Це можна досягти за допомогою [Pydantic's `AfterValidator`](https://docs.pydantic.dev/latest/concepts/validators/#field-after-validator) в середині `Annotated`.

/// tip | Порада

Pydantic також має [`BeforeValidator`](https://docs.pydantic.dev/latest/concepts/validators/#field-before-validator) та інші. 🤓

///

        // it refers to a snapshot artifact or meta-version.
        // NOTE: Release metadata includes version information about artifacts that have been released, to allow
        // meta-versions like RELEASE and LATEST to resolve, and also to allow retrieval of the range of valid, released
        // artifacts available.
        ArtifactRepositoryPolicy policy = metadata.getPolicy(repository);

        if (!policy.isEnabled()) {

`str`, `int`, `float` vb. normal tekil tiplerin yanında, `str`’den türeyen daha karmaşık tekil tipleri de kullanabilirsiniz.

Tüm seçenekleri görmek için [Pydantic Türlerine Genel Bakış](https://docs.pydantic.dev/latest/concepts/types/) sayfasına göz atın. Sonraki bölümde bazı örnekleri göreceksiniz.

/// check | Inspiró a **FastAPI** a

Usar código para definir "esquemas" que proporcionen tipos de datos y validación automáticamente.

///

### [Webargs](https://webargs.readthedocs.io/en/latest/) { #webargs }

Otra gran funcionalidad requerida por las APIs es el <dfn title="lectura y conversión a datos de Python">parsing</dfn> de datos de las requests entrantes.

/// check | Inspirou o **FastAPI** a

Usar código para definir "schemas" que forneçam, automaticamente, tipos de dados e validação.

///

### [Webargs](https://webargs.readthedocs.io/en/latest/) { #webargs }

Outra grande funcionalidade requerida pelas APIs é o <dfn title="ler e converter para dados do Python">parsing</dfn> de dados vindos de requisições de entrada.

To do that, use the standard Python type hint [`typing.Union`](https://docs.python.org/3/library/typing.html#typing.Union):

/// note

When defining a [`Union`](https://docs.pydantic.dev/latest/concepts/types/#unions), include the most specific type first, followed by the less specific type. In the example below, the more specific `PlaneItem` comes before `CarItem` in `Union[PlaneItem, CarItem]`.

///

Para ver todas as opções possíveis, consulte a [Visão geral dos tipos do Pydantic](https://docs.pydantic.dev/latest/concepts/types/). Você verá alguns exemplos no próximo capítulo.

Por exemplo, no modelo `Image` nós temos um campo `url`, nós podemos declará-lo como um `HttpUrl` do Pydantic invés de como uma `str`:

package replication

import (
	"bytes"
	"encoding/xml"
)

// Status represents Enabled/Disabled status
type Status string

// Supported status types
const (
	Enabled  Status = "Enabled"
	Disabled Status = "Disabled"
)

// DeleteMarkerReplication - whether delete markers are replicated - https://docs.aws.amazon.com/AmazonS3/latest/dev/replication-add-config.html
type DeleteMarkerReplication struct {

}

// Unused. Available for completion.
type topic struct {
	ARN string `xml:"Topic" json:"Topic"`
}

// Config - notification configuration described in
// http://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html
type Config struct {
	XMLNS      string   `xml:"xmlns,attr,omitempty"`
	XMLName    xml.Name `xml:"NotificationConfiguration"`
	QueueList  []Queue  `xml:"QueueConfiguration,omitempty"`

Pour voir toutes les options dont vous disposez, consultez [l’aperçu des types de Pydantic](https://docs.pydantic.dev/latest/concepts/types/). Vous verrez quelques exemples au chapitre suivant.

Par exemple, comme dans le modèle `Image` nous avons un champ `url`, nous pouvons le déclarer comme instance de `HttpUrl` de Pydantic au lieu de `str` :