optional ProbeHandler handler = 1;

  // Number of seconds after the container has started before liveness probes are initiated.
  // More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  // +optional
  optional int32 initialDelaySeconds = 2;

  // Number of seconds after which the probe times out.
  // Defaults to 1 second. Minimum value is 1.

     */
    SecureRandom getRandom ();


    /**
     * 
     * 
     * Property <tt>jcifs.smb.client.dfs.ttl</tt> (int, default 300)
     * 
     * @return title to live, in seconds, for DFS cache entries
     */
    long getDfsTtl ();


    /**
     * 
     * Property <tt>jcifs.smb.client.dfs.strictView</tt> (boolean, default false)
     * 

- Fix: use force detach for azure disk ([#91948](https://github.com/kubernetes/kubernetes/pull/91948), [@andyzhangx](https://github.com/andyzhangx)) [SIG Cloud Provider]
- Fixes a problem with 63-second or 1-second connection delays with some VXLAN-based
  network plugins which was first widely noticed in 1.16 (though some users saw it
  earlier than that, possibly only with specific network plugins). If you were previously

import static com.google.common.base.Preconditions.checkArgument;
import static java.nio.charset.StandardCharsets.UTF_8;
import static java.util.Objects.requireNonNull;
import static java.util.concurrent.TimeUnit.SECONDS;

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import com.google.common.base.CharMatcher;
import com.google.common.base.Defaults;

        throw (T) t;
      }
    }
    new SneakyThrower<Error>().throwIt(t);
  }

  /**
   * Returns a {@link Stream} containing the elements of the first stream, followed by the elements
   * of the second stream, and so on.
   *
   * <p>This is equivalent to {@code Stream.of(streams).flatMap(stream -> stream)}, but the returned
   * stream may perform better.
   *
   * @see Stream#concat(Stream, Stream)
   */

 */

package com.google.common.hash;

import static com.google.common.truth.Truth.assertThat;
import static java.nio.charset.StandardCharsets.UTF_8;
import static java.util.concurrent.TimeUnit.SECONDS;
import static org.junit.Assert.assertThrows;

import com.google.common.base.Stopwatch;
import com.google.common.collect.ImmutableSet;
import com.google.common.hash.BloomFilterStrategies.LockFreeBitArray;

		Data:    "something else",
	}

	result := DB.Clauses(clause.OnConflict{
		OnConstraint: "some_id_other_id_unique",
		UpdateAll:    true,
	}).Create(&thing2)
	if result.Error != nil {
		t.Errorf("creating second thing: %v", result.Error)
	}

	var things []Thing
	if err := DB.Find(&things).Error; err != nil {
		t.Errorf("Failed, got error: %v", err)
	}

	if len(things) > 1 {

     * approach would be for each caller CAS it from null to a Set populated with its exception. But
     * there's another race: If the first thread fails with an exception and a second thread
     * immediately fails with the same exception:
     *
     * Thread1: calls setException(), which returns true, context switch before it can CAS
     * seenExceptions to its exception
     *

    //    were added to the queue. It's easily possible for one thread to take the head of the
    //    queue, immediately followed by another thread taking the next element in the queue. That
    //    second thread can then dispatch to the subscriber it took before the first thread does.
    //
    // All this makes me really wonder if there's any value in queueing here at all. A dispatcher

* Hashage de **mots de passe sécurisé** par défaut.
* Authentification par **jetons JWT**.
* Modèles **SQLAlchemy** (indépendants des extensions Flask, afin qu'ils puissent être utilisés directement avec des *workers* Celery).
* Modèle de démarrages basiques pour les utilisateurs (à modifier et supprimer au besoin).