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new 056b8cf396 Document built in Timetables (#23099)
056b8cf396 is described below
commit 056b8cf3969137534f6f78b02166b71dd1b02ac6
Author: Collin McNulty <[email protected]>
AuthorDate: Thu Jun 30 13:56:40 2022 -0500
Document built in Timetables (#23099)
---
docs/apache-airflow/concepts/timetable.rst | 61 ++++++++++++++++++++++++++++++
1 file changed, 61 insertions(+)
diff --git a/docs/apache-airflow/concepts/timetable.rst
b/docs/apache-airflow/concepts/timetable.rst
index 9898204e99..986213df81 100644
--- a/docs/apache-airflow/concepts/timetable.rst
+++ b/docs/apache-airflow/concepts/timetable.rst
@@ -48,3 +48,64 @@ the schedule. Some examples are:
As such, Airflow allows for custom timetables to be written in plugins and
used by
DAGs. An example demonstrating a custom timetable can be found in the
:doc:`/howto/timetable` how-to guide.
+
+Built In Timetables
+-------------------
+
+Airflow comes with several common timetables built in to cover the most common
use cases. Additional timetables
+may be available in plugins.
+
+CronDataIntervalTimetable
+^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Set schedule based on a cron expression. Can be selected by providing a string
that is a valid
+cron expression to the ``schedule_interval`` parameter of a DAG as described
in the :doc:`/concepts/dags` documentation.
+
+.. code-block:: python
+
+ @dag(schedule_interval="0 1 * * 3") # At 01:00 on Wednesday.
+ def example_dag():
+ pass
+
+DeltaDataIntervalTimetable
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Schedules data intervals with a time delta. Can be selected by providing a
+:class:`datetime.timedelta` or ``dateutil.relativedelta.relativedelta`` to the
``schedule_interval`` parameter of a DAG.
+
+.. code-block:: python
+
+ @dag(schedule_interval=datetime.timedelta(minutes=30))
+ def example_dag():
+ pass
+
+EventsTimetable
+^^^^^^^^^^^^^^^
+
+Simply pass a list of ``datetime``\s for the DAG to run after. Useful for
timing based on sporting
+events, planned communication campaigns, and other schedules that are
arbitrary and irregular but predictable.
+
+The list of events must be finite and of reasonable size as it must be loaded
every time the DAG is parsed. Optionally,
+the ``restrict_to_events`` flag can be used to force manual runs of the DAG to
use the time of the most recent (or very
+first) event for the data interval, otherwise manual runs will run with a
``data_interval_start`` and
+``data_interval_end`` equal to the time at which the manual run was begun. You
can also name the set of events using the
+``description`` parameter, which will be displayed in the Airflow UI.
+
+.. code-block:: python
+
+ from airflow.timetables.events import EventsTimetable
+
+
+ @dag(
+ timetable=EventsTimetable(
+ event_dates=[
+ pendulum.datetime(2022, 4, 5, 8, 27, tz="America/Chicago"),
+ pendulum.datetime(2022, 4, 17, 8, 27, tz="America/Chicago"),
+ pendulum.datetime(2022, 4, 22, 20, 50, tz="America/Chicago"),
+ ],
+ description="My Team's Baseball Games",
+ restrict_to_events=False,
+ ),
+ )
+ def example_dag():
+ pass
