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.

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

## 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.

* 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.

```Dockerfile
CMD ["fastapi", "run", "app/main.py", "--proxy-headers", "--port", "80"]
```

## Recap

Using container systems (e.g. with **Docker** and **Kubernetes**) it becomes fairly straightforward to handle all the **deployment concepts**:

* HTTPS
* Running on startup
* Restarts