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  1. docs_src/path_params/tutorial005.py

    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

    
    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
        assert response.json() == {"model_name": "lenet", "message": "LeCNN all the images"}
    
    
    def test_get_enums_resnet():
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  3. docs/de/docs/tutorial/path-params.md

    ///
    
    /// 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.
    
    ///
    
    ### Deklarieren Sie einen *Pfad-Parameter*
    
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  4. docs/en/docs/tutorial/path-params.md

    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerations (or enums) are available in Python</a> since version 3.4.
    
    ///
    
    /// 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*
    
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  5. docs/es/docs/tutorial/path-params.md

    ///
    
    /// tip | Consejo
    
    Si lo estás dudando, "AlexNet", "ResNet", y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.
    
    ///
    
    ### Declara un *parámetro de path*
    
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  6. docs/ko/docs/tutorial/path-params.md

    /// info | "정보"
    
    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">열거형(또는 enums)</a>은 파이썬 버전 3.4 이후로 사용 가능합니다.
    
    ///
    
    /// tip | "팁"
    
    혹시 궁금하다면, "AlexNet", "ResNet", 그리고 "LeNet"은 그저 기계 학습 <abbr title="기술적으로 정확히는 딥 러닝 모델 구조">모델</abbr>들의 이름입니다.
    
    ///
    
    ### *경로 매개변수* 선언
    
    생성한 열거형 클래스(`ModelName`)를 사용하는 타입 어노테이션으로 *경로 매개변수*를 만듭니다:
    
    ```Python hl_lines="16"
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  7. 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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  8. docs/ru/docs/tutorial/path-params.md

    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Перечисления (enum) доступны в Python</a> начиная с версии 3.4.
    
    ///
    
    /// tip | "Подсказка"
    
    Если интересно, то "AlexNet", "ResNet" и "LeNet" - это названия <abbr title="Технически, это архитектуры моделей глубокого обучения">моделей</abbr> машинного обучения.
    
    ///
    
    ### Определение *параметра пути*
    
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  9. docs/fr/docs/tutorial/path-params.md

    ///
    
    /// tip | "Astuce"
    
    Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning.
    
    ///
    
    ### Déclarer un paramètre de chemin
    
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  10. docs/zh/docs/tutorial/path-params.md

    ```
    
    /// tip | "提示"
    
    使用 `ModelName.lenet.value` 也能获取值 `"lenet"`。
    
    ///
    
    #### 返回*枚举元素*
    
    即使嵌套在 JSON 请求体里(例如, `dict`),也可以从*路径操作*返回*枚举元素*。
    
    返回给客户端之前,要把枚举元素转换为对应的值(本例中为字符串):
    
    ```Python hl_lines="18  21  23"
    {!../../docs_src/path_params/tutorial005.py!}
    ```
    
    客户端中的 JSON 响应如下:
    
    ```JSON
    {
      "model_name": "alexnet",
      "message": "Deep Learning FTW!"
    }
    ```
    
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