Airflow task return value. format(bucket, obj) for obj in my_list] kwargs['ti'].

Airflow task return value Coercing mapped lazy proxy return value from task forward_values to list, which may degrade performance. Returns. decorators import dag, task from airflow. That is why I added a task downstream [2022-06-19, 18:27:00 +08] {standard_task_runner. Let's say the 'end_task' also Inside Airflow’s code, we often mix the concepts of Tasks and Operators, and they are mostly interchangeable. issue with I would like to create a conditional task in Airflow as described in the schema below. You just need to do : task1 >> task2 Operators have trigger_rule argument which sets the condition when to run. xx}} call. 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. def Here, there are three tasks - get_ip, compose_email, and send_email_notification. you can do @task(show_return_value_in_logs=False) or @task. This means that the b64decode function must be invoked within the template string. Apache Airflow not running any task. Retrieve SQL value in Airflow. external_python decorator allows you to run an Airflow task in pre-defined, immutable virtualenv (or Python binary installed at system level without virtualenv). example: var1 = I have a dag where I am using task decorators to pass the xcom's and task group to loop over a task. In terms that create_job_flow task must run and save the value to the database before add_steps task can read the value. models import TaskInstance from airflow. Objects that are not under control of Airflow, e. Skip to main content. sample value - ["val1", "val2", "val3"] return values for val in values_from_db(): task1(val) >> task2(val) values_from_db method will be called a lot of times to capture changes in the DAG file. task. View more examples on how to use Airflow task decorators in the Astronomer webinars and the Apache Airflow TaskFlow API tutorial. If you want to use additional task specific private python repositories to setup the virtual environment, you can pass the index_urls 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. These values are passed as arguments to the downstream task's function. 3. More information about trigger rules can be found here. utils. The list is returned by the task but I cannot access it inside the taskgroup. 7. Branch operator (like: BranchSQLOperator ) where the workflow branch based on the result of SQL query that checks if the table exist. I am not seeing consistency. Airflow treats non-zero return value as a failure task, however, it’s not. 1. How can I get the actual value inside my step function ? Thanks and happy holidays That strategy seems to work quite all for 96% of the entire tables of the schema, the thing is, as I said before, when the table is very large, around 60 million records, the task runs for a while, about 30 minutes, but normally after that, Airflow kills the task, just like that. google. decorators import dag, task @dag (schedule_interval = None, start_date = pendulum. This is used to determine how many task instances the scheduler should create for a downstream using this XComArg for task-mapping. But how can I store and access this returned value? For example: I have the following functions. 3 issue with passing return value from a task as an argument to another task. I'm doing something similar (dependencies A > B > C) and I've solved the approach using the XCOM pushed by default by the previous task. Ask Question Asked 3 years, 7 months ago. models import DAG from airflow. branch def choose_best_model(accuracy): I would like to calculate dates before I created next task, Ideally one task per date. 4. Is there any way to store the return value of a task in Python variable get_task_map_length (run_id, *, session) [source] ¶ Inspect length of pushed value for task-mapping. If not, value from the one single task instance is returned. I have also set the dependency, still no luck. So on I have several functions. 2, Airflow writes the tasks return values to the log files. hooks. The code in the question won't work as-is because the loop shown would run when the dag is parsed (happens when the scheduler starts up and periodically thereafter), but the data that it would loop over is not known until the task that generates it is actually run. I am trying to implement basic ETL job, using Airflow, but stucked in one point: I have 3 functions. :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 We're using Airflow 2. models import BaseOperator from airflow. If this behavior is not something that you want, you can disable it by Airflow does have a feature for operator cross-communication called XCom. I want my task to complete successfully only if all entries were processed successfully. task_group ¶ Implements the @task_group function decorator. Only on_failure_callback and on_success_callback contain this data. 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. def values_from_db(): # fetch data from DB. 