## Return the same input data

Here we are declaring a `UserIn` model, it will contain a plaintext password:

=== "Python 3.10+"

    ```Python hl_lines="7  9"
    {!> ../../../docs_src/response_model/tutorial002_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="9  11"

!!! tip
    Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

    For example, in `app/main.py` you could have a line like:

    ```
    from app.routers import items
    ```

* The `app` directory contains everything. And it has an empty file `app/__init__.py`, so it is a "Python package" (a collection of "Python modules"): `app`.
* It contains an `app/main.py` file. As it is inside a Python package (a directory with a file `__init__.py`), it is a "module" of that package: `app.main`.

* `float`
* `bool`
* `bytes`

```Python hl_lines="1"
{!../../../docs_src/python_types/tutorial005.py!}
```

### Generic types with type parameters

There are some data structures that can contain other values, like `dict`, `list`, `set` and `tuple`. And the internal values can have their own type too.

                            * `security_scopes.scopes` will contain `["me", "items"]` for the *path operation* `read_own_items`.
                            * `security_scopes.scopes` will contain `["me"]` for the *path operation* `read_users_me`, because it is declared in the dependency `get_current_active_user`.

    The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

!!! tip
    The SQLAlchemy model for `User` contains a `hashed_password` that should contain a secure hashed version of the password.

    But as what the API client provides is the original password, you need to extract it and generate the hashed password in your application.

            str,
            Doc(
                """
                The URL to obtain the OAuth2 token.
                """
            ),
        ],
        refreshUrl: Annotated[
            Optional[str],
            Doc(
                """
                The URL to refresh the token and obtain a new one.
                """
            ),
        ] = None,
        scheme_name: Annotated[

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

Another big feature needed by APIs is data validation, making sure that the data is valid, given certain parameters. For example, that some field is an `int`, and not some random string. This is especially useful for incoming data.

Without a data validation system, you would have to do all the checks by hand, in code.