potiuk commented on PR #27256:
URL: https://github.com/apache/airflow/pull/27256#issuecomment-1296450404

   Silly mistake. I tested it and yeah :( . Lools cool, but can you also maybe 
add a classic version in example_dag - this way we can easily test it. For 
example my example_python_operator.py is now: 
   
   
   ```
   #
   # 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 TaskFlow API to execute Python 
functions natively and within a
   virtual environment.
   """
   from __future__ import annotations
   
   import logging
   import os
   import shutil
   import sys
   import tempfile
   import time
   from pprint import pprint
   
   import pendulum
   
   from airflow import DAG
   from airflow.decorators import task
   from airflow.operators.python import ExternalPythonOperator, 
PythonVirtualenvOperator
   
   log = logging.getLogger(__name__)
   
   PYTHON = sys.executable
   
   BASE_DIR = tempfile.gettempdir()
   
   
   def x():
       pass
   
   
   with DAG(
       dag_id='example_python_operator',
       schedule=None,
       start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
       catchup=False,
       tags=['example'],
   ) as dag:
   
       # [START howto_operator_python]
       @task(task_id="print_the_context")
       def print_context(ds=None, **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 = print_context()
       # [END howto_operator_python]
   
       # [START howto_operator_python_render_sql]
       @task(task_id="log_sql_query", templates_dict={"query": 
"sql/sample.sql"}, templates_exts=[".sql"])
       def log_sql(**kwargs):
           logging.info("Python task decorator query: %s", 
str(kwargs["templates_dict"]["query"]))
   
       log_the_sql = log_sql()
       # [END howto_operator_python_render_sql]
   
       # [START howto_operator_python_kwargs]
       # Generate 5 sleeping tasks, sleeping from 0.0 to 0.4 seconds 
respectively
       for i in range(5):
   
           @task(task_id=f'sleep_for_{i}')
           def my_sleeping_function(random_base):
               """This is a function that will run within the DAG execution"""
               time.sleep(random_base)
   
           sleeping_task = my_sleeping_function(random_base=float(i) / 10)
   
           run_this >> log_the_sql >> sleeping_task
       # [END howto_operator_python_kwargs]
   
       if not shutil.which("virtualenv"):
           log.warning("The virtalenv_python example task requires virtualenv, 
please install it.")
       else:
           # [START howto_operator_python_venv]
           @task.virtualenv(
               task_id="virtualenv_python", requirements=["colorama==0.4.0"], 
system_site_packages=False
           )
           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 time import sleep
   
               from colorama import Back, Fore, Style
   
               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(4):
                   print(Style.DIM + 'Please wait...', flush=True)
                   sleep(1)
               print('Finished')
   
           virtualenv_task = callable_virtualenv()
           # [END howto_operator_python_venv]
   
           sleeping_task >> virtualenv_task
   
           # [START howto_operator_external_python]
           @task.external_python(task_id="external_python", 
python=os.fspath(sys.executable))
           def callable_external_python():
               """
               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.
               """
               import sys
               from time import sleep
   
               print(f"Running task via {sys.executable}")
               print("Sleeping")
               for _ in range(4):
                   print('Please wait...', flush=True)
                   sleep(1)
               print('Finished')
   
           external_python_task = callable_external_python()
           # [END howto_operator_external_python]
   
           external_classic = ExternalPythonOperator(
               task_id="external_python_classic",
               python=os.fspath(sys.executable),
               python_callable=x,
           )
   
           virtual_classic = PythonVirtualenvOperator(
               task_id="virualenv_classic",
               requirements="rich",
               python_callable=x,
           )
   
           run_this >> external_classic >> external_python_task >> 
virtual_classic
   
   ```


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