DependencyScope.SYSTEM.id(),
                DependencyScope.SYSTEM.isTransitive(),
                all(),
                MavenArtifactProperties.LOCAL_PATH));

        // == sanity check
        if (result.size() != org.apache.maven.api.DependencyScope.values().length - 1) { // sans "undefined"
            throw new IllegalStateException("Maven4 API dependency scope mismatch");
        }

## More info

For more info about <abbr title="Cross-Origin Resource Sharing">CORS</abbr>, check the <a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS" class="external-link" target="_blank">Mozilla CORS documentation</a>.

/// note | "Technical Details"

			}
		})
	}
}

// Test PutObject twice, one small and another bigger
// than small data threshold and checks reading them again
func TestPutObjectSmallInlineData(t *testing.T) {
	ctx, cancel := context.WithCancel(context.Background())
	defer cancel()

	const numberOfDisks = 4

	// Create an instance of xl backend.

            private Model findRawModel(Path from, String groupId, String artifactId) {
                FileModelSource source = getSource(groupId, artifactId);
                if (source == null) {
                    // we need to check the whole reactor in case it's a dependency
                    loadFullReactor();
                    source = getSource(groupId, artifactId);
                }
                if (source != null) {

```

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 {

import com.google.common.collect.Multisets.AbstractEntry;
import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.util.Arrays;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * {@code ObjectCountHashMap} uses arrays to store key objects and count values. Comparing to using
 * a traditional {@code HashMap} implementation which stores keys and count values as map entries,

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.