### Short

It has sensible **defaults** for everything, with optional configurations everywhere. All the parameters can be fine-tuned to do what you need and to define the API you need.

But by default, it all **"just works"**.

### Validation

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

<abbr title="A utility/system to store computed/generated values, to re-use them instead of computing them again.">"cache"</abbr> and pass it to all the "dependants" that need it in that specific request, instead of calling the dependency multiple times for the same request.

In an advanced scenario where you know you need the dependency to be called at every step (possibly multiple times) in the same request instead of using the "cached" value, you can set the parameter `use_cache=False`...

# Dependencies in path operation decorators

In some cases you don't really need the return value of a dependency inside your *path operation function*.

Or the dependency doesn't return a value.

But you still need it to be executed/solved.

For those cases, instead of declaring a *path operation function* parameter with `Depends`, you can add a `list` of `dependencies` to the *path operation decorator*.

be built using the **Dependency Injection** system. But in fact, there is actually **no need to create "plug-ins"**, as by using dependencies it's possible to declare an infinite number of integrations and interactions that become available to your *path operation functions*.

And dependencies can be created in a very simple and intuitive way that allows you to just import the Python packages you need, and integrate them with your API functions in a couple of lines of code, *literally*....

    * E.g., `await myfile.seek(0)` would go to the start of the file.
    * This is especially useful if you run `await myfile.read()` once and then need to read the contents again.
* `close()`: Closes the file.

As all these methods are `async` methods, you need to "await" them.

For example, inside of an `async` *path operation function* you can get the contents with:

```Python
contents = await myfile.read()
```

# WebSockets

You can use <a href="https://developer.mozilla.org/en-US/docs/Web/API/WebSockets_API" class="external-link" target="_blank">WebSockets</a> with **FastAPI**.

## Install `WebSockets`

First you need to install `WebSockets`:

<div class="termy">

```console
$ pip install websockets

---> 100%
```

</div>

## WebSockets client

### In production

## Write the callback documentation code

This code won't be executed in your app, we only need it to *document* how that *external API* should look like.

But, you already know how to easily create automatic documentation for an API with **FastAPI**.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

!!! danger
    Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.

    {!> ../../../docs_src/query_params_str_validations/tutorial002.py!}
    ```

As in this case (without using `Annotated`) we have to replace the default value `None` in the function with `Query()`, we now need to set the default value with the parameter `Query(default=None)`, it serves the same purpose of defining that default value (at least for FastAPI).

So:

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