Airflow conditional task example in python

Airflow conditional task example in python. python_operator import PythonOperator. Step 4: Running the Pipeline Jul 6, 2021 · 4. I never liked the need of a separate branch task to conditionally execute another task and was thinking of a way to somehow decorate/enhance an arbitrary operator to skip it on condition. This also allows passing a list: task1 >> [task2, task3] Will would run task1 first, again wait for it to complete, and then run tasks task2 and task3. Creating a PythonOperator Task. Once all this finishes then task6. Within your callable, you can access Airflow's variables and connections using the Variable and BaseHook classes, respectively. The BranchPythonOperator is a Python function that returns a string that represents the next task to be executed. decorators import task, task_group. Precedence Rules. The ShortCircuitOperator is derived from the PythonOperator. ie. The consecutive tasks don't wait until the previous task's successful completion. task_group import Dec 28, 2023 · Conditional task. Apr 19, 2023 · An ETL pipeline in Airflow typically consists of several tasks, defined as Operators in Airflow, strung together to form a Directed Acyclic Graph (DAG) of tasks. branch. def fn(): pass. Aug 25, 2022 · I was wondering if there is a way to make DAG (using python) in airflow using the PythonOperator (or other operator that is suitable to airflow 1. PythonOperator - calls an arbitrary Python function. Jan 7, 2017 · Then from the start task with the for loop we create 10 tasks with the same python callable. Below is an example of using the @task. It is your responsibility to ensure the return of a condition task goes to a correct successor task. Jun 23, 2021 · When triggering this DAG from the UI you could add an extra param: Params could be accessed in templated fields, as in BashOperator case: bash_task = BashOperator(. t1 = PythonOperator(. The task_id returned by the Python function has to be referencing a task directly downstream from the BranchPythonOperator task. answered Jun 3, 2021 at 11:25. It evaluates the condition that is itself in a Python callable function. I was thinking I could just check the value in the XCOM and publish if there is something or do nothing if it is empty. To each python callable we pass as arguments the total number of parallel tasks and the current task index. # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. Example:-. Nov 2, 2023 · Certain tasks might be more succinctly represented with traditional operators, while others might benefit from the brevity of the TaskFlow API. dag import DAG from airflow. This operator is a little bit different than the BranchPythonOperator. py in the dags/ directory of the Airflow project you just created. Here is an example: from airflow. kubernetes decorator to run a Python task. Basically I'm working with airflow and developed a task that my download a file from an external source. Here’s a basic example DAG: It defines four Tasks - A, B, C, and D - and dictates the order in which they have to run, and which tasks depend on what others. In this guide, we covered the basics of conditionals in Python including operators, complex conditional chains, nesting conditionals, ternary expressions, and common errors. Sep 3, 2021 · mapped to an airflow task. bash TaskFlow decorator allows you to combine both Bash and Python into a powerful combination within a task. py --approach daily. How do I tell Airflow to only do the publishing part of the workflow if certain conditions are met such as: If there is a message then publish it (or run the publish task). hooks. For example: Start date selected as 25 Aug and end date as 28 Aug. We examined real-world examples of using conditional logic for input Feb 25, 2021 · The script can be run daily or weekly depending on the user preferences as follows: python script. decorators import task, dag. EmailOperator - sends an email. You can find the following example included in the example_dags within Airflow distribution: Oct 16, 2023 · Here is an Airflow task branch example that shows you how to use the BranchPythonOperator to perform the Airflow branch task-from datetime import datetime. Apr 2, 2022 · Here's an example: from datetime import datetime from airflow import DAG from airflow. we can also see that Tasks C, H, J have no dependencies so they can be executed parallelly. utils. A DAG (Directed Acyclic Graph) is the core concept of Airflow, collecting Tasks together, organized with dependencies and relationships to say how they should run. We need to add a BranchSQLOperator to our DAG. In a Python program, the if statement is how you perform this sort of decision-making. While the TaskFlow API simplifies data passing with direct function-to-function parameter passing, there are scenarios where the explicit