response = client.post("/tuple-of-models/", json=data)
    assert response.status_code == 422, response.text

    data = [{"x": 1, "y": 2}]
    response = client.post("/tuple-of-models/", json=data)
    assert response.status_code == 422, response.text


def test_tuple_form_valid():
    response = client.post("/tuple-form/", data={"values": ("1", "2")})

////

/// info | Información

En la versión 1 de Pydantic el método para obtener el JSON Schema para un modelo se llamaba `Item.schema()`, en la versión 2 de Pydantic, el método se llama `Item.model_json_schema()`.

///

Sin embargo, aunque no estamos usando la funcionalidad integrada por defecto, aún estamos usando un modelo Pydantic para generar manualmente el JSON Schema para los datos que queremos recibir en YAML.

////

/// info | Informação

Na versão 1 do Pydantic, o método para obter o JSON Schema de um modelo é `Item.schema()`, na versão 2 do Pydantic, o método é `Item.model_json_schema()`.

///

Entretanto, mesmo que não utilizemos a funcionalidade integrada por padrão, ainda estamos usando um modelo Pydantic para gerar um JSON Schema manualmente para os dados que queremos receber no formato YAML.

            </goals>
            <configuration>
              <version>1.1.0</version>
              <models>
                <model>src/main/mdo/remote-resources.mdo</model>
              </models>
            </configuration>
          </execution>
          <execution>
            <id>supplemental-models</id>
            <goals>
              <goal>xpp3-writer</goal>
              <goal>java</goal>

  </build>
  <modules>
    <module>maven-core</module>
    <module>apache-maven</module>
    <module>maven-model</module>
    <module>maven-plugin-api</module>
    <module>maven-project</module>
    <module>maven-reporting-api</module>
    <module>maven-project-builder</module>
    <module>maven-mercury</module>
    <module>maven-embedder</module>
    <module>maven-toolchain</module>

     * This method finds out whether collecting projects failed because of the following scenario:
     * - A multi-module project containing a module which is a plugin and another module which depends on it.
     * - Just the plugin is being built with the -f <pom> flag.
     * - Because of inter-module dependency collection, all projects in the multi-module project are collected.
     * - The plugin is not yet installed in a repository.
     *

## Retorno Adicional com `model` { #additional-response-with-model }

Você pode fornecer o parâmetro `responses` aos seus *decoradores de caminho*.

Este parâmetro recebe um `dict`, as chaves são os códigos de status para cada retorno, como por exemplo `200`, e os valores são um outro `dict` com a informação de cada um deles.

## Other models { #other-models }

You can now get the current user directly in the *path operation functions* and deal with the security mechanisms at the **Dependency Injection** level, using `Depends`.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

But you are not restricted to using some specific data model, class or type.

        <executions>
          <execution>
            <id>attach-gradle-module-metadata</id>
            <goals>
              <goal>attach-artifact</goal>
            </goals>
            <configuration>
              <artifacts>
                <artifact>
                  <file>target/publish/module.json</file>
                  <type>module</type>
                </artifact>
              </artifacts>

    }

    /**
     * Describes the target processes that the code in this module may run on.
     */
    @get:Nested
    abstract val targetRuntimes: ModuleTargetRuntimes

    fun targetRuntimes(action: ModuleTargetRuntimes.() -> Unit) {
        action(targetRuntimes)
    }

    /**
     * Declares whether this module is published to an external repository.
     */
    abstract val published: Property<Boolean>