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.
  
  """Example DAG demonstrating the usage of the PythonOperator."""
  
  import time
  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):
      """Print the Airflow context and ds variable from the context."""
      pprint(kwargs)
      print(ds)
      return 'Whatever you return gets printed in the logs'
  
  
  run_this = PythonOperator(
      task_id='print_the_context',
      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]
  
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.
  
  """Example DAG demonstrating the usage of the PythonOperator."""
  
  import time
  from pprint import pprint
  
  import airflow
  from airflow.models import DAG
  from airflow.operators.python_operator import PythonOperator, PythonVirtualenvOperator
  
  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):
      """Print the Airflow context and ds variable from the context."""
      pprint(kwargs)
      print(ds)
      return 'Whatever you return gets printed in the logs'
  
  
  run_this = PythonOperator(
      task_id='print_the_context',
      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]
  
  
  def callable_virtualenv():
      """
      Example function that will be performed in a virtual environment.
  
      Importing at the module level ensures that it will not attempt to import the
      library before it is installed.
      """
      from colorama import Fore, Back, Style
      from time import sleep
      print(Fore.RED + 'some red text')
      print(Back.GREEN + 'and with a green background')
      print(Style.DIM + 'and in dim text')
      print(Style.RESET_ALL)
      for _ in range(10):
          print(Style.DIM + 'Please wait...', flush=True)
          sleep(10)
      print('Finished')
  
  
  virtualenv_task = PythonVirtualenvOperator(
      task_id="virtualenv_python",
      python_callable=callable_virtualenv,
      requirements=[
          "colorama==0.4.0"
      ],
      system_site_packages=False,
      dag=dag,
  )
  
subject: Add example for PythonVirtualenvOperator (#6441)