Our docs on dag policy demonstrate usage with type annotations:
https://airflow.apache.org/docs/apache-airflow/stable/concepts.html?highlight=dag_policy#dag-level-cluster-policy

```python
def dag_policy(dag: DAG):
    """Ensure that DAG has at least one tag"""
    if not dag.tags:
        raise AirflowClusterPolicyViolation(
            f"DAG {dag.dag_id} has no tags. At least one tag required. File path: {dag.filepath}"
        )
```

The problem is, by the time you import DAG with `from airflow import DAG`, airflow will have already loaded up the `settings.py` file (where processing of airflow_local_settings.py is done), and it seems nothing in your airflow local settings file gets imported.

So none of these examples would actually work.

To test this you can add a local settings file containing this:

```
from airflow import DAG

raise Exception('hello')
```

Now run `airflow dags list` and observe that no error will be raised.

Remove the `DAG` import.  Now you'll see the error.

Any suggestions how to handle this?  

There are a couple conf settings imported from settings. We could move these to `airflow/__init__.py`.  But less straightforward would be what to do about `settings.initialize()`.  Perhaps we could make it so that initialized is called within settings?


tests/cluster_policies/__init__.py
#
#
#
from datetime import timedelta
from typing import Callable, List
from airflow import DAG
from airflow.configuration import conf
from airflow.exceptions import AirflowClusterPolicyViolation
from airflow.models import TaskInstance
from airflow.models.baseoperator import BaseOperator
def task_must_have_owners(task: BaseOperator):