You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

## Recap, step by step

### Step 1: import `FastAPI`

```Python hl_lines="1"
{!../../../docs_src/first_steps/tutorial001.py!}
```

`FastAPI` is a Python class that provides all the functionality for your API.

    {!> ../../../docs_src/response_model/tutorial006_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="31  37"
    {!> ../../../docs_src/response_model/tutorial006.py!}
    ```

## Recap

Use the *path operation decorator's* parameter `response_model` to define response models and especially to ensure private data is filtered out.

You can learn how to use them and how they are integrated into **FastAPI** later in the **Advanced User Guide**.

## Recap

With what you have seen up to now, you can set up a secure **FastAPI** application using standards like OAuth2 and JWT.

In almost any framework handling the security becomes a rather complex subject quite quickly.

You can use simple tools like `htop` to see the CPU and RAM used in your server or the amount used by each process. Or you can use more complex monitoring tools, which may be distributed across servers, etc.

## Recap

You have been reading here some of the main concepts that you would probably need to keep in mind when deciding how to deploy your application:

* Security - HTTPS
* Running on startup
* Restarts

    {!> ../../../docs_src/body_updates/tutorial002_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="35"
    {!> ../../../docs_src/body_updates/tutorial002.py!}
    ```

### Partial updates recap

In summary, to apply partial updates you would:

* (Optionally) use `PATCH` instead of `PUT`.
* Retrieve the stored data.
* Put that data in a Pydantic model.

    {!> ../../../docs_src/extra_models/tutorial005_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="1  8"
    {!> ../../../docs_src/extra_models/tutorial005.py!}
    ```

## Recap

Use multiple Pydantic models and inherit freely for each case.

## Recap

You can use **Gunicorn** (or also Uvicorn) as a process manager with Uvicorn workers to take advantage of **multi-core CPUs**, to run **multiple processes in parallel**.

Password: `secret2`

And try to use the operation `GET` with the path `/users/me`.

You will get an "Inactive user" error, like:

```JSON
{
  "detail": "Inactive user"
}
```

## Recap

You now have the tools to implement a complete security system based on `username` and `password` for your API.

## Recap

You can use Pydantic Settings to handle the settings or configurations for your application, with all the power of Pydantic models.

* By using a dependency you can simplify testing.
* You can use `.env` files with it.

* The alternative documentation will also reflect the new query parameter and body:

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### Recap

In summary, you declare **once** the types of parameters, body, etc. as function parameters.

You do that with standard modern Python types.