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. Create dynamic tasks depending on the result of an sql query in airflow. From Airflow documentation. I first thought INFO - Task exited with return code 0 constituted a success, but I see some failure logs also have this. I am trying to pass a Python function in Airflow. Related questions. For example in my case I had to return 2 values from the upstream task, so a Tuple made sense to me. . This option will work both for writing task’s results data or reading it in the next task that has to use it. There is a pandas dataframe (df) getting generated as a query output in script. aws. But the printed value appears as 'None'. Return Values. expand? Using Airflow 2. The Transform and Load tasks are created in the same manner as the Extract task shown A Task is the basic unit of execution in Airflow. apache. This virtualenv or system python can also have different set of custom libraries installed and must be made available in all workers that can execute the 'new_config' generates the new config file, and 'next_task' tries to pull in the xcom value. so now I have this task in the dag: check_last_run_date=SnowflakeGetDataOperator( task_id='check_last_run_date', Iterating through a python list of dictionaries using a xcom return value. python_command. cloud. 1. 0 Airflow 2 - Creating 2 dynamic tasks within a TaskGroup that finish before the Passing a list of values from one task to another; Another way to pass data between tasks is to pass a list of values. one below: 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. You want to decode the XCOM return value when Airflow renders the remote_filepath property for the Task instance. Review resource requirements for this operation, and call list() explicitly to suppress this message. Is there any way that I can get a specific value from the spark script? One note: You will not be able to see the mapped task groups in the Airflow UI or be able to access their logs just yet, the feature is still quite new and the UI extension should come in 2. operators. json. On your note: end_task = DummyOperator( task_id='end_task', trigger_rule="none_failed_min_one_success" ). XComs can be “pushed” (sent) or “pulled” (received). { task_id }", key='return_value') }}", The explanation why it happens: In Airflow task_id is unique but when you use TaskGroup you can set the same task_id in different TaskGroups. __bool__ [source] ¶ class airflow. I've found examples of this and can pass a static JSON to the next DAG using conf: an Airflow task. 1 How to get DAG information from within a task in Python & Airflow. One of them returns a value that will later be used as a param of another operator. How to create airflow task dynamically. Milan Milan. py:156} INFO - Task exited with return code 1 [2022-06-19, 18:27:00 +08] {taskinstance. value (Any) – the object to serialize. Viewed 7k times Then, provided you used an ExternalTaskSensor sensor to wait for the specific task to have completed or used wait_for_completion=True in your TriggerDagRunOperator() task, you can later on pull the I am build an airflow DAG with multiple PythonOperator nodes. Note, if a key is not specified to xcom_pull(), it uses the default of return_value. Using XComs. There are a few best practices for passing How can I set the function argument to a task that is the return from a previous task / function that was run. The first two are declared using TaskFlow, and automatically pass the return value of get_ip into There are three main ways to pass data between tasks in Airflow: We will discuss each of these methods in more detail below. The way to access fields from the Tuple I'm passing then is the following: "{{ task_instance. int16 will need a registered serializer and deserializer. It is also common to use Jinja templating to access XCom values in the parameter of a traditional task. parse_boolean). xcom_pull(task_ids='Y') I expected to get value of xcom from task instance Y in DAGR 1. 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. 2 so I wasn't able to take advantage of dynamic task mapping with the @task_group decorator. XComs are principally defined by a key, value, and timestamp, but also track attributes like the task/DAG that created the XCom and when it should become visible. In addition, if a task returns a value (either from its Operator’s execute() method, or from a PythonOperator’s python_callable function), then an XCom containing that value is automatically pushed. To remove this filter, pass key=None (or any desired value). Airflow dynamic DAG and Task Ids. But I think the real issue is how airflow. Dict will unroll to XCom values with keys as XCom keys. To do this, you can use the `list_task` operator. Airflow 2 loosely coupling @task return values to receiving @task? 3. return the entry saved under key='return_value' The {{ }} is syntax of Jinja engine that means "print" the value. For example, when I do this in some function blah that is run in a ShortCircuitOperator:. values (): You signed in with another tab or window. Astronomer docs on this feature for more info but the first StackOverflow link above demonstrates that as well. 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('create_job_flow', key='return_value')}}", which causes my step to fail. datetime (2021, 1, 1, tz = "UTC"), catchup = False, tags = ['example'],) def tutorial_taskflow_api_etl (): """ ### TaskFlow API Tutorial Documentation This is a simple ETL data pipeline example which demonstrates the use of the TaskFlow API using Virtual environment setup options¶. You signed out in another tab or window. paths = ['gs://{}/{}'. Review resource requirements for this EDIT: For Airflow >= 2. 