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:mod:`airflow.executors.base_executor`
======================================
.. py:module:: airflow.executors.base_executor
.. autoapi-nested-parse::
Base executor - this is the base class for all the implemented executors.
Module Contents
---------------
.. data:: PARALLELISM
:annotation: :int
.. data:: NOT_STARTED_MESSAGE
:annotation: = The executor should be started first!
.. data:: CommandType
.. data:: QueuedTaskInstanceType
.. data:: EventBufferValueType
.. py:class:: BaseExecutor(parallelism: int = PARALLELISM)
Bases: :class:`airflow.utils.log.logging_mixin.LoggingMixin`
Class to derive in order to interface with executor-type systems
like Celery, Kubernetes, Local, Sequential and the likes.
:param parallelism: how many jobs should run at one time. Set to
``0`` for infinity
.. attribute:: job_id
:annotation: :Optional[str]
.. attribute:: slots_available
Number of new tasks this executor instance can accept
.. method:: start(self)
Executors may need to get things started.
.. method:: queue_command(self, task_instance: TaskInstance, command: CommandType, priority: int = 1, queue: Optional[str] = None)
Queues command to task
.. method:: queue_task_instance(self, task_instance: TaskInstance, mark_success: bool = False, pickle_id: Optional[str] = None, ignore_all_deps: bool = False, ignore_depends_on_past: bool = False, ignore_task_deps: bool = False, ignore_ti_state: bool = False, pool: Optional[str] = None, cfg_path: Optional[str] = None)
Queues task instance.
.. method:: has_task(self, task_instance: TaskInstance)
Checks if a task is either queued or running in this executor.
:param task_instance: TaskInstance
:return: True if the task is known to this executor
.. method:: sync(self)
Sync will get called periodically by the heartbeat method.
Executors should override this to perform gather statuses.
.. method:: heartbeat(self)
Heartbeat sent to trigger new jobs.
.. method:: order_queued_tasks_by_priority(self)
Orders the queued tasks by priority.
:return: List of tuples from the queued_tasks according to the priority.
.. method:: trigger_tasks(self, open_slots: int)
Triggers tasks
:param open_slots: Number of open slots
.. method:: change_state(self, key: TaskInstanceKey, state: str, info=None)
Changes state of the task.
:param info: Executor information for the task instance
:param key: Unique key for the task instance
:param state: State to set for the task.
.. method:: fail(self, key: TaskInstanceKey, info=None)
Set fail state for the event.
:param info: Executor information for the task instance
:param key: Unique key for the task instance
.. method:: success(self, key: TaskInstanceKey, info=None)
Set success state for the event.
:param info: Executor information for the task instance
:param key: Unique key for the task instance
.. method:: get_event_buffer(self, dag_ids=None)
Returns and flush the event buffer. In case dag_ids is specified
it will only return and flush events for the given dag_ids. Otherwise
it returns and flushes all events.
:param dag_ids: to dag_ids to return events for, if None returns all
:return: a dict of events
.. method:: execute_async(self, key: TaskInstanceKey, command: CommandType, queue: Optional[str] = None, executor_config: Optional[Any] = None)
This method will execute the command asynchronously.
:param key: Unique key for the task instance
:param command: Command to run
:param queue: name of the queue
:param executor_config: Configuration passed to the executor.
.. method:: end(self)
This method is called when the caller is done submitting job and
wants to wait synchronously for the job submitted previously to be
all done.
.. method:: terminate(self)
This method is called when the daemon receives a SIGTERM
.. method:: try_adopt_task_instances(self, tis: List[TaskInstance])
Try to adopt running task instances that have been abandoned by a SchedulerJob dying.
Anything that is not adopted will be cleared by the scheduler (and then become eligible for
re-scheduling)
:return: any TaskInstances that were unable to be adopted
:rtype: list[airflow.models.TaskInstance]
.. staticmethod:: validate_command(command: List[str])
Check if the command to execute is airflow command
.. method:: debug_dump(self)
Called in response to SIGUSR2 by the scheduler