)

// TestMain initializes the testing framework
func TestMain(m *testing.M) {
	startLockServers()

	// Initialize locker clients for dsync.
	var clnts []NetLocker
	for i := range nodes {
		clnts = append(clnts, newClient(nodes[i].URL))
	}

	ds = &Dsync{
		GetLockers: func() ([]NetLocker, string) { return clnts, uuid.New().String() },
		Timeouts: Timeouts{
			Acquire:         testDrwMutexAcquireTimeout,

 *  * `com.twitter.hpack.HpackUtil`
 *
 * [twitter_hpack]: https://github.com/twitter/hpack
 */
object Huffman {
  // Appendix C: Huffman Codes
  // http://tools.ietf.org/html/draft-ietf-httpbis-header-compression-12#appendix-B
  private val CODES =
    intArrayOf(
      0x1ff8,
      0x7fffd8,
      0xfffffe2,
      0xfffffe3,
      0xfffffe4,
      0xfffffe5,
      0xfffffe6,
      0xfffffe7,

# Response Status Code { #response-status-code }

Bir response model tanımlayabildiğiniz gibi, herhangi bir *path operation* içinde `status_code` parametresiyle response için kullanılacak HTTP status code'u da belirtebilirsiniz:

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* vb.

{* ../../docs_src/response_status_code/tutorial001_py310.py hl[6] *}

/// note | Not

from typing import Annotated

from annotated_doc import Doc
from fastapi.openapi.models import APIKey, APIKeyIn
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_401_UNAUTHORIZED


class APIKeyBase(SecurityBase):
    model: APIKey

    def __init__(
        self,
        location: APIKeyIn,
        name: str,

            <option value="$PROJECT_DIR$/platforms/core-configuration/kotlin-dsl-tooling-models" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-core" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-groovy" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-reflect" />

{* ../../docs_src/security/tutorial001_an_py310.py hl[12] *}

Но это всё ещё не слишком полезно.

Сделаем так, чтобы она возвращала текущего пользователя.

## Создать модель пользователя { #create-a-user-model }

Сначала создадим Pydantic-модель пользователя.

Точно так же, как мы используем Pydantic для объявления тел запросов, мы можем использовать его где угодно:

Request’leri işlemek için kullanmak istediğiniz bazı **machine learning modelleriniz** olduğunu hayal edelim. 🤖

Aynı modeller request’ler arasında paylaşılır; yani request başına bir model, kullanıcı başına bir model vb. gibi değil.

Modeli yüklemenin, diskten çok fazla **data** okunması gerektiği için **oldukça uzun sürebildiğini** düşünelim. Dolayısıyla bunu her request için yapmak istemezsiniz.

* Automatic data model documentation with [**JSON Schema**](https://json-schema.org/) (as OpenAPI itself is based on JSON Schema).
* Designed around these standards, after a meticulous study. Instead of an afterthought layer on top.

</div>

## Créer l'application avec un modèle unique { #create-the-app-with-a-single-model }

Nous allons d'abord créer la première version la plus simple de l'application avec un seul modèle **SQLModel**.

Ensuite, nous l'améliorerons en augmentant la sécurité et la polyvalence avec **plusieurs modèles** ci-dessous. 🤓

### Créer les modèles { #create-models }

Importez `SQLModel` et créez un modèle de base de données :

</div>

## 建立只有單一模型的應用 { #create-the-app-with-a-single-model }

我們先用單一 SQLModel 模型建立這個應用的最簡版。

接著我們會在下方用多個模型來提升安全性與彈性。🤓

### 建立模型 { #create-models }

匯入 `SQLModel` 並建立一個資料庫模型：

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

`Hero` 類別與 Pydantic 模型非常相似（事實上，在底層它就是一個 Pydantic 模型）。

有幾點差異：

* `table=True` 告訴 SQLModel 這是一個「資料表模型」（table model），它應該代表 SQL 資料庫中的一個資料表，而不僅僅是「資料模型」（就像一般的 Pydantic 類別）。