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  1. docs/en/docs/deployment/docker.md

    Linux containers run using the same Linux kernel of the host (machine, virtual machine, cloud server, etc). This just means that they are very lightweight (compared to full virtual machines emulating an entire operating system).
    
    This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).
    
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  2. docs/de/docs/deployment/https.md

        * Die Inhalte sind **verschlüsselt**, auch wenn sie mit dem **HTTP-Protokoll** gesendet werden.
    
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  3. docs/de/docs/deployment/concepts.md

    ### Serverspeicher
    
    Wenn Ihr Code beispielsweise ein Machine-Learning-Modell mit **1 GB Größe** lädt und Sie einen Prozess mit Ihrer API ausführen, verbraucht dieser mindestens 1 GB RAM. Und wenn Sie **4 Prozesse** (4 Worker) starten, verbraucht jeder 1 GB RAM. Insgesamt verbraucht Ihre API also **4 GB RAM**.
    
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  4. docs/fr/docs/tutorial/first-steps.md

    ```hl_lines="4"
    INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
    ```
    
    Cette ligne montre l'URL par laquelle l'app est actuellement accessible, sur votre machine locale.
    
    ### Allez voir le résultat
    
    Ouvrez votre navigateur à l'adresse <a href="http://127.0.0.1:8000" class="external-link" target="_blank">http://127.0.0.1:8000</a>.
    
    Vous obtiendrez cette réponse JSON :
    
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  5. docs/pt/docs/index.md

    ## Opiniões
    
    "*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"
    
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  6. docs/de/docs/tutorial/query-params-str-validations.md

    FastAPI wird nun:
    
    * Die Daten **validieren** und sicherstellen, dass sie nicht länger als 50 Zeichen sind
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  7. docs/de/docs/tutorial/response-model.md

    Hierbei können Sie **Typannotationen** genauso verwenden, wie Sie es bei Werten von Funktions-**Parametern** machen; verwenden Sie Pydantic-Modelle, Listen, Dicts und skalare Werte wie Nummern, Booleans, usw.
    
    === "Python 3.10+"
    
        ```Python hl_lines="16  21"
        {!> ../../../docs_src/response_model/tutorial001_01_py310.py!}
        ```
    
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  8. docs/de/docs/tutorial/dependencies/index.md

    Es ist so konzipiert, sehr einfach zu verwenden zu sein und es jedem Entwickler sehr leicht zu machen, andere Komponenten mit **FastAPI** zu integrieren.
    
    ## Was ist „Dependency Injection“
    
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  9. docs/ko/docs/deployment/docker.md

    컨테이너를 사용하지 않고서는, 어플리케이션을 구동하고 재시작하는 것이 매우 번거롭고 어려울 수 있습니다. 하지만 **컨테이너를 사용한다면** 대부분의 경우에 이런 기능은 기본적으로 포함되어 있습니다. ✨
    
    ## 복제 - 프로세스 개수
    
    만약 여러분이 **쿠버네티스**와 머신 <abbr title="A group of machines that are configured to be connected and work together in some way.">클러스터</abbr>, 도커 스왐 모드, 노마드, 또는 다른 여러 머신 위에 분산 컨테이너를 관리하는 복잡한 시스템을 다루고 있다면, 여러분은 각 컨테이너에서 (워커와 함께 사용하는 Gunicorn 같은) **프로세스 매니저** 대신 **클러스터 레벨**에서 **복제를 다루**고 싶을 것입니다.
    
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  10. docs/tr/docs/index.md

    ## Görüşler
    
    "_[...] Bugünlerde **FastAPI**'ı çok fazla kullanıyorum. [...] Aslında bunu ekibimin **Microsoft'taki Machine Learning servislerinin** tamamında kullanmayı planlıyorum. Bunlardan bazıları **Windows**'un ana ürünlerine ve **Office** ürünlerine entegre ediliyor._"
    
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