Example of dbt scheduling with Airflow

dbt_dag.py

# How to schedule dbt runs with Airflow using gocardless/airflow-dbt

# Folder structure is as such:
#
# /app
#   /airflow
#     /dags
#       /dbt_dag.py
#   /dbt
#     /config
#       /profiles.yml
#     /models
#       /web
#         /traffic.py

from airflow import DAG
from airflow_dbt.operators.dbt_operator import DbtRunOperator

default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': '2020-01-01',
    'email': ['email@example.com'],
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
    'dbt_dir': dbt_path
}

dbt_path = dbt_path = os.environ['DBT_PATH']  # /app/dbt

# Use a cron schedule in `schedule_interval`, here it will run every 20 minutes
dag = DAG(dag_id='update_models', default_args=default_args, schedule_interval='*/20 * * * *', catchup=False)

# DbtRunOperator from gocardless/airflow-dbt
# This will run the /app/dbt/models/web/traffic.py dbt model
dbt_run = DbtRunOperator(
  task_id='dbt_update_models',
  profiles_dir=dbt_path + '/config', # The folder where is profiles.yml (/app/dbt/config)
  dir=dbt_path,
  queue='airflow_queue_1',
  models='web.traffic',
  dag=dag
)

# Airflow dependency graph (with a single task here)
dbt_run