```Python hl_lines="6  11"
{!../../../docs_src/path_params/tutorial003.py!}
```

Otherwise, the path for `/users/{user_id}` would match also for `/users/me`, "thinking" that it's receiving a parameter `user_id` with a value of `"me"`.

Similarly, you cannot redefine a path operation:

```Python hl_lines="6  11"

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

!!! check "Inspired **FastAPI** to"
    Be a micro-framework. Making it easy to mix and match the tools and parts needed.

    Have a simple and easy to use routing system.

{% endif %}
{% endfor %}

</div>

{% endfor %}
{% endif %}

## Veriler - Teknik detaylar

Bu sayfanın temel amacı, topluluğun başkalarına yardım etme çabasını vurgulamaktır.

            - iter_json
            - send_text
            - send_bytes
            - send_json
            - close

When a client disconnects, a `WebSocketDisconnect` exception is raised, you can catch it.

You can import it directly form `fastapi`:

```python
from fastapi import WebSocketDisconnect
```

::: fastapi.WebSocketDisconnect

## WebSockets - additional classes

If you want to play with JWT tokens and see how they work, check <a href="https://jwt.io/" class="external-link" target="_blank">https://jwt.io</a>.

## Install `python-jose`

    * **Talks**:
        * [PyConBY 2020: Serve ML models easily with FastAPI](https://www.youtube.com/watch?v=z9K5pwb0rt8) by [Sebastián Ramírez (tiangolo)](https://twitter.com/tiangolo).
        * [[VIRTUAL] Py.Amsterdam's flying Software Circus: Intro to FastAPI](https://www.youtube.com/watch?v=PnpTY1f4k2U) by [Sebastián Ramírez (tiangolo)](https://twitter.com/tiangolo).

## 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+"

    ```Python hl_lines="79-81"
    {!> ../../../docs_src/websockets/tutorial003_py39.py!}
    ```

=== "Python 3.8+"

## Add regular expressions

You can define a <abbr title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">regular expression</abbr> `pattern` that the parameter should match:

=== "Python 3.10+"

    ```Python hl_lines="11"
    {!> ../../../docs_src/query_params_str_validations/tutorial004_an_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="11"

Let's put that data in the Pydantic `UserInDB` model first.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing

"Hashing" means: converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md){.internal-link target=_blank}.