Does nothing. false true false false false true generate-sources org.apache.maven.plugin.coreit.CMojo java per-lookup once-per-session models java.lang.String[] false true version java.lang.String false true ${version} xpp3-writer Does nothing. false true false false false true generate-sources org.apache.maven.plugin.coreit.BMojo java per-lookup once-per-session models java.lang.String[] false true version java.lang.String false true ${version} org.apache.maven maven-plugin-api jar 2.0 org/apache/m...

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

import java.util.Properties;

import org.apache.maven.api.model.Profile;
import org.apache.maven.model.building.SimpleProblemCollector;
import org.apache.maven.model.profile.DefaultProfileActivationContext;
import org.apache.maven.model.profile.ProfileActivationContext;
import org.junit.jupiter.api.AfterEach;

De la misma manera, esta base de datos no recibiría un modelo de Pydantic (un objeto con atributos), solo un `dict`.

Puedes usar `jsonable_encoder` para eso.

Recibe un objeto, como un modelo de Pydantic, y devuelve una versión compatible con JSON:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

En este ejemplo, convertiría el modelo de Pydantic a un `dict`, y el `datetime` a un `str`.

Genauso würde die Datenbank kein Pydantic-Modell (ein Objekt mit Attributen) akzeptieren, sondern nur ein `dict`.

Sie können für diese Fälle `jsonable_encoder` verwenden.

Es nimmt ein Objekt entgegen, wie etwa ein Pydantic-Modell, und gibt eine JSON-kompatible Version zurück:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

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

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

import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.io.Reader;
import java.util.Map;

import org.apache.maven.model.Model;
import org.apache.maven.model.io.ModelReader;
import org.apache.maven.model.locator.ModelLocator;

		}
	}

	r = dryDB.Table("(?) as u", DB.Model(&User{}).Select("name")).Find(&User{}).Statement
	if !regexp.MustCompile("SELECT \\* FROM \\(SELECT .name. FROM .users. WHERE .users.\\..deleted_at. IS NULL\\) as u WHERE .u.\\..deleted_at. IS NULL").MatchString(r.Statement.SQL.String()) {
		t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
	}

The same way, this database wouldn't receive a Pydantic model (an object with attributes), only a `dict`.

You can use `jsonable_encoder` for that.

It receives an object, like a Pydantic model, and returns a JSON compatible version:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

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

import org.apache.maven.model.DependencyManagement;
import org.apache.maven.model.Model;

/**
 * Describes a tag used by the model builder to access a {@link ModelCache}. This interface basically aggregates a name

* Execution model
* Metadata model
* Metadata tooling
 ** Metadata extractor
 ** Metadata reader
 ** Metadata writer
 ** Metadata adapter (if required for the target system)
* Maven packaging and lifecycle
* Maven test harness for plugin execution model
* Eclipse IDE tooling for plugin execution model and metadata model

- we also seem to have information like the plugin lifecycle model that's buried inside the maven execution model

		t.Fatalf("Failed to query product, got error: %v", err)
	}

	DB.Model(&result3).Update("Price", 800)
	var result4 Product2
	DB.First(&result4, "name = ?", "Nice2")

	if result4.Price != 600 {
		t.Errorf("Admin product's price should not be changed, expects: %v, got %v", 600, result4.Price)
	}
}

type Product3 struct {
	gorm.Model
	Name  string
	Code  string
	Price int64
	Owner string
}