```

注意，此处把 `current_user` 的类型声明为 Pydantic 的 `User` 模型。

这有助于在函数内部使用代码补全和类型检查。

/// tip | "提示"

还记得请求体也是使用 Pydantic 模型声明的吧。

放心，因为使用了 `Depends`，**FastAPI** 不会搞混。

///

/// check | "检查"

依赖系统的这种设计方式可以支持不同的依赖项返回同一个 `User` 模型。

而不是局限于只能有一个返回该类型数据的依赖项。

///

## 其它模型

接下来，直接在*路径操作函数*中获取当前用户，并用 `Depends` 在**依赖注入**系统中处理安全机制。

开发者可以使用任何模型或数据满足安全需求（本例中是 Pydantic 的 `User` 模型）。

    except (RuntimeError, PydanticSchemaGenerationError):
        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "
            "field (e.g. Union[Response, dict, None]) you can disable generating the "

	logger.LogOnceIf(ctx, logSubsys, err, id, errKind...)
}

// ErrTargetsOffline - Indicates single/multiple target failures.
var ErrTargetsOffline = errors.New("one or more targets are offline. Please use `mc admin info --json` to check the offline targets")

// TestSubSysLambdaTargets - tests notification targets of given subsystem
func TestSubSysLambdaTargets(ctx context.Context, cfg config.Config, subSys string, transport *http.Transport) error {

* Run a container based on your image:

<div class="termy">

```console
$ docker run -d --name mycontainer -p 80:80 myimage
```

</div>

## Check it

	currTime := UTCNow()

	var (
		username = cred.AccessKey
		claims   = cred.Claims
		groups   = cred.Groups
	)

	if cred.IsTemp() || cred.IsServiceAccount() {
		// For derived credentials, check the parent user's permissions.
		username = cred.ParentUser
	}

	principalType := "Anonymous"
	if username != "" {
		principalType = "User"
		if len(claims) > 0 {
			principalType = "AssumedRole"
		}

func stripStandardPorts(apiEndpoints []string, host string) (newAPIEndpoints []string) {
	if len(apiEndpoints) == 1 {
		return apiEndpoints
	}
	newAPIEndpoints = make([]string, len(apiEndpoints))
	// Check all API endpoints for standard ports and strip them.
	for i, apiEndpoint := range apiEndpoints {
		_, err := xnet.ParseHTTPURL(apiEndpoint)
		if err != nil {
			continue
		}
		u, err := url.Parse(apiEndpoint)

They tend to require more complex configurations, a message/job queue manager, like RabbitMQ or Redis, but they allow you to run background tasks in multiple processes, and especially, in multiple servers.

To see an example, check the [Project Generators](../project-generation.md){.internal-link target=_blank}, they all include Celery already configured.

//// tab | Python 3.8+

```Python hl_lines="9"
{!> ../../docs_src/query_params/tutorial002.py!}
```

////

In this case, the function parameter `q` will be optional, and will be `None` by default.

/// check

Also notice that **FastAPI** is smart enough to notice that the path parameter `item_id` is a path parameter and `q` is not, so, it's a query parameter.

///

## Query parameter type conversion

  }

  @Override
  public Set<E> edgesConnecting(N nodeU, N nodeV) {
    NetworkConnections<N, E> connectionsU = checkedConnections(nodeU);
    if (!allowsSelfLoops && nodeU == nodeV) { // just an optimization, only check reference equality
      return ImmutableSet.of();
    }
    checkArgument(containsNode(nodeV), NODE_NOT_IN_GRAPH, nodeV);
    return nodePairInvalidatableSet(connectionsU.edgesConnecting(nodeV), nodeU, nodeV);
  }

        return Ints.saturatedCast(edgeCount());
      }

      @Override
      public boolean remove(@CheckForNull Object o) {
        throw new UnsupportedOperationException();
      }

      // Mostly safe: We check contains(u) before calling successors(u), so we perform unsafe
      // operations only in weird cases like checking for an EndpointPair<ArrayList> in a
      // Graph<LinkedList>.
      @SuppressWarnings("unchecked")