throw new IllegalStateException();
        }
        values.remove(0);
    }

    public <T> void seed(Class<T> clazz, Provider<T> value) {
        getScopeState().seed(clazz, value);
    }

    public <T> void seed(Class<T> clazz, final T value) {
        seed(clazz, (Provider<T>) () -> value);
    }

    public <T> Provider<T> scope(final Key<T> key, final Provider<T> unscoped) {

## Caveat

If you need to perform heavy background computation and you don't necessarily need it to be run by the same process (for example, you don't need to share memory, variables, etc), you might benefit from using other bigger tools like <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a>.

// freezeServices will freeze all incoming S3 API calls.
// For each call, unfreezeServices must be called once.
func freezeServices() {
	// Use atomics for globalServiceFreeze, so we can read without locking.
	// We need a lock since we are need the 2 atomic values to remain in sync.
	globalServiceFreezeMu.Lock()
	// If multiple calls, first one creates channel.
	globalServiceFreezeCnt++
	if globalServiceFreezeCnt == 1 {

public class ChecksumBenchmark {

  // Use a constant seed for all of the benchmarks to ensure apples to apples comparisons.
  private static final int RANDOM_SEED = new Random().nextInt();

  @Param({"10", "1000", "100000", "1000000"})
  private int size;

  private byte[] testBytes;

  @BeforeExperiment
  void setUp() {
    testBytes = new byte[size];
    new Random(RANDOM_SEED).nextBytes(testBytes);
  }

  // CRC32

public class ChecksumBenchmark {

  // Use a constant seed for all of the benchmarks to ensure apples to apples comparisons.
  private static final int RANDOM_SEED = new Random().nextInt();

  @Param({"10", "1000", "100000", "1000000"})
  private int size;

  private byte[] testBytes;

  @BeforeExperiment
  void setUp() {
    testBytes = new byte[size];
    new Random(RANDOM_SEED).nextBytes(testBytes);
  }

  // CRC32

func checkExistingKubeConfigFile(cfg *config.InstallConfig, expectedKC kubeconfig) error {
	kubeconfigFilepath := filepath.Join(cfg.MountedCNINetDir, cfg.KubeconfigFilename)

	existingKC, err := os.ReadFile(kubeconfigFilepath)
	if err != nil {
		installLog.Debugf("no preexisting kubeconfig at %s, assuming we need to create one", kubeconfigFilepath)
		return err
	}

Doing this provides the following specific benefits:
- **Reduce the API surface** - We no longer need to maintain two methods.
- **Consistency** - All languages have consistent access to the same APIs and ergonomics in the DSL.
- **Reduce the size of the Gradle distribution** - We no longer need to carry multiple standard libraries for different languages.

## Decision

### Short

It has sensible **defaults** for everything, with optional configurations everywhere. All the parameters can be fine-tuned to do what you need and to define the API you need.

But by default, it all **"just works"**.

### Validation

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).

    environ_cp['TF_NEED_CUDA'] = '0'
  else:
    environ_cp['TF_NEED_CUDA'] = str(
        int(get_var(environ_cp, 'TF_NEED_CUDA', 'CUDA', False)))
  if (environ_cp.get('TF_NEED_CUDA') == '1' and
      'TF_CUDA_CONFIG_REPO' not in environ_cp):

    set_action_env_var(
        environ_cp,
        'TF_NEED_TENSORRT',
        'TensorRT',
        False,
        bazel_config_name='tensorrt')

import org.apache.maven.plugin.descriptor.MojoDescriptor;

// TODO lifecycles being executed
// TODO what runs in each phase
// TODO plugins that need downloading
// TODO project dependencies that need downloading
// TODO unfortunately the plugins need to be downloaded in order to get the plugin.xml file. need to externalize this
//      from the plugin archive.
// TODO this will be the class that people get in IDEs to modify

/**