Airflow task return value. decorators import task.
Airflow task return value 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. You can access the If you want a task to have a maximum runtime, set its execution_timeout attribute to a datetime. python and allows users to turn a python function into an Airflow task. If not, value from the one single task instance is returned. So on I I would like to create a conditional task in Airflow as described in the schema below. asked Dec 15, 2020 I am build an airflow DAG with multiple PythonOperator nodes. The last line of output is stored as an XCom and this can be used in any other operator. How to pass pandas dataframe to airflow tasks. I have created a operator and it returns a token (just a string so hello world operator example works fine). def values_from_db(): # fetch data from DB. 0. Here, there are three tasks - get_ip, compose_email, and send_email_notification. You can open a PR to Airflow for adding the functionality you seek. branch`` as well as the external Python version ``@task. That is all working fine, In simple terms, PythonOperator is just an operator that will execute a python function. 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. This works with Airflow 2. task_id to reflect this relationship. You signed out in another tab or window. 2; Helm chart 1. 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. example_dags. 6. 10. example_task_group_decorator # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. ALL_SUCCESS: will trigger a task if all of the previous are succesfull (default one). Similarly, task dependencies are automatically generated within TaskFlows based on the functional invocation of tasks. Dict will unroll to xcom values with keys as keys. format but it is neither f-string nor having . 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. airflow xcom value into custom operator from dynamic task id. xcom_pull() to access to returned value of first task. expand? Using Airflow 2. In Airflow, tasks can return values that can be used by downstream tasks. The first task executes a stored procedure which returns a parameter. 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. 0, the invocation itself automatically generates the dependencies. You switched accounts on another tab or window. __bool__ [source] ¶ class airflow. 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). So after execution I go into xcom and check the return_value and its just a string (screenshot below). format function followed by the string. format(bucket, obj) for obj in my_list] kwargs['ti']. Actual class BranchPythonOperator (PythonOperator, BranchMixIn): """ A workflow can "branch" or follow a path after the execution of this task. For Apache Airflow, How can I pass the parameters when manually trigger DAG via CLI? Unlike in version 2. 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. Even when I Each XCom value is tied to a DAG ID, task ID, and key. Expections : I was expecting that the 'Hello,dbt!' will be printed in the logs. 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. Stack Overflow. Instead I got from DAGR 3. What happened. It derives the PythonOperator and expects a Python function that returns a single task_id or list of task_ids to follow. Wrap the data in json. 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 got stuck with controlling the relationship between mapped instance value passed during runtime i. issue with passing return value from a task as an argument to another task. xcom_pull(task_ids='{id}_push_function', key='some_id') }}" is not f-string, therefore, the {id} is printed as literal "{id}". Note, if a key is not specified to xcom_pull(), it uses the default of return_value. Here's an example: from datetime import datetime from airflow import DAG from airflow. This is the original code that I am working with. 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. 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. The xcom_pull() method - It’s used to pull a list of return values from one or multiple Airflow tasks. timedelta value that is the maximum permissible runtime. Apache Airflow version. Additional/less values can be returned by DB in each call. **New style:**. In below example code, see fourth_task. 15 dynamic task creation. 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. I want my task to complete successfully only if all entries were processed successfully. 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. 2, Airflow writes the tasks return values to the log files. However, I have not found any public documentation or successful examples of using the BranchPythonOperator to Airflow 2. If you return a value from a function, this value is stored in xcom. The following is my code segment: Below code creates the dag (the graph is also attached) which contains 2 PythonSensors and a PythonOperator. I first thought INFO - Task exited with return code 0 constituted a success, but I see some failure logs also have this. Allows a workflow to “branch” or follow a path following the execution of this task. 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. At the moment, to be able to run the loop inside taskgroup, I have to pass the a hardcoded list. dag_id=dag10 I am trying to use XCom Push and Pull to use Variables between tasks. This is used to determine how many task instances the scheduler should create for a downstream using this XComArg for task-mapping. 2. The @task. short_circuit to create task nodes. 1. When next_task passes the xcom return_value into the python_callable 'next_task', it fails with: TypeError: string indices must be integers. set_upstream(task1). The issue I have is figuring out how to get the BashOperator to return something. 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. Since the task_ids are evaluated, or seem to be upfront, I cannot set the dependency in advance, any help would be appreciated. I am using pre_task5 to check condition for task5 execution. AFAIK the BranchPythonOperator will return either one task ID string or a list of task ID strings. xcom_pull(dag_id='my_dag', task_ids=f"execute_my_steps. None may be returned if the depended XCom has not been pushed. They just do the job. { task_instance. 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. from airflow import DAG from airflow. I am not sure what the key and values should be for a xcom_push function. :param is_done: Set to true to indicate the sensor can stop poking. A bit more involved @task. 