import org.apache.maven.project.MavenProject;

public class BuildStep {
    public static final int CREATED = 0;
    public static final int PLANNING = 1;
    public static final int SCHEDULED = 2;
    public static final int EXECUTED = 3;
    public static final int FAILED = 4;
    public static final int SKIPPED = 5;

    public static final String PLAN = "$plan$";

            completed.countDown();
          }
        };
    ListeningScheduledExecutorService service = listeningDecorator(delegate);
    ListenableFuture<Integer> future = service.schedule(Callables.returning(42), 1, MILLISECONDS);

    /*
     * Wait not just until the Future's value is set (as in future.get()) but
     * also until ListeningScheduledExecutorService's wrapper task is done

/**
 * Form class for editing job log entries in the admin interface.
 * This form handles the editing of system job execution logs,
 * providing details about scheduled tasks and their execution status.
 */
public class EditForm {

    /**
     * Creates a new EditForm instance.
     */
    public EditForm() {
        // Default constructor
    }

    /**

# limitations under the License.
# ============================================================================

on:
  workflow_dispatch:  # Allow manual triggers
  schedule:
    - cron: 0 4 * * *  # 4am UTC is 9pm PDT and 8pm PST
name: Set nightly branch to master HEAD

permissions: {}

jobs:
  master-to-nightly:

name: Translate

on:
  # schedule:
  #   - cron: "0 5 15 * *"  # Run at 05:00 on the 15 of every month

  workflow_dispatch:
    inputs:
      debug_enabled:
        description: Run with tmate debugging enabled (https://github.com/marketplace/actions/debugging-with-tmate)
        required: false
        default: "false"
      command:
        description: Command to run
        type: choice
        options:
          - translate-page

*   Added warmup capabilities to `tf.keras.optimizers.schedules.CosineDecay` learning rate scheduler. You can now specify an initial and target learning rate, and our scheduler will perform a linear interpolation between the two after which it will begin a decay phase.

name: Auto update performance test durations JSON

on:
  schedule:
    - cron: '53 3 * * 1'
  workflow_dispatch:

permissions:
  contents: write
  id-token: write
  pull-requests: write

jobs:
  update-perf-test-buckets:
    runs-on: ubuntu-latest

    if: github.repository == 'gradle/gradle'

    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
      - name: configure aws credentials

name: Test

on:
  push:
    branches:
      - master
  pull_request:
    types:
      - opened
      - synchronize
  schedule:
    # cron every week on monday
    - cron: "0 0 * * 1"

env:
  UV_SYSTEM_PYTHON: 1

jobs:
  test:
    strategy:
      matrix:
        os: [ windows-latest, macos-latest ]
        python-version: [ "3.14" ]
        include:
          - os: ubuntu-latest

name: Cleanup stale performance test data

on:
  schedule:
    - cron: '0 4 * * 1'  # Run every Monday at 4:00 AM UTC
  workflow_dispatch:

permissions:
  contents: read
  id-token: write

jobs:
  cleanup-stale-performance-data:
    runs-on: ubuntu-latest

    if: github.repository == 'gradle/gradle'

    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
      

        } catch (Exception e) {
            log.warn("Failed to recover channel {}: {}", channel.getChannelId(), e.getMessage());

            // Schedule next retry or remove
            handleFailure(channel, e);
        }
    }

    private void attemptRecoveryWithTransport(ChannelInfo channel, FailoverState state, SmbTransport newTransport) {
        try {