I have setup airflow and am running a DAG using the following vscode debug configuration:
{
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": false,
"env":{
"AIRFLOW__CORE__EXECUTOR": "DebugExecutor",
"AIRFLOW__DEBUG__FAIL_FAST": "True",
"LC_ALL": "en_US.UTF-8",
"LANG": "en_US.UTF-8"
}
}
]
}
It runs the file, my breakpoints DAG defs break as expected, then at the end of the file: It executes the dag.run() and then I wait forever for the dag to backfill, and my breakpoints within python_callable functions of tasks never break.
What airflow secret am I not seeing?
Here is my dag:
# scheduled to run every minute, poke for a new file every ten seconds
dag = DAG(
dag_id='download-from-s3',
start_date=days_ago(2),
catchup=False,
schedule_interval='*/1 * * * *',
is_paused_upon_creation=False
)
def new_file_detection(**context):
print("File found...") # a breakpoint here never lands
pprint(context)
init = BashOperator(
task_id='init',
bash_command='echo "My DAG initiated at $(date)"',
dag=dag,
)
file_sensor = S3KeySensor(
task_id='file_sensor',
poke_interval=10, # every 10 seconds
timeout=60,
bucket_key="s3://inbox/new/*",
bucket_name=None,
wildcard_match=True,
soft_fail=True,
dag=dag
)
file_found_message = PythonOperator(
task_id='file_found_message',
provide_context=True,
python_callable=new_file_detection,
dag=dag
)
init >> file_sensor >> file_found_message
if __name__ == '__main__':
dag.clear(reset_dag_runs=True)
dag.run() #this triggers a backfill job