The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

### About `**user_in.dict()`

#### Pydantic's `.dict()`

`user_in` is a Pydantic model of class `UserIn`.

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` when...

```JSON hl_lines="2"
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    }
}
```

instead of:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2
}
```

## Recap

We will soon also create the actual path operation.

!!! info
    If you are a very strict "Pythonista" you might dislike the style of the parameter name `tokenUrl` instead of `token_url`.

    That's because it is using the same name as in the OpenAPI spec. So that if you need to investigate more about any of these security schemes you can just copy and paste it to find more information about it.

the background task itself, and use internally only data that doesn't depend on the resources of dependencies with `yield`.

For example, instead of using the same database session, you would create a new database session inside of the background task, and you would obtain the objects from the database using this new session. And then instead of passing the object from the database as a parameter to the background task function, you would pass the ID of that object and then obtain the object...

if you run it without passing the required parameter.

When you don't use `Annotated` and instead use the **(old) default value style**, if you call that function without FastAPI in **other place**, you have to **remember** to pass the arguments to the function for it to work correctly, otherwise the values will be different from what you expect (e.g. `QueryInfo` or something similar instead of `str`). And your editor won't complain, and Python won't complain running that function, only when...

!!! tip
    This tutorial previously used <a href="https://pyjwt.readthedocs.io/" class="external-link" target="_blank">PyJWT</a>.

    But it was updated to use Python-jose instead as it provides all the features from PyJWT plus some extras that you might need later when building integrations with other tools.

## Password hashing

## `Security()`

For many scenarios, you can handle security (authorization, authentication, etc.) with dependencies, using `Depends()`.

But when you want to also declare OAuth2 scopes, you can use `Security()` instead of `Depends()`.

You can import `Security()` directly from `fastapi`:

```python
from fastapi import Security
```

## HTTPX

Even if your **FastAPI** application uses normal `def` functions instead of `async def`, it is still an `async` application underneath.

### Path operation functions

When you declare a *path operation function* with normal `def` instead of `async def`, it is run in an external threadpool that is then awaited, instead of being called directly (as it would block the server).