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 Each XCom value is tied to a DAG ID, task ID, and key. kubernetes decorator being "traditional" tasks -- however, what works (and is the way it's supposed to work in a taskflow dag, I think) was to import json import pendulum from airflow. Parameters. If a I'm not exactly sure what you are trying to do but the code you posted in the python function doesn't really execute the operator. I tried TaskInstance. See the template_fields, template_fields_renderers and template_ext attributes of the PythonOperator and BashOperator. gcs import GCSHook class GCSUploadOperator(BaseOperator) We have to remember that this is for sure not a production solution Especially if we would like to have another task after the group of dynamic tasks. Original Answer: Deprecated Variable. Description {{execution_date}}the execution date (logical date), same as logical_date {{next_execution_date}}the logical date of the next scheduled run (if applicable); you may be able to use data_interval_end instead {{next_ds}}the next execution date as YYYY-MM-DD if exists, else None {{next_ds_nodash}}the next execution date as YYYYMMDD if exists, One of the best use cases is to run one branch or another depending on the input of a user via Airflow parameters. And it's still the old syntax, and the Airflow docs promises. Commented Jun 29, 2023 at DAGs¶. ALL_SUCCESS: will trigger a task if all of the previous are succesfull taskX complains that there's no XCom return value from taskB (which is to be expected, as the underlying function was stopped before it returned). When only the order of task execution is important, don't pass the return value of the first task as a parameter to the second task - instead use >> to explicitly create the relationship. xcom_pull accepts task_ids: Optional[Union[str, Iterable[str]]] but with the same key. There are three basic kinds of 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. Since the task_ids are evaluated, or seem to be upfront, I cannot set the dependency in advance, any help would be appreciated. pushed to XCom (by the @task decorator). So now if I mark the dependency of taskX The @task. Is there any way I can achieve this to get away from hardcoding? I am new to Python and new to Airflow. For example: def forward_values (values): return values # This is a lazy proxy! will emit a warning like this: Coercing mapped lazy proxy return value from task forward_values to list, which may degrade performance. In contrast, with the TaskFlow API in Airflow 2. In Airflow, tasks can return values that can be used by downstream tasks. There are three ways to expand or collapse task groups: Click on the note (for example +2 tasks). When the decorated function is called, a task group will be created to represent a collection of closely related tasks on the same DAG that should be grouped together when the DAG is displayed graphically. log. Using Airflow 2. The third task, task_3, receives the value returned by task_2 and prints the value. I have created an operator SnowflakeGetDataOperator that returns the snowflake hook. jobconfig. My second function is to receive that file and delete null values and return the DF again without null values. python`` and allows users to turn a Python function into an Airflow task. Do you expect task1 to fail or success? A bit more involved @task. multiple_outputs. json_serialize_legacy (value) [source] ¶ JSON serializer replicating legacy watchtower behavior. Below is the DAG code. days'] if extract_days > 5 : return 'task_2' else value of a task is airflow. Tasks can push XComs at any time by calling the xcom_push() method. Using the @task allows to dynamically generate task_id by calling the decorated function. Any value that the execute method returns is saved as an Xcom message under the key return_value. g. There is a catch though, we have to make this function available in the template context by providing it as a parameter or on the DAG level as a user In Airflow (2. def sum(a, b): return a + b def compare(c, d): return c > d And the following dag: How to use the result of a BashOperator task as argument of another Airflow task? 0 Airflow, how to pass variables from BashOperator task to another. Operator [source] 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. 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. Can A bit more involved @task. To enable a 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. The default value is all_success thus no need to specifically mention it. xcom_pull(key=key)}" branch = BranchPythonOperator( task_id="branch", python_callback=branch_func ) tasks = [BaseOperator(task_id=f"task_{i}") for i in range(3)] branch >> tasks In some cases it's also not good to use this method (for example when I've 100 possible tasks), in those cases I'd You are trying to create tasks dynamically based on the result of the task get, this result is only available at runtime. Modified 3 years, 7 months ago. In the code snippet below, the first task return_greeting will push the string "Hello" to XCom, and the second task greet_friend will use a Jinja template to pull that value from the ti (task instance) object of the Airflow context and print Hello friend! :) into the logs. * 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. Follow answered Apr 3, 2019 at 13:06. dag_id=dag10-deferred Airflow checks the bash command return value as the task’s running result. If I can figure out how to pass a variable value at the TaskGroup level, so it uses that value in all sub tasks, then I should be able to meet my requirement. Dict will unroll to XCom values with its keys as XCom keys. set_upstream(task1). from datetime import datetime, an Airflow task. :param python_callable: A reference to an object that is callable:param op_kwargs: 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 legacy watchtower@2. To remove the filter, pass key=None. decorators. How do I pass the xcom return_value into the python callable 'next_task' as a dictionary? As that is what it Remember that many operators automatically push results to XCom under the return_value key. Any object that can be pickled can be used as an XCom value, so users should make sure to use objects of appropriate size. dates import days_ago # These args will get passed on to each operator # You can override them on a per-task basis during operator initialization default_args = {'owner': takes in the collection of order data and computes the total order value. 