item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {
            "start_process": "2018-12-22T14:05:00+00:00",
            "duration": 176_100,

    item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {
            "start_process": "2018-12-22T14:05:00+00:00",
            "duration": 176_100,

    item_id = "ff97dd87-a4a5-4a12-b412-cde99f33e00e"
    data = {
        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {
            "start_process": "2018-12-22T14:05:00+00:00",
            "duration": 176_100,

For example, in Visual Studio Code, you can:

* Go to the "Debug" panel.
* "Add configuration...".
* Select "Python"
* Run the debugger with the option "`Python: Current File (Integrated Terminal)`".

It will then start the server with your **FastAPI** code, stop at your breakpoints, etc.

Here's how it might look:

<img src="/img/tutorial/debugging/image01.png">

---

If you use Pycharm, you can:

async def read_items(
    item_id: UUID,
    start_datetime: datetime = Body(),
    end_datetime: datetime = Body(),
    process_after: timedelta = Body(),
    repeat_at: time | None = Body(default=None),
):
    start_process = start_datetime + process_after
    duration = end_datetime - start_process
    return {
        "item_id": item_id,
        "start_datetime": start_datetime,
        "end_datetime": end_datetime,

But Gunicorn supports working as a **process manager** and allowing users to tell it which specific **worker process class** to use. Then Gunicorn would start one or more **worker processes** using that class.

And **Uvicorn** has a **Gunicorn-compatible worker class**.

<div class="termy">

```console
$ python ./scripts/docs.py live

<span style="color: green;">[INFO]</span> Serving on http://127.0.0.1:8008
<span style="color: green;">[INFO]</span> Start watching changes
<span style="color: green;">[INFO]</span> Start detecting changes
```

</div>

Он запустит сайт документации по адресу: `http://127.0.0.1:8008`.

Es unterstützt auch die Ausführung von <a href="https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker#pre_start_path" class="external-link" target="_blank">**Vorab-Schritten vor dem Start** </a> mit einem Skript.

!!! tip "Tipp"

A container is running as long as the **main process** (command or program) is running.

A container normally has a **single process**, but it's also possible to start subprocesses from the main process, and that way you will have **multiple processes** in the same container.

            a custom encoder.
            """
        ),
    ] = None,
    sqlalchemy_safe: Annotated[
        bool,
        Doc(
            """
            Exclude from the output any fields that start with the name `_sa`.

            This is mainly a hack for compatibility with SQLAlchemy objects, they
            store internal SQLAlchemy-specific state in attributes named with `_sa`,