* `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` 。

코드에 보안 결함이 있다면, 그 결함은 여전히 존재할 것입니다.

문서를 숨기는 것은 API와 상호작용하는 방법을 이해하기 어렵게 만들며, 프로덕션에서 디버깅을 더 어렵게 만들 수 있습니다. 이는 단순히 <a href="https://en.wikipedia.org/wiki/Security_through_obscurity" class="external-link" target="_blank">'모호성에 의한 보안'</a>의 한 형태로 간주될 수 있습니다.

API를 보호하고 싶다면, 예를 들어 다음과 같은 더 나은 방법들이 있습니다:

* 요청 본문과 응답에 대해 잘 정의된 Pydantic 모델을 사용하도록 하세요.

* 종속성을 사용하여 필요한 권한과 역할을 구성하세요.

 */

/**
 * Collection interfaces and implementations, and other utilities for collections. This package is a
 * part of the open-source <a href="https://github.com/google/guava">Guava</a> library.
 *
 * <p>The classes in this package include:
 *
 * <h2>Immutable collections</h2>
 *
 * These are collections whose contents will never change. They also offer a few additional

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel, Field

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = Field(
        default=None, title="The description of the item", max_length=300
    )
    price: float = Field(gt=0, description="The price must be greater than zero")
    tax: float | None = None


@app.put("/items/{item_id}")

from typing import Union

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")
async def read_items(commons=Depends(CommonQueryParams)):

import org.opensearch.core.action.ActionListener;

import jakarta.annotation.Resource;

/**
 * Admin action for maintenance operations including reindexing, log management,
 * and system diagnostics.
 */
public class AdminMaintenanceAction extends FessAdminAction {

    /**
     * Default constructor for AdminMaintenanceAction.
     */
    public AdminMaintenanceAction() {
        super();
    }

    /**

import jcifs.internal.util.SMBUtil;
import jcifs.util.Hexdump;

/**
 * Base class for SMB1 transaction request messages.
 * This abstract class provides the foundation for all SMB1 transaction commands, handling
 * parameter and data buffer encoding, multi-part transactions, and setup word management.
 */
public abstract class SmbComTransaction extends ServerMessageBlock implements Enumeration<SmbComTransaction> {

І знову ж таки, ви отримуєте всю підтримку редактора:

<img src="/img/python-types/image06.png">

## Pydantic моделі

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> це бібліотека Python для валідації даних.

Ви оголошуєте «форму» даних як класи з атрибутами.

І кожен атрибут має тип.

{* ../../docs_src/python_types/tutorial010.py hl[6] *}


然后，你将再次获得所有的编辑器支持：

<img src="https://fastapi.tiangolo.com/img/python-types/image06.png">

## Pydantic 模型

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> 是一个用来执行数据校验的 Python 库。

你可以将数据的"结构"声明为具有属性的类。

每个属性都拥有类型。

接着你用一些值来创建这个类的实例，这些值会被校验，并被转换为适当的类型（在需要的情况下），返回一个包含所有数据的对象。

然后，你将获得这个对象的所有编辑器支持。

/**
 * SMB protocol utility class providing low-level data encoding and decoding operations.
 * Contains methods for reading and writing various data types (integers, strings, timestamps)
 * in SMB protocol format, handling endianness and data type conversions.
 *
 * @author mbechler
 */
public class SMBUtil {

    /**
     * Private constructor to prevent instantiation of utility class.
     */
    private SMBUtil() {
    }