!!! note "Technical Details"
    ASGI is a new "standard" being developed by Django core team members. It is still not a "Python standard" (a PEP), although they are in the process of doing that.

La valeur du *paramètre de chemin* sera un des "membres" de l'énumération.

#### Comparer les *membres d'énumération*

Vous pouvez comparer ce paramètre avec les membres de votre énumération `ModelName` :

```Python hl_lines="17"
{!../../../docs_src/path_params/tutorial005.py!}
```

#### Récupérer la *valeur de l'énumération*

{!../../../docs_src/path_params/tutorial005.py!}
```

#### Получение *значения перечисления*

Можно получить фактическое значение (в данном случае - `str`) с помощью `model_name.value` или в общем случае `your_enum_member.value`:

```Python hl_lines="20"
{!../../../docs_src/path_params/tutorial005.py!}
```

!!! tip "Подсказка"
    Значение `"lenet"` также можно получить с помощью `ModelName.lenet.value`.

### Mit Python-*<abbr title="Enumeration – Aufzählung">Enums</abbr>* arbeiten

Der *Pfad-Parameter* wird ein *<abbr title="Member – Mitglied: Einer der möglichen Werte einer Enumeration">Member</abbr> eines Enums* sein.

#### *Enum-Member* vergleichen

Sie können ihn mit einem Member Ihres Enums `ModelName` vergleichen:

```Python hl_lines="17"
{!../../../docs_src/path_params/tutorial005.py!}
```

* **Gyorsan kódolható**: A funkciók fejlesztési sebességét 200-300 százalékkal megnöveli. *
* **Kevesebb hiba**: Körülbelül 40%-al csökkenti az emberi (fejlesztői) hibák számát. *
* **Intuitív**: Kiváló szerkesztő támogatás. <abbr title="más néven auto-complete, autocompletion, IntelliSense">Kiegészítés</abbr> mindenhol. Kevesebb hibakereséssel töltött idő.

#### *열거형 멤버* 비교

열거형 `ModelName`의 *열거형 멤버*를 비교할 수 있습니다:

```Python hl_lines="17"
{!../../../docs_src/path_params/tutorial005.py!}
```

#### *열거형 값* 가져오기

`model_name.value` 또는 일반적으로 `your_enum_member.value`를 이용하여 실제 값(위 예시의 경우 `str`)을 가져올 수 있습니다:

```Python hl_lines="20"
{!../../../docs_src/path_params/tutorial005.py!}
```

!!! tip "팁"
    `ModelName.lenet.value`로도 값 `"lenet"`에 접근할 수 있습니다.

    * objetos JSON (`dict`).
    * arrays JSON (`list`), definindo tipos dos itens.
    * campos String (`str`), definindo tamanho mínimo e máximo.
    * Numbers (`int`, `float`) com valores mínimos e máximos, etc.

* Validação de tipos mais exóticos, como:
    * URL.
    * Email.
    * UUID.
    * ...e outros.

* `min_length`
* `max_length`
* `pattern`

In these examples you saw how to declare validations for `str` values.

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.
* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

```Python hl_lines="17"
{!../../../docs_src/path_params/tutorial005.py!}
```

#### *Enumeration Değerini* Edinelim

`model_name.value` veya genel olarak `your_enum_member.value` tanımlarını kullanarak (bu durumda bir `str` olan) gerçek değere ulaşabilirsiniz:

```Python hl_lines="20"
{!../../../docs_src/path_params/tutorial005.py!}
```

!!! tip "İpucu"