### 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.
return self.__class__._offset
            def dst(self, dt):
                return self.__class__._dst
            def tzname(self, dt):
                return self.__class__._name
        start = datetime.datetime(2018, 3, 25, 10, tzinfo=UTC0530())
        dag = DAG("tz_dag", start_date=start, schedule="@hourly")
        when = dag.following_schedule(start)
        assert when.isoformat() == "2018-03-25T05:30:00+00:00"
    def test_dagtag_repr(self):
        clear_db_dags()
        dag = DAG("dag-test-dagtag", start_date=DEFAULT_DATE, tags=["tag-1", "tag-2"])
        dag.sync_to_db()
        with create_session() as session:
            assert {"tag-1", "tag-2"} == {
                repr(t) for t in session.query(DagTag).filter(DagTag.dag_id == "dag-test-dagtag").all()
            }
    def test_bulk_write_to_db(self):
        clear_db_dags()
        dags = [DAG(f"dag-bulk-sync-{i}", start_date=DEFAULT_DATE, tags=["test-dag"]) for i in range(0, 4)]
        with assert_queries_count(5):
            DAG.bulk_write_to_db(dags)
        with create_session() as session:
            assert {"dag-bulk-sync-0", "dag-bulk-sync-1", "dag-bulk-sync-2", "dag-bulk-sync-3"} == {
                row[0] for row in session.query(DagModel.dag_id).all()
            }
            assert {
                ("dag-bulk-sync-0", "test-dag"),
                ("dag-bulk-sync-1", "test-dag"),