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  1. docs/en/docs/async.md

    The cashier goes to the kitchen.
    
    You wait, standing in front of the counter 🕙, so that no one else takes your burgers before you do, as there are no numbers for turns.
    
    <img src="/img/async/parallel-burgers/parallel-burgers-03.png" class="illustration">
    
    As you and your crush are busy not letting anyone get in front of you and take your burgers whenever they arrive, you cannot pay attention to your crush. 😞
    
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  2. docs/fr/docs/async.md

    Mais vous pouvez aussi profiter du parallélisme et multiprocessing afin de gérer des charges **CPU bound** qui sont récurrentes dans les systèmes de *Machine Learning*.
    
    Ça, ajouté au fait que Python soit le langage le plus populaire pour la **Data Science**, le **Machine Learning** et surtout le **Deep Learning**, font de **FastAPI** un très bon choix pour les APIs et applications de **Data Science** / **Machine Learning**.
    
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  3. docs/de/docs/async.md

        Wenn Sie über gute technische Kenntnisse verfügen (Coroutinen, Threads, Blocking, usw.) und neugierig sind, wie FastAPI mit `async def`s im Vergleich zu normalen `def`s umgeht, fahren Sie fort.
    
    ### Pfadoperation-Funktionen
    
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