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

## Crea tu modelo de datos { #create-your-data-model }

Luego, declaras tu modelo de datos como una clase que hereda de `BaseModel`.

Usa tipos estándar de Python para todos los atributos:

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

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.model.Model;

/**
 * Provides the super POM that all models implicitly inherit from.
 *
 * @since 4.0.0
 */
@Experimental
public interface SuperPomProvider extends Service {

    /**
     * Gets the super POM for the specified model version.
     *
     * @param version The model version to retrieve the super POM for (e.g. "4.0.0"), must not be {@code null}.

 *
 * <p>This factory is responsible for instantiating concrete toolchain implementations
 * based on toolchain model configurations or default settings.</p>
 *
 * @since 4.0.0
 */
@Experimental
@Consumer
public interface ToolchainFactory {
    /**
     * Creates a toolchain instance from the provided model configuration.
     *

 */
package org.apache.maven.model.composition;

import java.util.List;

import org.apache.maven.model.DependencyManagement;
import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles the import of dependency management from other models into the target model.
 *

          <basedir>${project.basedir}/../../api/maven-api-settings</basedir>
          <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
          <models>
            <model>src/main/mdo/settings.mdo</model>
          </models>
          <params>
            <param>forcedIOModelVersion=1.2.0</param>
            <param>packageModelV3=org.apache.maven.settings</param>

 */
package org.apache.maven.model.composition;

import javax.inject.Named;
import javax.inject.Singleton;

import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

import org.apache.maven.model.Dependency;
import org.apache.maven.model.DependencyManagement;
import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200

Zusammengefasst, um Teil-Aktualisierungen vorzunehmen:

* (Optional) verwenden Sie `PATCH` statt `PUT`.
* Lesen Sie die bereits gespeicherten Daten aus.
* Fügen Sie diese in ein Pydantic-Modell ein.
* Erzeugen Sie aus dem empfangenen Modell ein `dict` ohne Defaultwerte (mittels `exclude_unset`).

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.building;

/**
 * Caches auxiliary data used during model building like already processed raw/effective models. The data in the cache
 * is meant for exclusive consumption by the model builder and is opaque to the cache implementation. The cache key is

 * under the License.
 */
package org.apache.maven.model.superpom;

import javax.inject.Inject;
import javax.inject.Named;
import javax.inject.Singleton;

import java.io.IOException;
import java.io.InputStream;
import java.util.HashMap;
import java.util.Map;

import org.apache.maven.model.InputSource;
import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelProcessor;

/**