# Body - Fields

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field`

First, you have to import it:

=== "Python 3.10+"

    ```Python hl_lines="4"
    {!> ../../../docs_src/body_fields/tutorial001_an_py310.py!}
    ```

=== "Python 3.9+"

```Python
Base.metadata.create_all(bind=engine)
```

That is normally called in `main.py`, but the line in `main.py` uses the database file `sql_app.db`, and we need to make sure we create `test.db` for the tests.

So we add that line here, with the new file.

```Python hl_lines="16"
{!../../../docs_src/sql_databases/sql_app/tests/test_sql_app.py!}
```

    ```Python hl_lines="31"
    {!> ../../../docs_src/security/tutorial002.py!}
    ```

Notice that we declare the type of `current_user` as the Pydantic model `User`.

This will help us inside of the function with all the completion and type checks.

!!! tip
    You might remember that request bodies are also declared with Pydantic models.

    ```

    </div>

!!! note
    The command `uvicorn main:app` refers to:

    * `main`: the file `main.py` (the Python "module").
    * `app`: the object created inside of `main.py` with the line `app = FastAPI()`.

    It is equivalent to:

    ```Python
    from main import app
    ```

!!! warning

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
```

Sau đó có thể được sử dụng:

```Python

```

...并根据您的数据库数据和相关凭据（也适用于 MySQL、MariaDB 或任何其他）对其进行调整。

!!! tip

    如果您想使用不同的数据库，这是就是您必须修改的地方。

### 创建 SQLAlchemy 引擎

第一步，创建一个 SQLAlchemy的“引擎”。

我们稍后会将这个`engine`在其他地方使用。

```Python hl_lines="8-10"
{!../../../docs_src/sql_databases/sql_app/database.py!}
```

#### 注意

参数:

```Python
connect_args={"check_same_thread": False}
```

You can use `async def` or normal `def`.

And you can declare dependencies with `async def` inside of normal `def` *path operation functions*, or `def` dependencies inside of `async def` *path operation functions*, etc.

It doesn't matter. **FastAPI** will know what to do.

!!! note

* In Codeblöcken innerhalb des Markdown-Dokuments, übersetzen Sie Kommentare (`# ein Kommentar`), aber lassen Sie den Rest unverändert.

* Ändern Sie nichts, was in "``" (Inline-Code) eingeschlossen ist.

* In Zeilen, die mit `===` oder `!!!` beginnen, übersetzen Sie nur den ` "... Text ..."`-Teil. Lassen Sie den Rest unverändert.

Here we define the config `env_file` inside of your Pydantic `Settings` class, and set the value to the filename with the dotenv file we want to use.

### Creating the `Settings` only once with `lru_cache`

If you used to rely on this behavior, now you should create the resources for background tasks inside the background task itself, and use internally only data that doesn't depend on the resources of dependencies with `yield`.