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  1. docs/en/docs/advanced/generate-clients.md

    And it shows their true commitment to FastAPI and its **community** (you), as they not only want to provide you a **good service** but also want to make sure you have a **good and healthy framework**, FastAPI. 🙇
    
    For example, you might want to try <a href="https://speakeasyapi.dev/?utm_source=fastapi+repo&utm_medium=github+sponsorship" class="external-link" target="_blank">Speakeasy</a>.
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  2. docs/en/docs/benchmarks.md

        * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all in your code).
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  3. docs/en/docs/tutorial/response-model.md

        That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.
    
    ### `response_model` Priority
    
    If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.
    
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  4. docs/en/docs/tutorial/testing.md

        This allows you to use `pytest` directly without complications.
    
    !!! note "Technical Details"
        You could also use `from starlette.testclient import TestClient`.
    
        **FastAPI** provides the same `starlette.testclient` as `fastapi.testclient` just as a convenience for you, the developer. But it comes directly from Starlette.
    
    !!! tip
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  5. docs/en/docs/advanced/dataclasses.md

    ## Dataclasses in Nested Data Structures
    
    You can also combine `dataclasses` with other type annotations to make nested data structures.
    
    In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.
    
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  6. docs/en/docs/advanced/behind-a-proxy.md

    ```
    
    </div>
    
    ### Check the responses
    
    Now, if you go to the URL with the port for Uvicorn: <a href="http://127.0.0.1:8000/app" class="external-link" target="_blank">http://127.0.0.1:8000/app</a>, you will see the normal response:
    
    ```JSON
    {
        "message": "Hello World",
        "root_path": "/api/v1"
    }
    ```
    
    !!! tip
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  7. docs/en/docs/deployment/manually.md

    But if you want to directly use **Trio**, then you can use **Hypercorn** as it supports it. ✨
    
    ### Install Hypercorn with Trio
    
    First you need to install Hypercorn with Trio support:
    
    <div class="termy">
    
    ```console
    $ pip install "hypercorn[trio]"
    ---> 100%
    ```
    
    </div>
    
    ### Run with Trio
    
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  8. docs/en/docs/reference/request.md

    # `Request` class
    
    You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.
    
    You can import it directly from `fastapi`:
    
    ```python
    from fastapi import Request
    ```
    
    !!! tip
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  9. docs/en/docs/tutorial/first-steps.md

    ...and the more exotic ones:
    
    * `OPTIONS`
    * `HEAD`
    * `PATCH`
    * `TRACE`
    
    In the HTTP protocol, you can communicate to each path using one (or more) of these "methods".
    
    ---
    
    When building APIs, you normally use these specific HTTP methods to perform a specific action.
    
    Normally you use:
    
    * `POST`: to create data.
    * `GET`: to read data.
    * `PUT`: to update data.
    * `DELETE`: to delete data.
    
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  10. docs/en/docs/reference/background.md

    # Background Tasks - `BackgroundTasks`
    
    You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.
    
    You can import it directly from `fastapi`:
    
    ```python
    from fastapi import BackgroundTasks
    ```
    
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