airflow.example_dags.plugins.workday
Plugin to demonstrate timetable registration and accommodate example DAGs.
Attributes
Classes
Protocol that all Timetable classes are expected to implement. |
|
Class used to define AirflowPlugin. |
Module Contents
- airflow.example_dags.plugins.workday.log[source]
- class airflow.example_dags.plugins.workday.AfterWorkdayTimetable[source]
Bases:
airflow.timetables.base.TimetableProtocol that all Timetable classes are expected to implement.
- get_next_workday(d, incr=1)[source]
- infer_manual_data_interval(run_after)[source]
When a DAG run is manually triggered, infer a data interval for it.
This is used for e.g. manually-triggered runs, where
run_afterwould be when the user triggers the run. The default implementation raisesNotImplementedError.
- next_dagrun_info(*, last_automated_data_interval, restriction)[source]
Provide information to schedule the next DagRun.
The default implementation raises
NotImplementedError.- Parameters:
last_automated_data_interval (airflow.timetables.base.DataInterval | None) – The data interval of the associated DAG’s last scheduled or backfilled run (manual runs not considered). This is only
Nonewhen the Dag is being scheduled for the first time, which happens when the Dag processor first parses the Dag – before any Dag run exists.restriction (airflow.timetables.base.TimeRestriction) – Restriction to apply when scheduling the DAG run. See documentation of
TimeRestrictionfor details.
- Returns:
Information on when the next DagRun can be scheduled. None means a DagRun will not happen. This does not mean no more runs will be scheduled even again for this DAG; the timetable can return a DagRunInfo object when asked at another time.
- Return type: