But whenever you need them and go and learn them, know that you can already use them directly in **FastAPI**.

### Pydantic v1 `regex` instead of `pattern`

Before Pydantic version 2 and before FastAPI 0.100.0, the parameter was called `regex` instead of `pattern`, but it's now deprecated.

You could still see some code using it:

=== "Python 3.10+ Pydantic v1"

    ```Python hl_lines="11"

Starlette bietet alle grundlegenden Funktionen eines Web-Microframeworks.

Es bietet jedoch keine automatische Datenvalidierung, Serialisierung oder Dokumentation.

## Die `scopes` verwenden

Der Parameter `security_scopes` wird vom Typ `SecurityScopes` sein.

Dieses verfügt über ein Attribut `scopes` mit einer Liste, die alle von ihm selbst benötigten Scopes enthält und ferner alle Abhängigkeiten, die dieses als Unterabhängigkeit verwenden. Sprich, alle „Dependanten“ ... das mag verwirrend klingen, wird aber später noch einmal erklärt.

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details

Modern versions of Python have support for **"asynchronous code"** using something called **"coroutines"**, with **`async` and `await`** syntax.

Let's see that phrase by parts in the sections below:

* **Asynchronous Code**
* **`async` and `await`**
* **Coroutines**

## Asynchronous Code

## pytest.mark.anyio

If we want to call asynchronous functions in our tests, our test functions have to be asynchronous. AnyIO provides a neat plugin for this, that allows us to specify that some test functions are to be called asynchronously.

## HTTPX

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

Most of the code is actually the same.

So, we are going to focus only on the differences.

## File structure

Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```

```Python
if not (credentials.username == "stanleyjobson") or not (credentials.password == "swordfish"):
    # Return some error
    ...
```

But by using the `secrets.compare_digest()` it will be secure against a type of attacks called "timing attacks".

### Timing Attacks

But what's a "timing attack"?

Let's imagine some attackers are trying to guess the username and password.

<img src="/img/tutorial/path-params/image02.png">

Aynı şekilde, farklı diller için kod türetme araçları da dahil olmak üzere çok sayıda uyumlu araç bulunur.

## Pydantic

<span style="color: green;">[INFO]</span> Start watching changes
<span style="color: green;">[INFO]</span> Start detecting changes
```

</div>

Vous pouvez maintenant aller sur <a href="http://127.0.0.1:8008" class="external-link" target="_blank">http://127.0.0.1:8008</a> et voir vos changements en direct.

* `/items/`
* `/items/{item_id}`

Es ist alles die gleiche Struktur wie bei `app/routers/users.py`.

Aber wir wollen schlauer sein und den Code etwas vereinfachen.

Wir wissen, dass alle *Pfadoperationen* in diesem Modul folgendes haben:

* Pfad-`prefix`: `/items`.
* `tags`: (nur ein Tag: `items`).
* Zusätzliche `responses`.
* `dependencies`: Sie alle benötigen die von uns erstellte `X-Token`-Abhängigkeit.