assertEquals("module-2", pom.getValue("modules[1]"));
        assertEquals("module-1", pom.getValue("modules[2]"));
        assertEquals("module-3", pom.getValue("modules[3]"));
        assertEquals("module-4", pom.getValue("modules[4]"));
    }

    /**
     * Will throw an exception if it doesn't find parent(s) in build
     *
     * @throws Exception in case of issue

# Corpo - Campos { #body-fields }

Da mesma forma que você pode declarar validações adicionais e metadados nos parâmetros de uma *função de operação de rota* com `Query`, `Path` e `Body`, você pode declarar validações e metadados dentro de modelos do Pydantic usando `Field` do Pydantic.

## Importe `Field` { #import-field }

Primeiro, você tem que importá-lo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Atenção

Si quieres asegurar tu API, hay varias cosas mejores que puedes hacer, por ejemplo:

* Asegúrate de tener modelos Pydantic bien definidos para tus request bodies y responses.
* Configura los permisos y roles necesarios usando dependencias.
* Nunca guardes contraseñas en texto plano, solo hashes de contraseñas.

        Note that this change may break certain subclassed models. You can
        revert back to the previous behavior by adding upranking yourself in the
        `train_step()`/`test_step()`/`predict_step()` methods, e.g. `if
        x.shape.rank == 1: x = tf.expand_dims(x, axis=-1)`. Functional models as
        well as Sequential models built with an explicit input shape are not
        affected.

     *   where multiple modules in the reactor have the same artifactId.
     * <p>
     * {@code -rf :artifactId} will pick up the first module which matches, but when multiple modules in the reactor
     *   have the same artifactId, effective failed module might be later in build reactor.
     * This means that developer will either have to type groupId or wait for build execution of all modules which

* Documentación automática de modelos de datos con <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (ya que OpenAPI en sí mismo está basado en JSON Schema).

## Caso de Uso { #use-case }

Empecemos con un ejemplo de **caso de uso** y luego veamos cómo resolverlo con esto.

Imaginemos que tienes algunos **modelos de machine learning** que quieres usar para manejar requests. 🤖

Los mismos modelos son compartidos entre requests, por lo que no es un modelo por request, o uno por usuario o algo similar.

  if ($USE_MVND) {
    Write-Error "Checksum validation is not supported for maven-mvnd. `nPlease disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties."
  }
  Import-Module $PSHOME\Modules\Microsoft.PowerShell.Utility -Function Get-FileHash
  if ((Get-FileHash "$TMP_DOWNLOAD_DIR/$distributionUrlName" -Algorithm SHA256).Hash.ToLower() -ne $distributionSha256Sum) {

  <modelVersion>4.0.0</modelVersion>

  <parent>
    <groupId>org.apache.maven</groupId>
    <artifactId>maven-compat-modules</artifactId>
    <version>4.1.0-SNAPSHOT</version>
  </parent>

  <artifactId>maven-embedder</artifactId>

  <name>Maven Embedder (deprecated)</name>

plugins {
    id("gradlebuild.module-identity")
    `maven-publish`
    signing
    `java-gradle-plugin`
    id("com.gradle.plugin-publish")
}

extensions.create<PluginPublishExtension>("pluginPublish", gradlePlugin)

tasks.validatePlugins {
    enableStricterValidation = true
}

// Remove gradleApi() and gradleTestKit() as we want to compile/run against Gradle modules