Usar uma URL relativa é importante para garantir que sua aplicação continue funcionando mesmo em um caso de uso avançado como [Atrás de um Proxy](../../advanced/behind-a-proxy.md){.internal-link target=_blank}.

///

/// info | Información

Ten en cuenta que el `TestClient` recibe datos que pueden ser convertidos a JSON, no modelos de Pydantic.

Si tienes un modelo de Pydantic en tu prueba y quieres enviar sus datos a la aplicación durante las pruebas, puedes usar el `jsonable_encoder` descrito en [Codificador Compatible con JSON](encoder.md){.internal-link target=_blank}.

///

## Ejecútalo { #run-it }

 *   <li>orders {@link Network#nodes()} and {@link Network#edges()} in the order in which the
 *       elements were added (insertion order)
 * </ul>
 *
 * <p>{@code Network}s built by this class also guarantee that each collection-returning accessor
 * returns a <b>(live) unmodifiable view</b>; see <a
 * href="https://github.com/google/guava/wiki/GraphsExplained#accessor-behavior">the external
 * documentation</a> for details.
 *

 * <p>Note that this implementation is not synchronized. If multiple threads access the same cell of
 * an {@code ArrayTable} concurrently and one of the threads modifies its value, there is no
 * guarantee that the new value will be fully visible to the other threads. To guarantee that
 * modifications are visible, synchronize access to the table. Unlike other {@code Table}
 * implementations, synchronization is unnecessary between a thread that writes to one cell and a

      if (interrupted) {
        Thread.currentThread().interrupt();
      }
    }
    return added;
  }

  /**
   * Returns a synchronized (thread-safe) queue backed by the specified queue. In order to guarantee
   * serial access, it is critical that <b>all</b> access to the backing queue is accomplished
   * through the returned queue.
   *

## `async` et `await`

Les versions modernes de Python ont une manière très intuitive de définir le code asynchrone, tout en gardant une apparence de code "séquentiel" classique en laissant Python faire l'attente pour vous au bon moment.

<img src="/img/tutorial/body/image04.png">

Isso não é por acaso, todo o framework foi construído em volta deste design.

E foi imensamente testado na fase de design, antes de qualquer implementação, para garantir que funcionaria para todos os editores de texto.

Houveram mudanças no próprio Pydantic para que isso fosse possível.

addition to default policies [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## you can define additional policies with custom supported actions and resources policies: [] ## writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject"...

addition to default policies [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## you can define additional policies with custom supported actions and resources policies: [] ## writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject"...

addition to default policies [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## you can define additional policies with custom supported actions and resources policies: [] ## writeexamplepolicy policy grants creation or deletion of buckets with name ## starting with example. In addition, grants objects write permissions on buckets starting with ## example. # - name: writeexamplepolicy # statements: # - resources: # - 'arn:aws:s3:::example*/*' # actions: # - "s3:AbortMultipartUpload" # - "s3:GetObject"...