#Airflow xcom pythonoperator install
#Airflow xcom pythonoperator code

If you take a look at the python function _choose_best_result(). It expects a task_id and a python_callable function. Pay attention to the arguments of the BranchPythonOperator.

#Airflow xcom pythonoperator code

Copy paste the code in that file and execute the command docker-compose up -d in the folder docker-airflow. Create a file branching.py in the folder airflow-data/dags.

Airflow 2.0, not 1.10.14 😎 Clone the repo, go into it. Then, go to my beautiful repository to get the docker compose file that will help you running Airflow on your computer.

#Airflow xcom pythonoperator install

To run the code, install Docker on your computer. The code above gives you the same data pipeline as shown before. With DAG('branching', default_args=default_args, catchup=False) as dag:Ĭhoose_best_model = BranchPythonOperator(Ĭhoose_best_model > What about a bit of code to implement it? from airflow import DAGįrom import BranchPythonOperatorįrom import DummyOperator In practiceĪll right, you know the BranchPythonOperator and you know how it works. In the example, if you put a task after “Is inaccurate”, that task will be skipped. Consequently, downstream tasks that are not returned by the BranchPythonOperator get skipped! Also, tasks following skipped tasks are skipped as well. In our case, “Choosing Best ML” and “Is accurate” have succeeded whereas “Is inaccurate” has been skipped. Can you guess which task is executed next? “Is accurate” or “Is inaccurate”? Like the PythonOperator, the BranchPythonOperator executes a Python function returning the task id of the next task to execute. That condition is evaluated in a python callable function. The BranchPythonOperator allows to follow a specific path according to a condition. Ok, we are to happy to meet with the BranchPythonOperator but what does it do? Give a warm welcome to the BranchPythonOperator! The BranchPythonOperator Yes there is! And you know it, otherwise you wouldn’t be there 😅 How can you do this? Is there a mechanism to achieve this? Let’s say, if the accuracy is above 5.0 we trigger “Is accurate”, otherwise, “Is inaccurate” is run. Then, either the task “is accurate” or “is inaccurate” should get executed according to the accuracy of the best ML model. Once they all complete, “Choosing Best ML” task is getting triggered. The first three tasks are training machine learning models. Till next time….Quick explanation about the DAG.

If you like the blog entry do leave a comment and tell us what we can write about. Hope this blog gets you started on XCOMs and exploring them. It is the link to the source code of XCOM methods but also exposes some really nice methods which can come handy for some use-cases. Needless to say, if you feel you want to dig more. Make sure you have a look at the xcom_pull method in detail. When the dag is executed – In Admin->XComs the pushed key value pair is visibleĭAG execution log shows the value pulled via XCOM. Independent from where the tasks are being executed. Pull values between dags, tasks and values from previous runs. Note: This becomes more interesting when you add the following dimensions Step 8 – Defines a new task t3 which uses python operator.Step 2 – A new method f_get_value_via_xcom is defined which uses xcom_pull to get values from XCOM.The above DAG only adds an additional step to one before. Linux_command = 'echo xcom' # Step 6 - Create a task for running the Linux commandĭag =dag ) # Step 7 - Create a task for pushing key-value pair to XCOM, created in step1ĭag =dag ) # Step 8 - Create a task for pushing key-value pair via XCOMĭag =dag ) # Step 9 - Task execution order xcom_push (key = 'my_key', value = 'my_value' ) # Step 2 - Default arguments for airflow DAGĭefault_args = # Step 4 - Create an airflow DAGĭefault_args =default_args ) # Step 5 - Create a Linux command string python_operator import PythonOperator from datetime import datetime, timedelta # Step 1 - Define a method for pushing a key value pair to XCOM def f_send_value_via_xcom (**context ): print 'Hello xcom push'Ĭontext. bash_operator import BashOperator from airflow. # Filename: hello_xcom.py from airflow import DAG from airflow.