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. This works, but now we are actually not defining the dependencies between tasks, but Airflow return values? Still feels like a hack. 3. The following is my code segment: step_id="{{ task_instance. Improve this answer. If set to False (default), only at most one XCom value is pushed. {'NewMeterManufacturer': manufacturer, 'NewMeterModel': model } class DecoratedOperator (BaseOperator): """ Wraps a Python callable and captures args/kwargs when called for execution. org/docs/apache-airflow/stable/concepts/xcoms. 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. send_email_notification is a more traditional 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 If an XCom value is supplied when the sensor is done, then the XCom value will be pushed through the operator return value. Dynamic Task Mapping with Decorators in Airflow 2. The docs of _get_unique_task_id states:. Any pointers are much appreciated. 51 4 4 bronze badges. I would like to pass the result from stored procedure call status_return() back to the task-- Create a task that calls the stored procedure every hour create or replace task call_SP warehouse = SMALL schedule = '1 import json from datetime import datetime from airflow. As a result of this behaviour, my entire dataframe (84mb) is being written to a log file at every task execution. Airflow PythonOperator task fail - TypeError: The key has to be a string Unable to store Airflow task objects to a dictionary. I can use partial() and expand() to create tasks as well as here. 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 Problem. @user3595632 For the SimpleHttpOperator in that example, the data parameter is a template field so Jinja templating is completely fine to use. op_kwargs (dict (templated)) – a dictionary of keyword arguments that will get unpacked in your function. from airflow import DAG, XComArg from datetime import datetime from airflow. t2 = There is a slight difference between the two ways you are pulling the XCom in your code snippets: one has task_ids=["task_1"] (a list arg) while the other has task_ids="task_1" (a str arg). xcom_pull(task_ids='get_file_name')[0] }}" where [0] - used to access the first element of the Tuple - goes inside the Jinja template. 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. Yes, it means you have to write a custom task like e. In summary, xcom_pull is a versatile tool for task communication in Airflow, and when used correctly, it can greatly Unlike in version 2. I am not sure what the key and values should be for a xcom_push function. send_email is a more traditional Operator, but even it can use the return value of The best way to do this is to push your value into XCom in get_job_dts, and pull the value back from Xcom in first_task. xcom_pull() }} can only be used inside of parameters that support templates or they won't be rendered prior to execution. Even though the entire data argument is not wholly within a Jinja expression, any task = BashOperator( task_id=name, bash_command=spark_cmd, dag=dag, **kwargs ) return task The problem is that what I get back is the last print of the Airflow's log. Hot Network Questions MeshFunctions and MeshShading manipulation to get the desired plot Are pigs effective intermediate hosts of new viruses, due to being susceptible to human and avian Here, there are three tasks - get_ip, compose_email, and send_email. You switched accounts on another tab or window. python import 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. @task def my_task() Parameters. If you are pushing with report_id key, then you need to pull with it as well. TriggerRule. About; Products if xcom_value >= 5: return "big_task" # run just this one task, skip all else elif xcom_value >= 3: return Airflow is a distributed system - each task runs potentially ona different machine. The virtual environment is created based on the global python pip configuration on your worker. format(bucket, obj) for obj in my_list] kwargs['ti']. Airflow did this optimization in Source code for airflow. decorators import task from airflow import DAG with DAG( "hello_world", start_date=datetime(2022, 1, 1), schedule_interval="@daily", catchup=False, ) as dag: @task() def get_name(): return { 'first_name': 'Hongbo', 'last_name': 'Miao', } get_name() Currently I am using @task(). In the Grid View of the Airflow UI, task groups have a note showing how many tasks they contain. Airflow tasks iterating over list should run sequentially. I would want to send email only if df isn't empty. The expected scenario is the following: Task 1 executes If Task 1 succeed, then execute Task 2a Else If Task 1 . bash TaskFlow decorator allows you to combine both Bash and Python into a powerful combination within a task. within a @task. context import get_current_context def my_task(): context = get_current_context() ti = context["ti"] Current context will only have value if this Return value from one Airflow DAG into another one. templates_dict (dict[]) – a dictionary where the values are templates that task:airflow. xcom_push(key=db_con, value = db_log) return (db_con) Could anyone assist in getting the correct key and value for I have an airflow DAG which has task of sending an email. decorators import task. This key is automatically given to XComs returned by tasks (as opposed to being pushed manually). xcom_pull() to access to returned value of first task. 5 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. The good news is that those are not being executed by the Deprecated function that calls @task. providers. 