Airflow task return value. Unable to store Airflow task objects to a dictionary.

Airflow task return value The task-specific XCom view shows something like this: You can then fetch (known as "pull" in Airflow) the value in another task: The returned value, which in this case is a dictionary, will be made available for use in later tasks. Here, there are three tasks - get_ip, compose_email, and send_email_notification. It's hard to tell without context, but supposing that Task1 returns just a simple list of results, without any complex logic, you could do this if you want to build your DAG dynamically: def Task1: # Do something and return an array return ["a","b","c"] def Task2: # Do something return with DAG( Here, there are three tasks - get_ip, compose_email, and send_email. I did some research on xcom, and found that all results of Airflow tasks are stored there, which can be accessed via code task_instance = kwargs['t1'] task_instance. 11. Ask Question Asked 3 years, 10 months ago. Problem. The main difference between the two workflows are the use of TaskGroup inside the DAG and the way we CreateRobot = BashOperator(dag=dag_CreateRobot, task_id='CreateRobot', bash_command="databricks jobs create --json '{myjson}')", xcom_push=True #Specify this in older airflow versions) The above operator when executed pushes the last The returned value, which in this case is a dictionary, will be made available for use in later tasks. Reload to refresh your session. What happened. ALWAYS: will always trigger the task. As the number of values returned may vary, I am using the index as the key. apache. return the entry saved under key='return_value' The {{ }} is syntax of Jinja engine that means "print" the value. Apache Airflow version. Checking the xcom page, I'm not getting the expected result. SkipMixin. Process(pid=00000, status='terminated') (00000) terminated with exit code -15. xcom_pull(task_ids='t1') If we increase number of dynamic task they will not be process to the end when the next task starts executing its job - it will not wait for success of parent tasks because doesn't know about them - it will learn after airflow Here's my complete workflow: import base64 import pendulum from airflow. This stores the returned value as an "XCom" in Airflow. I'm mostly brand new to airflow. xcom key/value screenshot. ; Final code: import json from airflow. code:: python from airflow. So far, we create all the tasks in the workflow, we need to define the dependency among these tasks. This operator requires a connection ID, along with the SQL query to execute, and allows optional The task in airflow they have a trigger rule, which can be pass to the decorators you are using. use_dill. example_dags. Since the task_ids are evaluated, or seem to be upfront, I cannot set the dependency in advance, any help would be appreciated. Dict will unroll to xcom values with keys as keys. 0 - AttributeError: 'MyOperator' object has no To support data exchange, like arguments, between tasks, Airflow needs to serialize the data to be exchanged and deserialize it again when required in a downstream task. {'NewMeterManufacturer': manufacturer, 'NewMeterModel': model } You signed in with another tab or window. Airflow Dynamically adding airflow tasks on the basis of DB return value. If set, function return value will be unrolled to multiple XCom values. XComs are a way to pass data between tasks in Any time a task returns a value (for example, when your Python callable for your PythonOperator has a return), that value is automatically pushed to XCom. 0. XComs can be “pushed” (sent) or “pulled” (received). Follow edited Dec 15, 2020 at 11:53. You can observe XComs via the Grid View -> select task -> XCom, or see all XCom values via Admin -> XComs. if you need to return each key of the return value you should set the task decorator of compare_release_files with multiple_outputs=True. The above workflow was created by the Python scripts below. xcom_pull accepts task_ids: Optional[Union[str, Iterable[str]]] but with the same key. 1. I am trying to access XCOM value while learning Airflow, but every time, I get None returned. Task should fail otherwise. From Airflow documentation. """ from __future__ import annotations import random import sys import tempfile import The same workflow with grouping. 6. Below is the DAG code. issue with passing return value from a task as an argument to I am new to Python and new to Airflow. Airflow - getting the execution_date in task when calling an Operator. Airflow PythonOperator task fail - TypeError: The key has to be a string Unable to store Airflow task objects to a dictionary. short_circuit to create task nodes. I got stuck with controlling the relationship between mapped instance value passed during runtime i. Using Airflow 2. However, when we talk about a Task, we mean the generic “unit of execution” of a DAG; when we talk about an Operator, we mean a reusable, pre-made Task template whose logic is all done for you and that just needs some arguments. You might want to check out Airflow's XCOM: https://airflow. Only on_failure_callback and on_success_callback contain this