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  1. docs/pt/docs/tutorial/index.md

        E o mesmo para cada dependência opcional que você quiser usar.
    
    ## Guia Avançado de Usuário
    
    Há também um **Guia Avançado de Usuário** que você pode ler após esse **Tutorial - Guia de Usuário**.
    
    O **Guia Avançado de Usuário** constrói sobre esse, usa os mesmos conceitos e te ensina alguns recursos extras.
    
    Mas você deveria ler primeiro o **Tutorial - Guia de Usuário** (que você está lendo agora).
    
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  2. docs/en/docs/advanced/security/index.md

    !!! tip
        The next sections are **not necessarily "advanced"**.
    
        And it's possible that for your use case, the solution is in one of them.
    
    ## Read the Tutorial first
    
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  3. docs/en/docs/how-to/index.md

    !!! tip
    
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  4. docs/en/docs/tutorial/static-files.md

    You can read more about this in the [Advanced User Guide](../advanced/index.md){.internal-link target=_blank}.
    
    ## Details
    
    The first `"/static"` refers to the sub-path this "sub-application" will be "mounted" on. So, any path that starts with `"/static"` will be handled by it.
    
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  5. docs/es/docs/advanced/response-directly.md

    Por ejemplo, no puedes poner un modelo Pydantic en una `JSONResponse` sin primero convertirlo a un `dict` con todos los tipos de datos (como `datetime`, `UUID`, etc) convertidos a tipos compatibles con JSON.
    
    Para esos casos, puedes usar el `jsonable_encoder` para convertir tus datos antes de pasarlos a la respuesta:
    
    ```Python hl_lines="4 6 20 21"
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  6. docs/en/docs/tutorial/middleware.md

    ```Python hl_lines="10  12-13"
    {!../../../docs_src/middleware/tutorial001.py!}
    ```
    
    ## Other middlewares
    
    You can later read more about other middlewares in the [Advanced User Guide: Advanced Middleware](../advanced/middleware.md){.internal-link target=_blank}.
    
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  7. tests/test_tutorial/test_extra_data_types/test_tutorial001.py

                                "required": True,
                                "schema": {
                                    "title": "Item Id",
                                    "type": "string",
                                    "format": "uuid",
                                },
                                "name": "item_id",
                                "in": "path",
                            }
                        ],
                        "requestBody": {
    Python
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  8. docs_src/extra_data_types/tutorial001.py

    from datetime import datetime, time, timedelta
    from typing import Union
    from uuid import UUID
    
    from fastapi import Body, FastAPI
    
    app = FastAPI()
    
    
    @app.put("/items/{item_id}")
    async def read_items(
        item_id: UUID,
        start_datetime: datetime = Body(),
        end_datetime: datetime = Body(),
        process_after: timedelta = Body(),
        repeat_at: Union[time, None] = Body(default=None),
    ):
    Python
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  9. tests/test_tutorial/test_extra_data_types/test_tutorial001_an_py310.py

                                "required": True,
                                "schema": {
                                    "title": "Item Id",
                                    "type": "string",
                                    "format": "uuid",
                                },
                                "name": "item_id",
                                "in": "path",
                            }
                        ],
                        "requestBody": {
    Python
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  10. docs/ja/docs/tutorial/extra-data-types.md

    しかし、より複雑なデータ型を使用することもできます。
    
    そして、今まで見てきたのと同じ機能を持つことになります:
    
    * 素晴らしいエディタのサポート
    * 受信したリクエストからのデータ変換
    * レスポンスデータのデータ変換
    * データの検証
    * 自動注釈と文書化
    
    ## 他のデータ型
    
    ここでは、使用できる追加のデータ型のいくつかを紹介します:
    
    * `UUID`:
        * 多くのデータベースやシステムで共通のIDとして使用される、標準的な「ユニバーサルにユニークな識別子」です。
        * リクエストとレスポンスでは`str`として表現されます。
    * `datetime.datetime`:
        * Pythonの`datetime.datetime`です。
        * リクエストとレスポンスはISO 8601形式の`str`で表現されます: `2008-09-15T15:53:00+05:00`
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