nature of XComs in traditional operators can be advantageous for Nov 6, 2023 · Task groups are a way of grouping tasks together in a DAG, so that they appear as a single node in the Airflow UI. My understanding is that TriggerDagRunOperator is for when you want to use a python function to determine whether or not to trigger the SubDag. Example :-. The responsibility of this task is to return the no of tasks executed with the status. From PyPI. In your case you are using a sensor to control the flow and do not need to pass a function. In the case of the Python operator, the function returns the ids of the tasks to run. def task_to_fail(): raise AirflowFailException("Our api key is bad!") If you are looking for retries use AirflowException :-. (task_id='branch_task', dag=branch_dag, IPython Shell. Tip The @task. Airflow run takes three arguments, a dag_id, a task_id, and a start_date. Aug 4, 2020 · the correct way instead is to put both task instantiation (creation of PythonOperator taskn object) as well as task wiring within that if . In Airflow, you can define order between tasks using >>. The tasks are created in the function create_dynamic_task. example_task_group. py --approach weekly. models import DAG. If the condition is True, downstream tasks proceed as normal. g. Nov 20, 2023 · To use the Operator, you must: Import the Operator from the Python module. Implement the ShortCircuitOperator that calls the Python function/script. New data-aware scheduling options Logical operators and conditional expressions for DAG scheduling. dummy_operator import DummyOperator. The outline of this tutorial is as follows: First, you’ll get a quick overview of the if statement in its simplest form. py file. exceptions import AirflowException from airflow. The most intuitive way to skip tasks created via PythonOperator is to raise AirflowSkipException. from airflow import AirflowException. For example: task1 >> task2. Taskflow automatically manages dependencies and communications between other tasks. This means python_callable function that gets executed via PythonOperator needs to implement the logic that decides when to raise exception. From Airflow 2. else: return 'new_year_task'. task_id=mytask, bash_command="echo ${MYVAR}", env={"MYVAR": '{{ ti. This can enhance readability and manageability, especially for complex workflows. from airflow import DAG from airflow. Using the Taskflow API, we can initialize a DAG with the @dag decorator. Here's an example of defining a TaskGroup: from airflow. task_id__1. def function_1(**kwargs): if condition_1 == True : return 'function_2'. bash task can help define, augment, or even build the Bash command(s) to execute. For example, if you want to download files from S3, but rename those files, something like this would be possible: If your Airflow workers have access to Kubernetes, you can instead use a KubernetesPodOperator and add any needed arguments to correctly run the task. Explicitly passed arguments; Values in Now that Airflow has been installed, you’re ready to write your first DAG. Code Example Task Groups. decorators import task with DAG(dag_id="example_taskflow", start_date=datetime(2022, 1, 1), schedule_interval=None) as dag: @task def dummy_start_task(): pass tasks = [] for n in range(3): @task(task_id=f"make_images_{n}") def images_task(i): return i tasks. See full list on medium. More info on the BranchPythonOperator here. define. With this strategy, both dags/tasks would run once. Our testing pipeline runs the latest dbt-core with the latest Airflow release, and the latest version supported by AWS MWAA. 0, and you are likely to encounter DAGs written for previous versions of Airflow that instead use PythonOperator to achieve similar goals, albeit with a lot more code. com This is especially useful for conditional logic in task mapping. Tasks can also be set to execute conditionally using the BranchPythonOperator. Define the Python function/script that checks a condition and returns a boolean. The ASF licenses this file # to you under the Apache License, Version 2. Sep 24, 2023 · By mlamberti Sep 24, 2023 # airflow taskgroup # taskgroup. baseoperator import BaseOperator from airflow. exceptions import AirflowFailException. Mar 14, 2023 · I have found lineage to be imperfect within Airflow. Source code for airflow. Here is an example of Define a BranchPythonOperator: After learning about the power of conditional logic within Airflow, you wish to test out the Airflow has a very extensive set of operators available, with some built-in to the core or pre-installed providers. That ways, the unnecessary tasks won't be created (and hence won't run) Jul 9, 2020 · If the value of flag_value is true then all tasks need to get execute in such a way that , First task1 then parallell to (task2 & task3 together), parallell to task4, parallell to