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  1. common/scripts/setup_env.sh

    container_kubeconfig=''
    
    # docker conditional host mount (needed for make docker push)
    if [[ -d "${HOME}/.docker" ]]; then
      CONDITIONAL_HOST_MOUNTS+="--mount type=bind,source=${HOME}/.docker,destination=/config/.docker,readonly "
    fi
    
    # gcloud conditional host mount (needed for docker push with the gcloud auth configure-docker)
    if [[ -d "${HOME}/.config/gcloud" ]]; then
    Shell Script
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  2. docs/en/docs/advanced/sub-applications.md

    ```Python hl_lines="11  14-16"
    {!../../../docs_src/sub_applications/tutorial001.py!}
    ```
    
    ### Mount the sub-application
    
    In your top-level application, `app`, mount the sub-application, `subapi`.
    
    In this case, it will be mounted at the path `/subapi`:
    
    ```Python hl_lines="11  19"
    {!../../../docs_src/sub_applications/tutorial001.py!}
    ```
    
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  3. docs/en/docs/advanced/wsgi.md

    # Including WSGI - Flask, Django, others
    
    You can mount WSGI applications as you saw with [Sub Applications - Mounts](sub-applications.md){.internal-link target=_blank}, [Behind a Proxy](behind-a-proxy.md){.internal-link target=_blank}.
    
    For that, you can use the `WSGIMiddleware` and use it to wrap your WSGI application, for example, Flask, Django, etc.
    
    ## Using `WSGIMiddleware`
    
    You need to import `WSGIMiddleware`.
    
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  4. docs/fa/docs/advanced/sub-applications.md

    # زیر برنامه ها - اتصال
    
    اگر نیاز دارید که دو برنامه مستقل FastAPI، با OpenAPI مستقل و رابط‌های کاربری اسناد خود داشته باشید، می‌توانید یک برنامه
    اصلی داشته باشید و یک (یا چند) زیر برنامه را به آن متصل کنید.
    
    ## اتصال (mount) به یک برنامه **FastAPI**
    
    کلمه "Mounting" به معنای افزودن یک برنامه کاملاً مستقل در یک مسیر خاص است، که پس از آن مدیریت همه چیز در آن مسیر، با path operations (عملیات های مسیر) اعلام شده در آن زیر برنامه می باشد.
    
    ### برنامه سطح بالا
    
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  5. doc/next/6-stdlib/99-minor/path/filepath/63703.md

    On Windows, [EvalSymlinks] no longer evaluates mount points,
    which was a source of many inconsistencies and bugs.
    This behavior is controlled by the `winsymlink` setting.
    For Go 1.23, it defaults to `winsymlink=1`.
    Previous versions default to `winsymlink=0`.
    
    On Windows, [EvalSymlinks] no longer tries to normalize
    volumes to drive letters, which was not always even possible.
    This behavior is controlled by the `winreadlinkvolume` setting.
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  6. okhttp/src/test/java/okhttp3/internal/connection/ConnectionPoolTest.kt

      }
    
      private fun updateMaxConcurrentStreams(
        connection: Http2Connection,
        amount: Int,
      ) {
        val settings = Settings()
        settings[Settings.MAX_CONCURRENT_STREAMS] = amount
        connection.readerRunnable.applyAndAckSettings(true, settings)
        assertThat(connection.peerSettings[Settings.MAX_CONCURRENT_STREAMS]).isEqualTo(amount)
        taskFaker.runTasks()
      }
    
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  7. okhttp/src/main/kotlin/okhttp3/internal/connection/RealConnectionPool.kt

          return state.policy.backoffDelayMillis.jitterBy(state.policy.backoffJitterMillis) * 1_000_000
        }
      }
    
      private fun Long.jitterBy(amount: Int): Long {
        return this + ThreadLocalRandom.current().nextInt(amount * -1, amount)
      }
    
      class AddressState(
        val address: Address,
        val queue: TaskQueue,
        var policy: ConnectionPool.AddressPolicy,
      ) {
        /**
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  8. doc/next/6-stdlib/99-minor/os/61893.md

    On Windows, the mode bits reported by [Lstat] and [Stat] for
    reparse points changed. Mount points no longer have [ModeSymlink] set,
    and reparse points that are not symlinks, Unix sockets, or dedup files
    now always have [ModeIrregular] set.
    This behavior is controlled by the `winsymlink` setting.
    For Go 1.23, it defaults to `winsymlink=1`.
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  9. docs/en/docs/deployment/concepts.md

    And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.
    
    ### Server Memory
    
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  10. docs/en/docs/benchmarks.md

        * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all...
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