import org.jspecify.annotations.Nullable;
import org.junit.Ignore;

/**
 * Tester for {@link Multimap#put}.
 *
 * @author Louis Wasserman
 */
@GwtCompatible
@Ignore("test runners must not instantiate and run this directly, only via suites we build")
// @Ignore affects the Android test runner, which respects JUnit 4 annotations on JUnit 3 tests.
@SuppressWarnings("JUnit4ClassUsedInJUnit3")
@NullMarked

import static org.junit.jupiter.api.Assertions.assertTrue;

import org.junit.jupiter.api.Test;

/**
 * Tests for the Trans2QueryFSInformationResponse class.
 */
class Trans2QueryFSInformationResponseTest {

    /**
     * Tests the constructor to ensure it sets up the command and subcommand correctly.
     */
    @Test
    void testConstructor() {
        Trans2QueryFSInformationResponse response =

     * given user when the target object's ACL has local groups. Local groups
     * are not listed in a user's group membership (e.g. as represented by the
     * tokenGroups constructed attribute retrieved via LDAP).
     *
     * Domain groups nested inside a local group are currently not expanded. In
     * this case the key (SID) type will be SID_TYPE_DOM_GRP rather than
     * SID_TYPE_USER.

該 dataclass 會自動轉換為 Pydantic 的 dataclass。

如此一來，其結構描述（schema）會顯示在 API 文件介面中：

<img src="/img/tutorial/dataclasses/image01.png">

## 巢狀資料結構中的 Dataclasses { #dataclasses-in-nested-data-structures }

你也可以將 `dataclasses` 與其他型別註記結合，建立巢狀的資料結構。

在某些情況下，你可能仍需要使用 Pydantic 版本的 `dataclasses`。例如，當自動產生的 API 文件出現錯誤時。

這種情況下，你可以把標準的 `dataclasses` 直接換成 `pydantic.dataclasses`，它是可直接替換（drop-in replacement）的：

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

Diese Zeile zeigt die URL, unter der Ihre App auf Ihrem lokalen Computer bereitgestellt wird.

### Es testen { #check-it }

Öffnen Sie Ihren Browser unter [http://127.0.0.1:8000](http://127.0.0.1:8000).

Sie werden die JSON-<abbr title="Response – Antwort: Daten, die der Server zum anfragenden Client zurücksendet">Response</abbr> sehen:

{* ../../docs_src/metadata/tutorial004_py310.py hl[21,26] *}

/// info | Info

Lesen Sie mehr zu Tags unter [Pfadoperation-Konfiguration](path-operation-configuration.md#tags).

///

### Die Dokumentation testen { #check-the-docs }

Wenn Sie nun die Dokumentation ansehen, werden dort alle zusätzlichen Metadaten angezeigt:

<img src="/img/tutorial/metadata/image02.png">

### Reihenfolge der Tags { #order-of-tags }

* More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
* **GraphQL** integration with [Strawberry](https://strawberry.rocks) and other libraries.
* Many extra features (thanks to Starlette) as:
    * **WebSockets**
    * extremely easy tests based on HTTPX and `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...and more.

dataclass는 자동으로 Pydantic dataclass로 변환됩니다.

이렇게 하면 해당 스키마가 API docs 사용자 인터페이스에 표시됩니다:

<img src="/img/tutorial/dataclasses/image01.png">

## 중첩 데이터 구조에서 Dataclasses 사용하기 { #dataclasses-in-nested-data-structures }

`dataclasses`를 다른 타입 애너테이션과 조합해 중첩 데이터 구조를 만들 수도 있습니다.

일부 경우에는 Pydantic 버전의 `dataclasses`를 사용해야 할 수도 있습니다. 예를 들어 자동 생성된 API 문서에서 오류가 발생하는 경우입니다.

#### Um ataque "profissional" { #a-professional-attack }

Claro, os invasores não tentariam tudo isso de forma manual, eles escreveriam um programa para fazer isso, possivelmente com milhares ou milhões de testes por segundo. E obteriam apenas uma letra a mais por vez.

---
jjbb-template: periodic-trigger-lgc.yml
vars:
  - periodic-job: elastic+elasticsearch+%BRANCH%+periodic+packaging-tests
  - lgc-job: elastic+elasticsearch+%BRANCH%+intake