}

enum WorkloadStatus {
  // Workload is healthy and ready to serve traffic.
  HEALTHY = 0;
  // Workload is unhealthy and NOT ready to serve traffic.
  UNHEALTHY = 1;
}

enum WorkloadType {
  DEPLOYMENT = 0;
  CRONJOB = 1;
  POD = 2;
  JOB = 3;
}

// PorList represents the ports for a service
message PortList {
  repeated Port ports = 1;
}

message Port {

	Shutdown(context.Context) error
	NSScanner(ctx context.Context, updates chan<- DataUsageInfo, wantCycle uint32, scanMode madmin.HealScanMode) error
	BackendInfo() madmin.BackendInfo
	Legacy() bool // Only returns true for deployments which use CRCMOD as its object distribution algorithm.
	StorageInfo(ctx context.Context, metrics bool) StorageInfo
	LocalStorageInfo(ctx context.Context, metrics bool) StorageInfo

	// Bucket operations.

			})
		}
	}
	return res
}

func workloadNameAndType(pod *v1.Pod) (string, workloadapi.WorkloadType) {
	objMeta, typeMeta := kubeutil.GetDeployMetaFromPod(pod)
	switch typeMeta.Kind {
	case "Deployment":
		return objMeta.Name, workloadapi.WorkloadType_DEPLOYMENT
	case "Job":
		return objMeta.Name, workloadapi.WorkloadType_JOB
	case "CronJob":
		return objMeta.Name, workloadapi.WorkloadType_CRONJOB
	default:

!!! info "정보"
    FastAPI는 0.95.0 버전부터 `Annotated`에 대한 지원을 (그리고 이를 사용하기 권장합니다) 추가했습니다.

    옛날 버전을 가지고 있는 경우, `Annotated`를 사용하려 하면 에러를 맞이하게 될 것입니다.

    `Annotated`를 사용하기 전에 최소 0.95.1로 [FastAPI 버전 업그레이드](../../deployment/versions.md#fastapi_2){.internal-link target=_blank}를 확실하게 하세요.

### `Depends` 불러오기

=== "Python 3.10+"

    ```Python hl_lines="3"
    {!> ../../../docs_src/dependencies/tutorial001_an_py310.py!}
    ```

				host, _, err := net.SplitHostPort(getHost(r))
				if err != nil {
					host = r.Host
				}
				// Make sure to skip matching minio.<domain>` this is
				// specifically meant for operator/k8s deployment
				// The reason we need to skip this is for a special
				// usecase where we need to make sure that
				// minio.<namespace>.svc.<cluster_domain> is ignored
				// by the bucketDNS style to ensure that path style

并且，您也可以利用并行和多进程（让多个进程并行运行）的优点来处理与机器学习系统中类似的 **CPU 密集型** 工作。

这一点，再加上 Python 是**数据科学**、机器学习（尤其是深度学习）的主要语言这一简单事实，使得 **FastAPI** 与数据科学/机器学习 Web API 和应用程序（以及其他许多应用程序）非常匹配。

了解如何在生产环境中实现这种并行性，可查看此文 [Deployment](deployment/index.md){.internal-link target=_blank}。

## `async` 和 `await`

现代版本的 Python 有一种非常直观的方式来定义异步代码。这使它看起来就像正常的"顺序"代码，并在适当的时候"等待"。

当有一个操作需要等待才能给出结果，且支持这个新的 Python 特性时，您可以编写如下代码：

```Python

	maxHeaderSize = 8 * 1024

	// Maximum size for user-defined metadata - See: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingMetadata.html
	maxUserDataSize = 2 * 1024

	// maxBuckets upto 500000 for any MinIO deployment.
	maxBuckets = 500 * 1000
)

// ReservedMetadataPrefix is the prefix of a metadata key which
// is reserved and for internal use only.
const (
	ReservedMetadataPrefix      = "X-Minio-Internal-"

    }

    /**
     * Shortcut for <code>getService(ArtifactDeployer.class).deploy(...)</code>
     *
     * @throws ArtifactDeployerException if the artifacts deployment failed
     * @see ArtifactDeployer#deploy(Session, RemoteRepository, Collection)
     */
    @Override
    public void deployArtifact(RemoteRepository repository, Artifact... artifacts) {

	// replaces POD_NAME
	InstanceName string `json:"NAME,omitempty"`

	// Owner specifies the workload owner (opaque string). Typically, this is the owning controller of
	// of the workload instance (ex: k8s deployment for a k8s pod).
	Owner string `json:"OWNER,omitempty"`

	// PilotSAN is the list of subject alternate names for the xDS server.
	PilotSubjectAltName []string `json:"PILOT_SAN,omitempty"`

// patch directly; Kubernetes will take care of applying the patch.
//
// For kube-inject, we will parse out a Pod from YAML (which may involve
// extraction from higher level types like Deployment), then apply the patch
// locally.
//
// The injection logic works by first applying the rendered injection template on
// top of the input pod This is done using a Strategic Patch Merge