data. set_upstream(task1). partial( task_id="invoke_lambda", retries=1, retry_delay=timedelta(seconds=30), python_callable=invoke_lambda_function, ). TriggerRule. Actual class BranchPythonOperator (PythonOperator, BranchMixIn): """ A workflow can "branch" or follow a path after the execution of this task. Note that if your virtualenv runs in a different Python major version than Airflow, you cannot use return values, op_args, op_kwargs, or use any macros that are being XComs are what you use to allow tasks to communicate with each other, either in the same DAG run or across DAG runs. asked Dec 15, 2020 I am build an airflow DAG with multiple PythonOperator nodes. python_command. In case you are implementing a I am trying to pass a list of strings from one task to another one via XCom but I do not seem to manage to get the pushed list interpreted back as a list. 15 dynamic task creation. So on I I would like to create a conditional task in Airflow as described in the schema below. I am not sure what the key and values should be for a xcom_push function. { task_id }", key='return_value') }}", The explanation why it happens: When task is assigned to TaskGroup the id of the task is no longer the task_id but it becomes group_id. For Apache Airflow, How can I pass the parameters when manually trigger DAG via CLI? Unlike in version 2. external_python decorator allows you to run an Airflow task in pre-defined, immutable virtualenv (or Python binary installed at system level without virtualenv). For example, INFO - Task exited with return code 1 or INFO - Task exited with return code 0 or INFO - Process psutil. from airflow import DAG from airflow. 3 and Dynamic TaskGroup Mapping so I can iterate over rows in a table and use the values in those rows as parameters in this group of tasks. In Airflow, tasks can return values that can be used by downstream tasks. I am using airflow, i want to pass the output of the function of task 1 to the task 2. PythonOperator, airflow. Airflow provides a very intuitive 'new_config' generates the new config file, and 'next_task' tries to pull in the xcom value. I have a dag that begins with a k8s task that queries a list of table names that need to be it t1 = PythonOperator. def values_from_db(): # fetch data from DB. I have a python callable process_csv_entries that processes csv file entries. This is the original code that I am working with. decorators import dag, task from airflow. In Airflow 1. BashOperator( task_id='also_run_this', bash_command="<you command> {{ if you are using branch operator then the return value of the if/else block is the task_id itself. Use the SQLThresholdCheckOperator to compare a specific SQL query result against defined minimum and maximum thresholds. If not, value from the one single task instance is returned. dag_id=dag10 I am trying to use XCom Push and Pull to use Variables between tasks. 7. This import airflow from datetime import datetime, timedelta from airflow. xcom_pull() function documentation). 2. I have a two step process: Get all files that match a criteria Uncompress the files The files are half a gig compressed, and 2 - 3 gig when uncompressed. Hey so I am using Airflow 2. The first task executes a stored procedure which returns a parameter. Whether to use dill or pickle for serialization. models I have two tasks in an Airflow DAG like below. either pushed within the task's execution or via its return value, as an input into downstream tasks. 3 if that makes a difference. 10. issue with passing return value from a task as an argument to another task. How do I, in the next task, retrieve all the values from the previous task. It derives the PythonOperator and expects a Python function that returns a single task_id or list of task_ids to follow. Please use the following instead: from airflow. This is used to determine how many task instances the scheduler should create for a downstream using this XComArg for task-mapping. 3: Airflow create new tasks based on task return value. The task_id(s) returned should point to a task kwargs['task_instance']. That is all working fine, In simple terms, PythonOperator is just an operator that will execute a python function. 5. send_email is a more traditional Operator, but even it can use the return value of I wonder that is there any way for me to pass the return result from t1 directly to t2. Dynamic Task Mapping allows a way for a workflow to create a number of tasks at runtime based upon current data, rather than the DAG author having to know in advance how many tasks What is the appropriate way to reference an array parameter in . If I try to run this operation beforehand and pass task_1a to the list, then "step" is triggered at the same time as task_1b. I'm expecting the file size under Value. I have created an operator SnowflakeGetDataOperator that returns the snowflake hook. The expected scenario is the following: Task 1 executes If Task 1 succeed, then execute Task 2a Else If Task 1 return "big_task" # run Airflow does have a feature for operator cross-communication called XCom. You signed out in another tab or window. From the outline below it should have only two paths forward, clean_headers_Post_Perfromance