Airflow: TaskGroups

10 Aug, 2025

What problem(s) it solves

Large DAGs with 50+ individual tasks becomes hard to manage, hard to visualize in the UI, and lead to lots of duplication.

If Airflow tasks are like the messy collection of files on your desktop, then TaskGroups are like folders that organize and contain tasks in a particular way.

Implementation

Two main approaches:

@task_group decorator

@task_group(group_id="data_processing")
def process_data():
  task1 = Operator(task_id='foo')
  task2 = Operator(task_id='bar')
  task1 >> task2

process_data() # -> must call the function to create the group!

TaskGroup context manager:

with TaskGroup(group_id="foo") as tg:
  task1 = Operator(task_id='bar')
  task2 = Operator(task_id='baz')
  task1 >> task2

Examples:

Notes

• TaskGroups are on a per-DAG level. You can't group tasks across different DAGs.
• TaskGroups integrate with the TaskFlow API so you can pass data from taskgroup to taskgroup using xcoms

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