distribution = true

[tool.pdm.build]
source-includes = [
    "tests/",
    "docs_src/",
    "requirements*.txt",
    "scripts/",
    # For a test
    "docs/en/docs/img/favicon.png",
    ]

[tool.tiangolo._internal-slim-build.packages.fastapi-slim.project]
name = "fastapi-slim"

[tool.mypy]
strict = true

[[tool.mypy.overrides]]
module = "fastapi.concurrency"

///

## 与 OpenAPI 集成

依赖项及子依赖项的所有请求声明、验证和需求都可以集成至同一个 OpenAPI 概图。

所以，交互文档里也会显示依赖项的所有信息：

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

## 简单用法

观察一下就会发现，只要*路径* 和*操作*匹配，就可以使用声明的路径操作函数。然后，**FastAPI** 会用正确的参数调用函数，并提取请求中的数据。

实际上，所有（或大多数）网络框架的工作方式都是这样的。

开发人员永远都不需要直接调用这些函数，这些函数是由框架（在此为 **FastAPI** ）调用的。

have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

Este é o mesmo mecanismo utilizado quando você adiciona permissões enquanto se autentica com o Facebook, Google, GitHub, etc:

<img src="/img/tutorial/security/image11.png">

## Token JWT com escopos

Agora, modifique o *caminho de rota* para retornar os escopos solicitados.

///

## 🛠️ ⏮️ 🗄

🌐 📨 📄, 🔬 & 📄 👆 🔗 (& 🎧-🔗) 🔜 🛠️ 🎏 🗄 🔗.

, 🎓 🩺 🔜 ✔️ 🌐 ℹ ⚪️➡️ 👫 🔗 💁‍♂️:

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

## 🙅 ⚙️

🚥 👆 👀 ⚫️, *➡ 🛠️ 🔢* 📣 ⚙️ 🕐❔ *➡* &amp; *🛠️* 🏏, &amp; ⤴️ **FastAPI** ✊ 💅 🤙 🔢 ⏮️ ☑ 🔢, ❎ 📊 ⚪️➡️ 📨.

🤙, 🌐 (⚖️ 🏆) 🕸 🛠️ 👷 👉 🎏 🌌.

					<div class="mr-3">
						<a class="link d-none d-sm-flex" href="${doc.url_link}" data-uri="${doc.url_link}" data-id="${doc.doc_id}"
							data-order="${s.index}"
						> <img src="${fe:url('/images/blank.png')}" alt="thumbnail"
							data-src="${fe:url('/thumbnail/')}?docId=${f:u(doc.doc_id)}&queryId=${f:u(queryId)}" class="thumbnail"
						>
						</a>
					</div>
					</c:if>

![Interceptors Diagram](../assets/images/interceptors@2x.png)

### Application Interceptors

Interceptors are registered as either _application_ or _network_ interceptors. We'll use the `LoggingInterceptor` defined above to show the difference.

<img src="/img/tutorial/response-model/image01.png">

И также обе модели будут использованы в интерактивной документации API:

<img src="/img/tutorial/response-model/image02.png">

## Другие аннотации типов

    buffer.writeUtf8CodePoint(0x1a)
    buffer.writeUtf8CodePoint(0x0a)
    server.enqueue(
      MockResponse.Builder()
        .body(buffer)
        .setHeader("Content-Type", "image/png; charset=utf-8")
        .build(),
    )
    val response = client.newCall(request().build()).execute()
    response.body.close()
    applicationLogs
      .assertLogEqual("--> GET $url")

```

If you open the automatic API docs, your extension will show up at the bottom of the specific *path operation*.

<img src="/img/tutorial/path-operation-advanced-configuration/image01.png">

And if you see the resulting OpenAPI (at `/openapi.json` in your API), you will see your extension as part of the specific *path operation* too:

```JSON hl_lines="22"
{
    "openapi": "3.1.0",
    "info": {