or no_file_found. The list is returned by the task but I cannot access it inside the taskgroup. **New style:**. You can access the If you want a task to have a maximum runtime, set its execution_timeout attribute to a datetime. This virtualenv or system python can also have If an XCom value is supplied when the sensor is done, then the XCom value will be pushed through the operator return value. The last line of output is stored as an XCom and this can be used in any other operator. To send data from one task to another you can use Airflow XCOM feature. http. How can I set the function argument to a task that is the return from a previous task / function that was run. This is because if a task returns a result, Airflow will automatically push it to XCom under the return_value key. Actually the main function of an operator is the execute method, and most of them does not return anything. However, the SSHOperator's return value is encoded using UTF-8. decorators import task from airflow. python and allows users to turn a python function into an Airflow task. xcom_pull(task_ids='ssh', dag_id='adhoc_***', key='return_value') }} The SSHOperator code seems to return the aggregated stdout (base64 encoded). models import BaseOperator import pendulum class CustomDummyOperator(BaseOperator): # @apply_defaults deprecated now, no Check values against a threshold¶. 3. Returns. How do I pass the xcom return_value into the python callable 'next_task' as a dictionary? As that is what it Jinja-templated args for an operator can only be used for those fields that are listed as template_fields in the operator class. Ask Question Asked 1 year, 3 months ago. http import Here, there are three tasks - get_ip, compose_email, and send_email. But how can I store and access this returned value? For example: I have the following functions. g. Airflow 2. the output varies on each execution. Airflow 2 loosely coupling @task return values to receiving @task? 3. These values are passed as arguments to the downstream task's function. But when I schedule this Dag on airflow it works smoo Skip to main content. Second, and Here, there are three tasks - get_ip, compose_email, and send_email. This works as long as you triggered the subdag using the same execution date as your current DAG. You switched accounts on another tab or window. Airflow tasks in a loop based on dag_run conf value. models. execution_timeout controls the Here, there are three tasks - get_ip, compose_email, and send_email_notification. branch_virtualenv`` which builds a temporary Python virtual environment. I am using pre_task5 to check condition for task5 execution. def sum(a, b): return a + b def compare(c, d): return c > d And the following dag: I want to fetch value from DB and run tasks in parallel for each value. The @task. skipmixin. Runtime/dynamic generation of tasks in Airflow using JSON representation of tasks in XCOM. My second function is to receive that file and delete null values and return the DF again without null values. example_task_group_decorator # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. Python command for executing functions When generating tasks dynamically, I need to have Task 2 be dependent of Task 1, Task1 >> Task 2 or task2. I am using the Snowflake database. Could please exp I am trying to pass a Python function in Airflow. task_id to reflect this relationship. * is unknown until completion of Task A? I have looked at subdags but it looks like it can only work with a static set of tasks that have to be determined at Dag creation. ; Remove multiple_outputs=True from the task decorator of Get_payload. Modified 1 year, The task_ids value in xcom_pull() get_task_map_length (run_id, *, session) [source] ¶ Inspect length of pushed value for task-mapping. I am not seeing consistency. ONE_FAILED: will trigger a task if one of the previous failed. __bool__ [source] ¶ class airflow. xcom_push(key=db_con, value = db_log) return (db_con) use xcom_pull to pull a key's value that same task pushed I am new to Airflow and I am practicing a bit, for example I have a function that reads a file (excel) and returns the converted file to DataFrame. Using Python conditionals, other function calls, etc. so now I have this task in the dag: check_last_run_date=SnowflakeGetDataOperator( task_id='check_last_run_date', When pulling one single task (task_id is None or a str) without specifying map_indexes, the return value is inferred from whether the specified task is mapped. I want to return 2 or more tasks from a function that should be run in sequence in the spot they're inserted in the dependencies, see below. Iterating through a python list of dictionaries using a xcom return value. 0 I know I'm missing something basic, but I can't figure out what it is. The answer is No. Variables can be listed, created, updated and deleted from the UI I'm trying to get the appropriate values in this list of dictionaries, which includes calling classes from 'table_name'. Allows a workflow to “branch” or follow a path following the execution of this task. The task_id(s) returned should point to a task I am trying to write some airflow integration tests, where I imitate the gcs_list_operator by returning a file list from a custom PythonOperator, which is then passed to a PythonBranchOperator through xcomm. 