class Item(BaseModel):
    name: str

    if PYDANTIC_V2:
        model_config = {
            "json_schema_extra": {
                "x-something-internal": {"level": 4},
            }
        }
    else:

        class Config:
            schema_extra = {
                "x-something-internal": {"level": 4},
            }


@app.get("/foo", response_model=Item)
def foo():
    return {"name": "Foo item"}

Asynchronous code just means that the language 💬 has a way to tell the computer / program 🤖 that at some point in the code, it 🤖 will have to wait for *something else* to finish somewhere else. Let's say that *something else* is called "slow-file" 📝.

So, during that time, the computer can go and do some other work, while "slow-file" 📝 finishes.

At that point, by noticing that the server took some microseconds longer to send the "Incorrect username or password" response, the attackers will know that they got _something_ right, some of the initial letters were right.

And then they can try again knowing that it's probably something more similar to `stanleyjobsox` than to `johndoe`.

#### A "professional" attack

app = FastAPI()


def get_header(*, someheader: str = Header()):
    return someheader


def get_something_else(*, someheader: str = Depends(get_header)):
    return f"{someheader}123"


@app.get("/")
def get_deps(dep1: str = Depends(get_header), dep2: str = Depends(get_something_else)):
    return {"dep1": dep1, "dep2": dep2}


client = TestClient(app)

schema = {
    "components": {

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

しかし、依存関係を定義する方法はそれだけではありません（その方が一般的かもしれませんが）。

重要なのは、依存関係が「呼び出し可能」なものであることです。

Pythonにおける「**呼び出し可能**」とは、Pythonが関数のように「呼び出す」ことができるものを指します。

そのため、`something`オブジェクト（関数ではないかもしれませんが）を持っていて、それを次のように「呼び出す」（実行する）ことができるとします:

```Python
something()
```

または

```Python
something(some_argument, some_keyword_argument="foo")
```

これを「呼び出し可能」なものと呼びます。

## 依存関係としてのクラス

Pythonのクラスのインスタンスを作成する際に、同じ構文を使用していることに気づくかもしれません。

!!! info "`@decorator` Info"
    That `@something` syntax in Python is called a "decorator".

    You put it on top of a function. Like a pretty decorative hat (I guess that's where the term came from).

    A "decorator" takes the function below and does something with it.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
* It then takes the **response** generated by the application (by some *path operation*).
* It can do something to that **response** or run any needed code.
* Then it returns the **response**.

`Optional[Something]` là một cách viết ngắn gọn của `Union[Something, None]`, chúng là tương đương nhau.

Điều này cũng có nghĩa là trong Python 3.10, bạn có thể sử dụng `Something | None`:

=== "Python 3.10+"

    ```Python hl_lines="1"
    {!> ../../../docs_src/python_types/tutorial009_py310.py!}
    ```

def test_get_exception():
    response = client.get("/unicorns/yolo")
    assert response.status_code == 418, response.text
    assert response.json() == {
        "message": "Oops! yolo did something. There goes a rainbow..."
    }


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text
    assert response.json() == {