It improves editor support for Pydantic models, with:

* auto-completion
* type checks
* refactoring
* searching
* inspections

///

## Use the model { #use-the-model }

Inside of the function, you can access all the attributes of the model object directly:

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

We'll fix these things by adding a few **extra models**. Here's where SQLModel will shine. ✨

### Create Multiple Models { #create-multiple-models }

In **SQLModel**, any model class that has `table=True` is a **table model**.

And any model class that doesn't have `table=True` is a **data model**, these ones are actually just Pydantic models (with a couple of small extra features). 🤓

    /**
     * Injects plugin executions induced by lifecycle bindings into the specified model. The model has already undergone
     * injection of plugin management so any plugins that are injected by lifecycle bindings and are not already present
     * in the model's plugin section need to be subjected to the model's plugin management.
     *
     * @param model The model into which to inject the default plugin executions for its packaging, must not be

Usa base64 solo si definitivamente necesitas incluir datos binarios en JSON y no puedes usar archivos para eso.

## Pydantic `bytes` { #pydantic-bytes }

Puedes declarar un modelo de Pydantic con campos `bytes`, y luego usar `val_json_bytes` en la configuración del modelo para indicarle que use base64 para validar datos JSON de entrada; como parte de esa validación decodificará el string base64 en bytes.

* o evento de encerramento
* o evento de lifespan

* o manipulador
* o manipulador de eventos
* o manipulador de exceções
* tratar

* o modelo
* o modelo Pydantic
* o modelo de dados
* o modelo de banco de dados
* o modelo de formulário
* o objeto de modelo

* a classe
* a classe base
* a classe pai
* a subclasse
* a classe filha
* a classe irmã
* o método de classe

* o cabeçalho

package gorm

import "time"

// Model a basic GoLang struct which includes the following fields: ID, CreatedAt, UpdatedAt, DeletedAt
// It may be embedded into your model or you may build your own model without it
//
//	type User struct {
//	  gorm.Model
//	}
type Model struct {
	ID        uint `gorm:"primarykey"`
	CreatedAt time.Time
	UpdatedAt time.Time
	DeletedAt DeletedAt `gorm:"index"`

## Optimizar el Rendimiento del Response - Modelo de Response - Tipo de Retorno { #optimize-response-performance-response-model-return-type }

## Response Adicional con `model` { #additional-response-with-model }

Puedes pasar a tus *decoradores de path operation* un parámetro `responses`.

Recibe un `dict`: las claves son los códigos de estado para cada response (como `200`), y los valores son otros `dict`s con la información para cada uno de ellos.

Cada uno de esos `dict`s de response puede tener una clave `model`, conteniendo un modelo de Pydantic, así como `response_model`.

Bunu yapmanın birkaç yolu var.

## Pydantic modellerinde ek JSON Schema verisi { #extra-json-schema-data-in-pydantic-models }

Oluşturulan JSON Schema’ya eklenecek şekilde bir Pydantic model için `examples` tanımlayabilirsiniz.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

Bu ek bilgi, o modelin çıktı **JSON Schema**’sına olduğu gibi eklenir ve API dokümanlarında kullanılır.

Ces informations sont disponibles dans le **schéma OpenAPI** de l’application, puis affichées dans la documentation de l’API.

Ces mêmes informations issues des modèles, incluses dans OpenAPI, peuvent être utilisées pour **générer le code client**.

### Hey API { #hey-api }