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. 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'. Inside Airflow’s code, we often mix the concepts of Tasks and Operators, and they are mostly interchangeable. 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. 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. Using Python conditionals, other function calls, etc. Instead, you can use the new concept Dynamic Task Mapping to create multiple task at runtime. 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. 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. But, not sure how to proceed with that. 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. 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. And it's still the old syntax, and the Airflow docs promises. In terms that create_job_flow task must run and save the value to the database before add_steps task can read the value. 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. py:156} INFO - Task exited with return code 1 [2022-06-19, 18:27:00 +08] {taskinstance. Task should fail otherwise. get_records method (i am returning a small amount of kines - usually a single cell). 3 with k8s executor. I tried TaskInstance. branch_external_python`` which calls an external Python interpreter and the ``@task. Please use the following instead: from airflow. How to create airflow task dynamically. skipmixin. 2. sensors. 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. { 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. the output varies on each execution. Whether to use dill or pickle for serialization. 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. 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. 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. send_email_notification is a more traditional This works because any task that returns a value is stored in xcom . 3: Airflow create new tasks based on task return value. Beta Was this translation helpful? Give feedback. 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. 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. Below is the DAG code. The above workflow was created by the Python scripts below. 7. multiple_outputs. You might want to check out Airflow's XCOM: https://airflow. return the entry saved under key='return_value' The {{ }} is syntax of Jinja engine that means "print" the value. I have a python callable process_csv_entries that processes csv file entries. python_command. Improve this question. Hey so I am using Airflow 2. 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. 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. 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. 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. Both thresholds can either be a numeric value or another SQL query that evaluates to a numeric value. :param xcom_value: An optional XCOM value to be returned by the operator. Using XComs. excluding bytes, can be returned as can dicts. I'm expecting the file size under Value. grep command will return-1 if no exception is found. 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. The SSHOperator returns the last line printed, in this case, "remote_IP". The first two are declared using TaskFlow, and automatically pass the return value of get_ip into Return Values. The list is returned by the task but I cannot access it inside the taskgroup. Ask Question Asked 1 year, 3 months ago. I am trying to access XCOM value while learning Airflow, but every time, I get None returned. My second function is to receive that file and delete null values and return the DF again without null values. 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. I'm mostly brand new to airflow. 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. I have created an operator SnowflakeGetDataOperator that returns the snowflake hook. Dynamically adding airflow tasks on the basis of DB return value. The "process_titanic_data" is most likely pulling nothing from XCom because it is running concurrently with the "get_titanic_data" task. * 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. The problem is Airflow: Best way to store a value in Airflow task that could be retrieved in the recurring task runs. task. An alternative to this is to use ShortCircuitOperator. XComs can be “pushed” (sent) or “pulled” (received). 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. 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. Currently I am only returning the last XCOM from t1 but would like all of them. Examples: BranchPythonOperator, TriggerDagRunOperator, DatabricksRunNowOperator, etc. Airflow 2 loosely coupling @task return values to receiving @task? 1. Ask Question Asked 3 years, 10 months ago. – if set, function return value will be unrolled to multiple XCom values. xcom_pull() function documentation). base. 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. One of them returns a value that will later be used as a param of another operator. """ from __future__ import annotations import random import sys import tempfile import The same workflow with grouping. bash task can help define, augment, or even build the Bash command(s) to execute. 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. In Airflow 1. The task_id(s) returned should point to a task kwargs['task_instance']. Returns. This is because if a task returns a result, Airflow will automatically push it to XCom under the return_value key. sample value - [& The returned value, which in this case is a dictionary, will be made available for use in later tasks. operators. 0. The custom operator pushes a string True or False as an Xcom Value which then read by the BranchPythonOperator. This import airflow from datetime import datetime, timedelta from airflow. I have two Airflow tasks that I want to communicate. xcom_pull(task_ids='ssh', dag_id='adhoc_***', key='return_value') }} The SSHOperator code seems to return the aggregated stdout (base64 encoded). branch_virtualenv`` which builds a temporary Python virtual environment. 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. As for number of queries: I assume that by "repeats a single query" you are asking if it execute a query per task_id. Only on_failure_callback and on_success_callback contain this data. Airflow 2. If i'm correct, airflow automatically pushes to xcom when a query returns a value. Dict will unroll to XCom values with keys as XCom keys. xcom_pull accepts task_ids: Optional[Union[str, Iterable[str]]] but with the same key. xcom_pull(task_ids='dbt_task') logging. If you are pushing with report_id key, then you need to pull with it as well. 