@Override
    public Map<String, Collection<Integer>> create(Object... elements) {
      ImmutableMap.Builder<String, Integer> builder = ImmutableMap.builder();
      // assumes that each set is a singleton or less (as is done for the samples)
      for (Object elem : elements) {
        @SuppressWarnings("unchecked") // safe by generator contract
        Entry<String, Collection<Integer>> entry = (Entry<String, Collection<Integer>>) elem;

PYTHON_VERSIONS=("python3.9" "python3.10" "python3.11" "python3.12")
for v in "${PYTHON_VERSIONS[@]}"; do
  ln -s "/usr/local/include/${v}" "${TARGET}/usr/include/aarch64-linux-gnu/${v}"

	initialStackSnapShot := NewLeakDetect()
	return func() {
		initialStackSnapShot.DetectLeak(t)
	}
}

// list of functions to be ignored from the stack trace.
// Leak detection is done when tests are run, should ignore the tests related functions,
// and other runtime functions while identifying leaks.
var ignoredStackFns = []string{
	"",
	// Below are the stacks ignored by the upstream leaktest code.

protect against two drive failure whereas in MinIO erasure code you can lose as many as half of drives and still the data remains safe. Further, MinIO's erasure code is at the object level and can heal one object at a time. For RAID, healing can be done only at the volume level which translates into high downtime. As MinIO encodes each object individually, it can heal objects incrementally. Storage servers once deployed should not require drive replacement or healing for the lifetime of the server....

* Intégration Python facile avec **Jupyter Kernels** pour le développement à distance ou intra-Docker avec des extensions comme Atom Hydrogen ou Visual Studio...

	return jpool
}

func (j *BatchJobPool) cleanupReports(randomWait func() time.Duration) {
	t := time.NewTimer(randomWait())
	defer t.Stop()

	for {
		select {
		case <-GlobalContext.Done():
			return
		case <-t.C:
			results := make(chan itemOrErr[ObjectInfo], 100)
			ctx, cancel := context.WithCancel(j.ctx)
			defer cancel()

OkHttp
======

See the [project website][okhttp] for documentation and APIs.

HTTP is the way modern applications network. It’s how we exchange data & media. Doing HTTP
efficiently makes your stuff load faster and saves bandwidth.

OkHttp is an HTTP client that’s efficient by default:

 * HTTP/2 support allows all requests to the same host to share a socket.
 * Connection pooling reduces request latency (if HTTP/2 isn’t available).

Then your API will (let's imagine):

* Send the invoice to some customer of the external developer.
* Collect the money.
* Send a notification back to the API user (the external developer).
    * This will be done by sending a POST request (from *your API*) to some *external API* provided by that external developer (this is the "callback").

## The normal **FastAPI** app { #the-normal-fastapi-app }

   * become idle after the [onResponse][Callback.onResponse] or [onFailure][Callback.onFailure]
   * callback has returned. Synchronous calls become idle once [execute()][Call.execute] returns.
   * This means that if you are doing synchronous calls the network layer will not truly be idle
   * until every returned [Response] has been closed.
   */
  @get:Synchronized
  @set:Synchronized
  var idleCallback: Runnable? = null

  }

  /**
   * Helper method to grow the character buffer as needed, this only happens once in a while so it's
   * ok if it's in a method call. If the index passed in is 0 then no copying will be done.
   */
  private static char[] growBuffer(char[] dest, int index, int size) {
    if (size < 0) { // overflow - should be OutOfMemoryError but GWT/j2cl don't support it