:py:mod:`airflow.executors.local_executor`
==========================================

.. py:module:: airflow.executors.local_executor

.. autoapi-nested-parse::

   LocalExecutor

   .. seealso::
       For more information on how the LocalExecutor works, take a look at the guide:
       :ref:`executor:LocalExecutor`


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   airflow.executors.local_executor.LocalWorkerBase
   airflow.executors.local_executor.LocalWorker
   airflow.executors.local_executor.QueuedLocalWorker
   airflow.executors.local_executor.LocalExecutor


Attributes
~~~~~~~~~~

.. autoapisummary::

   airflow.executors.local_executor.ExecutorWorkType


.. py:data:: ExecutorWorkType
   

.. py:class:: LocalWorkerBase(result_queue)

   Bases: :py:obj:`multiprocessing.Process`, :py:obj:`airflow.utils.log.logging_mixin.LoggingMixin`

   LocalWorkerBase implementation to run airflow commands. Executes the given
   command and puts the result into a result queue when done, terminating execution.

   :param result_queue: the queue to store result state

   .. py:method:: run()

      Method to be run in sub-process; can be overridden in sub-class


   .. py:method:: execute_work(key, command)

      Executes command received and stores result state in queue.

      :param key: the key to identify the task instance
      :param command: the command to execute


   .. py:method:: do_work()
      :abstractmethod:

      Called in the subprocess and should then execute tasks


.. py:class:: LocalWorker(result_queue, key, command)

   Bases: :py:obj:`LocalWorkerBase`

   Local worker that executes the task.

   :param result_queue: queue where results of the tasks are put.
   :param key: key identifying task instance
   :param command: Command to execute

   .. py:method:: do_work()

      Called in the subprocess and should then execute tasks


.. py:class:: QueuedLocalWorker(task_queue, result_queue)

   Bases: :py:obj:`LocalWorkerBase`

   LocalWorker implementation that is waiting for tasks from a queue and will
   continue executing commands as they become available in the queue.
   It will terminate execution once the poison token is found.

   :param task_queue: queue from which worker reads tasks
   :param result_queue: queue where worker puts results after finishing tasks

   .. py:method:: do_work()

      Called in the subprocess and should then execute tasks


.. py:class:: LocalExecutor(parallelism = PARALLELISM)

   Bases: :py:obj:`airflow.executors.base_executor.BaseExecutor`

   LocalExecutor executes tasks locally in parallel.
   It uses the multiprocessing Python library and queues to parallelize the execution
   of tasks.

   :param parallelism: how many parallel processes are run in the executor

   .. py:class:: UnlimitedParallelism(executor)

      Implements LocalExecutor with unlimited parallelism, starting one process
      per each command to execute.

      :param executor: the executor instance to implement.

      .. py:method:: start()

         Starts the executor.


      .. py:method:: execute_async(key, command, queue = None, executor_config = None)

         Executes task asynchronously.

         :param key: the key to identify the task instance
         :param command: the command to execute
         :param queue: Name of the queue
         :param executor_config: configuration for the executor


      .. py:method:: sync()

         Sync will get called periodically by the heartbeat method.


      .. py:method:: end()

         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.


   .. py:class:: LimitedParallelism(executor)

      Implements LocalExecutor with limited parallelism using a task queue to
      coordinate work distribution.

      :param executor: the executor instance to implement.

      .. py:method:: start()

         Starts limited parallelism implementation.


      .. py:method:: execute_async(key, command, queue = None, executor_config = None)

         Executes task asynchronously.

         :param key: the key to identify the task instance
         :param command: the command to execute
         :param queue: name of the queue
         :param executor_config: configuration for the executor


      .. py:method:: sync()

         Sync will get called periodically by the heartbeat method.


      .. py:method:: end()

         Ends the executor. Sends the poison pill to all workers.


   .. py:method:: start()

      Starts the executor


   .. py:method:: execute_async(key, command, queue = None, executor_config = None)

      Execute asynchronously.


   .. py:method:: sync()

      Sync will get called periodically by the heartbeat method.


   .. py:method:: end()

      Ends the executor.
      :return:


   .. py:method:: terminate()

      Terminate the executor is not doing anything.