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  1. CONTRIBUTING.md

    # Contributing to the Gradle Build Tool
    
    Thank you for your interest in contributing to Gradle!
    This guide explains how to contribute to the core Gradle components, 
    extensions and documentation located in this repository.
    For other extensions and components, see the 
    [Gradle Community Resources](https://gradle.org/resources/).
    
    This guide will help you to...
    
    * maximize the chance of your changes being accepted
    * work on the Gradle code base
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  2. docs/en/docs/async.md

    And as you can have parallelism and asynchronicity at the same time, you get higher performance than most of the tested NodeJS frameworks and on par with Go, which is a compiled language closer to C <a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">(all thanks to Starlette)</a>.
    
    ### Is concurrency better than parallelism?
    
    Nope! That's not the moral of the story.
    
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  3. README.md

    * More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
    * **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
    * Many extra features (thanks to Starlette) as:
        * **WebSockets**
        * extremely easy tests based on HTTPX and `pytest`
        * **CORS**
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  4. okhttp/src/main/kotlin/okhttp3/internal/concurrent/TaskRunner.kt

       * expect a newly-started thread to call [Runnable.run]. We shouldn't request new threads until
       * the already-requested ones are in service, otherwise we might create more threads than we need.
       *
       * We use [executeCallCount] and [runCallCount] to defend against starting more threads than we
       * need. Both fields are guarded by [lock].
       */
      private var executeCallCount = 0
      private var runCallCount = 0
    
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  5. okhttp/src/main/kotlin/okhttp3/ResponseBody.kt

     *
     * This class may be used to stream very large responses. For example, it is possible to use this
     * class to read a response that is larger than the entire memory allocated to the current process.
     * It can even stream a response larger than the total storage on the current device, which is a
     * common requirement for video streaming applications.
     *
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  6. common-protos/k8s.io/api/certificates/v1/generated.proto

      //      implementations prior to v1.22)
      //   2. Signer whose configured maximum is shorter than the requested duration
      //   3. Signer whose configured minimum is longer than the requested duration
      //
      // The minimum valid value for expirationSeconds is 600, i.e. 10 minutes.
      //
      // +optional
      optional int32 expirationSeconds = 8;
    
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  7. docs/en/docs/advanced/custom-response.md

    Import the `Response` class (sub-class) you want to use and declare it in the *path operation decorator*.
    
    For large responses, returning a `Response` directly is much faster than returning a dictionary.
    
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  8. okhttp/src/main/kotlin/okhttp3/internal/http2/Http2Writer.kt

       * `promisedStreamId` to which response frames will be delivered. Push promise frames are sent as
       * a part of the response to `streamId`. The `promisedStreamId` has a priority of one greater than
       * `streamId`.
       *
       * @param streamId client-initiated stream ID.  Must be an odd number.
       * @param promisedStreamId server-initiated stream ID.  Must be an even number.
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  9. docs/en/docs/how-to/sql-databases-peewee.md

    If you are developing an application with an older non-async framework, and can work with all its defaults, **it can be a great tool**.
    
    But if you need to change some of the defaults, support more than one predefined database, work with an async framework (like FastAPI), etc, you will need to add quite some complex extra code to override those defaults.
    
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  10. architecture/networking/pilot.md

    of a collection of controllers. Per Kubernetes, "controllers are control loops that watch the state of your cluster, then make or request changes where needed."
    
    In Istio, we use the term a bit more liberally. Istio controllers watch more than just the state of *a* cluster -- many are reading from multiple clusters, or even external sources (files and XDS). Generally, Kubernetes controllers are then writing state back to the cluster; Istio does have a few of these controllers, but most of...
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