* So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all in your code).

```

### Testing file

Then you could have a file `test_main.py` with your tests. It could live on the same Python package (the same directory with a `__init__.py` file):

``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

Because this file is in the same package, you can use relative imports to import the object `app` from the `main` module (`main.py`):

```Python hl_lines="3"

    {!> ../../../docs_src/response_model/tutorial002.py!}
    ```

Now, whenever a browser is creating a user with a password, the API will return the same password in the response.

In this case, it might not be a problem, because it's the same user sending the password.

But if we use the same model for another *path operation*, we could be sending our user's passwords to every client.

!!! danger

    !!! tip
        Prefer to use the `Annotated` version if possible.

    ```Python hl_lines="11-14"
    {!> ../../../docs_src/body_fields/tutorial001.py!}
    ```

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.

!!! note "Technical Details"

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

The same error would appear if you provided a `float` instead of an `int`, as in: <a href="http://127.0.0.1:8000/items/4.2" class="external-link" target="_blank">http://127.0.0.1:8000/items/4.2</a>

!!! check
    So, with the same Python type declaration, **FastAPI** gives you data validation.

SQLALCHEMY_DATABASE_URL = "sqlite:///./sql_app.db"
# SQLALCHEMY_DATABASE_URL = "postgresql://user:password@postgresserver/db"

engine = create_engine(
    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# GraphQL

As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

# Testing WebSockets

You can use the same `TestClient` to test WebSockets.

For this, you use the `TestClient` in a `with` statement, connecting to the WebSocket:

```Python hl_lines="27-31"
{!../../../docs_src/app_testing/tutorial002.py!}
```

!!! note

## Read the Tutorial first

The next sections assume you already read the main [Tutorial - User Guide: Security](../../tutorial/security/index.md){.internal-link target=_blank}.