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  1. docs/en/docs/async.md

    So, during that time, the computer can go and do some other work, while "slow-file" 📝 finishes.
    
    Then the computer / program 🤖 will come back every time it has a chance because it's waiting again, or whenever it 🤖 finished all the work it had at that point. And it 🤖 will see if any of the tasks it was waiting for have already finished, doing whatever it had to do.
    
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  2. docs/pt/docs/async.md

    * **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
    
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  3. docs/fr/docs/async.md

    Donc, pendant ce temps, l'ordinateur pourra effectuer d'autres tâches, pendant que "fichier-lent" 📝 se termine.
    
    Ensuite l'ordinateur / le programme 🤖 reviendra à chaque fois qu'il en a la chance que ce soit parce qu'il attend à nouveau, ou car il 🤖 a fini tout le travail qu'il avait à faire. Il 🤖 regardera donc si les tâches qu'il attend ont terminé d'être effectuées.
    
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  4. docs/es/docs/async.md

    Pagas 💸.
    
    <img src="https://fastapi.tiangolo.com/img/async/parallel-burgers/parallel-burgers-02.png" alt="illustration">
    
    El cajero va a la cocina 👨‍🍳.
    
    Esperas, de pie frente al mostrador 🕙, para que nadie más recoja tus hamburguesas 🍔, ya que no hay números para los turnos.
    
    <img src="https://fastapi.tiangolo.com/img/async/parallel-burgers/parallel-burgers-03.png" alt="illustration">
    
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  5. docs/de/docs/async.md

    Dennoch besteht in beiden Fällen eine gute Chance, dass **FastAPI** [immer noch schneller](index.md#performanz){.internal-link target=_blank} als Ihr bisheriges Framework (oder zumindest damit vergleichbar) ist.
    
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