///

## Import Pydantic's `BaseModel` { #import-pydantics-basemodel }

First, you need to import `BaseModel` from `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model { #create-your-data-model }

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

	}

	fields := []schema.Field{
		{Name: "ID", DBName: "id", BindNames: []string{"VersionModel", "BaseModel", "ID"}, DataType: schema.Uint, PrimaryKey: true, Size: 64, HasDefaultValue: true, AutoIncrement: true},
		{Name: "CreatedBy", DBName: "created_by", BindNames: []string{"VersionModel", "BaseModel", "CreatedBy"}, DataType: schema.Uint, Size: 64},

非推奨なので、Swagger UIを使った対話型のドキュメントにはGETのボディ情報は表示されません。さらに、中継するプロキシが対応していない可能性があります。

///

## Pydanticの `BaseModel` をインポート

ます初めに、 `pydantic` から `BaseModel` をインポートする必要があります:

{* ../../docs_src/body/tutorial001.py hl[4] *}

## データモデルの作成

そして、`BaseModel` を継承したクラスとしてデータモデルを宣言します。

すべての属性にpython標準の型を使用します:

{* ../../docs_src/body/tutorial001.py hl[7:11] *}

{* ../../docs_src/dataclasses/tutorial001.py hl[1,7:12,19:20] *}

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.

Оголошуйте вміст запиту за допомогою стандартних типів Python завдяки Pydantic.

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}

You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

That can then be used like:

```Python

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}

Deklarieren Sie den Body mithilfe von Standard-Python-Typen, dank Pydantic.

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}

Dichiara il _body_ usando le annotazioni di tipo standard di Python, grazie a Pydantic.

```Python hl_lines="2  7-10  23-25"
from fastapi import FastAPI
from pydantic import BaseModel
from typing import Optional

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = Optional[None]


@app.get("/")
def read_root():
    return {"Hello": "World"}