```python
    from fastapi import Depends, FastAPI
    from fastapi.security import APIKeyQuery

    app = FastAPI()

    query_scheme = APIKeyQuery(name="api_key")


    @app.get("/items/")
    async def read_items(api_key: str = Depends(query_scheme)):
        return {"api_key": api_key}
    ```
    """

    def __init__(
        self,
        *,
        name: Annotated[
            str,

package callbacks

import (
	"reflect"
	"sync"
	"testing"
	"time"

	"gorm.io/gorm"
	"gorm.io/gorm/clause"
	"gorm.io/gorm/schema"
)

var schemaCache = &sync.Map{}

func TestConvertToCreateValues_DestType_Slice(t *testing.T) {
	type user struct {
		ID    int `gorm:"primaryKey"`
		Name  string
		Email string `gorm:"default:(-)"`
		Age   int    `gorm:"default:(-)"`
	}

# Without aliases


@app.post("/optional-str", operation_id="optional_str")
async def read_optional_str(p: Annotated[str | None, Form()] = None):
    return {"p": p}


class FormModelOptionalStr(BaseModel):
    p: str | None = None


@app.post("/model-optional-str", operation_id="model_optional_str")
async def read_model_optional_str(p: Annotated[FormModelOptionalStr, Form()]):
    return {"p": p.p}

# =====================================================================================
# Without aliases


@app.get("/required-str")
async def read_required_str(p: str):
    return {"p": p}


class QueryModelRequiredStr(BaseModel):
    p: str


@app.get("/model-required-str")
async def read_model_required_str(p: Annotated[QueryModelRequiredStr, Query()]):
    return {"p": p.p}


@pytest.mark.parametrize(
    "path",

## `Async` ou não, eis a questão { #to-async-or-not-to-async }

Como as dependências também serão chamadas pelo **FastAPI** (da mesma forma que *funções de operação de rota*), as mesmas regras se aplicam ao definir suas funções.

Você pode utilizar `async def` ou apenas `def`.

    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.put("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    update_item_encoded = jsonable_encoder(item)
    items[item_id] = update_item_encoded

from fastapi.testclient import TestClient
from inline_snapshot import snapshot

app = FastAPI()


@app.get("/hidden_cookie")
async def hidden_cookie(
    hidden_cookie: str | None = Cookie(default=None, include_in_schema=False),
):
    return {"hidden_cookie": hidden_cookie}


@app.get("/hidden_header")
async def hidden_header(
    hidden_header: str | None = Header(default=None, include_in_schema=False),
):

### 文件与异步 { #files-and-async }

大多数情况下，类文件对象默认与 async 和 await 不兼容。

例如，它们没有 `await file.read()`，也不支持 `async for chunk in file`。

而且很多情况下，读取它们是一个阻塞操作（可能会阻塞事件循环），因为数据来自磁盘或网络。

/// info | 信息

上面的示例其实是个例外，因为 `io.BytesIO` 对象已经在内存中，所以读取它不会阻塞。

但在许多情况下，读取文件或类文件对象会发生阻塞。

///

为避免阻塞事件循环，你可以简单地把*路径操作函数*声明为常规的 `def`（而不是 `async def`），这样 FastAPI 会在一个线程池工作线程上运行它，从而避免阻塞主事件循环。

如果你要回傳的每個 JSON 項目型別都是 `Item`（一個 Pydantic 模型），而且該函式是 async，你可以將回傳型別宣告為 `AsyncIterable[Item]`：

{* ../../docs_src/stream_json_lines/tutorial001_py310.py ln[1:24] hl[9:11,22] *}

如果你宣告了回傳型別，FastAPI 會用它來進行資料的**驗證**、在 OpenAPI 中**文件化**、**過濾**，並使用 Pydantic 進行**序列化**。

/// tip

由於 Pydantic 會在 **Rust** 端進行序列化，宣告回傳型別可獲得比未宣告時高得多的**效能**。

///

### 非 async 的*路徑操作函式* { #non-async-path-operation-functions }

app = FastAPI()

T = TypeVar("T")

Dep = Annotated[T, Depends()]


class A:
    pass


class B:
    pass


@app.get("/a")
async def a(dep: Dep[A]):
    return {"cls": dep.__class__.__name__}


@app.get("/b")
async def b(dep: Dep[B]):
    return {"cls": dep.__class__.__name__}


client = TestClient(app)


def test_generic_parameterless_depends():