Created
July 14, 2018 08:41
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DAG dynamically generating tasks
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from airflow import DAG | |
from airflow.operators.bash_operator import BashOperator | |
from datetime import datetime, timedelta | |
default_args = { | |
'owner': 'airflow', | |
'depends_on_past': False, | |
'start_date': datetime(2018,10,1), | |
'email': ['robinlinacre@hotmail.com'], | |
'email_on_failure': False, | |
'email_on_retry': False, | |
'retries': 10, | |
'retry_delay': timedelta(minutes=0.1) | |
} | |
dag = DAG('dynamic_task_number_test', default_args=default_args,schedule_interval=None) | |
import random | |
t1 = BashOperator( | |
task_id='print_date_1', | |
bash_command='date', | |
dag = dag | |
) | |
number_tasks = random.choice([1,2,3,4,5,6]) | |
final = BashOperator( | |
task_id='final', | |
bash_command='date', | |
dag = dag | |
) | |
for i in range(number_tasks): | |
task = BashOperator( | |
task_id= f'ls_{i}', | |
bash_command='ls', | |
retries=3, | |
dag=dag) | |
t1 >> task | |
final << task | |
# This seems to fail because the DAG gets changed whilst it is running. Airflow gets confused about whether upstream dependencies have been met | |
# because some get deleted and some get created during the run |
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