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  1. docs_src/path_params/tutorial005_py39.py

    from enum import Enum
    
    from fastapi import FastAPI
    
    
    class ModelName(str, Enum):
        alexnet = "alexnet"
        resnet = "resnet"
        lenet = "lenet"
    
    
    app = FastAPI()
    
    
    @app.get("/models/{model_name}")
    async def get_model(model_name: ModelName):
        if model_name is ModelName.alexnet:
            return {"model_name": model_name, "message": "Deep Learning FTW!"}
    
        if model_name.value == "lenet":
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  2. tests/test_tutorial/test_path_params/test_tutorial005.py

    from docs_src.path_params.tutorial005_py39 import app
    
    client = TestClient(app)
    
    
    def test_get_enums_alexnet():
        response = client.get("/models/alexnet")
        assert response.status_code == 200
        assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}
    
    
    def test_get_enums_lenet():
        response = client.get("/models/lenet")
        assert response.status_code == 200
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  3. docs/de/docs/tutorial/path-params.md

    Erstellen Sie dann Klassen-Attribute mit festgelegten Werten, welches die erlaubten Werte sein werden:
    
    {* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}
    
    
    /// tip | Tipp
    
    Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.
    
    ///
    
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  4. docs/en/docs/tutorial/path-params.md

    Then create class attributes with fixed values, which will be the available valid values:
    
    {* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}
    
    /// tip
    
    If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.
    
    ///
    
    ### Declare a *path parameter* { #declare-a-path-parameter }
    
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  5. docs/es/docs/tutorial/path-params.md

    Luego crea atributos de clase con valores fijos, que serán los valores válidos disponibles:
    
    {* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}
    
    /// tip | Consejo
    
    Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.
    
    ///
    
    ### Declarar un *path parameter* { #declare-a-path-parameter }
    
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  6. docs/tr/docs/tutorial/path-params.md

    ///
    
    /// tip | İpucu
    
    Merak ediyorsanız söyleyeyim, "AlexNet", "ResNet" ve "LeNet" isimleri Makine Öğrenmesi <abbr title="Teknik olarak, Derin Öğrenme model mimarileri">modellerini</abbr> temsil eder.
    
    ///
    
    ### Bir *Yol Parametresi* Tanımlayalım
    
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  7. docs/uk/docs/tutorial/path-params.md

    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Перелічення (або enums) доступні в Python</a> починаючи з версії 3.4.
    
    ///
    
    /// tip | Порада
    
    Якщо вам цікаво, "AlexNet", "ResNet" та "LeNet" — це просто назви ML моделей <abbr title="Технічно, архітектури Deep Learning моделей">Machine Learning</abbr>.
    
    ///
    
    
    ### Оголосіть *параметр шляху*
    
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  8. docs/ru/docs/tutorial/path-params.md

    Затем создайте атрибуты класса с фиксированными допустимыми значениями:
    
    {* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}
    
    /// tip | Подсказка
    
    Если интересно, то "AlexNet", "ResNet" и "LeNet" - это названия <abbr title="Технически, архитектуры моделей глубокого обучения">моделей</abbr> Машинного обучения.
    
    ///
    
    ### Определение *параметра пути* { #declare-a-path-parameter }
    
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  9. docs/pt/docs/tutorial/path-params.md

    Em seguida, crie atributos de classe com valores fixos, que serão os valores válidos disponíveis:
    
    {* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}
    
    /// tip | Dica
    Se você está se perguntando, "AlexNet", "ResNet" e "LeNet" são apenas nomes de <abbr title="Tecnicamente, arquiteturas de modelos de Deep Learning">modelos</abbr> de Aprendizado de Máquina.
    ///
    
    ### Declare um parâmetro de path { #declare-a-path-parameter }
    
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