task5. They contain the logic of how data is processed in a pipeline. This should help ! Adding an example as requested by author, here is the code. UPDATE: do NOT use this as pointed out by @Vit. def branch_function(**kwargs): if some_condition: return 'first_branch_task'. Some operators such as Python functions execute general code provided by the user Mar 11, 2021 · These tasks have dependencies for each of them and in order for a task to execute, all of its dependencies must be executed. . If not don't do anything. BaseBranchOperator. It evaluates a condition and short-circuits the workflow if the condition is False. datetime. The status of the “demo” DAG is visible in the web interface: This example demonstrates a simple Bash and Python script, but these tasks can run any arbitrary code. To have a DAG fully registered you need a dataset object(s) as schedule and to have a dataset as a task outlet ( defined in the @task) The whole input param / return value of a task never gave me lineage on Airflow (i did not test external tools). # Define the BranchPythonOperator. Dec 20, 2023 · In Airflow, conditional tasks are managed using the BranchPythonOperator and the ShortCircuitOperator. The TaskFlow API is new as of Airflow 2. 5. Since am new to airflow and DAG i dont know how to run for this condition. This could be 1 to N tasks immediately downstream. Which would run task1 first, wait for it to complete, and only then run task2. To use the @task. example_dags. Any downstream tasks are marked with a state of "skipped". Requirement: Run SQL query for each date using while loop. task_id='check_task', python_callable=function_1, # defined above method holds the branching condition. within a @task. Operators are the building blocks of Airflow DAGs. The download function is: Trigger rules define the conditions under which a task should run based on the states of its upstream tasks. 0 return 'current_year_task'. The more basic approach could be something like: Jun 3, 2021 · To do that, from Airflow Web UI: Mark task C as failed. Send the JAR filename and other arguments for forming the command to xcom and consume it in the subsequent tasks. trigger_rule import It evaluates a condition and short-circuits the workflow if the condition is False. There is a shorter way. The ASF licenses this file # to you under the Apache License, Version Airflow operators. Nov 8, 2019 · 7. By understanding how the BranchOperator works and following best practices, you can create more efficient and flexible DAGs that maximize the potential of your Airflow environment. Clear task C with options "upstream" and "failed": This should rerun all failed task (either A or B or any other that is in upstream of C) as well as C (because we marked it as failed). Mar 5, 2019 · UPDATE-1. DAGs. xcom_pull(key=\'my_xcom_var\') }}'}, dag=dag. original_execute ( context ) else : Aug 8, 2017 · 9. Using Python conditionals, other function calls, etc. 3. May 6, 2021 · The dependencies you have in your code are correct for branching. Here Here's an example: my_task = PythonOperator( task_id='my_task', python_callable=my_callable, op_args=[1, 2], op_kwargs={'key': 'value'} ) Accessing Airflow Variables and Connections. However, there are several other rules you can use: all_failed: Runs if all upstream tasks have failed. We can run it using different methods, the simplest is using the airflow run a shell command. Any downstream tasks are marked with a state of “skipped”. external_python decorator or the ExternalPythonOperator, you need to create a separate Python environment to reference. Jan 30, 2024 · Older versions of Airflow and dbt may work with airflow-dbt-python, although we cannot guarantee this. execute(context=context) Feb 8, 2023 · Skipping PythonOperator tasks. The ExternalPython operator, @task. Jun 10, 2023 · In the task definition of task_save_to_file, we use op_kwargs to pass the data returned by the previous task (fetch_weather_data()) to the save_to_file(data) function. This operator allows you to run different tasks based on the outcome of a Python function: from airflow. 12, so you’ll need to use Pendulum 3 if you upgrade to Python 3. When Datasets were added in Airflow 2. Task groups can also contain other task groups, creating a hierarchical structure of tasks. run('echo "wwwwwwwwwwwwwww"', shell=True, check=True) Feb 2, 2024 · from airflow. the default operator is the PythonOperator. The hope is this variable to be passed Aug 31, 2018 · 1. now() falls below target_upper and above target_lower. Task A can only be executed if Tasks B, C, D are executed before. This is useful for dynamic Apache Airflow's ShortCircuitOperator is a powerful tool for controlling the execution flow of tasks within a DAG. getLogger("airflow. The example below implements a simple yet commonly used feedback loop through a Jan 9, 2020 · You can achieve the same using BranchPythonOperator as below. decorators import apply_defaults from airflow. Slides. 