* function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced
 * load on the garbage collector by only using a constant number of internal objects.
 *

}

// Len returns the number of items in the cache.
func (c *LRU[K, V]) Len() int {
	c.mu.RLock()
	defer c.mu.RUnlock()
	return c.evictList.Length()
}

// Resize changes the cache size. Size of 0 means unlimited.
func (c *LRU[K, V]) Resize(size int) (evicted int) {
	c.mu.Lock()
	defer c.mu.Unlock()
	if size <= 0 {
		c.size = 0
		return 0
	}
	diff := c.evictList.Length() - size
	if diff < 0 {

ion(){var e=this,t=n.default("body");t.hasClass(L)||t.hasClass(D)?(n.default(k).not(this._config.target).hide(),n.default(this._config.target).css("display","block")):n.default(k).hide(),this._fixHeight(),this._fixScrollHeight(),n.default(window).resize((function(){e._fixHeight(),e._fixScrollHeight()})),n.default(window).scroll((function(){var t=n.default("body");(t.hasClass(L)||t.hasClass(D))&&e._fixScrollHeight()}))},t._isNavbarFixed=function(){var e=n.default("body");return e.hasClass("layout...

Y como la mayor parte del tiempo de ejecución se dedica al trabajo real (en lugar de esperar), y el trabajo en una computadora lo realiza una <abbr title="Central Processing Unit - Unidad Central de Procesamiento">CPU</abbr>, llaman a estos problemas "CPU bound".

---

:(!/^([a-zA-Z:]*\/\/)/.test(e)&&!r||e.replace(RegExp.$1,"").split("/")[0]===a.location.host)&&("//"===e.substring(0,2)&&(e=a.location.protocol+e),d.push({href:e,media:f})))}w()};x(),c.update=x,c.getEmValue=t,a.addEventListener?a.addEventListener("resize",b,!1):a.attachEvent&&a.attachEvent("onresize",b)}}(this);...

void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs,
                                TF_Status* s) {
  unwrap(o)->expected_num_outputs = num_outputs;
  unwrap(o)->outputs.clear();
  unwrap(o)->outputs.resize(num_outputs);
}
int TF_OutputListNumOutputs(TF_OutputList* o) {
  return unwrap(o)->outputs.size();
}
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i) {
  return wrap(unwrap(o)->outputs[i]);
}

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashMap}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger

Dans **SQLModel**, toute classe de modèle qui a `table=True` est un **modèle de table**.

Et toute classe de modèle qui n'a pas `table=True` est un **modèle de données**, ceux-ci sont en réalité juste des modèles Pydantic (avec deux petites fonctionnalités en plus). 🤓

Avec SQLModel, nous pouvons utiliser **l'héritage** pour **éviter de dupliquer** tous les champs dans tous les cas.

ction(e){var n=e.state,r=e.instance,o=e.options,i=o.scroll,a=void 0===i||i,s=o.resize,f=void 0===s||s,c=t(n.elements.popper),p=[].concat(n.scrollParents.reference,n.scrollParents.popper);return a&&p.forEach((function(e){e.addEventListener("scroll",r.update,$)})),f&&c.addEventListener("resize",r.update,$),function(){a&&p.forEach((function(e){e.removeEventListener("scroll",r.update,$)})),f&&c.removeEventListener("resize",r.update,$)}},data:{}};var te={name:"popperOffsets",enabled:!0,phase:"read",fn:function(e){var...

 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like