import org.junit.jupiter.api.AfterEach
import org.junit.jupiter.api.BeforeEach
import org.junit.jupiter.api.Test

/**
 * Jetty HTTP client.
 *
 * https://www.eclipse.org/jetty/documentation/current/http-client.html
 *
 * Baseline test if we ned to validate OkHttp behaviour against other popular clients.
 */
class JettyHttpClientTest {
  private val client = HttpClient()

  @StartStop
  private val server = MockWebServer()

In diesem Beispiel wird das Pydantic-Modell in ein `dict`, und das `datetime`-Objekt in ein `str` konvertiert.

Das Resultat dieses Aufrufs ist etwas, das mit Pythons Standard-<a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a> kodiert werden kann.

fi

# Note: the profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

                    withPendingChangesOnly = branch.isMainBranch
                    enabled = branch.enableVcsTriggers
                    // https://www.jetbrains.com/help/teamcity/2022.04/configuring-schedule-triggers.html#general-syntax-1
                    // We want it to be triggered only when there're pending changes in the specific vcs root, i.e. GradleMaster/GradleRelease

## Prerequisites

To get started with MinIO, refer [MinIO QuickStart Document](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html).
Follow below steps to get started with MinIO monitoring using Prometheus.

### 1. Download Prometheus

[Download the latest release](https://prometheus.io/download) of Prometheus for your platform, then extract it

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

The result of calling it is something that can be encoded with the Python standard <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.

Neste exemplo, ele converteria o modelo Pydantic em um `dict`, e o `datetime` em um `str`.

O resultado de chamar a função é algo que pode ser codificado com o padrão do Python <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.

## API Response

XML response for this API is similar to [AWS STS AssumeRoleWithWebIdentity](https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html#API_AssumeRoleWithWebIdentity_ResponseElements)

## Example request and response

Sample request with `curl`:

```sh

    }

    @Override
    protected String getActionRole() {
        return ROLE;
    }

    /**
     * Displays the log management index page.
     *
     * @return HTML response for the log list page
     */
    @Execute
    @Secured({ ROLE, ROLE + VIEW })
    public HtmlResponse index() {
        return asIndexHtml();
    }

    /**

En este ejemplo, convertiría el modelo de Pydantic a un `dict`, y el `datetime` a un `str`.

El resultado de llamarlo es algo que puede ser codificado con la función estándar de Python <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.