airflow.timetables.datasets

Module Contents

Classes

DatasetOrTimeSchedule

Combine time-based scheduling with event-based scheduling.
class airflow.timetables.datasets.DatasetOrTimeSchedule(*, timetable, datasets)[source]

Bases: airflow.timetables.simple.DatasetTriggeredTimetable

Combine time-based scheduling with event-based scheduling.

property summary: str[source]

A short summary for the timetable.

This is used to display the timetable in the web UI. A cron expression timetable, for example, can use this to display the expression. The default implementation returns the timetable’s type name.

classmethod deserialize(data)[source]

Deserialize a timetable from data.

This is called when a serialized DAG is deserialized. data will be whatever was returned by serialize during DAG serialization. The default implementation constructs the timetable without any arguments.

serialize()[source]

Serialize the timetable for JSON encoding.

This is called during DAG serialization to store timetable information in the database. This should return a JSON-serializable dict that will be fed into deserialize when the DAG is deserialized. The default implementation returns an empty dict.

validate()[source]

Validate the timetable is correctly specified.

Override this method to provide run-time validation raised when a DAG is put into a dagbag. The default implementation does nothing.

Raises

AirflowTimetableInvalid on validation failure.

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_after would be when the user triggers the run. The default implementation raises NotImplementedError.

next_dagrun_info(*, last_automated_data_interval, restriction)[source]

Provide information to schedule the next DagRun.

The default implementation raises NotImplementedError.

Parameters
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

airflow.timetables.base.DagRunInfo | None

generate_run_id(*, run_type, **kwargs)[source]

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