def infer_manual_data_interval(self, *, run_after: DateTime) -> DataInterval:
# If Timetable not restricted to events, run for the time specified
if not self.restrict_to_events:
return DataInterval.exact(run_after)
# If restricted to events, run for the most recent past event
# or for the first event if all events are in the future
if run_after < self.event_dates[0]:
return DataInterval.exact(self.event_dates[0])
else:
past_events = itertools.dropwhile(lambda when: when > run_after, self.event_dates[::-1])
most_recent_event = next(past_events)
return DataInterval.exact(most_recent_event)
def infer_manual_data_interval(self, *,
run_after: DateTime) -> DataInterval:
# Get the last complete period before run_after, e.g. if a DAG run is
# scheduled at each midnight, the data interval of a manually triggered
# run at 1am 25th is between 0am 24th and 0am 25th.
end = self._get_prev(self._align(run_after))
return DataInterval(start=self._get_prev(end), end=end)
def infer_data_interval(self, run_after: DateTime) -> DataInterval:
weekday = run_after.weekday()
if weekday in (0, 6): # Monday and Sunday -- interval is last Friday.
days_since_friday = (run_after.weekday() - 4) % 7
delta = timedelta(days=days_since_friday)
else: # Otherwise the interval is yesterday.
delta = timedelta(days=1)
start = DateTime.combine((run_after - delta).date(), Time.min).replace(tzinfo=UTC)
return DataInterval(start=start, end=(start + timedelta(days=1)))
def infer_manual_data_interval(self, run_after: DateTime) -> DataInterval:
return DataInterval(start=self._get_prev(run_after), end=run_after)
def infer_manual_data_interval(self, *,
run_after: DateTime) -> DataInterval:
return DataInterval(run_after - self._interval, run_after)
def infer_data_interval(self, *, run_after: DateTime) -> DataInterval:
return DataInterval.exact(run_after)
def infer_data_interval(self, run_after: DateTime) -> DataInterval:
return DataInterval(start=self._schedule.get_prev(run_after),
end=run_after)