old_contents: # -*- 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
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  
  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 10 sleeping tasks, sleeping from 0 to 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]
  
new_contents: # -*- 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
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  
  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]
  
subject: Fix inconsistent comment in example_python_operator.py (#4337)