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docs/pt/docs/tutorial/body-nested-models.md
!!! info "informação" Note como `Offer` tem uma lista de `Item`s, que por sua vez possui opcionalmente uma lista `Image`s ## Corpos de listas puras Se o valor de primeiro nível do corpo JSON que você espera for um `array` do JSON (uma` lista` do Python), você pode declarar o tipo no parâmetro da função, da mesma forma que nos modelos do Pydantic: ```Python images: List[Image] ``` como em: ```Python hl_lines="15"
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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] ```
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docs/de/docs/tutorial/body-nested-models.md
Beachten Sie, wie `Offer` eine Liste von `Item`s hat, von denen jedes seinerseits eine optionale Liste von `Image`s hat. ## 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:
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docs/ko/docs/tutorial/body-nested-models.md
{!../../../docs_src/body_nested_models/tutorial007.py!} ``` !!! info "정보" `Offer`가 선택사항 `Image` 리스트를 차례로 갖는 `Item` 리스트를 어떻게 가지고 있는지 주목하세요 ## 순수 리스트의 본문 예상되는 JSON 본문의 최상위 값이 JSON `array`(파이썬 `list`)면, Pydantic 모델에서와 마찬가지로 함수의 매개변수에서 타입을 선언할 수 있습니다: ```Python images: List[Image] ``` 이를 아래처럼: ```Python hl_lines="15" {!../../../docs_src/body_nested_models/tutorial008.py!} ```
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docs/en/docs/tutorial/body-nested-models.md
``` !!! info Notice how `Offer` has a list of `Item`s, which in turn have an optional list of `Image`s ## Bodies of pure lists If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models: ```Python images: List[Image] ``` or in Python 3.9 and above: ```Python
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docs/ja/docs/tutorial/body-nested-models.md
{!../../../docs_src/body_nested_models/tutorial007.py!} ``` !!! info "情報" `Offer`は`Item`のリストであり、オプションの`Image`のリストを持っていることに注目してください。 ## 純粋なリストのボディ 期待するJSONボディのトップレベルの値がJSON`array`(Pythonの`list`)であれば、Pydanticモデルと同じように、関数のパラメータで型を宣言することができます: ```Python images: List[Image] ``` 以下のように: ```Python hl_lines="15" {!../../../docs_src/body_nested_models/tutorial008.py!} ```
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docs/zh/docs/tutorial/body-nested-models.md
{!> ../../../docs_src/body_nested_models/tutorial007.py!} ``` !!! info 请注意 `Offer` 拥有一组 `Item` 而反过来 `Item` 又是一个可选的 `Image` 列表是如何发生的。 ## 纯列表请求体 如果你期望的 JSON 请求体的最外层是一个 JSON `array`(即 Python `list`),则可以在路径操作函数的参数中声明此类型,就像声明 Pydantic 模型一样: ```Python images: List[Image] ``` 例如: === "Python 3.9+" ```Python hl_lines="13"
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docs/em/docs/tutorial/body-nested-models.md
{!> ../../../docs_src/body_nested_models/tutorial007_py310.py!} ``` !!! info 👀 ❔ `Offer` ✔️ 📇 `Item`Ⓜ, ❔ 🔄 ✔️ 📦 📇 `Image`Ⓜ ## 💪 😁 📇 🚥 🔝 🎚 💲 🎻 💪 👆 ⌛ 🎻 `array` (🐍 `list`), 👆 💪 📣 🆎 🔢 🔢, 🎏 Pydantic 🏷: ```Python images: List[Image] ``` ⚖️ 🐍 3️⃣.9️⃣ & 🔛: ```Python images: list[Image] ``` : === "🐍 3️⃣.6️⃣ & 🔛"
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