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. Doing so I see the value in the xcom value for the dag execution. If the task to pull is mapped, an iterator (not a list) yielding XComs from mapped task instances is returned. class DecoratedOperator (BaseOperator): """ Wraps a Python callable and captures args/kwargs when called for execution. models I have two tasks in an Airflow DAG like below. . 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). Defaults to False. Airflow 2 loosely coupling @task return values to receiving @task? 3. 0 I know I'm missing something basic, but I can't figure out what it is. The answer is No. 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. 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. either pushed within the task's execution or via its return value, as an input into downstream tasks. otherwise the value of the xcom id "return_value" and its value its a dictionary. The way to access fields from the Tuple I'm passing then is the following: "{{ task_instance. Using Airflow 2. How to Trigger a Task based on previous task status? 2. info(value) ` print_task=DbtRunOperationOperator(task_id='dbt_task',macro='return_hello',do_xcom_push=True) print_task. I am using the Snowflake database. ' port = '5439' sslmode = 'require' ") task_instance = context['task_instance'] task_instance. g. 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. Airflow - getting the execution_date in task when calling an Operator. get_previous_dagrun() previous_task_state = False previous_xcom_value = False if previous_dagrun: previous_ti = . partial( task_id="invoke_lambda", retries=1, retry_delay=timedelta(seconds=30), python_callable=invoke_lambda_function, ). This works as long as you triggered the subdag using the same execution date as your current DAG. from datetime import datetime from airflow. 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. x, tasks had to be explicitly created and dependencies specified as shown below. 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. Bases: airflow. Airflow Taskflows: Chaining tasks with return values. Checking the xcom page, I'm not getting the expected result. These values are passed as arguments to the downstream task's function. 1 version and Python 3. 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. {'NewMeterManufacturer': manufacturer, 'NewMeterModel': model } You signed in with another tab or window. Problem. Tasks can also be configured to push XComs by calling the xcom_push () method. models. From Airflow documentation. XComs are implicitly set when using the BashOperator. "{{ task_instance. issue with passing return value from a task as an argument to I am new to Python and new to Airflow. ALWAYS: will always trigger the task. 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. Passing task outputs with AirFlow XCOM. PythonOperator, airflow. Airflow provides a very intuitive 'new_config' generates the new config file, and 'next_task' tries to pull in the xcom value. The second task needs this parameter as an input. 3 if that makes a difference. For example, INFO - Task exited with return code 1 or INFO - Task exited with return code 0 or INFO - Process psutil. So it's better you use xcoms to pass data between tasks rather than as task callable parameters. 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. But when I schedule this Dag on airflow it works smoo Skip to main content. 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. 5. Iterating through a python list of dictionaries using a xcom return value. So far, we create all the tasks in the workflow, we need to define the dependency among these tasks. 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. Airflow treats non-zero return value as a failure task, however, it’s not. But how can I store and access this returned value? For example: I have the following functions. When attempting to use dynamic task mapping over a task_group() based on a non-standard XCom (e. Second, and Here, there are three tasks - get_ip, compose_email, and send_email. providers. Airflow Dynamically adding airflow tasks on the basis of DB return value. 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 . 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. At the same time, use ignore_downstream_trigger_rules and trigger_rule to determine the node trigger rules, use ShortCircuitOperator or @task. The returned value, which in this case is a dictionary, will be made available for use in later tasks. How can I set the function argument to a task that is the return from a previous task / function that was run. As the number of values returned may vary, I am using the index as the key. Process(pid=00000, status='terminated') (00000) terminated with exit code -15. 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. For the PythonOperator that is op_args, op_kwargs, and templates_dict. Both methods do not return anything, as such it pushes nothing to xcom. 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. py:1395} INFO - Marking task as UP_FOR_RETRY. I can use partial() and expand() to create tasks as well as here. In contrast, with the TaskFlow API in Airflow 2. That's trivially achieved by templating the execution_date value:. 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. I have a workflow like below, Task2 generates a list and saves it to airflow variable "var1". use_dill. 8. Runtime/dynamic generation of tasks in Airflow using JSON representation of tasks in XCOM. 11. html. 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. However, the SSHOperator's return value is encoded using UTF-8. 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. 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. So any return value of PythonOperator is saved to XCom (something to be careful with!). TriggerRule. This is needed since the value that you are seeking exist only during run time. I have a dag that begins with a k8s task that queries a list of table names that need to be it t1 = PythonOperator. 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 . This stores the returned value as an "XCom" in Airflow. Airflow create new tasks based on task return value. Hello world. Use the SQLThresholdCheckOperator to compare a specific SQL query result against defined minimum and maximum thresholds. 