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

    ## Bodies of arbitrary `dict`s
    
    You can also declare a body as a `dict` with keys of some type and values of some other type.
    
    This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).
    
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  2. docs/en/docs/tutorial/extra-models.md

        'full_name': None,
    }
    ```
    
    #### Unwrapping a `dict`
    
    If we take a `dict` like `user_dict` and pass it to a function (or class) with `**user_dict`, Python will "unwrap" it. It will pass the keys and values of the `user_dict` directly as key-value arguments.
    
    So, continuing with the `user_dict` from above, writing:
    
    ```Python
    UserInDB(**user_dict)
    ```
    
    would result in something equivalent to:
    
    ```Python
    UserInDB(
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  3. docs/en/docs/features.md

        "name": "Mary",
        "joined": "2018-11-30",
    }
    
    my_second_user: User = User(**second_user_data)
    ```
    
    !!! info
        `**second_user_data` means:
    
        Pass the keys and values of the `second_user_data` dict directly as key-value arguments, equivalent to: `User(id=4, name="Mary", joined="2018-11-30")`
    
    ### Editor support
    
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  4. docs/em/docs/tutorial/header-params.md

        ```
    
    ๐Ÿšฅ ๐Ÿ‘† ๐Ÿ”— โฎ๏ธ ๐Ÿ‘ˆ *โžก ๐Ÿ› ๏ธ* ๐Ÿ“จ 2๏ธโƒฃ ๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ” ๐ŸŽš ๐Ÿ’–:
    
    ```
    X-Token: foo
    X-Token: bar
    ```
    
    ๐Ÿ“จ ๐Ÿ”œ ๐Ÿ’–:
    
    ```JSON
    {
        "X-Token values": [
            "bar",
            "foo"
        ]
    }
    ```
    
    ## ๐ŸŒƒ
    
    ๐Ÿ“ฃ ๐ŸŽš โฎ๏ธ `Header`, โš™๏ธ ๐ŸŽ โš  โš“ `Query`, `Path` & `Cookie`.
    
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  5. docs/ja/docs/tutorial/header-params.md

    {!../../../docs_src/header_params/tutorial003.py!}
    ```
    
    ใ‚‚ใ—ใ€ใใฎ*path operation*ใง้€šไฟกใ™ใ‚‹ๅ ดๅˆใฏใ€ๆฌกใฎใ‚ˆใ†ใซ๏ผ’ใคใฎHTTPใƒ˜ใƒƒใƒ€ใƒผใ‚’้€ไฟกใ—ใพใ™:
    
    ```
    X-Token: foo
    X-Token: bar
    ```
    
    ใ“ใฎใƒฌใ‚นใƒใƒณใ‚นใฏไปฅไธ‹ใฎใ‚ˆใ†ใซใชใ‚Šใพใ™:
    
    ```JSON
    {
        "X-Token values": [
            "bar",
            "foo"
        ]
    }
    ```
    
    ## ใพใจใ‚
    
    ใƒ˜ใƒƒใƒ€ใƒผใฏ`Header`ใงๅฎฃ่จ€ใ—ใ€`Query`ใ‚„`Path`ใ€`Cookie`ใจๅŒใ˜ใƒ‘ใ‚ฟใƒผใƒณใ‚’ไฝฟ็”จใ™ใ‚‹ใ€‚
    
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  6. docs/en/docs/tutorial/dependencies/sub-dependencies.md

    === "Python 3.8+"
    
        ```Python hl_lines="1"
        async def needy_dependency(fresh_value: Annotated[str, Depends(get_value, use_cache=False)]):
            return {"fresh_value": fresh_value}
        ```
    
    === "Python 3.8+ non-Annotated"
    
        !!! tip
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  7. docs/ja/docs/tutorial/body.md

    ## Pydanticใ‚’ไฝฟใ‚ใชใ„ๆ–นๆณ•
    
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  8. docs/en/docs/tutorial/dependencies/index.md

    * An optional query parameter `skip` that is an `int`, and by default is `0`.
    * An optional query parameter `limit` that is an `int`, and by default is `100`.
    
    And then it just returns a `dict` containing those values.
    
    !!! info
        FastAPI added support for `Annotated` (and started recommending it) in version 0.95.0.
    
        If you have an older version, you would get errors when trying to use `Annotated`.
    
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  9. fastapi/applications.py

                    have their default values. This is different from
                    `response_model_exclude_defaults` in that if the fields are set,
                    they will be included in the response, even if the value is the same
                    as the default.
    
                    When `True`, default values are omitted from the response.
    
                    Read more about it in the
    Python
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  10. docs_src/header_params/tutorial003.py

    from typing import List, Union
    
    from fastapi import FastAPI, Header
    
    app = FastAPI()
    
    
    @app.get("/items/")
    async def read_items(x_token: Union[List[str], None] = Header(default=None)):
    Python
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