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**Description**

When using decorators to define dags, e.g. dag_1.py:

```python
from airflow.decorators import dag, task
from airflow.utils.dates import days_ago

DEFAULT_ARGS = {
    "owner": "airflow",
}


@task
def some_task():
    pass


@dag(
    default_args=DEFAULT_ARGS,
    schedule_interval=None,
    start_date=days_ago(2),
)
def my_dag():
    some_task()


DAG_1 = my_dag()

```

and

dag_2.py:

```python
from airflow.decorators import dag, task
from airflow.utils.dates import days_ago

DEFAULT_ARGS = {
    "owner": "airflow",
}


@task
def some_other_task():
    pass


@dag(
    default_args=DEFAULT_ARGS,
    schedule_interval=None,
    start_date=days_ago(2),
)
def my_dag():
    some_other_task()


DAG_2 = my_dag()

```

We have two different dags which have been written in isolation, but by sheer bad luck both define `my_dag()`. This seems fine for each file in isolation, but on the airflow UI, we only end up seeing one entry for `my_dag`, where it has picked up `dag_1.py` and ignored `dag_2.py`.

**Use case / motivation**

We currently end up with only one DAG showing up on the UI, and no indication as to why the other one hasn't appeared.

Suggestion: popup similar to 'DAG import error' to highlight what needs changing in one of the DAG files in order for both to show up ("DAG import error: duplicate dag names found - please review {duplicate files} and ensure all dag definitions are unique"?)

**Are you willing to submit a PR?**

No time to spare on this at present

**Related Issues**

I haven't found any related issues with the search function.
tests/api_connexion/endpoints/test_log_endpoint.py
DAG_ID = 'dag_for_testing_log_endpoint'
    TASK_ID = 'task_for_testing_log_endpoint'
    TRY_NUMBER = 1
    default_time = "2020-06-10T20:00:00+00:00"
    @pytest.fixture(autouse=True)
    def setup_attrs(self, configured_app, configure_loggers) -> None:  
        self.app = configured_app
        self.client = self.app.test_client()
        
        self.old_modules = dict(sys.modules)
        self._prepare_db()
    def _create_dagrun(self, session):
        dagrun_model = DagRun(
            dag_id=self.DAG_ID,
            run_id='TEST_DAG_RUN_ID',
            run_type=DagRunType.MANUAL,
            execution_date=timezone.parse(self.default_time),
            start_date=timezone.parse(self.default_time),
            external_trigger=True,
        )
        session.add(dagrun_model)
        session.commit()
    @pytest.fixture
    def configure_loggers(self, tmp_path):