provided in one of multiple optional ways (for example, with OpenID
                Connect or in a cookie).
                """
            ),
        ] = True,
    ):
        self.model = OpenIdConnectModel(
            openIdConnectUrl=openIdConnectUrl, description=description
        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

import org.apache.maven.artifact.resolver.ArtifactResolutionResult;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.model.Dependency;
import org.apache.maven.model.Plugin;
import org.apache.maven.model.Repository;
import org.apache.maven.settings.Mirror;
import org.apache.maven.settings.Server;
import org.eclipse.aether.RepositorySystemSession;

/**
 * @since 3.0-alpha

Es verbessert die Editor-Unterstützung für Pydantic-Modelle, mit:

* Code-Vervollständigung
* Typüberprüfungen
* Refaktorisierung
* Suche
* Inspektionen

///

## Das Modell verwenden { #use-the-model }

Innerhalb der Funktion können Sie alle Attribute des Modellobjekts direkt verwenden:

{* ../../docs_src/body/tutorial002_py310.py *}

</div>

## Créer l'application avec un modèle unique { #create-the-app-with-a-single-model }

Nous allons d'abord créer la première version la plus simple de l'application avec un seul modèle **SQLModel**.

Ensuite, nous l'améliorerons en augmentant la sécurité et la polyvalence avec **plusieurs modèles** ci-dessous. 🤓

### Créer les modèles { #create-models }

Importez `SQLModel` et créez un modèle de base de données :

import org.apache.maven.toolchain.io.ToolchainsReader;
import org.apache.maven.toolchain.io.ToolchainsWriter;
import org.apache.maven.toolchain.merge.MavenToolchainMerger;
import org.apache.maven.toolchain.model.PersistedToolchains;
import org.apache.maven.toolchain.model.TrackableBase;
import org.codehaus.plexus.interpolation.EnvarBasedValueSource;
import org.codehaus.plexus.interpolation.InterpolationException;

import org.apache.maven.api.xml.XmlService;
import org.apache.maven.impl.DefaultMessageBuilderFactory;
import org.apache.maven.lifecycle.MojoExecutionConfigurator;
import org.apache.maven.model.Plugin;
import org.apache.maven.model.PluginExecution;
import org.apache.maven.plugin.MojoExecution;
import org.apache.maven.plugin.descriptor.MojoDescriptor;
import org.apache.maven.plugin.descriptor.Parameter;

import org.apache.maven.api.cache.RequestCacheFactory;
import org.apache.maven.api.cli.extensions.CoreExtension;
import org.apache.maven.api.di.Inject;
import org.apache.maven.api.di.Named;
import org.apache.maven.api.model.Plugin;
import org.apache.maven.api.services.ArtifactCoordinatesFactory;
import org.apache.maven.api.services.ArtifactManager;
import org.apache.maven.api.services.ArtifactResolver;

/// warning | Atenção

Note que `Field` é importado diretamente do `pydantic`, não do `fastapi` como todo o resto (`Query`, `Path`, `Body`, etc).

///

## Declare atributos do modelo { #declare-model-attributes }

Você pode então utilizar `Field` com atributos do modelo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` funciona da mesma forma que `Query`, `Path` e `Body`, ele possui todos os mesmos parâmetros, etc.

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Crie seu modelo de dados { #create-your-data-model }

Então você declara seu modelo de dados como uma classe que herda `BaseModel`.

Utilize os tipos Python padrão para todos os atributos:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package gradlebuild.buildutils.model

import org.gradle.util.GradleVersion


data class ReleasedVersion(val version: String, val buildTime: String) {
    fun gradleVersion() = GradleVersion.version(version)