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Repovive

Writing Production DAGs - Python for Data Engineering | Data Engineer Interview Prep | Repovive

Repovive.

Data Engineer Interview Prep16 sections · 140 units8h total

Open in Course

Writing Production DAGs

Airflow Python patterns

Production DAGs follow patterns:

from airflow.decorators import dag, task
from datetime import datetime

@dag(schedule='@daily', start_date=datetime(2024, 1, 1), catchup=False)
def daily_pipeline():
    
    @task
    def extract():
        # Fetch data from source
        return data
    
    @task
    def transform(raw_data):
        # Clean and transform
        return cleaned
    
    @task
    def load(transformed):
        # Write to destination
        pass
    
    load(transform(extract()))

daily_pipeline()

Use TaskFlow API (decorators) for cleaner code. Keep business logic in separate modules. Make tasks idempotent.