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  1. docs/ko/docs/advanced/index.md

    ## TestDriven.io 강좌
    
    여러분이 문서의 이 부분을 보완하시기 위해 심화-기초 강좌 수강을 희망하신다면 다음을 참고 하시기를 바랍니다: **TestDriven.io**의 <a href="https://testdriven.io/courses/tdd-fastapi/" class="external-link" target="_blank">FastAPI와 Docker를 사용한 테스트 주도 개발</a>.
    
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  2. docs/ko/docs/advanced/middlewares.md

    new_app = UnicornMiddleware(app, some_config="rainbow")
    ```
    
    하지만 내부 미들웨어가 서버 오류를 처리하고 사용자 정의 예외 처리기가 제대로 작동하도록 하는 더 간단한 방법을 제공하는 FastAPI(실제로는 Starlette)가 있습니다.
    
    이를 위해 `app.add_middleware()`를 사용합니다(CORS의 예에서와 같이).
    
    ```Python
    from fastapi import FastAPI
    from unicorn import UnicornMiddleware
    
    app = FastAPI()
    
    app.add_middleware(UnicornMiddleware, some_config="rainbow")
    ```
    
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  3. docs/es/docs/deployment/server-workers.md

    ///
    
    ## Múltiples Workers
    
    Puedes iniciar múltiples workers con la opción de línea de comando `--workers`:
    
    //// tab | `fastapi`
    
    Si usas el comando `fastapi`:
    
    <div class="termy">
    
    ```console
    $ <pre> <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:single">main.py</u>
    <font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>
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  4. docs/pt/docs/benchmarks.md

        * Se você quer fazer comparações com o Starlette, compare com Sanic, Flask, Django, etc. _Frameworks Web_ (ou _microframeworks_).
    * **FastAPI**:
        * Do mesmo modo que Starlette utiliza Uvicorn e não pode ser mais rápido que ele, **FastAPI** utiliza o Starlette, então não tem como ser mais rápido do que o Starlette.
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  5. docs/ru/docs/tutorial/sql-databases.md

    /// tip | Подсказка
    
    Существует официальный генератор проектов на **FastAPI** и **PostgreSQL**, который также включает frontend и дополнительные инструменты <a href="https://github.com/fastapi/full-stack-fastapi-template" class="external-link" target="_blank">https://github.com/fastapi/full-stack-fastapi-template</a>
    
    ///
    
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  6. docs/en/docs/tutorial/response-model.md

    ### FastAPI Data Filtering { #fastapi-data-filtering }
    
    Now, for FastAPI, it will see the return type and make sure that what you return includes **only** the fields that are declared in the type.
    
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  7. docs/es/docs/advanced/behind-a-proxy.md

    }
    ```
    
    En este ejemplo, el "Proxy" podría ser algo como **Traefik**. Y el servidor sería algo como FastAPI CLI con **Uvicorn**, ejecutando tu aplicación de FastAPI.
    
    ### Proporcionando el `root_path`
    
    Para lograr esto, puedes usar la opción de línea de comandos `--root-path` como:
    
    <div class="termy">
    
    ```console
    $ fastapi run main.py --root-path /api/v1
    
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  8. docs/es/docs/advanced/middleware.md

    new_app = UnicornMiddleware(app, some_config="rainbow")
    ```
    
    Pero FastAPI (en realidad Starlette) proporciona una forma más simple de hacerlo que asegura que los middlewares internos manejen errores del servidor y los controladores de excepciones personalizadas funcionen correctamente.
    
    Para eso, usas `app.add_middleware()` (como en el ejemplo para CORS).
    
    ```Python
    from fastapi import FastAPI
    from unicorn import UnicornMiddleware
    
    app = FastAPI()
    
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  9. docs/en/docs/benchmarks.md

        * If you are comparing Starlette, compare it against Sanic, Flask, Django, etc. Web frameworks (or microframeworks).
    * **FastAPI**:
        * The same way that Starlette uses Uvicorn and cannot be faster than it, **FastAPI** uses Starlette, so it cannot be faster than it.
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  10. docs/fa/docs/features.md

    ## ویژگی های Starlette
    
    **FastAPI** کاملا (و براساس) با <a href="https://www.starlette.io/" class="external-link" target="_blank"><strong>Starlette</strong></a> سازگار است. بنابراین، هرکد اضافی Starlette که دارید، نیز کار خواهد کرد.
    
    ‍‍`FastAPI` در واقع یک زیرکلاس از `Starlette` است. بنابراین اگر از قبل Starlette را میشناسید یا با آن کار کرده اید، بیشتر قابلیت ها به همین روش کار خواهد کرد.
    
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