8. If your goal is to use the output of the map_manufacturer_model function to another tasks, I would consider treating the object as a dict or string. The xcom_pull() method - It’s used to pull a list of return values from one or multiple Airflow tasks. def check_condition(**kwargs): # do something return True # or return False task1 = PythonOperator( task_id='condition_task', task 2 invoked only when the return value of task 1 is True? airflow; Share. otherwise the value of the xcom id "return_value" and its value its a dictionary. { task_instance. 2; Helm chart 1. As a result of this behaviour, my entire dataframe (84mb) is being written to a log file at every task execution. And it's still the old syntax, and the Airflow docs promises. I am using Apache Airflow 2. decorators import task. But when I tried to used that in a for loop, it will fail due to NoneType, which makes sense since it hasn't be generated yet. To access the return value from the previous task, you can read it from xcom, but the read should be in an airflow operator in order to access the run context: Python Airflow - Return result from PythonOperator. 0. def process_csv_entries(csv_file): # Boolean file_completely_parsed = <call_to_module_to_parse_csv> return not file_completely_parsed CSV_FILE=<Sets path to Coercing mapped lazy proxy return value from task forward_values to list, which may degrade performance. py:156} INFO - Task exited with return code 1 [2022-06-19, 18:27:00 +08] {taskinstance. But when I schedule this Dag on airflow it works smoothly. timestamp = time_of_run. In terms that create_job_flow task must run and save the value to the database before add_steps task can read the value. Airflow treats non-zero return value as a failure task, however, it’s not. The TaskFlow API is a functional API for using decorators to define DAGs and tasks, which simplifies the process for passing data between tasks and defining dependencies. The task_id(s) and/or task_group_id(s) returned should point to a It shows how to use standard Python ``@task. t1 = PythonOperator() def generate_tasks(): t2 = PythonOperator() t3 = PythonOperator() return magic(t2, t3) # magic needed here (preferably) t1 >> generate_tasks() # otherwise here # desired result: t1 >> t2 >> t3 I went through the airflow docs and other articles came across sensors and poke method. timedelta value that is the maximum permissible runtime. The problem is Airflow: Best way to store a value in Airflow task that could be retrieved in the recurring task runs. In contrast, with the TaskFlow API in Airflow 2. ' port = '5439' sslmode = 'require' ") task_instance = context['task_instance'] task_instance. Instead, you can use the new concept Dynamic Task Mapping to create multiple task at runtime. airflow xcom value into custom operator from dynamic task id. Note that these tasks are defined programmatically, therefore I cannot simply use xcom_pull(task_id="some_task") because the tasks are defined in I would like to calculate dates before I created next task, Ideally one task per date. If the task to pull is mapped, an iterator (not a list) yielding XComs from mapped task instances is returned. Hot Network Questions Who is this man being noticed by Robert in this scene? Various groupings of 8th ` def fetch_result(context): ti=context['ti'] value=ti. But, not sure how to proceed with that. Expections : I was expecting that the 'Hello,dbt!' will be printed in the logs. The way to access fields from the Tuple I'm passing then is the following: "{{ task_instance. Note, if a key is not specified to xcom_pull(), it uses the default of return_value. Fetching XCOM returns None value in Airflow. branch`` as well as the external Python version ``@task. Airflow Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company Bear with me since I've just started using Airflow, and what I'm trying to do is to collect the return code from a BashOperator task and save it to a local variable, and then based on that return code branch out to another task. This works with Airflow 2. org/docs/apache-airflow/stable/concepts/xcoms. :param python_callable: A reference to an object that is callable:param op_kwargs: a dictionary of keyword arguments that will get unpacked in your function (templated):param op_args: a list of positional arguments that will get unpacked when calling In my actual DAG, I need to first get a list of IDs and then for each ID run a set of tasks. So it's better you use xcoms to pass data between tasks rather than as task callable parameters. Beta Was this translation helpful? Give feedback. So any return value of PythonOperator is saved to XCom (something to be careful with!). expand? Using Airflow 2. Review resource requirements for this operation, and call list() explicitly to suppress this message. Using XComs. py:1395} INFO - Marking task as UP_FOR_RETRY. Airflow 1. For example, use conditional logic to determine task behavior: Answering your questions: There is no such feature. paths = ['gs://{}/{}'. I have two Airflow tasks