4, DAGs only had scheduling support for logical AND combinations of Datasets. Jan 26, 2020 · I am going to call the function "a" in my airflow script using python operator, now I have to send an email notification with some content if the "if statement" in the function becomes true, if the else statement is executed we shouldn't get any email notification. def func( May 18, 2023 · Python provides an intuitive syntax using if, else, elif for implementing conditional code execution. exceptions import AirflowSkipException def conditionally_skip_task(): if some_condition: raise AirflowSkipException In above code, when the task is run, the condition will be evaluated. Mar 9, 2020 · A simple Python class designed to facilitate investment portfolio analysis How many numbers have a units digit that equals the digit sum of previous digits? How to say "it is thought" in German? Feb 6, 2021 · Additionally, each task can specify trigger_rule which allows users to make the relations between tasks even more complex. Downstream tasks will be marked with a state of "skipped" based on the short-circuiting mode configured. Apr 30, 2020 · As requested by @pankaj, I'm hereby adding a snippet depicting reactive-triggering using TriggerDagRunOperator (as opposed to poll-based triggering of ExternalTaskSensor). Next, instantiate a PythonOperator in your DAG file, passing the callable and any necessary arguments. It allows for conditional execution of a statement or group of statements based on the value of an expression. from datetime import datetime. If the value of flag_value is false then the Oct 4, 2023 · The BranchPythonOperator allows you to follow a specific path in your DAG according to a condition. Original point: on_success_callback / on_failure_callback: Depending of whether Task 2 is supposed to run upon success or failure of Task 1, you can pass lambda: time. from typing import List from airflow. models. Examples of trigger rules are: all_success—meaning that all tasks in Aug 29, 2023 · from airflow. dagrun_operator import TriggerDagRunOperator from airflow. check_task = BranchPythonOperator(. Feb 22, 2024 · If I got it, what you need are two DAGs with one task each to do the job. http_hook import HttpHook from typing import Optional, Dict """ Extend Simple Http Operator with a callable function to formulate data. task_id="handle_failure", provide_context=True, queue="master", python_callable=handle_failure) return set_train_status_failed. Next glue job task is called as soon as the previous glue job task is invoked. Your BranchPythonOperator is created with a python_callable, which will be a function. It allows a task to halt the execution of downstream tasks based on a condition, effectively 'short-circuiting' the DAG. My guess is to go for the bashoperator as to create a task t1 = bashoperator that executes the bash Jan 10, 2023 · Jan 10, 2023. get_campaign_active = PythonOperator( task_id='get_campaign_active', provide_context=True, python_callable=get_campaign_active, xcom_push=True, op_kwargs={'client': client_production}, dag=dag) As you can see I pass in the client_production variable into op_kwargs with the task. Apache Airflow is an orchestration platform to programmatically author, schedule, and execute workflows. external_python decorator or ExternalPythonOperator, runs a Python function in an existing virtual Python environment, isolated from your Airflow environment. python_task = PythonOperator(. short_circuit decorator is recommended over the classic ShortCircuitOperator to short-circuit pipelines via Python callables. Nov 5, 2023 · Introduce a branch operator, in the function present the condition. 31. http_operator import SimpleHttpOperator from airflow. Aug 23, 2021 · Any downstream tasks are marked with a state of "skipped". if you want to fail the task without retries use AirflowFailException :-. param1 }}') Params are accessible within execution context, like in python_callable: Dec 4, 2020 · Running a workflow in Airflow. Oct 6, 2020 · XComs are used for communicating messages between tasks. execute (self, context) [source] ¶ class airflow. For more information on how to use this operator, take a look at the guide: BranchDateTimeOperator. dummy_operator import DummyOperator from airflow. Task groups can have their own dependencies, retries, trigger rules, and other parameters, just like regular tasks. Workflows are built by chaining together Operators, building blocks that May 28, 2019 · Even though the flow depends on each task in Ariflow. Assuming your example with 9-13h peak: DAG 1, scheduled to run 9am, with decrease_bandwidth task; and. def wrapped_execute ( self, context ): if condition ( context ): self. from airflow. Here is an example of an