### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"""Restriction on when a DAG can be scheduled for a run.
    Specifically, the run must not be earlier than ``earliest``, nor later than
    ``latest``. If ``catchup`` is *False*, the run must also not be earlier than
    the current time, i.e. "missed" schedules are not backfilled.
    These values are generally set on the DAG or task's ``start_date``,
    ``end_date``, and ``catchup`` arguments.
    Both ``earliest`` and ``latest``, if not *None*, are inclusive; a DAG run
    can happen exactly at either point of time. They are guaranteed to be aware
    (i.e. contain timezone information) for ``TimeRestriction`` instances
    created by Airflow.
    """
    earliest: DateTime | None
    latest: DateTime | None
    catchup: bool
class DagRunInfo(NamedTuple):
    """Information to schedule a DagRun.
    Instances of this will be returned by timetables when they are asked to
    schedule a DagRun creation.
    """
    run_after: DateTime
    """The earliest time this DagRun is created and its tasks scheduled.
    This **MUST** be "aware", i.e. contain timezone information.
    """
    data_interval: DataInterval
    """The data interval this DagRun to operate over."""
    @classmethod
    def exact(cls, at: DateTime) -> DagRunInfo: