The `lifespan` parameter of the `FastAPI` app takes an **async context manager**, so we can pass our new `lifespan` async context manager to it.

```Python hl_lines="22"
{!../../../docs_src/events/tutorial003.py!}
```

## Alternative Events (deprecated)

!!! warning

In the case of our dependency `get_settings()`, the function doesn't even take any arguments, so it always returns the same value.

That way, it behaves almost as if it was just a global variable. But as it uses a dependency function, then we can override it easily for testing.

Because it's a Python exception, you don't `return` it, you `raise` it.

# Deployment

Deploying a **FastAPI** application is relatively easy.

## What Does Deployment Mean

To **deploy** an application means to perform the necessary steps to make it **available to the users**.

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

    This defines the name of the query parameter that should be provided in the request
    with the API key and integrates that into the OpenAPI documentation. It extracts
    the key value sent in the query parameter automatically and provides it as the
    dependency result. But it doesn't define how to send that API key to the client.

    ## Usage

    Create an instance object and use that object as the dependency in `Depends()`.

```

</div>

It is **HIGHLY encouraged** that you write or copy the code, edit it and run it locally.

Using it in your editor is what really shows you the benefits of FastAPI, seeing how little code you have to write, all the type checks, autocompletion, etc.

---

## Install FastAPI

The first step is to install FastAPI.

For the tutorial, you might want to install it with all the optional dependencies and features:

```Python
id = data["id"]
```

it will also try to get it from an attribute, as in:

```Python
id = data.id
```

And with this, the Pydantic *model* is compatible with ORMs, and you can just declare it in the `response_model` argument in your *path operations*.

You will be able to return a database model and it will read the data from it.

#### Technical Details about ORM mode

<img src="/img/tutorial/separate-openapi-schemas/image02.png">
</div>

This means that it will **always have a value**, it's just that sometimes the value could be `None` (or `null` in JSON).

That means that, clients using your API don't have to check if the value exists or not, they can **assume the field will always be there**, but just that in some cases it will have the default value of `None`.

You send it a token and it returns an authenticated user.

This provider might be charging you per request, and calling it might take some extra time than if you had a fixed mock user for tests.

You probably want to test the external provider once, but not necessarily call it for every test that runs.

    ```

!!! note
    A path parameter is always required as it has to be part of the path.

    So, you should declare it with `...` to mark it as required.

    Nevertheless, even if you declared it with `None` or set a default value, it would not affect anything, it would still be always required.

## Order the parameters as you need

!!! tip