l'application efficacement et sans interruption ni problème.

Ceci contraste avec les étapes de **développement**, où vous êtes constamment en train de modifier le code, de le casser
et de le réparer, d'arrêter et de redémarrer le serveur de développement, _etc._

## Stratégies de déploiement

Il existe plusieurs façons de procéder, en fonction de votre cas d'utilisation spécifique et des outils que vous

URLs that share the same address may also share the same underlying TCP socket connection. Sharing a connection has substantial performance benefits: lower latency, higher throughput (due to [TCP slow start](https://www.igvita.com/2011/10/20/faster-web-vs-tcp-slow-start/)) and conserved battery. OkHttp uses a [ConnectionPool](https://square.github.io/okhttp/4.x/okhttp/okhttp3/-connection-pool/) that automatically reuses HTTP/1.x connections and multiplexes HTTP/2 connections.

internal fun <T> List<T>.toImmutableList(): List<T> =
  when {
    this.isEmpty() -> emptyList()
    this.size == 1 -> Collections.singletonList(this[0])
    // Collection.toArray returns Object[] (covariant).
    // It is faster than creating real T[] via reflection (Arrays.copyOf).
    else -> (this as java.util.Collection<*>).toArray().asList().unmodifiable() as List<T>
  }

/** Returns an immutable list containing [elements]. */
@SafeVarargs

 * Otherwise, at least reduce <i>explicit</i> dependencies on this type by using lambda expressions
 * or method references instead of classes, leaving your code easier to migrate in the future.
 *
 * <p>See the Guava User Guide article on <a
 * href="https://github.com/google/guava/wiki/FunctionalExplained">the use of {@code Function}</a>.
 *
 * @author Kevin Bourrillion
 * @since 2.0

 * iterators that don't support {@code remove()}. Otherwise, all optional operations are supported.
 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs

And you can declare dependencies with `async def` inside of normal `def` *path operation functions*, or `def` dependencies inside of `async def` *path operation functions*, etc.

It doesn't matter. **FastAPI** will know what to do.

/// note

If you don't know, check the [Async: *"In a hurry?"*](../../async.md#in-a-hurry){.internal-link target=_blank} section about `async` and `await` in the docs.

///

   * moved to index "distance", and the element at index {@code i} ends up at index {@code (distance
   * + i) mod array.length}. This is equivalent to {@code Collections.rotate(Ints.asList(array),
   * distance)}, but is considerably faster and avoids allocation and garbage collection.
   *
   * <p>The provided "distance" may be negative, which will rotate left.
   *
   * @since 32.0.0
   */
  public static void rotate(int[] array, int distance) {

   * moved to index "distance", and the element at index {@code i} ends up at index {@code (distance
   * + i) mod array.length}. This is equivalent to {@code Collections.rotate(Chars.asList(array),
   * distance)}, but is considerably faster and avoids allocation and garbage collection.
   *
   * <p>The provided "distance" may be negative, which will rotate left.
   *
   * @since 32.0.0
   */
  public static void rotate(char[] array, int distance) {

       * Static final fields are presumed to be fastest, based on our experience with
       * UnsignedBytesBenchmark. TODO(cpovirk): benchmark this
       */
      /*
       * A CopyOnWriteArraySet<WeakReference> is faster than a newSetFromMap of a MapMaker map with
       * weakKeys() and concurrencyLevel(1), even up to at least 12 cached exception types.
       */

      int n, @Nullable Entry<K, V>[] entryArray, boolean throwIfDuplicateKeys) {
    checkPositionIndex(n, entryArray.length);
    if (n == 0) {
      @SuppressWarnings("unchecked") // it has no entries so the type variables don't matter
      ImmutableMap<K, V> empty = (ImmutableMap<K, V>) EMPTY;
      return empty;
    }
    try {
      return fromEntryArrayCheckingBucketOverflow(n, entryArray, throwIfDuplicateKeys);