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  1. docs/zh/docs/deployment/server-workers.md

            ```
    
         * 因此,`main:app` 中的冒号相当于 `from main import app` 中的 Python `import` 部分。
    
    * `--workers`:要使用的worker进程数量,每个进程将运行一个 Uvicorn worker进程,在本例中为 4 个worker进程。
    
    * `--worker-class`:在worker进程中使用的与 Gunicorn 兼容的工作类。
         * 这里我们传递了 Gunicorn 可以导入和使用的类:
    
             ```Python
             import uvicorn.workers.UvicornWorker
             ```
    
    * `--bind`:这告诉 Gunicorn 要监听的 IP 和端口,使用冒号 (`:`) 分隔 IP 和端口。
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  2. docs/de/docs/deployment/server-workers.md

    ## Gunicorn mit Uvicorn-Workern ausführen
    
    Dann können Sie Gunicorn ausführen mit:
    
    <div class="termy">
    
    ```console
    $ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80
    
    [19499] [INFO] Starting gunicorn 20.1.0
    [19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
    [19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
    [19511] [INFO] Booting worker with pid: 19511
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  3. docs/en/docs/deployment/server-workers.md

    ```console
    $ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80
    
    [19499] [INFO] Starting gunicorn 20.1.0
    [19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
    [19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
    [19511] [INFO] Booting worker with pid: 19511
    [19513] [INFO] Booting worker with pid: 19513
    [19514] [INFO] Booting worker with pid: 19514
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  4. docs/em/docs/deployment/server-workers.md

    ```console
    $ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80
    
    [19499] [INFO] Starting gunicorn 20.1.0
    [19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
    [19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
    [19511] [INFO] Booting worker with pid: 19511
    [19513] [INFO] Booting worker with pid: 19513
    [19514] [INFO] Booting worker with pid: 19514
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  5. docs/ja/docs/deployment/server-workers.md

    ```console
    $ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80
    
    [19499] [INFO] Starting gunicorn 20.1.0
    [19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
    [19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
    [19511] [INFO] Booting worker with pid: 19511
    [19513] [INFO] Booting worker with pid: 19513
    [19514] [INFO] Booting worker with pid: 19514
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  6. docs/zh/docs/deployment/docker.md

    下面一些什么时候这种做法有意义的示例:
    
    
    #### 一个简单的应用程序
    
    如果你的应用程序**足够简单**,你不需要(至少现在不需要)过多地微调进程数量,并且你可以使用自动默认值,那么你可能需要容器中的进程管理器 (使用官方 Docker 镜像),并且你在**单个服务器**而不是集群上运行它。
    
    #### Docker Compose
    
    你可以使用 **Docker Compose** 部署到**单个服务器**(而不是集群),因此你没有一种简单的方法来管理容器的复制(使用 Docker Compose),同时保留共享网络和 **负载均衡**。
    
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  7. docs/ko/docs/deployment/server-workers.md

    ```console
    $ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80
    
    [19499] [INFO] Starting gunicorn 20.1.0
    [19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
    [19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
    [19511] [INFO] Booting worker with pid: 19511
    [19513] [INFO] Booting worker with pid: 19513
    [19514] [INFO] Booting worker with pid: 19514
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  8. docs/en/docs/deployment/concepts.md

    !!! tip
        Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.
    
        I'll tell you more about container images, Docker, Kubernetes, etc. in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.
    
    ## Previous Steps Before Starting
    
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  9. docs/tr/docs/project-generation.md

    ### Full Stack FastAPI PostgreSQL - Özellikler
    
    * Full **Docker** entegrasyonu (Docker based).
    * Docker Swarm Mode ile deployment.
    * **Docker Compose** entegrasyonu ve lokal geliştirme için optimizasyon.
    * Uvicorn ve Gunicorn ile **Production ready** Python web server'ı.
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  10. docs/en/docs/deployment/docker.md

    In those cases, you can use the **official Docker image** that includes **Gunicorn** as a process manager running multiple **Uvicorn worker processes**, and some default settings to adjust the number of workers based on the current CPU cores automatically. I'll tell you more about it below in [Official Docker Image with Gunicorn - Uvicorn](#official-docker-image-with-gunicorn-uvicorn).
    
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