docs-archive/apache-airflow/2.0.0/apache-airflow/stable/_sources/executor/debug.rst.txt

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.. _executor:DebugExecutor:

Debug Executor
==================

The :class:`~airflow.executors.debug_executor.DebugExecutor` is meant as
a debug tool and can be used from IDE. It is a single process executor that
queues :class:`~airflow.models.taskinstance.TaskInstance` and executes them by running
``_run_raw_task`` method.

Due to its nature the executor can be used with SQLite database. When used
with sensors the executor will change sensor mode to ``reschedule`` to avoid
blocking the execution of DAG.

Additionally ``DebugExecutor`` can be used in a fail-fast mode that will make
all other running or scheduled tasks fail immediately. To enable this option set
``AIRFLOW__DEBUG__FAIL_FAST=True`` or adjust ``fail_fast`` option in your ``airflow.cfg``.
For more information on setting the configuration, see :doc:`../howto/set-config`.

**IDE setup steps:**

1. Add ``main`` block at the end of your DAG file to make it runnable.
It will run a backfill job:

.. code-block:: python

  if __name__ == '__main__':
    from airflow.utils.state import State
    dag.clear(dag_run_state=State.NONE)
    dag.run()


2. Setup ``AIRFLOW__CORE__EXECUTOR=DebugExecutor`` in run configuration of your IDE. In
   this step you should also setup all environment variables required by your DAG.

3. Run / debug the DAG file.