0 Execute gcloud commands with python I am using 'airflow test' to first run task 'set-tag' and then run 'get-tag' hoping to see the 'test_value' printed. It's because the entire data argument can be templated. 0, the invocation itself automatically generates the dependencies. About; Products OverflowAI; 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 the following. cloudwatch_task_handler. 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? Hi thanks for the answer. sensors. 11. key = "return_value",) # will print out a list of results from map index 2 and 3 of the add_42 task print (pulled_xcom) # creating 6 mapped task group instances of the task group group1 (2. send_email is a more traditional Operator, but even it can use the return value of from airflow. I am using the Snowflake database. I have a branch task (choose_best_model) and I would like to know if it's possible to return 'is_accurate' with the data @task. At the moment, to be able to run the loop inside taskgroup, I have to pass the a hardcoded list. """ total_order_value = 0 for value in order_data_dict. 6. example_task_group_decorator # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. Using Python conditionals, other function calls, etc. I suspect you might be wondering how it's used for the start key in the data dict. Hot Network Questions Calls ``@task. Based on the document https://airflow Should a language Answering your questions: There is no such feature. bash task can help define, augment, or even build the Bash command(s) to execute. Airflow will infer that if you pass a list of task IDs, there should be multiple tasks to pull XComs from and will return a list 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 ["ti"] **New style:**. :param xcom_value: An optional XCOM value to be returned by the operator. grep command will return -1 if no exception is found. code:: python from airflow. python and allows users to turn a python function into an Airflow task. task_group import TaskGroup from airflow. For example, a simple DAG could consist of three tasks: A, B, airflow. Below code creates the dag (the graph is also attached) which contains 2 PythonSensors and a PythonOperator. You need to set render_template_as_native_obj=True in your DAG constructor. kwargs['task_instance']. This should work just fine: The problem is that, when I check the EMR, instead of seeing the --cluster-id j-1234 in the load_data step, I see --cluster-id "{{task_instance. 0 and want to trigger a DAG and pass a variable to it (an S3 file name) using TriggerDagRunOperator. task_ids (str or iterable of strings (representing task_ids)) – Only XComs from tasks with matching ids will be pulled. You should have a task that takes the parameter you 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 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. For example: @task def first_task (): return "hello world" The task in airflow they have a trigger rule, which can be pass to the decorators you are using. decorators import dag, task @dag (schedule_interval = None, start_date = datetime (2021, 1, 1), catchup = False, tags = ['example']) def tutorial_taskflow_api_etl (): """ ### TaskFlow API Tutorial Documentation This is a simple ETL data pipeline example which demonstrates the use of the TaskFlow API using three simple Even if you use something like the following to get an access to XCOM values generated by some upstream task: from airflow. XComs are a way to pass data between tasks in What is the appropriate way to reference an array parameter in . decorators import task from airflow. We’ll cover this topic later. The problem is Dynamically adding airflow tasks on the basis of DB return value. Tasks can also be configured to push XComs by calling the xcom_push () method. So unless you use Local Executor (there all tasks run on single machine and can use local storage for storing the state) you somehow HAVE TO be able to move state information from one machine to the other. 2. Hot Network Questions Realization of fundamental group When generating tasks dynamically, I need to have Task 2 be dependent of Task 1, Task1 >> Task 2 or task2. My Airflow version is behind at 2. 5. This is needed since the value that you are seeking exist only during run time. multiple_outputs – if set, function return value will be unrolled to multiple XCom values. Dynamically generate multiple tasks based on output dictionary from task in Airflow. task_decorator_factory (python_callable = None, *, multiple_outputs = None, decorated_operator_class, None) – If set to True, the decorated function’s return value will be unrolled to multiple XCom values. 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 I am trying to access XCOM value while learning Airflow, but every time, I get None returned. Here, there are three tasks - get_ip, compose_email, and send_email. Add a comment | Your Answer Reminder: use xcom_pull to pull a key's value that same task pushed - Airflow. You might want to check out Airflow's XCOM: https://airflow. 