In this case, it is an `async` function.

---

You could also define it as a normal function instead of `async def`:

{* ../../docs_src/first_steps/tutorial003_py39.py hl[7] *}

/// note

If you don't know the difference, check the [Async: *"In a hurry?"*](../async.md#in-a-hurry){.internal-link target=_blank}.

///

In diesem Fall handelt es sich um eine `async`-Funktion.

---

Sie könnten sie auch als normale Funktion anstelle von `async def` definieren:

{* ../../docs_src/first_steps/tutorial003_py39.py hl[7] *}

/// note | Hinweis

Wenn Sie den Unterschied nicht kennen, lesen Sie [Async: *„In Eile?“*](../async.md#in-a-hurry){.internal-link target=_blank}.

///

from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Annotated[
        Item,
        Body(
            openapi_examples={
                "normal": {
                    "summary": "A normal example",

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item = Body(
        openapi_examples={
            "normal": {
                "summary": "A normal example",

package tests_test

import (
	"regexp"
	"sync"
	"testing"

	"gorm.io/driver/gaussdb"
	"gorm.io/driver/postgres"
	"gorm.io/gorm"
	"gorm.io/gorm/schema"
	"gorm.io/gorm/utils/tests"
	. "gorm.io/gorm/utils/tests"
)

type UserWithTable struct {
	gorm.Model
	Name string
}

func (UserWithTable) TableName() string {
	return "gorm.user"
}

func TestTable(t *testing.T) {

from fastapi.testclient import TestClient

from .utils import needs_py310


def get_client():
    app = FastAPI()
    with pytest.warns(FastAPIDeprecationWarning):

        @app.get("/items/")
        async def read_items(
            q: Annotated[str | None, Query(regex="^fixedquery$")] = None,
        ):
            if q:
                return f"Hello {q}"
            else:
                return "Hello World"

<details markdown="1">
<summary>Or use <code>async def</code>...</summary>

If your code uses `async` / `await`, use `async def`:

```Python hl_lines="9  14"
from typing import Union

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
async def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
async def read_item(item_id: int, q: Union[str, None] = None):

```Python
contents = myfile.file.read()
```

/// note | Detalhes Técnicos do `async`

Quando você usa os métodos `async`, o **FastAPI** executa os métodos de arquivo em um threadpool e aguarda por eles.

///

/// note | Detalhes Técnicos do Starlette

Es solo una función estándar que puede recibir parámetros.

Puede ser una función `async def` o una función normal `def`, **FastAPI** sabrá cómo manejarla correctamente.

En este caso, la función de tarea escribirá en un archivo (simulando el envío de un email).

Y como la operación de escritura no usa `async` y `await`, definimos la función con un `def` normal:

	trash:   make(map[string]metacache),
}

type metacacheManager struct {
	mu      sync.RWMutex
	init    sync.Once
	buckets map[string]*bucketMetacache
	trash   map[string]metacache // Recently deleted lists.
}

const metacacheMaxEntries = 5000

// initManager will start async saving the cache.
func (m *metacacheManager) initManager() {
	// Add a transient bucket.