* expect a newly-started thread to call [Runnable.run]. We shouldn't request new threads until
   * the already-requested ones are in service, otherwise we might create more threads than we need.
   *
   * We use [executeCallCount] and [runCallCount] to defend against starting more threads than we
   * need. Both fields are guarded by [lock].
   */
  private var executeCallCount = 0

## Installation

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

## Example

### Create it

* Create a file `main.py` with:

```Python
from typing import Union

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}

### Create a callback `APIRouter`

First create a new `APIRouter` that will contain one or more callbacks.

```Python hl_lines="3  25"
{!../../../docs_src/openapi_callbacks/tutorial001.py!}
```

### Create the callback *path operation*

To create the callback *path operation* use the same `APIRouter` you created above.

But it's the simplest way to focus on the server-side of WebSockets and have a working example:

```Python hl_lines="2  6-38  41-43"
{!../../../docs_src/websockets/tutorial001.py!}
```

## Create a `websocket`

In your **FastAPI** application, create a `websocket`:

```Python hl_lines="1  46-47"
{!../../../docs_src/websockets/tutorial001.py!}
```

!!! note "Technical Details"

!!! info
    Webhooks are available in OpenAPI 3.1.0 and above, supported by FastAPI `0.99.0` and above.

## An app with webhooks

When you create a **FastAPI** application, there is a `webhooks` attribute that you can use to define *webhooks*, the same way you would define *path operations*, for example with `@app.webhooks.post()`.

```Python hl_lines="9-13  36-53"

    The Apache projects are characterized by a collaborative, consensus based development process, an open and
    pragmatic software license, and a desire to create high quality software that leads the way in its field.
    We consider ourselves not simply a group of projects sharing a server, but rather a community of developers
    and users.
  </description>
  <licenses>
    <license>

        tf.TensorSpec([], dtypes.int32) ]) def _remote_multiply(a, b): return
        tf.math.multiply(a, b)

        server.register("multiply", _remote_multiply) ```

    *   Example usage to create client: `python client =
        tf.distribute.experimental.rpc.Client.create("grpc", address) a =
        tf.constant(2, dtype=tf.int32) b = tf.constant(3, dtype=tf.int32)

### Unlimited "plug-ins"

Or in other way, no need for them, import and use the code you need.

Any integration is designed to be so simple to use (with dependencies) that you can create a "plug-in" for your application in 2 lines of code using the same structure and syntax used for your *path operations*.

### Tested

* 100% <abbr title="The amount of code that is automatically tested">test coverage</abbr>.

- sends UDS events to ztunnel via a socket whenever a pod is enabled for ambient mesh (whether from CNI plugin or node watcher), instructing ztunnel to create the "tube" socket.

The ambient CNI agent is the only place where ambient network config and pod redirection machinery happens.

### Building a distribution from source

To create a Gradle distribution from the source tree you can run either of the following:

    ./gradlew :distributions-full:binDistributionZip