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  1. docs/zh/docs/tutorial/body.md

    使用 <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> 模型声明**请求体**,能充分利用它的功能和优点。
    
    /// info | "说明"
    
    发送数据使用 `POST`(最常用)、`PUT`、`DELETE`、`PATCH` 等操作。
    
    规范中没有定义使用 `GET` 发送请求体的操作,但不管怎样,FastAPI 也支持这种方式,只不过仅用于非常复杂或极端的用例。
    
    我们不建议使用 `GET`,因此,在 Swagger UI 交互文档中不会显示有关 `GET` 的内容,而且代理协议也不一定支持 `GET`。
    
    ///
    
    ## 导入 Pydantic 的 `BaseModel`
    
    从 `pydantic` 中导入 `BaseModel`:
    
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  2. docs/em/docs/tutorial/extra-models.md

    {!> ../../docs_src/extra_models/tutorial001_py310.py!}
    ```
    
    ////
    
    ### 🔃 `**user_in.dict()`
    
    #### Pydantic `.dict()`
    
    `user_in` Pydantic 🏷 🎓 `UserIn`.
    
    Pydantic 🏷 ✔️ `.dict()` 👩‍🔬 👈 📨 `dict` ⏮️ 🏷 💽.
    
    , 🚥 👥 ✍ Pydantic 🎚 `user_in` 💖:
    
    ```Python
    user_in = UserIn(username="john", password="secret", email="******@****.***")
    ```
    
    &amp; ⤴️ 👥 🤙:
    
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  3. fastapi/routing.py

                Any,
                Doc(
                    """
                    The type to use for the response.
    
                    It could be any valid Pydantic *field* type. So, it doesn't have to
                    be a Pydantic model, it could be other things, like a `list`, `dict`,
                    etc.
    
                    It will be used for:
    
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  4. docs/en/docs/features.md

    * 100% test coverage.
    * 100% type annotated codebase.
    
    ## Pydantic features
    
    **FastAPI** is fully compatible with (and based on) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. So, any additional Pydantic code you have, will also work.
    
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  5. docs/pl/docs/features.md

    * 100% pokrycie testami.
    * 100% adnotacji typów.
    
    ## Cechy Pydantic
    
    **FastAPI** jest w pełni kompatybilny z (oraz bazuje na) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. Tak więc każdy dodatkowy kod Pydantic, który posiadasz, również będzie działał.
    
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  6. docs/de/docs/tutorial/extra-data-types.md

    * `Decimal`:
        * Standard-Python-`Decimal`.
        * In Requests und Responses wird es wie ein `float` behandelt.
    * Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>.
    
    ## Beispiel
    
    Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.
    
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  7. tests/test_tutorial/test_body_multiple_params/test_tutorial003_py310.py

                        "msg": "Field required",
                        "input": None,
                    },
                ]
            }
        ) | IsDict(
            # TODO: remove when deprecating Pydantic v1
            {
                "detail": [
                    {
                        "loc": ["body", "item"],
                        "msg": "field required",
                        "type": "value_error.missing",
                    },
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  8. docs/ru/docs/tutorial/extra-models.md

    {!> ../../docs_src/extra_models/tutorial001.py!}
    ```
    
    ////
    
    ### Про `**user_in.dict()`
    
    #### `.dict()` из Pydantic
    
    `user_in` - это Pydantic-модель класса `UserIn`.
    
    У Pydantic-моделей есть метод `.dict()`, который возвращает `dict` с данными модели.
    
    Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:
    
    ```Python
    user_in = UserIn(username="john", password="secret", email="******@****.***")
    ```
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  9. docs/pt/docs/tutorial/extra-models.md

    {!> ../../docs_src/extra_models/tutorial001_py310.py!}
    ```
    
    ////
    
    ### Sobre `**user_in.dict()`
    
    #### O `.dict()` do Pydantic
    
    `user_in` é um modelo Pydantic da classe `UserIn`.
    
    Os modelos Pydantic possuem um método `.dict()` que retorna um `dict` com os dados do modelo.
    
    Então, se criarmos um objeto Pydantic `user_in` como:
    
    ```Python
    user_in = UserIn(username="john", password="secret", email="******@****.***")
    ```
    
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  10. docs/en/docs/deployment/versions.md

    So, you can just let **FastAPI** use the correct Starlette version.
    
    ## About Pydantic
    
    Pydantic includes the tests for **FastAPI** with its own tests, so new versions of Pydantic (above `1.0.0`) are always compatible with FastAPI.
    
    You can pin Pydantic to any version above `1.0.0` that works for you.
    
    For example:
    
    ```txt
    pydantic>=2.7.0,<3.0.0
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