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. 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. Airflow PythonOperator task fail - TypeError: The key has to be a string Unable to store Airflow task objects to a dictionary. 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. This applies to all Airflow tasks, including sensors. def create_dag(dag_id, schedule, default_args): def getData(**kwargs): I have the following DAG with two SSHExecuteOperator tasks. xcom_push(key='return_value', value=full_paths) As suggested by @Josh Fell in the comments, I had two mistakes in my DAG. 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. 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. Airflow tasks in a loop based on dag_run conf value. models import BaseOperator import pendulum class CustomDummyOperator(BaseOperator): # @apply_defaults deprecated now, no Check values against a threshold¶. def check_last_run_date(context): previous_execution_date = False previous_dagrun = context['ti']. It seems small enough to not need the complexity of being turned into a Series at this point. org/docs/apache-airflow/stable/concepts/xcoms. 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. Review resource requirements for this operation, and call list() explicitly to suppress this message. 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. From the outline below it should have only two paths forward, clean_headers_Post_Perfromance or no_file_found. But when I schedule this Dag on airflow it works smoothly. example: var1 = [1,2,3,4] branch_operator takes the value from var1 Deprecated function that calls @task. xcom key/value screenshot. How do I, in the next task, retrieve all the values from the previous task. To send data from one task to another you can use Airflow XCOM feature. 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. http. 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. xcom_pull(task_ids='get_file_name')[0] }}" where [0] - used to access the first element of the Tuple - goes inside the Jinja template. Could please exp I am trying to pass a Python function in Airflow. The task_id(s) and/or task_group_id(s) returned should point to a It shows how to use standard Python ``@task. Introduction to the TaskFlow API and Airflow decorators. 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. 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. 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. When a task pushes an XCom, it makes it generally available to other tasks. Custom airflow operator does not return values. Note the plural of the first argument. Airflow 1. decorators import task. ONE_FAILED: will trigger a task if one of the previous failed. 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. 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 am using Apache Airflow 2. 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. I am using airflow, i want to pass the output of the function of task 1 to the task 2. I am not seeing consistency. 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. If set, function return value will be unrolled to multiple XCom values. 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. python. 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. execution_timeout controls the Here, there are three tasks - get_ip, compose_email, and send_email_notification. ; Remove multiple_outputs=True from the task decorator of Get_payload. Follow edited Dec 15, 2020 at 11:53. 58. NOT return_value), the group expands to n=len(return_value) instances instead of n=len(specified_key). For example, when I do this in some function blah that is run in a ShortCircuitOperator:. 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. dumps(data) before returning it from Get_payload. 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. paths = ['gs://{}/{}'. ; Final code: import json from airflow. pass step_id="{{ task_instance. SkipMixin. Branch operator (like: BranchSQLOperator ) where the workflow branch based on the result of SQL query that checks if the table exist. Is there any way in Airflow to create a workflow such that the number of tasks B. For example, use conditional logic to determine task behavior: Answering your questions: There is no such feature. within a @task. 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). code:: python from airflow. Currently the check_for_Post_Performance returns cleans_headers_for_gcm task and I'm at a total loss how that happens. 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. As a result of this behaviour, my entire dataframe (84mb) is being written to a log file at every task execution. 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. Reload to refresh your session. 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. 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. First, replace your params parameter to op_kwargs and remove the extra curly brackets for Jinja -- only 2 on either side of the expression. 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'. The documentation page on XComs is a good place to start. 3. http import Here, there are three tasks - get_ip, compose_email, and send_email. Provide context is required to use the referenced **kwargs, which I usually name that as **context. 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. What I'm getting is key: return_value ; Value:ODAwMAo=. You can observe XComs via the Grid View -> select task -> XCom, or see all XCom values via Admin -> XComs. apache. Airflow did this optimization in PR. 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. bash TaskFlow decorator allows you to combine both Bash and Python into a powerful combination within a task. decorators import dag, task from airflow. xcom_pull(task_ids='Y') I expected to get value of xcom from task instance Y in DAGR 1. :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. 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. external_python decorator allows you to run an Airflow task in pre-defined, immutable virtualenv (or Python binary installed at system level without virtualenv). The below code worked for me. Again dict values do not need to be serialized, but its keys need to be of primitive form. timestamp = time_of_run. Fetching XCOM returns None value in Airflow. decorators import task from airflow. Skip to main content. Actually the main function of an operator is the execute method, and most of them does not return anything. 9. sbog nrsh gwzoscf xzp akuf qkvut dxe qhbdw fxitm yccaew