```Python
UserInDB(**user_in.dict())
```

...because `user_in.dict()` is a `dict`, and then we make Python "unwrap" it by passing it to `UserInDB` prefixed with `**`.

So, we get a Pydantic model from the data in another Pydantic model.

#### Unwrapping a `dict` and extra keywords

And then adding the extra keyword argument `hashed_password=hashed_password`, like in:

```Python

And then, that system (in this case **FastAPI**) will take care of doing whatever is needed to provide your code with those needed dependencies ("inject" the dependencies).

This is very useful when you need to:

* Have shared logic (the same code logic again and again).
* Share database connections.

The process that happens when your API app calls the *external API* is named a "callback". Because the software that the external developer wrote sends a request to your API and then your API *calls back*, sending a request to an *external API* (that was probably created by the same developer).

    {!> ../../../docs_src/query_params/tutorial004.py!}
    ```

## Required query parameters

When you declare a default value for non-path parameters (for now, we have only seen query parameters), then it is not required.

If you don't want to add a specific value but just make it optional, set the default as `None`.

But when you want to make a query parameter required, you can just not declare any default value:

    {!> ../../../docs_src/dependencies/tutorial005.py!}
    ```

It declares an optional query parameter `q` as a `str`, and then it just returns it.

This is quite simple (not very useful), but will help us focus on how the sub-dependencies work.

## Second dependency, "dependable" and "dependant"

Then you can create another dependency function (a "dependable") that at the same time declares a dependency of its own (so it is a "dependant" too):

Then, we can pass more parameters to `Query`. In this case, the `max_length` parameter that applies to strings:

```Python
q: Union[str, None] = Query(default=None, max_length=50)
```

This will validate the data, show a clear error when the data is not valid, and document the parameter in the OpenAPI schema *path operation*.

For production you would use `fastapi run` instead. 🚀

Internally, **FastAPI CLI** uses <a href="https://www.uvicorn.org" class="external-link" target="_blank">Uvicorn</a>, a high-performance, production-ready, ASGI server. 😎

## `fastapi dev`

When you run `fastapi dev`, it will run on development mode.

With that you can connect the WebSocket and then send and receive messages:

<img src="/img/tutorial/websockets/image05.png">

## Handling disconnections and multiple clients

When a WebSocket connection is closed, the `await websocket.receive_text()` will raise a `WebSocketDisconnect` exception, which you can then catch and handle like in this example.

=== "Python 3.9+"

## Use the instance as a dependency

Then, we could use this `checker` in a `Depends(checker)`, instead of `Depends(FixedContentQueryChecker)`, because the dependency is the instance, `checker`, not the class itself.

And when solving the dependency, **FastAPI** will call this `checker` like:

```Python
checker(q="somequery")
```

**FastAPI** will make sure to read that data from the right place instead of JSON.

!!! note "Technical Details"
    Data from forms is normally encoded using the "media type" `application/x-www-form-urlencoded` when it doesn't include files.

    But when the form includes files, it is encoded as `multipart/form-data`. If you use `File`, **FastAPI** will know it has to get the files from the correct part of the body.