assertEquals("time.adjust.time.millis", FessEnv.TIME_ADJUST_TIME_MILLIS);
        assertEquals("mail.send.mock", FessEnv.MAIL_SEND_MOCK);
        assertEquals("mail.smtp.server.main.host.and.port", FessEnv.MAIL_SMTP_SERVER_MAIN_HOST_AND_PORT);
        assertEquals("mail.subject.test.prefix", FessEnv.MAIL_SUBJECT_TEST_PREFIX);
        assertEquals("mail.return.path", FessEnv.MAIL_RETURN_PATH);
    }

👆 ✍ 🐩 🐍 ⏮️ 🆎:

```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

* And it could also have a declaration of the response it should return, e.g. `response_model=InvoiceEventReceived`.

{* ../../docs_src/openapi_callbacks/tutorial001.py hl[16:18,21:22,28:32] *}

There are 2 main differences from a normal *path operation*:

* It doesn't need to have any actual code, because your app will never call this code. It's only used to document the *external API*. So, the function could just have `pass`.

<div class="termy">

```console
$ cd ~/code/prisoner-of-azkaban

$ python main.py

// Error importing sirius, it's not installed 😱
Traceback (most recent call last):
    File "main.py", line 1, in <module>
        import sirius
```

</div>

    //                                                                      ==============

    /**
     * Displays the wizard index page.
     *
     * @return HTML response for the wizard main page
     */
    @Execute
    @Secured({ ROLE, ROLE + VIEW })
    public HtmlResponse index() {
        return asIndexHtml();
    }

    private HtmlResponse asIndexHtml() {

* Data validation
* API annotation and automatic documentation

And you only have to declare them once.

```Python
from datetime import date

from pydantic import BaseModel

# Объявляем параметр user_id с типом `str`
# и получаем поддержку редактора внутри функции
def main(user_id: str):
    return user_id


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

Это можно использовать так:

```Python

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Değişkeni str olarak belirt
# ve o fonksiyon için harika bir editör desteği al
def main(user_id: str):
    return user_id


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

Sonrasında bu şekilde kullanabilirsin

```Python

Wystarczy, że napiszesz standardowe deklaracje typów Pythona:

```Python
from datetime import date

from pydantic import BaseModel

# Zadeklaruj parametr jako str
# i uzyskaj wsparcie edytora wewnątrz funkcji
def main(user_id: str):
    return user_id


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

A one będą mogły zostać później użyte w następujący sposób:

```Python

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein `str`
# und bekommen Sie Editor-Unterstütung innerhalb der Funktion
def main(user_id: str):
    return user_id


# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

```Python