# -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
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from __future__ import print_function
import time
from builtins import range
from pprint import pprint
import airflow
from airflow.models import DAG
from airflow.operators.python_operator import PythonOperator
args = {
'owner': 'airflow',
'start_date': airflow.utils.dates.days_ago(2),
}
dag = DAG(
dag_id='example_python_operator',
default_args=args,
schedule_interval=None,
)
# [START howto_operator_python]
def print_context(ds, **kwargs):
pprint(kwargs)
print(ds)
return 'Whatever you return gets printed in the logs'
run_this = PythonOperator(
task_id='print_the_context',
provide_context=True,
python_callable=print_context,
dag=dag,
)
# [END howto_operator_python]
# [START howto_operator_python_kwargs]
def my_sleeping_function(random_base):
"""This is a function that will run within the DAG execution"""
time.sleep(random_base)
# Generate 5 sleeping tasks, sleeping from 0.0 to 0.4 seconds respectively
for i in range(5):
task = PythonOperator(
task_id='sleep_for_' + str(i),
python_callable=my_sleeping_function,
op_kwargs={'random_base': float(i) / 10},
dag=dag,
)
run_this >> task
# [END howto_operator_python_kwargs]