that I want to communicate. You can open a PR to Airflow for adding the functionality you seek. Additional/less values can be returned by DB in each call. Then I have an operator that follows named task2 takes an input from the xcom value from task1 like below: issue with passing return value from a task as an argument to another task. excluding bytes, can be returned as can dicts. However, when you look at the code of the postgresoperator you see that it has an execute method that calls the run method of the PostgresHook (extension of dbapi_hook). xcom_push(key='return_value', value=full_paths) As suggested by @Josh Fell in the comments, I had two mistakes in my DAG. That's trivially achieved by templating the execution_date value:. example: var1 = [1,2,3,4] branch_operator takes the value from var1 Deprecated function that calls @task. On the other hand, the poke method of the sensors need to return True or False since The issue is the inside of format function, you have {id} formatting variable which needs to be used in f-string or followed by . The issue I have is figuring out how to get the BashOperator to return something. Doing so I see the value in the xcom value for the dag execution. 58. The custom operator pushes a string True or False as an Xcom Value which then read by the BranchPythonOperator. task. I am struggling to pull the returned values from the previous task from a PythonOperator in the BranchOperator without using a key when running Source code for airflow. So after execution I go into xcom and check the return_value and its just a string (screenshot below). get_records method (i am returning a small amount of kines - usually a single cell). Instead I got from DAGR 3. base. It seems small enough to not need the complexity of being turned into a Series at this point. What I'm getting is key: return_value ; Value:ODAwMAo=. trigger = TriggerDagRunOperator( The problem I'm having with airflow is that the @task decorator appears to wrap all the outputs of my functions and makes their output value of type PlainXComArgs. Wrap the data in json. About; I'm trying to handle datetime output from the first BashOperator task but when I call the process_datetime task only the dt value returns None. sample value - [& The returned value, which in this case is a dictionary, will be made available for use in later tasks. send_email is a more traditional Operator, but even it can use the return value of [2022-06-19, 18:27:00 +08] {standard_task_runner. Below is the description from the Apache This works, but now we are actually not defining the dependencies between tasks, but Airflow return values? Still feels like a hack. timestamp() * 1000 return str(int(timestamp)) class TemplatedArgsGlueOperator(AwsGlueJobOperator): template_fields = ("script_args",) table @PhilippJohannis thanks for this, I changed xcom_push argument in my SSHOperator to do_xcom_push. xcom_pull(dag_id='my_dag', task_ids=f"execute_my_steps. Airflow Taskflows: Chaining tasks with return values. expand(op_kwargs=generate_lambda_config()) How do you access the values and use it to trigger a following task for each value from the returned task? I have tried using it directly like Similarly, task dependencies are automatically generated within TaskFlows based on the functional invocation of tasks. 0, the invocation itself automatically generates the dependencies. If xcom_pull is passed a single string for task_ids, then the most recent XCom value from that task is returned; Why Airflow xcom_pull return the most recent xcom value? In the previous example, a dictionary with two values was returned, one from each of the tasks in the task group, that are then passed to the downstream load() task. :param xcom_value: An optional XCOM value to be returned by the operator. format(bucket, obj) for obj in my_list] kwargs['ti']. If i'm correct, airflow automatically pushes to xcom when a query returns a value. Currently the check_for_Post_Performance returns cleans_headers_for_gcm task and I'm at a total loss how that happens. When attempting to use dynamic task mapping over a task_group() based on a non-standard XCom (e. info(value) ` print_task=DbtRunOperationOperator(task_id='dbt_task',macro='return_hello',do_xcom_push=True) print_task. py:92} ERROR - Failed to execute job 100 for task wait (too many values to unpack (expected 2); 107) [2022-06-19, 18:27:00 +08] {local_task_job. . The returned value, which in this case is a dictionary, will be made available for use in later tasks. A bit more involved @task. Introduction to the TaskFlow API and Airflow decorators. When a task pushes an XCom, it makes it generally available to other tasks. As for number of queries: I assume that by "repeats a single query" you are asking if it execute a query per task_id. They just do the job. I have used Dynamic Task Mapping to pass a list to a single task or operator to have it process the list Specify the ti argument - It stands for task instance, and allows you to pull values stored in Airflow XComs. 