### Description

A count of datasets that are currently registered/declared in an Airflow deployment.

### Use case/motivation

Would be nice to see how deployments are adopting datasets.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Unconditionally create a DAG run for the given DAG, and update the dag_model's fields to control
        if/when the next DAGRun should be created
        """
        
        
        
        
        existing_dagruns = (
            session.query(DagRun.dag_id, DagRun.execution_date)
            .filter(
                tuple_in_condition(
                    (DagRun.dag_id, DagRun.execution_date),
                    ((dm.dag_id, dm.next_dagrun) for dm in dag_models),
                ),
            )
            .all()
        )
        active_runs_of_dags = defaultdict(
            int,
            DagRun.active_runs_of_dags(dag_ids=(dm.dag_id for dm in dag_models), session=session),
        )
        for dag_model in dag_models:
            dag = self.dagbag.get_dag(dag_model.dag_id, session=session)