**Güncelleme** için tüm değerleri optional olan modeller ile **oluşturma** için zorunlu değerlere sahip modelleri ayırmak için, [Extra Models](extra-models.md) bölümünde anlatılan fikirleri kullanabilirsiniz.

### Modèle pour l'entrée { #model-for-input }

Si vous utilisez ce modèle en entrée comme ici :

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

... alors, le champ `description` ne sera **pas requis**. Parce qu'il a une valeur par défaut de `None`.

### Modèle d'entrée dans les documents { #input-model-in-docs }

### Modelo para Entrada { #model-for-input }

Si usas este modelo como entrada, como aquí:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

...entonces el campo `description` **no será requerido**. Porque tiene un valor por defecto de `None`.

### Modelo de Entrada en la Documentación { #input-model-in-docs }

### Modelo para Entrada { #model-for-input }

Se você usar esse modelo como entrada, como aqui:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

... então o campo `description` **não será obrigatório**. Porque ele tem um valor padrão de `None`.

### Modelo de Entrada na Documentação { #input-model-in-docs }

//
//	// CREATE VIEW `user_view` AS SELECT * FROM `users` WHERE age > 20
//	q := DB.Model(&User{}).Where("age > ?", 20)
//	DB.Debug().Migrator().CreateView("user_view", gorm.ViewOption{Query: q})
//
//	// CREATE OR REPLACE VIEW `users_view` AS SELECT * FROM `users` WITH CHECK OPTION
//	q := DB.Model(&User{})

<img src="/img/python-types/image06.png">

これは「`one_person` はクラス `Person` の **インスタンス** である」ことを意味します。

「`one_person` は `Person` という名前の **クラス** である」という意味ではありません。

## Pydantic のモデル { #pydantic-models }

[Pydantic](https://docs.pydantic.dev/) はデータ検証を行うための Python ライブラリです。

データの「形」を属性付きのクラスとして宣言します。

そして、それぞれの属性は型を持ちます。

さらに、いくつかの値を持つクラスのインスタンスを作成すると、その値を検証し、適切な型に変換して（もしそうであれば）すべてのデータを持つオブジェクトを提供してくれます。

Regression test: Ensure app-level responses with Union models and content/examples
don't accumulate duplicate $ref entries in anyOf arrays.
See https://github.com/fastapi/fastapi/pull/14463
"""

from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel


class ModelA(BaseModel):
    a: str


class ModelB(BaseModel):
    b: str


app = FastAPI(

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.

/// check | Inspired **FastAPI** to

### Input için Model { #model-for-input }

Bu modeli şöyle input olarak kullanırsanız:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

...`description` alanı **zorunlu olmaz**. Çünkü `None` default değerine sahiptir.

### Dokümanlarda Input Modeli { #input-model-in-docs }

If your application is **simple**, this will probably **not be a problem**, and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more machines to your cluster).