Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
| Principle | Description |
|---|---|
| Idempotent | Running twice produces same result |
| Atomic | Tasks succeed or fail completely |
| Incremental | Process only new/changed data |
| Observable | Logs, metrics, alerts at every step |
# Linear
task1 >> task2 >> task3
# Fan-out
task1 >> [task2, task3, task4]
# Fan-in
[task1, task2, task3] >> task4
# Complex
task1 >> task2 >> task4
task1 >> task3 >> task4
# dags/example_dag.py
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.operators.empty import EmptyOperator
default_args = {
'owner': 'data-team',
'depends_on_past': False,
'email_on_failure': True,
'email_on_retry': False,
'retries': 3,
'retry_delay': timedelta(minutes=5),
'retry_exponential_backoff': True,
'max_retry_delay': timedelta(hours=1),
}
with DAG(
dag_id='example_etl',
default_args=default_args,
description='Example ETL pipeline',
schedule='0 6 * * *', # Daily at 6 AM
start_date=datetime(2024, 1, 1),
catchup=False,
tags=['etl', 'example'],
max_active_runs=1,
) as dag:
start = EmptyOperator(task_id='start')
def extract_data(**context):
execution_date = context['ds']
# Extract logic here
return {'records': 1000}
extract = PythonOperator(
task_id='extract',
python_callable=extract_data,
)
end = EmptyOperator(task_id='end')
start >> extract >> end
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
mode='reschedule' - For sensors, free up workersdepends_on_past=True - Creates bottlenecks{{ ds }} macros
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Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).