Elle simplifie le processus de **création**, de **déploiement** et **d'accès** à une API avec un effort minimal.

Elle apporte la même **expérience développeur** que celle de la création d'applications avec FastAPI au **déploiement** de celles-ci dans le cloud. 🎉

FastAPI Cloud est le sponsor principal et le financeur des projets open source *FastAPI and friends*. ✨

## Fournisseurs cloud - Sponsors { #cloud-providers-sponsors }

      return "Suppliers.compose(" + function + ", " + supplier + ")";
    }

    @GwtIncompatible @J2ktIncompatible private static final long serialVersionUID = 0;
  }

  /**
   * Returns a supplier which caches the instance retrieved during the first call to {@code get()}
   * and returns that value on subsequent calls to {@code get()}. See: <a
   * href="http://en.wikipedia.org/wiki/Memoization">memoization</a>
   *

 * on the same [call] to process the next event.
 *
 * By forcing the list of listeners to change after every event, we can detect if buggy code caches
 * a stale [EventListener] in a field or local variable.
 */
class EventListenerRelay(
  val call: Call,
  val eventRecorder: EventRecorder,
) {
  private val eventListenerAdapter =
    EventListenerAdapter()

     * This method creates a new function that caches the results of the original function,
     * improving performance for repeated calls with the same input.
     *
     * @param callback The original function to be memoized. It takes a String as input and returns a String.
     * @return A new {@code UnaryOperator<String>} that caches the results of the original function.

        assertEquals(3, third.length, "Allocated buffer length matches configured maximum size");
    }

    // Parameterized: exercise small variations of cache size for a simple reuse cycle
    @ParameterizedTest
    @ValueSource(ints = { 1, 2 })
    @DisplayName("Parameterized: buffer reuse works for various small cache sizes")
    void reuseWorksForVariousCacheSizes(int cacheSize) {

        }
    }

    @Override
    public void omitForCycle(Artifact omitted) {
        logger.debug(indent + omitted + " (removed - causes a cycle in the graph)");
    }

    @Override
    public void updateScopeCurrentPom(Artifact artifact, String ignoredScope) {

C'est ce que nous allons voir ici.

Dans ce cas, vous accepteriez n'importe quel `dict` tant qu'il a des clés `int` avec des valeurs `float` :

{* ../../docs_src/body_nested_models/tutorial009_py310.py hl[7] *}

/// tip | Astuce

Gardez à l'esprit que JSON ne prend en charge que des `str` comme clés.

Mais Pydantic dispose d'une conversion automatique des données.

}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  absl::Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;
  }
  summary = resolved->SummarizeValue();

        }
    }

    @Nested
    @DisplayName("Integration tests")
    class IntegrationTests {

        @Test
        @DisplayName("Should handle complete read-write cycle")
        void testCompleteReadWriteCycle() throws SMBProtocolDecodingException {
            // Given
            byte[] writeBuffer = new byte[100];
            byte[] readBuffer = new byte[100];

        if (result.hasMetadataResolutionExceptions()) {
            throw result.getMetadataResolutionException(0);
        }

        // Metadata cannot be retrieved

        // Cyclic Dependency Error

        if (result.hasCircularDependencyExceptions()) {
            throw result.getCircularDependencyException(0);
        }

        // Version Range Violation