You can set `"json_schema_extra"` with a `dict` containing any additional data you would like to show up in the generated JSON Schema, including `examples`.

=== "Pydantic v1"

    Sie können `json_schema_extra` setzen, mit einem `dict`, das alle zusätzlichen Daten enthält, die im generierten JSON-Schema angezeigt werden sollen, einschließlich `examples`.

=== "Pydantic v1"

Also, the best approach was to use already existing standards.

So, before even starting to code **FastAPI**, I spent several months studying the specs for OpenAPI, JSON Schema, OAuth2, etc. Understanding their relationship, overlap, and differences.

## Design

Then I spent some time designing the developer "API" I wanted to have as a user (as a developer using FastAPI).

Também, a melhor abordagem era usar padrões já existentes.

Então, antes mesmo de começar a codificar o **FastAPI**, eu investi vários meses estudando as especificações do OpenAPI, JSON Schema, OAuth2 etc. Entendendo suas relações, sobreposições e diferenças.

## Design

Eu então dediquei algum tempo projetando a "API" de desenvolvimento que eu queria como usuário (como um desenvolvedor usando o FastAPI).

import "k8s.io/apimachinery/pkg/api/resource/generated.proto";
import "k8s.io/apimachinery/pkg/apis/meta/v1/generated.proto";
import "k8s.io/apimachinery/pkg/runtime/generated.proto";
import "k8s.io/apimachinery/pkg/runtime/schema/generated.proto";

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/node/v1beta1";

// Overhead structure represents the resource overhead associated with running a pod.

一个常见的用例是添加一个将在文档中显示的`example`。

有几种方法可以声明额外的 JSON 模式信息。

## Pydantic `schema_extra`

您可以使用 `Config` 和 `schema_extra` 为Pydantic模型声明一个示例，如<a href="https://docs.pydantic.dev/latest/concepts/json_schema/#schema-customization" class="external-link" target="_blank">Pydantic 文档：定制 Schema </a>中所述:

=== "Python 3.10+"

    ```Python hl_lines="13-21"
    {!> ../../../docs_src/schema_extra_example/tutorial001_py310.py!}
    ```

=== "Python 3.8+"

* 使用 <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (因为 OpenAPI 本身就是基于 JSON Schema 的)自动生成数据模型文档。
* 经过了缜密的研究后围绕这些标准而设计。并非狗尾续貂。
* 这也允许了在很多语言中自动**生成客户端代码**。

### 自动生成文档

交互式 API 文档以及具探索性 web 界面。因为该框架是基于 OpenAPI，所以有很多可选项，FastAPI 默认自带两个交互式 API 文档。

    These Pydantic models define more or less a "schema" (a valid data shape).

    So this will help us avoiding confusion while using both.

### Create the Pydantic *models* / schemas

Create all the same Pydantic models as in the SQLAlchemy tutorial:

import "k8s.io/api/core/v1/generated.proto";
import "k8s.io/apimachinery/pkg/apis/meta/v1/generated.proto";
import "k8s.io/apimachinery/pkg/runtime/generated.proto";
import "k8s.io/apimachinery/pkg/runtime/schema/generated.proto";

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/events/v1";

👆 💪 📣 🖼 💽 👆 📱 💪 📨.

📥 📚 🌌 ⚫️.

## Pydantic `schema_extra`

👆 💪 📣 `example` Pydantic 🏷 ⚙️ `Config` &amp; `schema_extra`, 🔬 <a href="https://docs.pydantic.dev/latest/concepts/json_schema/#customizing-json-schema" class="external-link" target="_blank">Pydantic 🩺: 🔗 🛃</a>:

=== "🐍 3️⃣.6️⃣ &amp; 🔛"

    ```Python hl_lines="15-23"
    {!> ../../../docs_src/schema_extra_example/tutorial001.py!}
    ```