airflow.executors.local_executor
¶
LocalExecutor
See also
For more information on how the LocalExecutor works, take a look at the guide: Local Executor
Module Contents¶
Classes¶
LocalWorkerBase implementation to run airflow commands. Executes the given |
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Local worker that executes the task. |
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LocalWorker implementation that is waiting for tasks from a queue and will |
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LocalExecutor executes tasks locally in parallel. |
Attributes¶
- class airflow.executors.local_executor.LocalWorkerBase(result_queue)[source]¶
Bases:
multiprocessing.Process
,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.
- Parameters
result_queue (Queue[TaskInstanceStateType]) -- the queue to store result state
- execute_work(self, key, command)[source]¶
Executes command received and stores result state in queue.
- Parameters
key (airflow.models.taskinstance.TaskInstanceKey) -- the key to identify the task instance
command (airflow.executors.base_executor.CommandType) -- the command to execute
- class airflow.executors.local_executor.LocalWorker(result_queue, key, command)[source]¶
Bases:
LocalWorkerBase
Local worker that executes the task.
- Parameters
result_queue (Queue[TaskInstanceStateType]) -- queue where results of the tasks are put.
key (airflow.models.taskinstance.TaskInstanceKey) -- key identifying task instance
command (airflow.executors.base_executor.CommandType) -- Command to execute
- class airflow.executors.local_executor.QueuedLocalWorker(task_queue, result_queue)[source]¶
Bases:
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.
- Parameters
task_queue (Queue[ExecutorWorkType]) -- queue from which worker reads tasks
result_queue (Queue[TaskInstanceStateType]) -- queue where worker puts results after finishing tasks
- class airflow.executors.local_executor.LocalExecutor(parallelism=PARALLELISM)[source]¶
Bases:
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.
- Parameters
parallelism (int) -- how many parallel processes are run in the executor
- class UnlimitedParallelism(executor)[source]¶
Implements LocalExecutor with unlimited parallelism, starting one process per each command to execute.
- Parameters
executor (LocalExecutor) -- the executor instance to implement.
- execute_async(self, key, command, queue=None, executor_config=None)[source]¶
Executes task asynchronously.
- Parameters
key (airflow.models.taskinstance.TaskInstanceKey) -- the key to identify the task instance
command (airflow.executors.base_executor.CommandType) -- the command to execute
queue (Optional[str]) -- Name of the queue
executor_config (Optional[Any]) -- configuration for the executor
- class LimitedParallelism(executor)[source]¶
Implements LocalExecutor with limited parallelism using a task queue to coordinate work distribution.
- Parameters
executor (LocalExecutor) -- the executor instance to implement.
- execute_async(self, key, command, queue=None, executor_config=None)[source]¶
Executes task asynchronously.
- Parameters
key (airflow.models.taskinstance.TaskInstanceKey) -- the key to identify the task instance
command (airflow.executors.base_executor.CommandType) -- the command to execute
queue (Optional[str]) -- name of the queue
executor_config (Optional[Any]) -- configuration for the executor