example for GA meeting

README.md

@@ -4,7 +4,7 @@ eFlows4HPC Data Logistics Service
 
 
 ```
-mkdir ./logs
+mkdir ./logs ./tmp
 echo -e "AIRFLOW_UID=$(id -u)" > .env
 reqs=`cat requirements.txt | tr '\n' ' '`
 echo "_PIP_ADDITIONAL_REQUIREMENTS=$reqs" >> .env

dags/GAdemo.py

+from datetime import timedelta
+
+from airflow import DAG
+from airflow.operators.bash import BashOperator
+from airflow.utils.dates import days_ago
+from airflow.sensors.filesystem import FileSensor
+from airflow.operators.python import PythonOperator
+from airflow.operators.dummy import DummyOperator
+
+def_args = {
+    'owner': 'airflow',
+    'depends_on_past': False,
+    'email_on_failure': False,
+    'email_on_retry': False,
+    'retries': 1,
+    'retry_delay': timedelta(minutes=5)
+
+}
+
+def train_model():
+    print('Will start model training')
+
+with DAG('GAtest', default_args=def_args, description='testing GA', schedule_interval=timedelta(days=1), start_date=days_ago(2)) as dag:
+    s1 = FileSensor(task_id='file_sensor', filepath='/work/afile.txt')
+    t1 = BashOperator(task_id='move_data', bash_command='date')
+    t2 = PythonOperator(task_id='train_model', python_callable=train_model)
+    t3 = BashOperator(task_id='eval_model', bash_command='echo "evaluating"')
+    t4 = DummyOperator(task_id='upload_model_to_repo')
+    t5 = DummyOperator(task_id='publish_results')
+    
+    s1 >> t1 >> t2 >> t4 
+    t2 >> t3 >> t5