ETL pipeline: Source code for airflow. Make sure BranchPythonOperator returns the task_id of the task at the start of the branch based on whatever logic you need. Indeed, SubDAGs are too complicated only for grouping tasks. py file from airflow. It is essentially a placeholder task that can be used for various purposes within your DAGs. append(images_task(n)) @task def dummy_collector Mar 30, 2023 · The Taskflow API is an easy way to define a task using the Python decorator @task. task_id='my_python_task', python_callable=my_python_callable, op_args=[], # Optional. If the return falls beyond the range of the successors, the executor will not schedule any tasks. Oct 16, 2019 · Is there a way for Airflow to skip current task from the PythonOperator? For example: def execute(): if condition: skip_current_task() task = PythonOperator(task_id='task', python_callable=execute, dag=some_dag) And also marking the task as "Skipped" in Airflow UI? In the example below, the tasks that follow the “condition_is_true” task will execute while the tasks downstream of the “condition_is_false” task will be skipped. The DummyOperator inherits from the BaseOperator class, and despite its simplicity, it can be a valuable tool for structuring and organizing your workflows. Airflow taskgroups are meant to replace SubDAGs, the historical way of grouping your tasks. #36479. Feb 16, 2019 · This is how you can pass arguments for a Python operator in Airflow. One last important note is related to the "complete" task. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. As for the PythonOperator, the BranchPythonOperator executes a Python function that returns a single task ID or a list of task IDs corresponding to the task (s) to run. If you want to skip some tasks, keep in mind that you can’t have an empty path, if so make a dummy task. ai. Some popular operators from core include: BashOperator - executes a bash command. python_operator import PythonOperator from time import sleep from datetime import datetime def my_func(*op_args): print(op_args) return op_args[0] with DAG('python_dag', description='Python DAG', schedule_interval='*/5 Logging within Tasks. An Airflow TaskGroup helps make a complex DAG easier to organize and read. info("Task started") Passing Arbitrary Objects. task_id='bash_task', bash_command='echo bash_task: {{ params. The default trigger rule is all_success, meaning a task will run only if all its upstream tasks have succeeded. Oct 25, 2020 · Of course, we will not do it by querying the SQL database in the Python function. Using the @task allows to dynamically generate task_id by calling the decorated function. When using task decorator as-is like. For example, check_status >> handle_status check_status - checks status from DB and write JAR filename and arguments to xcom Dec 23, 2021 · Is there any difference between the following ways for handling Airflow tasks failure? First way -. Issue: In below DAG, it only execute query for start date and then complete job. The condition is determined by the result of `python_callable`. This operator is particularly useful in scenarios where the continuation of a workflow depends on the outcome Jan 24, 2023 · One may have ever suffered the pain of handling task skipping through a pipeline with an elegant, efficient and quick solution. python import PythonOperator def alert_on_failure(context): pass task = PythonOperator( task_id='my_task' python_callable=my_python_function on_failure_callback=alert_on_failure ) When the task fails, the function specified in on_failure_callback will be executed. That function is called conditionally_trigger in your code and the examples. Here are some other ways of introducing delay. Use the @task decorator to execute an arbitrary Python function. If you want to pass an xcom to a bash operator in airflow 2 use env; let's say you have pushed to a xcom my_xcom_var, then you can use jinja inside env to pull the xcom value, e. DAG 2, scheduled to run 1pm, with return_to_normal_bandwidth task. Using conditional tasks, you can execute tasks depending on The ShortCircuitOperator is derived from the PythonOperator and evaluates the result of a ``python_callable``. Which is a bummer but you have been warned ! ^^ If the output is False or a falsy value, the pipeline will be short-circuited based on the configured short-circuiting (more on this later). May 12, 2021 · # extended_http_operator. There are many different types of operators available in Airflow. @task. Jul 4, 2021 · Assuming that Airflow is already setup, we will create our first hello world DAG. The Apache Airflow BranchOperator is a powerful tool for creating dynamic, conditional workflows that can adapt to different situations and requirements. example_python_operator. Using the BranchPythonOperator, you can build branches into your DAGs, allowing you to