workerId': 'worker-1234567890abcdef1234567890abcdef'}, {'farmId': 'farm-1234567890abcdef1234567890abcdef', 'fleetId': 'fleet-1234567890abcdef1234567890abcdef', 'workerId': 'worker-234567890abcdef1234567890abcdef1'}])
Source code in docs_src/capo_deadline/_services/deadline.py
def batch_get_worker(
    self,
    identifiers: "capo_deadline.types.batch_get_worker_identifiers.BatchGetWorkerIdentifiers",
    *,
    config_overrides: Optional[deadlineClientConfig] = None,
) -> "capo_deadline.types.batch_get_worker_response.BatchGetWorkerResponse":
    """<p>Retrieves multiple workers in a single request. This is a batch version of the <code>GetWorker</code> API.</p> <p>The result of getting each worker is reported individually in the response. Because the batch request can result in a combination of successful and unsuccessful actions, you should check for batch errors even when the call returns an HTTP status code of 200.</p>

    Args:
        identifiers: <p>The list of worker identifiers to retrieve. You can specify up to 100 identifiers per request.</p>

    Raises:
        capo_deadline.errors.access_denied_exception.AccessDeniedException: <p>You don't have permission to perform the action.</p>
        capo_deadline.errors.internal_server_error_exception.InternalServerErrorException: <p>Deadline Cloud can't process your request right now. Try again later.</p>
        capo_deadline.errors.throttling_exception.ThrottlingException: <p>Your request exceeded a request rate quota.</p>
        capo_deadline.errors.validation_exception.ValidationException: <p>The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.</p>
        capo_deadline.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        Get multiple workers in a single request

        >>> client.batch_get_worker(identifiers=[{'farmId': 'farm-1234567890abcdef1234567890abcdef', 'fleetId': 'fleet-1234567890abcdef1234567890abcdef', 'workerId': 'worker-1234567890abcdef1234567890abcdef'}, {'farmId': 'farm-1234567890abcdef1234567890abcdef', 'fleetId': 'fleet-1234567890abcdef1234567890abcdef', 'workerId': 'worker-234567890abcdef1234567890abcdef1'}])
    """

    def _handler(
        req: "OperationRequest[capo_deadline.types.batch_get_worker_request.BatchGetWorkerRequest]",
    ) -> OperationResponse[
        "capo_deadline.types.batch_get_worker_response.BatchGetWorkerResponse"
    ]:
        import capo_deadline._operations.deadline.batch_get_worker

        output, http_response = (
            capo_deadline._operations.deadline.batch_get_worker.batch_get_worker(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("BatchGetWorker")
    )
    input_: capo_deadline.types.batch_get_worker_request.BatchGetWorkerRequest = {
        "identifiers": identifiers
    }

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