So we create a new `dict`, that contains the key-value pairs from `note.dict()` with:

```Python
{**note.dict()}
```

`**note.dict()` "unpacks" the key value pairs directly, so, `{**note.dict()}` would be, more or less, a copy of `note.dict()`.

And then, we extend that copy `dict`, adding another key-value pair: `"id": last_record_id`:

```Python
{**note.dict(), "id": last_record_id}
```

{% endfor %}
{% endif %}

## About the data - technical details

The main intention of this page is to highlight the effort of the community to help others.

Especially including efforts that are normally less visible, and in many cases more arduous, like helping others with questions and reviewing Pull Requests with translations.

    * Normally, a token is set to expire after some time.
        * So, the user will have to log in again at some point later.
        * And if the token is stolen, the risk is less. It is not like a permanent key that will work forever (in most of the cases).
* The frontend stores that token temporarily somewhere.
* The user clicks in the frontend to go to another section of the frontend web app.

An interesting detail is that the percentage of the **CPU used** by each process can **vary** a lot over time, but the **memory (RAM)** normally stays more or less **stable**.

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

Pydantic version 2 has the **core** re-written in **Rust** and includes a lot of improvements and features, for example:

* Improved **correctness** in corner cases.
* **Safer** types.
* Better **performance** and **less energy** consumption.
* Better **extensibility**.
* etc.

...all this while keeping the **same Python API**. In most of the cases, for simple models, you can simply upgrade the Pydantic version and get all the benefits. 🚀

그리고 숫자 검증 또한 선언할 수 있습니다:

* `gt`: 크거나(`g`reater `t`han)
* `ge`: 크거나 같은(`g`reater than or `e`qual)
* `lt`: 작거나(`l`ess `t`han)
* `le`: 작거나 같은(`l`ess than or `e`qual)

!!! info "정보"
    `Query`, `Path`, 그리고 나중에게 보게될 것들은 (여러분이 사용할 필요가 없는) 공통 `Param` 클래스의 서브 클래스입니다.

    그리고 이들 모두는 여태까지 본 추가 검증과 메타데이터의 동일한 모든 매개변수를 공유합니다.

!!! note "기술 세부사항"

而且你还可以声明数值校验：

* `gt`：大于（`g`reater `t`han）
* `ge`：大于等于（`g`reater than or `e`qual）
* `lt`：小于（`l`ess `t`han）
* `le`：小于等于（`l`ess than or `e`qual）

!!! info
    `Query`、`Path` 以及你后面会看到的其他类继承自一个共同的 `Param` 类（不需要直接使用它）。

    而且它们都共享相同的所有你已看到并用于添加额外校验和元数据的参数。

!!! note "技术细节"
    当你从 `fastapi` 导入 `Query`、`Path` 和其他同类对象时，它们实际上是函数。

    当被调用时，它们返回同名类的实例。

    如此，你导入 `Query` 这个函数。当你调用它时，它将返回一个同样命名为 `Query` 的类的实例。

Dann könnten Sie dieses Python-Programm aufrufen:

<div class="termy">

```console
// Hier legen wir die Umgebungsvariable noch nicht fest
$ python main.py

// Da wir die Umgebungsvariable nicht festgelegt haben, erhalten wir den Standardwert

Hello World from Python

// Aber wenn wir zuerst eine Umgebungsvariable erstellen

When you run `fastapi dev`, it will run on development mode.

By default, it will have **auto-reload** enabled, so it will automatically reload the server when you make changes to your code. This is resource intensive and could be less stable than without it, you should only use it for development.

By default it will listen on the IP address `127.0.0.1`, which is the IP for your machine to communicate with itself alone (`localhost`).

## `fastapi run`

!!! note
    When defining a <a href="https://docs.pydantic.dev/latest/concepts/types/#unions" class="external-link" target="_blank">`Union`</a>, include the most specific type first, followed by the less specific type. In the example below, the more specific `PlaneItem` comes before `CarItem` in `Union[PlaneItem, CarItem]`.

=== "Python 3.10+"

    ```Python hl_lines="1  14-15  18-20  33"