Apache Airflow is an open-source platform designed to programmatically author, schedule, and monitor workflows. It utilizes directed acyclic graphs (DAGs) to manage and organize tasks. The “dag report” command is one of the many commands provided by Airflow’s CLI to help users manage and get insights into their DAGs. In this article, we’ll dive deep into the “dag report” command, providing examples and explanations.
What is the “dag report” Command?
The “dag report” command provides users with a report of their DAGs in terms of task dependencies and metadata. It’s essentially a way to quickly visualize the structure of your DAG without having to go through the web interface.
How to Use the “dag report” Command:
The general syntax for the “dag report” command is:
airflow dags report <DAG_ID>
Where <DAG_ID> is the identifier of your DAG.
Example:
Consider a simple DAG named freshers_in_example_dag:
from datetime import datetime
from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator
default_args = {
'owner': 'airflow',
'start_date': datetime(2023, 1, 1)
}
dag = DAG('freshers_in_example_dag',
default_args=default_args,
description='A simple tutorial DAG',
schedule_interval='@daily',
catchup=False)
start = DummyOperator(task_id='start_task', dag=dag)
end = DummyOperator(task_id='end_task', dag=dag)
start >> end
For this DAG, you can generate a report by running:
airflow dags report freshers_in_example_dag
1. DAG ID
2. Owner
3. Start Date
4. Schedule Interval
5. Number of tasks
6. List of tasks with their upstream and downstream dependencies
Reading the Report:
The report offers a textual representation of the DAG, making it easier to understand dependencies without having to look at the code or the web interface. For our simple freshers_in_example_dag, the report will show that start_task is the initial task, followed by end_task, with no intermediate dependencies.
Why Use the “dag report” Command?
1. Quick Overview: If you have multiple DAGs or complex DAGs with many tasks, the “dag report” command can provide a fast summary of the DAG structure.
2. Dependency Check: Easily see which tasks depend on others without navigating the web interface or reviewing the DAG code.
3. Troubleshooting: If a DAG is failing or behaving unexpectedly, the “dag report” can help identify structural or dependency issues.
4. Documentation: For larger teams, the report can be used to document the DAG structure and dependencies.