1 version and Python 3. xcom_pull(task_ids='Y') I expected to get value of xcom from task instance Y in DAGR 1. I have created a operator and it returns a token (just a string so hello world operator example works fine). If you are not directly using the output of a task directly as an input for another (via TaskFlow API or otherwise), you need to explicitly set the dependencies. If your task group function returns an output that another task takes as I have a dag where I am using task decorators to pass the xcom's and task group to loop over a task. within a @task. send_email_notification is a more traditional This works because any task that returns a value is stored in xcom . You can use TaskFlow decorator functions (for example, @task) to pass data between tasks by providing the output of one task as an argument to Since I'm building this for people who use airflow and build dags and I'm not an actual airflow user or dag developer I want to get advice on doing it properly. This is not possible, and in general dynamic tasks are not recommended: The way the Airflow scheduler works is by reading the dag file, loading the tasks into the memory and then checks which dags and which tasks it need to schedule, while xcom are a runtime values that are related to a specific dag run, so the scheduler cannot relay on xcom values. Again dict values do not need to be serialized, but its keys need to be of primitive form. You should have a task that takes the parameter you It derives the PythonOperator and expects a Python function that returns a single task_id, a single task_group_id, or a list of task_ids and/or task_group_ids to follow. multiple_outputs. Is there any way in Airflow to create a workflow such that the number of tasks B. grep command will return-1 if no exception is found. I want my task to complete successfully only if all entries were processed successfully. If you are pushing with report_id key, then you need to pull with it as well. get_previous_dagrun() previous_task_state = False previous_xcom_value = False if previous_dagrun: previous_ti = . – if set, function return value will be unrolled to multiple XCom values. Defaults to False. I can use partial() and expand() to create tasks as well as here. Option 4: the "pythonic" way For example in my case I had to return 2 values from the upstream task, so a Tuple made sense to me. The SSHOperator returns the last line printed, in this case, "remote_IP". format but it is neither f-string nor having . Similarly, task dependencies are automatically generated within TaskFlows based on the functional invocation of tasks. class DecoratedOperator (BaseOperator): """ Wraps a Python callable and captures args/kwargs when called for execution. How to Trigger a Task based on previous task status? 2. Passing return value In this task, when some event happened, I need to store the timestamp and retrieve this value in next task run (for the same task) and update it again if required. How to pass pandas dataframe to airflow tasks. If you return a value from a function, this value is stored in xcom. I tried TaskInstance. First, create task1 and return the conditions of each short-circuit task: I make this function to get previous execution date, task state, xcom value. One of them returns a value that will later be used as a param of another operator. send_email is a more traditional Operator, but even it can use the return value of Is there any difference between the following ways for handling Airflow tasks failure? First way - def handle_failure(**kwargs): do_something(kwargs) def on_failure_callback(context): set_train_status_failed = PythonOperator( task_id="handle_failure", provide_context=True, queue="master", python_callable=handle_failure) return When orchestrating workflows in Apache Airflow®, DAG authors often find themselves at a crossroad: choose the modern, Pythonic approach of the TaskFlow API or stick to the well-trodden path of traditional operators (e. python. Even when I Each XCom value is tied to a DAG ID, task ID, and key. In below example code, see fourth_task. NOT return_value), the group expands to n=len(return_value) instances instead of n=len(specified_key). Dynamic instances which correspond to a valid index in the specified_key succeed, but What should be kept in mind is that if task returns results then these results will be available for “pull” in the next task. Airflow create new tasks based on task return value. xcom_pull(task_ids='dbt_task') logging. sensors. providers. It is possible to override the integer index for each mapped task in the Airflow UI with a name based on the task’s input. def check_last_run_date(context): previous_execution_date = False previous_dagrun = context['ti']. context import How do I reuse a value that is calculated on the DAG run between tasks? Reuse parameter value across different tasks in Airflow. branch_external_python`` which calls an external Python interpreter and the ``@task. But consider the following Knowing the size of the data you are passing between Airflow tasks is important when deciding which implementation method to use. 