Você pode limitar as linhas utilizadas a partir de uma docstring de uma *função de operação de rota* para o OpenAPI.

Adicionar um `\f` (um caractere de escape para alimentação de formulário) faz com que o **FastAPI** restrinja a saída utilizada pelo OpenAPI até esse ponto.

Ele não será mostrado na documentação, mas outras ferramentas (como o Sphinx) serão capazes de utilizar o resto do texto.

///

**FastAPI** повністю базується на Pydantic.

Ви побачите набагато більше цього всього на практиці в [Tutorial - User Guide](tutorial/index.md){.internal-link target=_blank}.

## Анотації типів у **FastAPI**

**FastAPI** використовує ці підказки для виконання кількох речей.

З **FastAPI** ви оголошуєте параметри з підказками типу, і отримуєте:

from typing import Annotated, Union

from fastapi import Depends, FastAPI, HTTPException, Query
from sqlmodel import Field, Session, SQLModel, create_engine, select


class Hero(SQLModel, table=True):
    id: Union[int, None] = Field(default=None, primary_key=True)
    name: str = Field(index=True)
    age: Union[int, None] = Field(default=None, index=True)
    secret_name: str


sqlite_file_name = "database.db"

### Errores Pequeños Manejados Automáticamente { #small-errors-automatically-handled }

Al construir APIs web con FastAPI, si hay un error en nuestro código, FastAPI normalmente lo contiene al request único que desencadenó el error. 🛡

import importlib

import pytest
from fastapi.testclient import TestClient

from ...utils import needs_py310


@pytest.fixture(
    name="client",
    params=[
        "tutorial003_py39",
        pytest.param("tutorial003_py310", marks=needs_py310),
        "tutorial003_an_py39",
        pytest.param("tutorial003_an_py310", marks=needs_py310),
    ],
)
def get_client(request: pytest.FixtureRequest):

        check=True,
    )
    branch_name = f"fastapi-topic-repos-{secrets.token_hex(4)}"
    logging.info(f"Creating a new branch {branch_name}")
    subprocess.run(["git", "checkout", "-b", branch_name], check=True)
    logging.info("Adding updated file")
    subprocess.run(["git", "add", str(repos_path)], check=True)
    logging.info("Committing updated file")
    message = "👥 Update FastAPI GitHub topic repositories"

import importlib
import os
import shutil

import pytest
from fastapi.testclient import TestClient

from tests.utils import needs_py310


@pytest.fixture(
    name="client",
    params=[
        pytest.param("tutorial002_py39"),
        pytest.param("tutorial002_py310", marks=needs_py310),
    ],
)
def get_client(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.additional_responses.{request.param}")

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

# 部署

部署 **FastAPI** 应用程序相对容易。

## 部署是什么意思

**部署**应用程序意味着执行必要的步骤以使其**可供用户使用**。

对于**Web API**来说，通常涉及将上传到**云服务器**中，搭配一个性能和稳定性都不错的**服务器程序**，以便你的**用户**可以高效地**访问**你的应用程序，而不会出现中断或其他问题。

这与**开发**阶段形成鲜明对比，在**开发**阶段，你不断更改代码、破坏代码、修复代码, 来回停止和重启服务器等。

## 部署策略

根据你的使用场景和使用的工具，有多种方法可以实现此目的。

你可以使用一些工具自行**部署服务器**，你也可以使用能为你完成部分工作的**云服务**，或其他可能的选项。

我将向你展示在部署 **FastAPI** 应用程序时你可能应该记住的一些主要概念（尽管其中大部分适用于任何其他类型的 Web 应用程序）。

import importlib

import pytest
from fastapi.testclient import TestClient

from ...utils import needs_py310


@pytest.fixture(
    name="client",
    params=[
        pytest.param("tutorial001_py39"),
        pytest.param("tutorial001_py310", marks=needs_py310),
        pytest.param("tutorial001_an_py39"),
        pytest.param("tutorial001_an_py310", marks=needs_py310),
    ],
)