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  1. docs/en/docs/advanced/response-cookies.md

        So, you will have to make sure your data is of the correct type. E.g. it is compatible with JSON, if you are returning a `JSONResponse`.
    
        And also that you are not sending any data that should have been filtered by a `response_model`.
    
    ### More info
    
    !!! note "Technical Details"
        You could also use `from starlette.responses import Response` or `from starlette.responses import JSONResponse`.
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  2. docs/en/docs/tutorial/background-tasks.md

    This includes, for example:
    
    * Email notifications sent after performing an action:
        * As connecting to an email server and sending an email tends to be "slow" (several seconds), you can return the response right away and send the email notification in the background.
    * Processing data:
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  3. docs/en/docs/tutorial/header-params.md

        !!! tip
            Prefer to use the `Annotated` version if possible.
    
        ```Python hl_lines="9"
        {!> ../../../docs_src/header_params/tutorial003.py!}
        ```
    
    If you communicate with that *path operation* sending two HTTP headers like:
    
    ```
    X-Token: foo
    X-Token: bar
    ```
    
    The response would be like:
    
    ```JSON
    {
        "X-Token values": [
            "bar",
            "foo"
        ]
    }
    ```
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  4. docs/en/docs/tutorial/handling-errors.md

    You could use it while developing your app to log the body and debug it, return it to the user, etc.
    
    ```Python hl_lines="14"
    {!../../../docs_src/handling_errors/tutorial005.py!}
    ```
    
    Now try sending an invalid item like:
    
    ```JSON
    {
      "title": "towel",
      "size": "XL"
    }
    ```
    
    You will receive a response telling you that the data is invalid containing the received body:
    
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  5. docs/en/docs/tutorial/body.md

    !!! info
        To send data, you should use one of: `POST` (the more common), `PUT`, `DELETE` or `PATCH`.
    
        Sending a body with a `GET` request has an undefined behavior in the specifications, nevertheless, it is supported by FastAPI, only for very complex/extreme use cases.
    
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  6. docs/en/docs/deployment/docker.md

    3. Install Poetry in this Docker stage.
    
    4. Copy the `pyproject.toml` and `poetry.lock` files to the `/tmp` directory.
    
        Because it uses `./poetry.lock*` (ending with a `*`), it won't crash if that file is not available yet.
    
    5. Generate the `requirements.txt` file.
    
    6. This is the final stage, anything here will be preserved in the final container image.
    
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