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 Bases: airflow. I have a workflow like below, Task2 generates a list and saves it to airflow variable "var1". Tasks can also be configured to push XComs by calling the xcom_push () method. xcom_pull() to access to returned value of first task. format function followed by the string. The following is my code segment: Below code creates the dag (the graph is also attached) which contains 2 PythonSensors and a PythonOperator. Both thresholds can either be a numeric value or another SQL query that evaluates to a numeric value. In my use case, I would write a python function that's called from a python operator that pulls the value from xcom and returns it, instead of using the pusher function. If there are any errors and you want the task to failed state then you need to raise an Exception inside your python callable function. XComs are implicitly set when using the BashOperator. Passing task outputs with AirFlow XCOM. ALL_SUCCESS: will trigger a task if all of the previous are succesfull (default one). However, I have not found any public documentation or successful examples of using the BranchPythonOperator to Airflow 2. bash task can help define, augment, or even build the Bash command(s) to execute. An alternative to this is to use ShortCircuitOperator. Custom airflow operator does not return values. html. I'm currently experimenting with Airflow for monitoring tasks regarding Snowflake and I'd like to execute a simple DAG with one task that pushes a SQL query to in Snowflake and should check the returned value that should be a number to be greater than a defined threshold. Ah, was totally unaware that you could directly use the return value of Python tasks as input to other tasks--I thought you had to pass from one task to another using XComs or something. :param is_done: Set to true to indicate the sensor can stop poking. Airflow did this optimization in PR. xcom_pull(task_ids='get_file_name')[0] }}" where [0] - used to access the first element of the Tuple - goes inside the Jinja template. You can do that with or without task_group, but if you want the task_group just to group these tasks, it will be useless because they are already grouped in No, an Operator class does not need to return anything. Stack Overflow. For example, when I do this in some function blah that is run in a ShortCircuitOperator:. Here's an example: from datetime import datetime from airflow import DAG from airflow. AFAIK the BranchPythonOperator will return either one task ID string or a list of task ID strings. Currently I am only returning the last XCOM from t1 but would like all of them. The documentation page on XComs is a good place to start. 3 with k8s executor. This is needed since the value that you are seeking exist only during run time. At the same time, use ignore_downstream_trigger_rules and trigger_rule to determine the node trigger rules, use ShortCircuitOperator or @task. "{{ task_instance. x, tasks had to be explicitly created and dependencies specified as shown below. I am running Airflow in a Docker container using the AIP-42 added the ability to map list data into task kwargs in airflow 2. Branch operator (like: BranchSQLOperator ) where the workflow branch based on the result of SQL query that checks if the table exist. Examples: BranchPythonOperator, TriggerDagRunOperator, DatabricksRunNowOperator, etc. I tried the following code def check_type_func(**kwargs): auto_job1 = '' execution_date = kwargs['execution_date'] I am pushing multiple values to XCOM based on values returned from a database. from datetime import datetime from airflow. To enable a There are three main ways to pass data between tasks in Airflow: We will discuss each of these methods in more detail below. def process_datetime(ti): dt = ti Using the TaskFlow API simplifies this a bit, but you can also pull a task's return value directly from the TaskInstance object in the context. Provide context is required to use the referenced **kwargs, which I usually name that as **context. In your case, you could access it like so from You may find it necessary to consume an XCom from traditional tasks, either pushed within the task’s execution or via its return value, as an input into downstream tasks. Bases: airflow. Hot Network Questions Is there a natural topology for sets of topological spaces? This is so easy to implement , follow any three ways: Introduce a branch operator, in the function present the condition; Use the trigger rule for the task, to skip the task based on previous parameter Note that if your virtualenv runs in a different Python major version than Airflow, you cannot use return values, op_args, op_kwargs, or use any macros that are being provided to Airflow through plugins. The second task needs this parameter as an input. 9. When next_task passes the xcom return_value into the python_callable 'next_task', it fails with: TypeError: string indices must be integers. At the moment, to be able to run the loop inside taskgroup, I have to pass the a hardcoded list. First, replace your params parameter to op_kwargs and remove the extra curly brackets for Jinja -- only 2 on either side of the expression. operators. Improve this question. pass step_id="{{ task_instance. Unfortunately, the only way you would know if they do/don’t return results is to dive into Operator’s source code (which I highly recommend as it will greatly improve your understanding how Airflow works). 