choose multiple execution paths depending on certain conditions. Use Python's built-in logging to record task-specific information: import logging logger = logging. return 'second_branch_task'. Nov 17, 2021 · 4. airflow-dbt-python is available in PyPI and can be installed with pip: pip install airflow-dbt-python The DummyOperator is a no-op operator in Apache Airflow that does not execute any action. python_operator import BranchPythonOperator. Mar 8, 2019 · The task_id returned is followed, and all of the other paths are skipped. Think of running a Spark job, moving data between two buckets, or sending an Bases: airflow. python_operator. Example: task_id. Use the trigger rule for the task, to skip the task based on previous parameter. 0 on Docker) and in the python_callable decide which task will be called next, it will be based on the previous tasks status. 0, you can pass objects decorated with @dataclass or @attr. else: return 'function_3'. One way to organize tasks within a DAG is by using TaskGroup, which groups tasks in a visually structured way in the Airflow UI. edited Jun 3, 2021 at 13:24. First, let’s instantiate the DAG. Then BigQueryOperator first run for 25 Aug, then 26 Aug and so on till we reach to 28 Aug. First, create a file called sample_dag. Airflow’s basic task dependencies can be used to define linear task dependencies and fan-in/fan-out structures in Airflow DAGs. Even if the possibilities of using Sensors are infinite, there may be some circumstances where a simple condition needs to be set to decide whether a task must run. The @task. sleep(300) in either of these params of Task 1. More context around the addition and design of the TaskFlow API can be found as part of its Airflow Improvement Proposal AIP-31 Feb 15, 2024 · In our example, notif_a_task will execute if neither download_website_a_task nor download_website_b_task fails. For me, the task ran successfully, but it didn't trigger the operator inside the function. 12. Branches into one of two lists of tasks depending on the current datetime. branch_task = BranchPythonOperator. In the example below, the tasks that follow the “condition_is_true” task will execute while the tasks downstream of the “condition_is_false” task will be skipped. The condition is determined by the result of python_callable. Oct 10, 2020 · Im planning to use an airflow operator inside a function and then call it from a different task. I want to automate this dataflow workflow process to be run every 10 minutes via Airflow. Below is the code for the DAG. If the returned result is False or a falsy value, the pipeline will be short-circuited. At the end even though the Airflow looks like successfully completed the glue jobs are still running for several minutes. Oct 10, 2020 · may I offer a different approach, since I think what you try to do is not meant to be: you could use the subprocess library from python import subprocess and do somthing like this subprocess. All it will do is print a message to the log. one_failed : This rule mandates that the task should execute as soon as at least one Sep 21, 2022 · Save the multiple_outputs optional argument declared in the task_decoratory_factory, every other option passed is forwarded to the underlying Airflow Operator. They bring a lot of complexity as you must create a DAG in Jun 22, 2022 · Need help to extract the list of all tasks along with their current status [Success/Failed] for the current dag run. Apr 8, 2024 · However, Pendulum 2 does not support Python 3. python script. I have a task with a python operator which executes at the end of the workflow. That function shall return, based on your business logic, the task name of the immediately downstream tasks that you have connected. task") logger. The docs of _get_unique_task_id states: Generate unique task id given a DAG (or if run in a DAG context) Ids are generated by appending a unique number to the end of the original task id. The ShortCircuitOperator is a sensor that stops the execution of the DAG if a condition is met. Airflow evaluates this script and executes the tasks at the set interval and in the defined order. For example, use conditional logic to determine task behavior: . Condition task can go cyclic to describe iterative control flow. task_id='download', python_callable=download, provide_context=True, dag=dag) and this airflow is running in a virtual environment (pipenv). True branch will be returned when datetime. do_something(kwargs) set_train_status_failed = PythonOperator(. 35. else block. operators. Using your favorite text editor or IDE, open the sample_dag. Each task in a DAG is defined by instantiating an operator. python import BranchPythonOperator. If all the task’s logic can be written with Python, then a simple annotation can define a new task. from airflow import DAG. ev er bt hk ky cp tr jg ks ml