* `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` 。

## Concepts de déploiement

Ces exemples lancent le programme serveur (e.g. Uvicorn), démarrant **un seul processus**, sur toutes les IPs (`0.0.
0.0`) sur un port prédéfini (par example, `80`).

C'est l'idée de base. Mais vous vous préoccuperez probablement de certains concepts supplémentaires, tels que ... :

* la sécurité - HTTPS
* l'exécution au démarrage

/// tip | Совет

Атрибут `model_config` используется только для конфигурации Pydantic. Подробнее см. <a href="https://docs.pydantic.dev/latest/concepts/config/" class="external-link" target="_blank">Pydantic: Concepts: Configuration</a>.

///

////

//// tab | Pydantic v1

{* ../../docs_src/settings/app03_an_py39/config_pv1.py hl[9:10] *}

/// tip | Совет

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Это по-прежнему поддерживается благодаря **Pydantic**, так как в нём есть <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">встроенная поддержка `dataclasses`</a>.

/// tip | Tipp

Das Attribut `model_config` wird nur für die Pydantic-Konfiguration verwendet. Weitere Informationen finden Sie unter <a href="https://docs.pydantic.dev/latest/concepts/config/" class="external-link" target="_blank">Pydantic: Concepts: Configuration</a>.

///

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

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>.

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}

Esto sigue siendo soportado gracias a **Pydantic**, ya que tiene <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">soporte interno para `dataclasses`</a>.

## Conceptos de Despliegue { #deployment-concepts }

Aquí viste cómo usar múltiples **workers** para **paralelizar** la ejecución de la aplicación, aprovechar los **múltiples núcleos** del CPU, y poder servir **más requests**.

## Deployment Concepts { #deployment-concepts }

Let's talk again about some of the same [Deployment Concepts](concepts.md){.internal-link target=_blank} in terms of containers.

Containers are mainly a tool to simplify the process of **building and deploying** an application, but they don't enforce a particular approach to handle these **deployment concepts**, and there are several possible strategies.

/// tip

The `model_config` attribute is used just for Pydantic configuration. You can read more at <a href="https://docs.pydantic.dev/latest/concepts/config/" class="external-link" target="_blank">Pydantic: Concepts: Configuration</a>.

///

Here we define the config `env_file` inside of your Pydantic `Settings` class, and set the value to the filename with the dotenv file we want to use.