If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.

////

### Das Passwort überprüfen

Zu diesem Zeitpunkt liegen uns die Benutzerdaten aus unserer Datenbank vor, das Passwort haben wir jedoch noch nicht überprüft.

Lassen Sie uns diese Daten zunächst in das Pydantic-Modell `UserInDB` einfügen.

Sie sollten niemals Klartext-Passwörter speichern, daher verwenden wir ein (gefaktes) Passwort-Hashing-System.

Wenn die Passwörter nicht übereinstimmen, geben wir denselben Fehler zurück.

Vamos imaginar que o carregamento do modelo pode **demorar bastante tempo**, porque ele tem que ler muitos **dados do disco**. Então você não quer fazer isso a cada requisição.

platforms/core-configuration/kotlin-dsl-provider-plugins/   @gradle/bt-kotlin-dsl-maintainers
platforms/core-configuration/kotlin-dsl-tooling-builders/   @gradle/bt-kotlin-dsl-maintainers
platforms/core-configuration/kotlin-dsl-tooling-models/     @gradle/bt-kotlin-dsl-maintainers

# Core automation platform (Declarative DSL)
platforms/core-configuration/declarative-dsl-api/                   @gradle/bt-declarative-dsl

```

/// warning | "Aviso"

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

///

## Declare atributos do modelo

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

```Python hl_lines="11-14"
{!../../docs_src/body_fields/tutorial001.py!}
```

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

## Resources

*   [TensorFlow.org](https://www.tensorflow.org)
*   [TensorFlow Tutorials](https://www.tensorflow.org/tutorials/)
*   [TensorFlow Official Models](https://github.com/tensorflow/models/tree/master/official)
*   [TensorFlow Examples](https://github.com/tensorflow/examples)
*   [TensorFlow Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow)

    }

    static Model transform(Model model, MavenProject project) {
        String packaging = model.getPackaging();
        if (POM_PACKAGING.equals(packaging)) {
            // raw to consumer transform
            model = model.withRoot(false).withModules(null).withSubprojects(null);
            if (model.getParent() != null) {
                model = model.withParent(model.getParent().withRelativePath(null));

import org.apache.maven.api.model.Model;
import org.apache.maven.api.model.ModelBase;
import org.apache.maven.api.model.Plugin;
import org.apache.maven.api.model.PluginContainer;
import org.apache.maven.api.model.PluginExecution;
import org.apache.maven.api.model.Profile;
import org.apache.maven.api.model.ReportPlugin;
import org.apache.maven.api.model.ReportSet;
import org.apache.maven.api.model.Reporting;

import jetbrains.buildServer.configs.kotlin.RelativeId
import model.CIBuildModel
import model.FlameGraphGeneration
import model.FunctionalTestBucketProvider
import model.GRADLE_BUILD_SMOKE_TEST_NAME
import model.PerformanceTestBucketProvider
import model.PerformanceTestCoverage
import model.SpecificBuild
import model.Stage
import model.StageName
import model.TestCoverage
import model.TestType

class StageProject(
    model: CIBuildModel,

        handleModelVersion(model);
        handleParent(pomFile, context, model);
        handleReactorDependencies(context, model);
        handleCiFriendlyVersion(context, model);
    }

    //
    // Infer modelVersion from namespace URI
    //
    void handleModelVersion(Model model) {
        String namespace = model.getDelegate().getNamespaceUri();