Notice that the query `token` will be handled by a dependency.

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.

   * until one is ready. If there are no ready queues, or if other threads have everything under
   * control this will return null. If there is more than a single task ready to execute immediately
   * this will start another thread to handle that work.
   */
  fun awaitTaskToRun(): Task? {
    lock.assertHeld()

    while (true) {
      if (readyQueues.isEmpty()) {
        return null // Nothing to do.
      }

*   Updates `libjpeg-turbo` to `2.0.5` to handle
    [CVE-2020-13790](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-13790).
*   Updates `junit` to `4.13.1` to handle
    [CVE-2020-15250](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15250).
*   Updates `PCRE` to `8.44` to handle
    [CVE-2019-20838](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-20838)
    and

In most cases, the same tool that is used to **run the program on startup** is also used to handle automatic **restarts**.

For example, this could be handled by:

* Docker
* Kubernetes
* Docker Compose
* Docker in Swarm Mode
* Systemd
* Supervisor
* Handled internally by a cloud provider as part of their services
* Others...

## Replication - Processes and Memory

    * Numbers (`int`, `float`) with min and max values, etc.

* Validation for more exotic types, like:
    * URL.
    * Email.
    * UUID.
    * ...and others.

All the validation is handled by the well-established and robust **Pydantic**.

### Security and authentication

Security and authentication integrated. Without any compromise with databases or data models.

## Reference

### Design details

the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled by one of the multiple **replicated containers** running your app.

And normally this **load balancer** would be able to handle requests that go to *other* apps in your cluster (e.g. to a different domain, or under a different URL path prefix), and would transmit that communication to the right containers...

        * [Override the default exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#override-the-default-exception-handlers).
        * [Re-use **FastAPI's** exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#re-use-fastapis-exception-handlers).
    * PR [#273](https://github.com/tiangolo/fastapi/pull/273).

                val operatorCall = binaryExpression.getResolvedCall(context) ?: return null
                resolvedCalls += operatorCall
                // This method only handles compound assignment. Other cases like `plusAssign`, `rangeTo`, `contains` are handled by plain
                // `handleAsFunctionCall`
                if (operatorCall.resultingDescriptor.name !in operatorWithAssignmentVariant) return null

    "W",  # pycodestyle warnings
    "F",  # pyflakes
    "I",  # isort
    "B",  # flake8-bugbear
    "C4",  # flake8-comprehensions
    "UP",  # pyupgrade
]
ignore = [
    "E501",  # line too long, handled by black
    "B008",  # do not perform function calls in argument defaults
    "C901",  # too complex
    "W191",  # indentation contains tabs
]

[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F401"]