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

    {!../../docs_src/body_nested_models/tutorial008.py!}
    ```
    
    ## Suporte de editor em todo canto
    
    E você obtém suporte do editor em todos os lugares.
    
    Mesmo para itens dentro de listas:
    
    <img src="/img/tutorial/body-nested-models/image01.png">
    
    Você não conseguiria este tipo de suporte de editor se estivesse trabalhando diretamente com `dict` em vez de modelos Pydantic.
    
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  2. docs/en/docs/tutorial/body-nested-models.md

    And it will be annotated / documented accordingly too.
    
    ## Nested Models
    
    Each attribute of a Pydantic model has a type.
    
    But that type can itself be another Pydantic model.
    
    So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.
    
    All that, arbitrarily nested.
    
    ### Define a submodel
    
    For example, we can define an `Image` model:
    
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  3. docs/de/docs/tutorial/body-nested-models.md

    ```
    
    ////
    
    ## Editor-Unterstützung überall
    
    Und Sie erhalten Editor-Unterstützung überall.
    
    Selbst für Dinge in Listen:
    
    <img src="/img/tutorial/body-nested-models/image01.png">
    
    Sie würden diese Editor-Unterstützung nicht erhalten, wenn Sie direkt mit `dict`, statt mit Pydantic-Modellen arbeiten würden.
    
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  4. docs/em/docs/tutorial/body-nested-models.md

    ```Python hl_lines="13"
    {!> ../../docs_src/body_nested_models/tutorial008_py39.py!}
    ```
    
    ////
    
    ## 👨‍🎨 🐕‍🦺 🌐
    
    &amp; 👆 🤚 👨‍🎨 🐕‍🦺 🌐.
    
    🏬 🔘 📇:
    
    <img src="/img/tutorial/body-nested-models/image01.png">
    
    👆 🚫 🚫 🤚 👉 😇 👨‍🎨 🐕‍🦺 🚥 👆 👷 🔗 ⏮️ `dict` ↩️ Pydantic 🏷.
    
    ✋️ 👆 🚫 ✔️ 😟 🔃 👫 👯‍♂️, 📨 #️⃣ 🗜 🔁 &amp; 👆 🔢 🗜 🔁 🎻 💁‍♂️.
    
    ## 💪 ❌ `dict`Ⓜ
    
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  5. docs/ja/docs/tutorial/body-nested-models.md

    ```Python hl_lines="15"
    {!../../docs_src/body_nested_models/tutorial008.py!}
    ```
    
    ## あらゆる場所でのエディタサポート
    
    エディタのサポートもどこでも受けることができます。
    
    以下のようにリストの中の項目でも:
    
    <img src="https://fastapi.tiangolo.com/img/tutorial/body-nested-models/image01.png">
    
    Pydanticモデルではなく、`dict`を直接使用している場合はこのようなエディタのサポートは得られません。
    
    しかし、それらについて心配する必要はありません。入力された辞書は自動的に変換され、出力も自動的にJSONに変換されます。
    
    ## 任意の`dict`のボディ
    
    また、ある型のキーと別の型の値を持つ`dict`としてボディを宣言することもできます。
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  6. docs/ru/docs/tutorial/body-nested-models.md

    ```
    
    ////
    
    ## Универсальная поддержка редактора
    
    И вы получаете поддержку редактора везде.
    
    Даже для элементов внутри списков:
    
    <img src="/img/tutorial/body-nested-models/image01.png">
    
    Вы не могли бы получить такую поддержку редактора, если бы работали напрямую с `dict`, а не с моделями Pydantic.
    
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  7. docs/ko/docs/tutorial/body-nested-models.md

    이를 아래처럼:
    
    ```Python hl_lines="15"
    {!../../docs_src/body_nested_models/tutorial008.py!}
    ```
    
    ## 어디서나 편집기 지원
    
    그리고 어디서나 편집기 지원을 받을수 있습니다.
    
    리스트 내부 항목의 경우에도:
    
    <img src="/img/tutorial/body-nested-models/image01.png">
    
    Pydantic 모델 대신에 `dict`를 직접 사용하여 작업할 경우, 이러한 편집기 지원을 받을수 없습니다.
    
    하지만 수신한 딕셔너리가 자동으로 변환되고 출력도 자동으로 JSON으로 변환되므로 걱정할 필요는 없습니다.
    
    ## 단독 `dict`의 본문
    
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  8. docs/zh/docs/tutorial/body-nested-models.md

    ```Python hl_lines="15"
    {!> ../../docs_src/body_nested_models/tutorial008.py!}
    ```
    
    ////
    
    ## 无处不在的编辑器支持
    
    你可以随处获得编辑器支持。
    
    即使是列表中的元素:
    
    <img src="https://fastapi.tiangolo.com/img/tutorial/body-nested-models/image01.png">
    
    如果你直接使用 `dict` 而不是 Pydantic 模型,那你将无法获得这种编辑器支持。
    
    但是你根本不必担心这两者,传入的字典会自动被转换,你的输出也会自动被转换为 JSON。
    
    ## 任意 `dict` 构成的请求体
    
    你也可以将请求体声明为使用某类型的键和其他类型值的 `dict`。
    
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  9. docs/en/docs/advanced/dataclasses.md

    This way, its schema will show up in the API docs user interface:
    
    <img src="/img/tutorial/dataclasses/image01.png">
    
    ## Dataclasses in Nested Data Structures
    
    You can also combine `dataclasses` with other type annotations to make nested data structures.
    
    In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.
    
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  10. docs/en/docs/alternatives.md

    It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.
    
    /// check | "Inspired **FastAPI** to"
    
    Use Python types to have great editor support.
    
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