}{
		{
			SQL:           "create table users (name, age, height, actived, bytes, create_at, update_at, deleted_at, email, role, pass) values (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
			NumericRegexp: nil,
			Vars:          []interface{}{"jinzhu", 1, 999.99, true, []byte("12345"), tt, &tt, nil, "w@g.\"com", myrole, pwd},

    position: relative;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    line-height: 1.2;
}

[data-termynal]:before {
    content: '';
    position: absolute;
    top: 15px;
    left: 15px;
    display: inline-block;
    width: 15px;
    height: 15px;
    border-radius: 50%;
    /* A little hack to display the window buttons in one pseudo element. */
    background: #d9515d;

    </div>
  </div>
  <div id="announce-right" style="position: relative;">
    <div class="item">

                    },
                    "summary": "Create Index Weights",
                    "operationId": "create_index_weights_index_weights__post",
                    "requestBody": {
                        "content": {
                            "application/json": {
                                "schema": {
                                    "title": "Weights",
                                    "type": "object",

   * The maximum number of requests to execute concurrently. Above this requests queue in memory,
   * waiting for the running calls to complete.
   *
   * If more than [maxRequests] requests are in flight when this is invoked, those requests will
   * remain in flight.
   */
  var maxRequests = 64
    get() = this.withLock { field }
    set(maxRequests) {
      require(maxRequests >= 1) { "max < 1: $maxRequests" }
      this.withLock {

	apiRequestsIncomingTotalMD = NewGaugeMD(apiRequestsIncomingTotal,
		"Total number of incoming requests", "type")

	apiRequestsInFlightTotalMD = NewGaugeMD(apiRequestsInFlightTotal,
		"Total number of requests currently in flight", "name", "type")
	apiRequestsTotalMD = NewCounterMD(apiRequestsTotal,
		"Total number of requests", "name", "type")
	apiRequestsErrorsTotalMD = NewCounterMD(apiRequestsErrorsTotal,

    Isso significa que, embora os clientes da API só possam enviar strings como chaves, desde que essas strings contenham inteiros puros, o Pydantic irá convertê-los e validá-los.

    E o `dict` que você recebe como `weights` terá, na verdade, chaves `int` e valores` float`.

## Recapitulação

Com **FastAPI** você tem a flexibilidade máxima fornecida pelos modelos Pydantic, enquanto seu código é mantido simples, curto e elegante.

      this.streamId = streamId
      this.windowSizeIncrement = windowSizeIncrement
    }

    override fun priority(
      streamId: Int,
      streamDependency: Int,
      weight: Int,
      exclusive: Boolean,
    ) {
      throw UnsupportedOperationException()
    }

    override fun pushPromise(
      streamId: Int,
      associatedStreamId: Int,

    Die obige Anwendung ist ein minimales und einfaches Beispiel, das zeigt, wie Nachrichten verarbeitet und an mehrere WebSocket-Verbindungen gesendet werden.

    Beachten Sie jedoch, dass, da alles nur im Speicher in einer einzigen Liste verwaltet wird, es nur funktioniert, während der Prozess ausgeführt wird, und nur mit einem einzelnen Prozess.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`