python_operator

Example DAG demonstrating the usage of the PythonOperator.

Airflow Fundamentals


Providers:

Run this DAG

1. Install Astronomer CLISkip if you already have the CLI

2. Initate the project:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your requirements.txt file:

5. Run the DAG:

#
# 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
from airflow import DAG
from airflow.operators.python import PythonOperator, PythonVirtualenvOperator
from airflow.utils.dates import days_ago
args = {
'owner': 'airflow',
}
with DAG(
dag_id='example_python_operator',
default_args=args,
schedule_interval=None,
start_date=days_ago(2),
tags=['example'],
) as dag:
# [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,
)
# [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},
)
run_this >> task
# [END howto_operator_python_kwargs]
# [START howto_operator_python_venv]
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(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,
)
# [END howto_operator_python_venv]