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Adding retries

You've noticed that one particular Dag is failing often on a task that extracts data from a given source. Frustratingly, running the task a few minutes later seems to remedy the problem. After learning about the retry functionality in Airflow Dags, you decide to implement retries on this task to keep from restarting it manually.

The dag, task, and timedelta are already imported for you.

Diese Übung ist Teil des Kurses

Einführung in Apache Airflow mit Python

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Anleitung zur Übung

  • Set the extract_data task to retry 3 times before failing.
  • Add a delay of 10 minutes between retries on the extract_data task.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

@dag(schedule="@daily", start_date=datetime(2026, 5, 1))
def etl_pipeline():

  # Set retries and retry delay on extract_data
  @task(____=3, ____=____(minutes=10))
  def extract_data():
    print("Extracting data from source...")
  
  @task()
  def process_source_data():
    print("Now processing data...")

  extract_data() >> process_source_data()
  
etl_pipeline()
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