airflow DummyOperator

Airflow DummyOperator tutorial with examples in 2023

In this blog, we will learn about the airflow DummyOperator.So let’s get started:

What is DummyOperator in Airflow?

airflow_DummyOperator

The DummyOperator in airflow is a simple operator that does nothing and is typically used as a placeholder in a DAG. It can be useful when you need to add an operator to a DAG for organizational purposes

How to import the airflow DummyOperator

The DummyOperator is defined in the airflow.operators.dummy_operator module and can be imported by typing the below command

from airflow.operators.dummy_operator import DummyOperator

Airflow DummyOperator arguments

DummyOperator in airflow is very simple to use. Below are the few arguments supported by DummyOperator:

  • task_id(Mandatory): a unique identifier for the task.
  • dag(Mandatory): the DAG object to which the task belongs.
  • owner(optional): the owner of the task.
  • email_on_retry (optional): if True, an email will be sent to the task’s owner whenever the task is retried after a failure.
  • start_date (optional): the date and time at which the task should start running.
  • retries (optional): the number of times the task should be retried in case of failure.
  • retry_delay (optional): the amount of time to wait between retries.

Airflow DummyOperator example

Below is a simple example of airflow DummyOperator

from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator
from datetime import datetime

my_dag = DAG(
    dag_id='dummyoperator_dag',
    start_date=datetime(2022, 2, 21),
    schedule_interval='@daily'
)

dummy_task = DummyOperator(
    task_id='dummy_task',
    dag=my_dag
)

The DAG is named “dummyoperator_dag” and has a start date of February 21, 2022. The schedule interval for the DAG is set to run daily using the @daily cron expression.

The DummyOperator is named “dummy_task” and is added to the DAG. This operator does not perform any actual work and is used to represent a task that needs to be completed before other tasks in the DAG can run.

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