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  1. .github/workflows/issue-manager.yml

    name: Issue Manager
    
    on:
      schedule:
        - cron: "10 3 * * *"
      issue_comment:
        types:
          - created
      issues:
        types:
          - labeled
      pull_request_target:
        types:
          - labeled
      workflow_dispatch:
    
    jobs:
      issue-manager:
        if: github.repository_owner == 'tiangolo'
        runs-on: ubuntu-latest
        steps:
          - name: Dump GitHub context
            env:
    Others
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  2. docs/en/docs/deployment/concepts.md

    ### Multiple Processes - An Example
    
    In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.
    
    This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.
    
    Plain Text
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  3. docs/ru/docs/deployment/concepts.md

    * HAProxy
        * С дополнительным компонентом типа Certbot для обновления сертификатов
    * Kubernetes с Ingress Controller похожим на Nginx
        * С дополнительным компонентом типа cert-manager для обновления сертификатов
    * Использование услуг облачного провайдера (читайте ниже 👇)
    
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  4. docs/de/docs/tutorial/background-tasks.md

    Sie erfordern in der Regel komplexere Konfigurationen und einen Nachrichten-/Job-Queue-Manager wie RabbitMQ oder Redis, ermöglichen Ihnen jedoch die Ausführung von Hintergrundtasks in mehreren Prozessen und insbesondere auf mehreren Servern.
    
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  5. docs/en/docs/advanced/events.md

    ```Python
    with open("file.txt") as file:
        file.read()
    ```
    
    In recent versions of Python, there's also an **async context manager**. You would use it with `async with`:
    
    ```Python
    async with lifespan(app):
        await do_stuff()
    ```
    
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  6. docs/en/docs/deployment/server-workers.md

    But Gunicorn supports working as a **process manager** and allowing users to tell it which specific **worker process class** to use. Then Gunicorn would start one or more **worker processes** using that class.
    
    And **Uvicorn** has a **Gunicorn-compatible worker class**.
    
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  7. fastapi/concurrency.py

    @asynccontextmanager
    async def contextmanager_in_threadpool(
        cm: ContextManager[_T],
    ) -> AsyncGenerator[_T, None]:
        # blocking __exit__ from running waiting on a free thread
        # can create race conditions/deadlocks if the context manager itself
        # has its own internal pool (e.g. a database connection pool)
        # to avoid this we let __exit__ run without a capacity limit
        # since we're creating a new limiter for each call, any non-zero limit
    Python
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  8. docs/en/docs/tutorial/dependencies/dependencies-with-yield.md

    Underneath, the `open("./somefile.txt")` creates an object that is called a "Context Manager".
    
    When the `with` block finishes, it makes sure to close the file, even if there were exceptions.
    
    When you create a dependency with `yield`, **FastAPI** will internally create a context manager for it, and combine it with some other related tools.
    
    ### Using context managers in dependencies with `yield`
    
    !!! warning
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  9. docs/ja/docs/deployment/concepts.md

        * 証明書の更新を自動的に処理 ✨
    * Caddy
        * 証明書の更新を自動的に処理 ✨
    * Nginx
        * 証明書更新のためにCertbotのような外部コンポーネントを使用
    * HAProxy
        * 証明書更新のためにCertbotのような外部コンポーネントを使用
    * Nginx のような Ingress Controller を持つ Kubernetes
        * 証明書の更新に cert-manager のような外部コンポーネントを使用
    * クラウド・プロバイダーがサービスの一部として内部的に処理(下記を参照👇)
    
    もう1つの選択肢は、HTTPSのセットアップを含んだより多くの作業を行う**クラウド・サービス**を利用することです。 このサービスには制限があったり、料金が高くなったりする可能性があります。しかしその場合、TLS Termination Proxyを自分でセットアップする必要はないです。
    
    次の章で具体例をいくつか紹介します。
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  10. docs/de/docs/deployment/concepts.md

    ### Mehrere Prozesse – Ein Beispiel
    
    Im folgenden Beispiel gibt es einen **Manager-Prozess**, welcher zwei **Workerprozesse** startet und steuert.
    
    Dieser Manager-Prozess wäre wahrscheinlich derjenige, welcher der IP am **Port** lauscht. Und er würde die gesamte Kommunikation an die Workerprozesse weiterleiten.
    
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