Thread.currentThread().interrupt() // Retain interrupted status.
      throw InterruptedIOException()
    }
  }

  /**
   * The Okio timeout watchdog will call [timedOut] if the timeout is reached. In that case we close
   * the stream (asynchronously) which will notify the waiting thread.
   */
  internal inner class StreamTimeout : AsyncTimeout() {
    override fun timedOut() {
      closeLater(ErrorCode.CANCEL)

   * Response and normal event sequences will not be received.
   *
   * This event will only be received when a Cache is configured for the client.
   */
  open fun cacheHit(
    call: Call,
    response: Response,
  ) {
  }

  /**
   * Invoked when a response will be served from the network. The Response will be
   * available from normal event sequences.
   *

### Server Memory

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

  optional bool hostIPC = 9;

  // seLinux is the strategy that will dictate the allowable labels that may be set.
  optional SELinuxStrategyOptions seLinux = 10;

  // runAsUser is the strategy that will dictate the allowable RunAsUser values that may be set.
  optional RunAsUserStrategyOptions runAsUser = 11;

  // RunAsGroup is the strategy that will dictate the allowable RunAsGroup values that may be set.

!!! info
    These docs are about to be updated. 🎉

    The current version assumes Pydantic v1.

    The new docs will hopefully use Pydantic v2 and will use <a href="https://art049.github.io/odmantic/" class="external-link" target="_blank">ODMantic</a> with MongoDB.

!!! warning "Deprecated"
    This tutorial is deprecated and will be removed in a future version.

### Technical Details: `root_path`

When you mount a sub-application as described above, FastAPI will take care of communicating the mount path for the sub-application using a mechanism from the ASGI specification called a `root_path`.

That way, the sub-application will know to use that path prefix for the docs UI.

* Large payloads.

Only a single connection is ever made between two servers.
Likely this means that this connection will not be able to saturate network bandwidth.
Therefore, using this for large payloads will likely be slower than using a separate connection,
and other connections will be blocked while the large payload is being sent.

## Handlers & Routes

Handlers have a predefined Handler ID. 

```

### Create a custom `GzipRoute` class

Next, we create a custom subclass of `fastapi.routing.APIRoute` that will make use of the `GzipRequest`.

This time, it will overwrite the method `APIRoute.get_route_handler()`.

This method returns a function. And that function is what will receive a request and return a response.

Here we use it to create a `GzipRequest` from the original request.

```Python hl_lines="18-26"

So, the prefix in this case is `/items`.

We can also add a list of `tags` and extra `responses` that will be applied to all the *path operations* included in this router.

And we can add a list of `dependencies` that will be added to all the *path operations* in the router and will be executed/solved for each request made to them.

!!! tip

    {!> ../../../docs_src/security/tutorial001.py!}
    ```

This dependency will provide a `str` that is assigned to the parameter `token` of the *path operation function*.

**FastAPI** will know that it can use this dependency to define a "security scheme" in the OpenAPI schema (and the automatic API docs).

!!! info "Technical Details"