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  1. docs/de/docs/tutorial/body-nested-models.md

    ## Bodys aus reinen Listen
    
    Wenn Sie möchten, dass das äußerste Element des JSON-Bodys ein JSON-`array` (eine Python-`list`e) ist, können Sie den Typ im Funktionsparameter deklarieren, mit der gleichen Syntax wie in Pydantic-Modellen:
    
    ```Python
    images: List[Image]
    ```
    
    oder in Python 3.9 und darüber:
    
    ```Python
    images: list[Image]
    ```
    
    so wie in:
    
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  2. docs/ru/docs/tutorial/body-nested-models.md

    ## Тела с чистыми списками элементов
    
    Если верхний уровень значения тела JSON-объекта представляет собой JSON `array` (в Python - `list`), вы можете объявить тип в параметре функции, так же, как в моделях Pydantic:
    
    ```Python
    images: List[Image]
    ```
    
    в Python 3.9 и выше:
    
    ```Python
    images: list[Image]
    ```
    
    например так:
    
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  3. docs/en/docs/deployment/concepts.md

    !!! tip
        Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.
    
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  4. docs/en/docs/deployment/docker.md

    !!! warning
        There's a high chance that you **don't** need this base image or any other similar one, and would be better off by building the image from scratch as [described above in: Build a Docker Image for FastAPI](#build-a-docker-image-for-fastapi).
    
    This image has an **auto-tuning** mechanism included to set the **number of worker processes** based on the CPU cores available.
    
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  5. docs/fr/docs/async.md

    ---
    
    Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes.
    
    Par exemple :
    
    * Traitements d'**audio** et d'**images**.
    * La **vision par ordinateur** : une image est composée de millions de pixels, chaque pixel ayant 3 valeurs / couleurs, les traiter tous va nécessiter d'effectuer des traitements sur chaque pixel, et de préférence tous en même temps.
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  6. docs/de/docs/deployment/docker.md

    ## Offizielles Docker-Image mit Gunicorn – Uvicorn
    
    Es gibt ein offizielles Docker-Image, in dem Gunicorn mit Uvicorn-Workern ausgeführt wird, wie in einem vorherigen Kapitel beschrieben: [Serverworker – Gunicorn mit Uvicorn](server-workers.md){.internal-link target=_blank}.
    
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  7. docs/ru/docs/python-types.md

    В тот же момент вы пытаетесь запустить автодополнение с помощью `Ctrl+Space` и вы видите:
    
    <img src="/img/python-types/image02.png">
    
    При этом вы можете просматривать варианты, пока не найдёте подходящий:
    
    <img src="/img/python-types/image03.png">
    
    ## Больше мотивации
    
    Проверьте эту функцию, она уже имеет аннотации типов:
    
    ```Python hl_lines="1"
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  8. docs/ru/docs/tutorial/path-params.md

    <img src="/img/tutorial/path-params/image01.png">
    
    !!! check "Заметка"
        Ещё раз, просто используя определения типов, **FastAPI** обеспечивает автоматическую интерактивную документацию (с интеграцией Swagger UI).
    
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  9. docs/fr/docs/tutorial/path-params.md

    documentation générée automatiquement et interactive :
    
    <img src="/img/tutorial/path-params/image01.png">
    
    !!! info
        À nouveau, en utilisant uniquement les déclarations de type Python, **FastAPI** vous fournit automatiquement une documentation interactive (via Swagger UI).
    
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  10. docs/en/docs/advanced/generate-clients.md

    Now you can import and use the client code, it could look like this, notice that you get autocompletion for the methods:
    
    <img src="/img/tutorial/generate-clients/image02.png">
    
    You will also get autocompletion for the payload to send:
    
    <img src="/img/tutorial/generate-clients/image03.png">
    
    !!! tip
        Notice the autocompletion for `name` and `price`, that was defined in the FastAPI application, in the `Item` model.
    
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