* `COMPATIBLE_TLS` is a secure configuration that connects to secure–but not current–HTTPS servers.
 * `CLEARTEXT` is an insecure configuration that is used for `http://` URLs.

These loosely follow the model set in [Google Cloud Policies](https://cloud.google.com/load-balancing/docs/ssl-policies-concepts). We [track changes](../security/tls_configuration_history.md) to this policy.

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

👈 💪 ⤴️ ⚙️ 💖:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {

Temporarily adopting this point of view (of the *external developer*) can help you feel like it's more obvious where to put the parameters, the Pydantic model for the body, for the response, etc. for that *external API*.

///

### Create a callback `APIRouter` { #create-a-callback-apirouter }

First create a new `APIRouter` that will contain one or more callbacks.

Ayrıca, Pydantic modelleri de döndürebilirsiniz (bu konu ileriki aşamalarda irdelenecektir).

Otomatik olarak JSON'a dönüştürülecek (ORM'ler vb. dahil) başka birçok nesne ve model vardır. En beğendiklerinizi kullanmayı deneyin, yüksek ihtimalle destekleniyordur.

## Özet

* `FastAPI`'yı projemize dahil ettik.
* Bir `app` örneği oluşturduk.

	if err := DB.Create(&user).Error; err != nil {
		t.Fatalf("errors happened when create: %v", err)
	}

	var result struct {
		Something string
		User
	}

	DB.Model(User{}).Preload("Account", clause.Eq{Column: "number", Value: user.Account.Number}).Select(
		"users.*, 'yo' as something").First(&result, "name = ?", user.Name)

	CheckUser(t, user, result.User)
}

*   [TensorFlow Twitter](https://twitter.com/tensorflow)
*   [TensorFlow YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ)
*   [TensorFlow model optimization roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap)
*   [TensorFlow White Papers](https://www.tensorflow.org/about/bib)
*   [TensorBoard Visualization Toolkit](https://github.com/tensorflow/tensorboard)

  <mime-type type="model/vnd.flatland.3dml"/>
  <mime-type type="model/vnd.gdl">
    <glob pattern="*.gdl"/>
  </mime-type>
  <mime-type type="model/vnd.gs-gdl"/>
  <mime-type type="model/vnd.gs.gdl"/>
  <mime-type type="model/vnd.gtw">
    <glob pattern="*.gtw"/>
  </mime-type>
  <mime-type type="model/vnd.moml+xml"/>
  <mime-type type="model/vnd.mts">
    <glob pattern="*.mts"/>
  </mime-type>

`hashed_password`. To fix this, the declared `response_model` is cloned, if it is a Pydantic model class (or contains Pydantic model classes in it, e.g. in a `List[Item]`), the Pydantic model class(es) will be a different one (the "cloned" one). So, an object that is a subclass won't simply pass the validation and returned as-is, because it is no longer a sub-class of the cloned `response_model`. Instead, a new Pydantic model object will be created with the contents of the returned object. So, it will be a...

<span style="color: green;">INFO</span>:     Application startup complete.
```

</div>

/// note | Hinweis

Der Befehl `uvicorn main:app` bezieht sich auf:

* `main`: die Datei `main.py` (das sogenannte Python-„Modul“).
* `app`: das Objekt, welches in der Datei `main.py` mit der Zeile `app = FastAPI()` erzeugt wurde.
* `--reload`: lässt den Server nach Codeänderungen neu starten. Verwenden Sie das nur während der Entwicklung.

///

<img src="/img/tutorial/body/image01.png">

이를 필요로 하는 각각의 *경로 작동*내부의 API 문서에도 사용됩니다:

<img src="/img/tutorial/body/image02.png">

## 편집기 지원

편집기에서, 함수 내에서 타입 힌트와 완성을 어디서나 (만약 Pydantic model 대신에 `dict`을 받을 경우 나타나지 않을 수 있습니다) 받을 수 있습니다:

<img src="/img/tutorial/body/image03.png">

잘못된 타입 연산에 대한 에러 확인도 받을 수 있습니다:

<img src="/img/tutorial/body/image04.png">

단순한 우연이 아닙니다. 프레임워크 전체가 이러한 디자인을 중심으로 설계되었습니다.