So, we get a Pydantic model from the data in another Pydantic model.

#### Unwrapping a `dict` and extra keywords

And then adding the extra keyword argument `hashed_password=hashed_password`, like in:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

...ends up being like:

```Python
UserInDB(

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。

例えば:

```Python
class Cat:
    def __init__(self, name: str):

关键因素是依赖项应该是 "可调用对象"。

Python 中的 "**可调用对象**" 是指任何 Python 可以像函数一样 "调用" 的对象。

所以，如果你有一个对象 `something` (可能*不是*一个函数)，你可以 "调用" 它(执行它)，就像：

```Python
something()
```

或者

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

这就是 "可调用对象"。

## 类作为依赖项

您可能会注意到，要创建一个 Python 类的实例，您可以使用相同的语法。

举个例子:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name

```

`.add_task()` receives as arguments:

* A task function to be run in the background (`write_notification`).
* Any sequence of arguments that should be passed to the task function in order (`email`).
* Any keyword arguments that should be passed to the task function (`message="some notification"`).

## Dependency Injection

Wenn Sie also ein Objekt `something` haben (das möglicherweise _keine_ Funktion ist) und Sie es wie folgt aufrufen (ausführen) können:

```Python
something()
```

oder

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

dann ist das ein „Callable“ (ein „Aufrufbares“).

## Klassen als Abhängigkeiten

"**🇧🇲**" 🐍 🕳 👈 🐍 💪 "🤙" 💖 🔢.

, 🚥 👆 ✔️ 🎚 `something` (👈 💪 _🚫_ 🔢) & 👆 💪 "🤙" ⚫️ (🛠️ ⚫️) 💖:

```Python
something()
```

⚖️

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

⤴️ ⚫️ "🇧🇲".

## 🎓 🔗

👆 5️⃣📆 👀 👈 ✍ 👐 🐍 🎓, 👆 ⚙️ 👈 🎏 ❕.

🖼:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name

!!! tip
    Instead of passing each of the keyword arguments to `Item` and reading each one of them from the Pydantic *model*, we are generating a `dict` with the Pydantic *model*'s data with:

    `item.dict()`

    and then we are passing the `dict`'s key-value pairs as the keyword arguments to the SQLAlchemy `Item`, with:

    `Item(**item.dict())`

...Python has a little special syntax for that.

Pass `*`, as the first parameter of the function.

Python won't do anything with that `*`, but it will know that all the following parameters should be called as keyword arguments (key-value pairs), also known as <abbr title="From: K-ey W-ord Arg-uments"><code>kwargs</code></abbr>. Even if they don't have a default value.

```Python hl_lines="7"

So, if you have an object `something` (that might _not_ be a function) and you can "call" it (execute it) like:

```Python
something()
```

or

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

then it is a "callable".

## Classes as dependencies

You might notice that to create an instance of a Python class, you use that same syntax.

For example:

```Python

!!! info
    OpenAPI 3.1.0 (used since FastAPI 0.99.0) added support for `examples`, which is part of the **JSON Schema** standard.

    Before that, it only supported the keyword `example` with a single example. That is still supported by OpenAPI 3.1.0, but is deprecated and is not part of the JSON Schema standard. So you are encouraged to migrate `example` to `examples`. 🤓