2, Airflow writes the tasks return values to the log files. For the PythonOperator that is op_args, op_kwargs, and templates_dict. Dynamically adding airflow tasks on the basis of DB return value. Dict will unroll to XCom values with keys as XCom keys. decorators import task You are trying to create tasks dynamically based on the result of the task get, this result is only available at runtime. Hello world. Note the plural of the first argument. Skip to main content. The below code worked for me. e when the deferrable operator gets into a deferred state it actually trigger the tasks inside the task group for the next mapped instance Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company In Airflow (2. python; airflow; airflow-scheduler; def do_a(**kwargs): # Assuming that your TASK A is not returning a value return None task_a = PythonOperator(task_id='do_a', python_callable=do_a, provide_context=True, dag=dag The following parameters are supported in Docker Task decorator. Both methods do not return anything, as such it pushes nothing to xcom. However, post_execute can't seem to access whether or not the task succeeded or not (the status of the task instance isn't updated until after it is called). resolve (context, session = NEW_SESSION) [source] ¶ Consider the following example, the first task will correspond to your SparkSubmitOperator task: _get_upstream_task Takes care of getting the state of the first task Using BigQueryCheckOperator to run a query that return boolean value (True if table exist, False otherwise) then you will be able to pull the boolean value from XCOM in your BashOperator. In addition, if a task returns a value (either from its Operator’s execute() method, Variables are a generic way to store and retrieve arbitrary content or settings as a simple key value store within Airflow. Adding get_titanic_data >> process_titanic_data add the end of the DAG file I have an airflow operator that returns a string value and the task is named 'task1'. 1) I would like to use the output of a task with multiple_outputs in a dynamic task mapping call: @task(multiple_outputs=multiple_outputs) def get_variable_key(variable): return Because when I do task_1a >> task_1b, the return value of this operation is task_1b and start connects to it directly while the task_1a is orphaned. First Sensors creates a random integer list as data and a random boolean with 50% chance You can pull XCOM values from another dag, by passing in the dag_id to xcom_pull() (see the task_instance. The first two are declared using TaskFlow, and automatically pass the return value of get_ip into Return Values. def create_dag(dag_id, schedule, default_args): def getData(**kwargs): I have the following DAG with two SSHExecuteOperator tasks. This applies to all Airflow tasks, including sensors. bash TaskFlow decorator allows you to combine both Bash and Python into a powerful combination within a task. The "process_titanic_data" is most likely pulling nothing from XCom because it is running concurrently with the "get_titanic_data" task. None may be returned if the depended XCom has not been pushed. We are going to have a look at a few use cases where TaskFlow excels and see how it compares to writing a DAG using the traditional PythonOperator. The first two are declared using TaskFlow, and automatically pass the return value of get_ip into compose_email, not only linking the XCom across, but automatically declaring that compose_email is downstream of get_ip. Using PythonOperator, the returned value will be stored in XCOM by default, so all you need to do is add a xcom_pull in the BashOperator, something like this: also_run_this = bash_operator. How to create airflow task dynamically. ALL_DONE: at the end of all I have implemented dynamic task group mapping with a Python operator and a deferrable operator inside the task group. It derives the PythonOperator and expects a Python function that returns a single task_id, a single task_group_id, or a list of task_ids and/or task_group_ids to follow. Airflow 2 loosely coupling @task return values to receiving @task? 1. I first thought INFO - Task exited with return code 0 constituted a success, but I see some failure logs also have this. 2. Is there any way I can achieve this to get away from hardcoding? The same context dictionary is used for pre_execute, post_execute, on_execute_callback, and execute() itself. dumps(data) before returning it from Get_payload. xcom_pull(task_ids='{id}_push_function', key='some_id') }}" is not f-string, therefore, the {id} is printed as literal "{id}". Hot Network Questions The Desktop, Downloads and Documents folders have disappeared from the Sidebar Drill a hole into fiber cement siding Is biological stress related to covid lockdown policies a better explanation of Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company Airflow checks the bash command return value as the task’s running result. Inside Airflow’s code, we often mix the concepts of Tasks and Operators, and they are mostly interchangeable. brs vflz gpyrh khwnbo jghilag thz xoasev ewciv hwtqh myfqf