* body, server processing, and reading the response body. If the call requires redirects or
   * retries all must complete within one timeout period.
   *
   * Configure the client's default timeout with [OkHttpClient.Builder.callTimeout].
   */
  fun timeout(): Timeout

  /**
   * Configure this call to publish all future events to [eventListener], in addition to the

    }
    server2.close()
  }

  @Test
  fun recordedBodyIsNullForGetRequests() {
    server.enqueue(MockResponse())
    val client = OkHttpClient()
    val request =
      Request(
        url = server.url("/"),
      )
    client.newCall(request).execute().use { response ->
      assertThat(response.body.string()).isEqualTo("")
    }
    val recordedRequest = server.takeRequest()

        try {
            final RESULT result = entityType.newInstance();
            result.setAccessType(DfTypeUtil.toString(source.get("accessType")));
            result.setClientIp(DfTypeUtil.toString(source.get("clientIp")));
            result.setHitCount(DfTypeUtil.toLong(source.get("hitCount")));
            result.setHitCountRelation(DfTypeUtil.toString(source.get("hitCountRelation")));

MockWebServer
=============

A scriptable web server for testing HTTP clients


### Motivation

This library makes it easy to test that your app Does The Right Thing when it
makes HTTP and HTTPS calls. It lets you specify which responses to return and
then verify that requests were made as expected.

Because it exercises your full HTTP stack, you can be confident that you're

/// tip

Keep in mind that JSON only supports `str` as keys.

But Pydantic has automatic data conversion.

This means that, even though your API clients can only send strings as keys, as long as those strings contain pure integers, Pydantic will convert them and validate them.

And the `dict` you receive as `weights` will actually have `int` keys and `float` values.

///

            * **FastAPI** fügt hier eine Referenz auf die globalen JSON-Schemas an einer anderen Stelle in Ihrer OpenAPI hinzu, anstatt es direkt einzubinden. Auf diese Weise können andere Anwendungen und Clients diese JSON-Schemas direkt verwenden, bessere Tools zur Codegenerierung bereitstellen, usw.

///

Die generierten Responses in der OpenAPI für diese *Pfadoperation* lauten:

```JSON hl_lines="3-12"
{

            * **FastAPI** adds a reference here to the global JSON Schemas in another place in your OpenAPI instead of including it directly. This way, other applications and clients can use those JSON Schemas directly, provide better code generation tools, etc.

///

The generated responses in the OpenAPI for this *path operation* will be:

```JSON hl_lines="3-12"
{
    "responses": {

Vous pourriez aussi l'utiliser pour générer du code automatiquement, pour les clients qui communiquent avec votre API. Comme par exemple, des applications frontend, mobiles ou IOT.

## Récapitulatif, étape par étape

### Étape 1 : import `FastAPI`

## Déprécier des paramètres

Disons que vous ne vouliez plus utiliser ce paramètre désormais.

Il faut qu'il continue à exister pendant un certain temps car vos clients l'utilisent, mais vous voulez que la documentation mentionne clairement que ce paramètre est <abbr title="obsolète, recommandé de ne pas l'utiliser">déprécié</abbr>.

On utilise alors l'argument `deprecated=True` de `Query` :

### Erforderlich, kann `None` sein { #required-can-be-none }

Sie können deklarieren, dass ein Parameter `None` akzeptieren kann, aber trotzdem erforderlich ist. Dadurch müssten Clients den Wert senden, selbst wenn der Wert `None` ist.

Um das zu tun, können Sie deklarieren, dass `None` ein gültiger Typ ist, einfach indem Sie keinen Defaultwert deklarieren: