`@lru_cache` ist Teil von `functools`, welches Teil von Pythons Standardbibliothek ist. Weitere Informationen dazu finden Sie in der <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python Dokumentation für `@lru_cache`</a>.

## Zusammenfassung

`@lru_cache` 🍕 `functools` ❔ 🍕 🐍 🐩 🗃, 👆 💪 ✍ 🌅 🔃 ⚫️ <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">🐍 🩺 `@lru_cache`</a>.

## 🌃

👆 💪 ⚙️ Pydantic ⚒ 🍵 ⚒ ⚖️ 📳 👆 🈸, ⏮️ 🌐 🏋️ Pydantic 🏷.

* ⚙️ 🔗 👆 💪 📉 🔬.
* 👆 💪 ⚙️ `.env` 📁 ⏮️ ⚫️.

`@lru_cache` é definido no módulo `functools` que faz parte da biblioteca padrão do Python, você pode ler mais sobre esse decorador no link <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python Docs sobre `@lru_cache`</a>.

## Recapitulando

`@lru_cache` is part of `functools` which is part of Python's standard library, you can read more about it in the <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python docs for `@lru_cache`</a>.

## Recap

这样，它的行为几乎就像是一个全局变量。但是由于它使用了依赖项函数，因此我们可以轻松地进行测试时的覆盖。

`@lru_cache` 是 `functools` 的一部分，它是 Python 标准库的一部分，您可以在<a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python 文档中了解有关 `@lru_cache` 的更多信息</a>。

## 小结

您可以使用 Pydantic 设置处理应用程序的设置或配置，利用 Pydantic 模型的所有功能。

* 通过使用依赖项，您可以简化测试。
* 您可以使用 `.env` 文件。

import json
import logging
import os
import re
import shutil
import subprocess
from functools import lru_cache
from http.server import HTTPServer, SimpleHTTPRequestHandler
from importlib import metadata
from multiprocessing import Pool
from pathlib import Path
from typing import Any, Dict, List, Optional, Union

import mkdocs.utils
import typer
import yaml
from jinja2 import Template
from ruff.__main__ import find_ruff_bin

from collections import deque
from copy import copy
from dataclasses import dataclass, is_dataclass
from enum import Enum
from functools import lru_cache
from typing import (
    Any,
    Callable,
    Deque,
    Dict,
    FrozenSet,
    List,
    Mapping,
    Sequence,
    Set,
    Tuple,
    Type,
    Union,
)

from fastapi.exceptions import RequestErrorModel
from fastapi.types import IncEx, ModelNameMap, UnionType

* Start Portuguese translations. PR [#1210](https://github.com/tiangolo/fastapi/pull/1210) by [@cassiobotaro](https://github.com/cassiobotaro).
* Update docs for Pydantic's `Settings` using a dependency with `@lru_cache()`. PR [#1214](https://github.com/tiangolo/fastapi/pull/1214).