### 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.
with_row_locks,
)
from airflow.utils.state import DagRunState, State, TaskInstanceState
from airflow.utils.trigger_rule import TriggerRule
from airflow.utils.types import NOTSET, ArgNotSet, DagRunType, EdgeInfoType
if TYPE_CHECKING:
    from types import ModuleType
    from pendulum.tz.timezone import Timezone
    from sqlalchemy.orm.query import Query
    from sqlalchemy.orm.session import Session
    from airflow.datasets import Dataset
    from airflow.decorators import TaskDecoratorCollection
    from airflow.models.dagbag import DagBag
    from airflow.models.operator import Operator
    from airflow.models.slamiss import SlaMiss
    from airflow.serialization.pydantic.dag import DagModelPydantic
    from airflow.serialization.pydantic.dag_run import DagRunPydantic
    from airflow.typing_compat import Literal
    from airflow.utils.task_group import TaskGroup
log = logging.getLogger(__name__)
DEFAULT_VIEW_PRESETS = ["grid", "graph", "duration", "gantt", "landing_times"]
ORIENTATION_PRESETS = ["LR", "TB", "RL", "BT"]
TAG_MAX_LEN = 100
DagStateChangeCallback = Callable[[Context], None]
ScheduleInterval = Union[None, str, timedelta, relativedelta]
ScheduleIntervalArg = Union[ArgNotSet, ScheduleInterval]
ScheduleArg = Union[ArgNotSet, ScheduleInterval, Timetable, Collection["Dataset"]]
SLAMissCallback = Callable[["DAG", str, str, List["SlaMiss"], List[TaskInstance]], None]
DEFAULT_SCHEDULE_INTERVAL = timedelta(days=1)
class InconsistentDataInterval(AirflowException):