parallel(runITsTasks)

// JENKINS-34376 seems to make it hard to detect the aborted builds
} catch (org.jenkinsci.plugins.workflow.steps.FlowInterruptedException e) {
    echo "[FAILURE-002] FlowInterruptedException ${e}"
    // this ambiguous condition means a user probably aborted
    if (e.causes.size() == 0) {
        currentBuild.result = "ABORTED"
    } else {
        currentBuild.result = "FAILURE"
    }
    throw e

parallel(runITsTasks)

// JENKINS-34376 seems to make it hard to detect the aborted builds
} catch (org.jenkinsci.plugins.workflow.steps.FlowInterruptedException e) {
    echo "[FAILURE-002] FlowInterruptedException ${e}"
    // this ambiguous condition means a user probably aborted
    if (e.causes.size() == 0) {
        currentBuild.result = "ABORTED"
    } else {
        currentBuild.result = "FAILURE"
    }
    throw e

# Exceptions - `HTTPException` and `WebSocketException`

These are the exceptions that you can raise to show errors to the client.

When you raise an exception, as would happen with normal Python, the rest of the execution is aborted. This way you can raise these exceptions from anywhere in the code to abort a request and show the error to the client.

You can use:

* `HTTPException`
* `WebSocketException`

        super(message, e);
        this.url = url;
        this.abort = abort;
    }

    public String getUrl() {
        return url;
    }

    public boolean aborted() {
        return abort;
    }

When you check the benchmarks, it is common to see several tools of different types compared as equivalent.

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server

The core-runtime module defines each runtime:

- The target JVM for the runtime. Each runtime has its own JVM compatibility constraints.
- Some base services that are available to code hosted by the runtime. This varies by runtime.
- Additional constraints. For example, the CLI client runtimes limit the libraries that are available to the code in that runtime, for performance reasons. 

// A cross-domain policy file is an XML document that grants a web client, such as Adobe Flash Player
// or Adobe Acrobat (though not necessarily limited to these), permission to handle data across domains.
// When clients request content hosted on a particular source domain and that content make requests
// directed towards a domain other than its own, the remote domain needs to host a cross-domain

與使用 FastAPI 建置相同的開銷。在許多情況下，這種資料驗證和序列化是應用程式中編寫最大量的程式碼。
L33:    * 因此透過使用 FastAPI，你可以節省開發時間、錯誤與程式碼數量，並且相比不使用 FastAPI 你很大可能會獲得相同或更好的效能（因為那樣你必須在程式碼中實現所有相同的功能）。
L34:    * 如果你要與 FastAPI 比較，請將其與能夠提供資料驗證、序列化和文件的網頁應用程式框架（或工具集）進行比較，例如 Flask-apispec、NestJS、Molten 等框架。
...

      - v2.**
  schedule:
    - cron: '0 4 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |

      - r2.**
  schedule:
    - cron: '0 8 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |