return new MockResponse()
          .setStatus("HTTP/1.1 404")
          .addHeader("content-type: text/plain; charset=utf-8")
          .setBody("NOT FOUND: " + path);
    } catch (IOException e) {
      return new MockResponse()
          .setStatus("HTTP/1.1 500")
          .addHeader("content-type: text/plain; charset=utf-8")
          .setBody("SERVER ERROR: " + e);
    }
  }

```Python hl_lines="1  7-12  19-20"
{!../../docs_src/dataclasses/tutorial001.py!}
```

Isso ainda é suportado graças ao **Pydantic**, pois ele tem <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">suporte interno para `dataclasses`</a>.

* `datetime.timedelta`:
    * 一个 Python `datetime.timedelta`.
    * 在请求和响应中将表示为 `float` 代表总秒数。
    * Pydantic 也允许将其表示为 "ISO 8601 时间差异编码", <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">查看文档了解更多信息</a>。
* `frozenset`:
    * 在请求和响应中，作为 `set` 对待：
        * 在请求中，列表将被读取，消除重复，并将其转换为一个 `set`。
        * 在响应中 `set` 将被转换为 `list` 。

// user or cluster provisioner, and referenced in the PodSpec. The Kubelet is
// responsible for resolving the RuntimeClassName reference before running the
// pod.  For more details, see
// https://kubernetes.io/docs/concepts/containers/runtime-class/
message RuntimeClass {
  // More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata
  // +optional

     * required resolving with the authority. SID cache entries are currently not
     * expired because under normal circumstances SID information never changes.
     * 
     * @param tc
     *            context to use
     * @param authorityServerName
     *            The hostname of the server that should be queried. For maximum efficiency this should be the hostname

## Pydantic `schema_extra`

Вы можете объявить ключ `example` для модели Pydantic, используя класс `Config` и переменную `schema_extra`, как описано в <a href="https://docs.pydantic.dev/latest/concepts/json_schema/#schema-customization" class="external-link" target="_blank">Pydantic документации: Настройка схемы</a>:

//// tab | Python 3.10+

```Python hl_lines="13-21"

Veja como pode parecer:

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

---

Se você usar o Pycharm, você pode:

* Abrir o menu "Executar".
* Selecionar a opção "Depurar...".
* Então um menu de contexto aparece.
* Selecionar o arquivo para depurar (neste caso, `main.py`).

Em seguida, ele iniciará o servidor com seu código **FastAPI**, parará em seus pontos de interrupção, etc.

Veja como pode parecer:

                        "200": {
                            "description": "Successful Response",
                            "content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

	Pools     []rebalancePoolStatus `json:"pools"` // contains all pools, including inactive
	StoppedAt time.Time             `json:"stoppedAt,omitempty"`
}

func rebalanceStatus(ctx context.Context, z *erasureServerPools) (r rebalanceAdminStatus, err error) {
	// Load latest rebalance status
	meta := &rebalanceMeta{}
	err = meta.load(ctx, z.serverPools[0])
	if err != nil {
		return r, err
	}

```Python hl_lines="1  7-12  19-20"
{!../../docs_src/dataclasses/tutorial001.py!}
```

👉 🐕‍🦺 👏 **Pydantic**, ⚫️ ✔️ <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">🔗 🐕‍🦺 `dataclasses`</a>.

, ⏮️ 📟 🔛 👈 🚫 ⚙️ Pydantic 🎯, FastAPI ⚙️ Pydantic 🗜 📚 🐩 🎻 Pydantic 👍 🍛 🎻.