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AIP-39: Handle DAG scheduling with timetables (#15397)
This creates a new subpackage airflow.timetables, and implements timetable constructs that provides DAG scheduling logic. The timetable classes are used to refactor schedule inference logic out of the DAG class, and existing functions related to scheduling are refactored to use timetables (and deprecated). Usages of the deprecated DAG functions in Airflow's code base are modified to either use the timetable, or infer the information by other means. For example, usages of previous_schedule() (what was a DAG last scheduled to run before this run?) are refactored to query the database when the previous scheduled run actually happened, instead of using the schedule interval (cron or timedelta) in infer the information. This is because an AIP-39 timetable does not necessarily run on a periodic-ish schedule, and we cannot reliably infer when the previous run happened.
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
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# This stub exists to work around false linter errors due to python/mypy#10408. | ||
# TODO: Remove this file after the upstream fix is available in our toolchain. | ||
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from typing import Callable, TypeVar | ||
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T = TypeVar("T") | ||
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def cached_property(f: Callable[..., T]) -> T: ... | ||
def cache(f: T) -> T: ... |
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