old_contents: # Copyright 2018 Google LLC
  #
  # Licensed 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
  #
  #     https://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.
  
  """An example DAG demonstrating simple Apache Airflow operators."""
  
  # [START composer_simple]
  from __future__ import print_function
  
  # [START composer_simple_define_dag]
  import datetime
  
  from airflow import models
  # [END composer_simple_define_dag]
  # [START composer_simple_operators]
  from airflow.operators import bash_operator
  from airflow.operators import python_operator
  # [END composer_simple_operators]
  
  
  # [START composer_simple_define_dag]
  default_dag_args = {
      # The start_date describes when a DAG is valid / can be run. Set this to a
      # fixed point in time rather than dynamically, since it is evaluated every
      # time a DAG is parsed. See:
      # https://airflow.apache.org/faq.html#what-s-the-deal-with-start-date
      'start_date': datetime.datetime(2018, 1, 1),
  }
  
  # Define a DAG (directed acyclic graph) of tasks.
  # Any task you create within the context manager is automatically added to the
  # DAG object.
  with models.DAG(
          'composer_sample_simple_greeting',
          schedule_interval=datetime.timedelta(days=1),
          default_args=default_dag_args) as dag:
      # [END composer_simple_define_dag]
      # [START composer_simple_operators]
      def greeting():
          print('Hello World!')
  
      # An instance of an operator is called a task. In this case, the
      # hello_python task calls the "greeting" Python function.
      hello_python = python_operator.PythonOperator(
          task_id='hello',
          python_callable=greeting)
  
      # Likewise, the goodbye_bash task calls a Bash script.
      goodbye_bash = bash_operator.BashOperator(
          task_id='bye',
          bash_command='echo Goodbye.')
      # [END composer_simple_operators]
  
      # [START composer_simple_relationships]
      # Define the order in which the tasks complete by using the >> and <<
      # operators. In this example, hello_python executes before goodbye_bash.
      hello_python >> goodbye_bash
      # [END composer_simple_relationships]
  # [END composer_simple]
  
new_contents: # Copyright 2018 Google LLC
  #
  # Licensed 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
  #
  #     https://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.
  
  """An example DAG demonstrating simple Apache Airflow operators."""
  
  # [START composer_simple]
  from __future__ import print_function
  
  # [START composer_simple_define_dag]
  import datetime
  
  from airflow import models
  # [END composer_simple_define_dag]
  # [START composer_simple_operators]
  from airflow.operators import bash_operator
  from airflow.operators import python_operator
  # [END composer_simple_operators]
  
  
  # [START composer_simple_define_dag]
  default_dag_args = {
      # The start_date describes when a DAG is valid / can be run. Set this to a
      # fixed point in time rather than dynamically, since it is evaluated every
      # time a DAG is parsed. See:
      # https://airflow.apache.org/faq.html#what-s-the-deal-with-start-date
      'start_date': datetime.datetime(2018, 1, 1),
  }
  
  # Define a DAG (directed acyclic graph) of tasks.
  # Any task you create within the context manager is automatically added to the
  # DAG object.
  with models.DAG(
          'composer_sample_simple_greeting',
          schedule_interval=datetime.timedelta(days=1),
          default_args=default_dag_args) as dag:
      # [END composer_simple_define_dag]
      # [START composer_simple_operators]
      def greeting():
          import logging
          logging.info('Hello World!')
  
      # An instance of an operator is called a task. In this case, the
      # hello_python task calls the "greeting" Python function.
      hello_python = python_operator.PythonOperator(
          task_id='hello',
          python_callable=greeting)
  
      # Likewise, the goodbye_bash task calls a Bash script.
      goodbye_bash = bash_operator.BashOperator(
          task_id='bye',
          bash_command='echo Goodbye.')
      # [END composer_simple_operators]
  
      # [START composer_simple_relationships]
      # Define the order in which the tasks complete by using the >> and <<
      # operators. In this example, hello_python executes before goodbye_bash.
      hello_python >> goodbye_bash
      # [END composer_simple_relationships]
  # [END composer_simple]
  
subject: Use logging on the PythonOperator in simple.py (#1663)