شما پایتون استاندارد را با استفاده از تایپ ها مینویسید:

```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
```

![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

## Example upgrade

Now modify the file `main.py` to receive a body from a `PUT` request.

Declare the body using standard Python types, thanks to Pydantic.

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

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

                            * `security_scopes.scopes` terá `[]` (nada) para a *operação de rota* `read_system_status`, porque ele não declarou nenhum `Security` com `scopes`, e sua dependência, `get_current_user`, não declara nenhum `scopes` também.

/// tip | Dica

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
```

          }
        }
      }
    },
    /*
     * This one comes last to work around b/367716565. (One *possible* alternative would be to not
     * declare any methods in this enum, converting assertFailsToDecode into a static method that is
     * implemented with a `switch`. I haven't tested that.)
     */
    @GwtIncompatible // decodingStream(Reader)
    DECODING_STREAM {

    </server>
    -->
  </servers>

  <!-- mirrors
   | This is a list of mirrors to be used in downloading artifacts from remote repositories.
   |
   | It works like this: a POM may declare a repository to use in resolving certain artifacts.
   | However, this repository may have problems with heavy traffic at times, so people have mirrored
   | it to several places.
   |

Bạn viết chuẩn Python với kiểu dữ liệu như sau:

```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
```

如果你需要2分钟来学习如何使用 Python 类型（即使你不使用 FastAPI ），看看这个简短的教程：[Python Types](python-types.md){.internal-link target=_blank}。

编写带有类型标注的标准 Python：

```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
```

///

### Create the `Settings` object

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

Você escreve Python padrão com tipos:

```Python
from datetime import date

from pydantic import BaseModel

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date