### Body

Currently `start_date` is mandatory parameter.
For DAGs with `schedule=None` we can relax this requirement as no scheduling calculation needed so the `start_date` parameter isn't used.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"""Asserts that logging occurs as expected"""
        with mock.patch.object(self.OPERATOR.log, "info") as mock_log_info:
            self.OPERATOR.execute_complete(
                context=context,
                event={"status": "success", "message": "Job completed", "matches": [TEST_OBJECT]},
            )
        mock_log_info.assert_called_with("Resuming from trigger and checking status")
class TestGCSUploadSessionCompleteSensor:
    def setup_method(self):
        self.dag = DAG(
            TEST_DAG_ID + "test_schedule_dag_once",
            schedule="@once",
            start_date=DEFAULT_DATE,
        )
        self.sensor = GCSUploadSessionCompleteSensor(
            task_id="sensor_1",
            bucket="test-bucket",
            prefix="test-prefix/path",
            inactivity_period=12,
            poke_interval=10,
            min_objects=1,
            allow_delete=False,
            google_cloud_conn_id=TEST_GCP_CONN_ID,
            impersonation_chain=TEST_IMPERSONATION_CHAIN,
            dag=self.dag,
        )
        self.last_mocked_date = datetime(2019, 4, 24, 0, 0, 0)
    @mock.patch("airflow.providers.google.cloud.sensors.gcs.GCSHook")
    def test_get_gcs_hook(self, mock_hook):