0. 3 with k8s executor. You can use the Python code to perform a calculation and then return the results. previous_schedule(datetime. The first set of keys are the check names, which are referenced in the templated query the operator builds. There are ways to do something similar though. In the dynamic world of Apache Airflow®, there's no one-size-fits-all approach to writing your DAGs. class 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 import json from airflow. This is done by providing a Jinja template for the task How can I get this TaskGroup to only run the function and get its return value once its reached in its dependencies? run_active_campaigns_query >> get_active_campaign_data >> format_active_campaigns_dict() >> dt_group. Using additional ENVs in your environment or adjustments in the general pip configuration as described in pip config. In the example you provided, you are making two connections to the metadata DB in each sequence_x task, one per each {{var. 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). As for number of queries: I assume that by "repeats a single query" you are asking if it execute a query per task_id. Whether to use dill or pickle for serialization. Dynamically adding airflow tasks on the basis of DB return value. I am having trouble passing it as a variable and do xcom_pull in next task. 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 excess pandemic In short when you return result from @task decorated method, it is . If the task to pull is mapped, an iterator (not a list) yielding XComs from mapped task instances is returned. 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. Defaults to False. This is because if a task returns a result, Airflow will automatically push it to XCom under the return_value key. xcom_pull(dag_id='my_dag', task_ids=f"execute_my_steps. Returns The serialize method should return a primitive or a dict. You can then use the `get_variable` operator to retrieve the results from another task. None may be returned if the depended XCom has not been pushed. Tasks are arranged into DAGs, and then have upstream and downstream dependencies set between them in order to express the order they should run in. How to Trigger a Task based on previous task status? 2. Could anyone assist on this. You can follow this documentation example. resolve (context, session = NEW_SESSION) [source] ¶ 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. operator. ' port = '5439' sslmode = 'require' ") task_instance = context['task_instance'] task_instance. Process(pid=00000, status='terminated') (00000) terminated with exit code -15. op_args (list (templated)) – a list of positional arguments that will get unpacked when calling your callable. And I want to define global variables for each of them like: function a(): return a_result About the tasks bellow. So op_kwargs/op_args can be used to pass templates to your Python operator:. The default value for `key` limits the search to XComs that were returned by other tasks (as opposed to those that were pushed manually). First point: I am not sure how many DB calls will be made to fetch the values required inside the jinja templates (in the below example). By following these guidelines and utilizing the xcom_push and xcom_pull methods effectively, you can enhance data sharing between tasks in your Airflow DAGs. When next_task passes the xcom return_value into the python_callable 'next_task', it fails with: TypeError: string indices must be integers. Modified 2 years ago. def branch_func(**context) return f"task_{context['ti']. The answer is No. from airflow. def create_dag(dag_id, schedule, default_args): def getData(**kwargs): The issue I was having (I think) was that I was trying to access task functionality in the dag, and either that's not possible or I haven't figured out how to do it , combined with the KubernetesPodOperator / @task. Viewed 361 times 2 . 0. :param is_done: Set to true to indicate the sensor can stop poking. use_dill. Whether you're a fan of The default key is ‘return_value’, also available as a constant XCOM_RETURN_KEY. 2. pull xcom value inside I am using airflow, i want to pass the output of the function of task 1 to the task 2. Please use the following instead: from airflow. The argument type of task_ids matters when using xcom_pull(). The issue I have is figuring out how to get the BashOperator to return something. decorators import apply_defaults from airflow. It does not need to serialize the values in the dict, that will be taken care of, but the keys should be of a primitive form. It seems small enough to not need the complexity of being turned into a Series at this point. Task should fail otherwise def 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. First Sensors creates a random integer list as data and a random boolean with 50% chance def xcom_pull (self, task_ids = None, dag_id = None, key = XCOM_RETURN_KEY, include_prior_dates = False): """ Pull XComs that optionally meet certain criteria. send_email is a more traditional Operator, but even it can use the return value of Airflow tries to be smart and coerce the value automatically, but will emit a warning for this so you are aware of this. 0 Passing task outputs with AirFlow XCOM. 0: Airflow added the ability to render fields as native Python objects. Airflow tasks in a loop based on dag_run conf value. amazon. If set, function return value will be unrolled to multiple XCom values. html. numpy. Option 4: the "pythonic" way Templates like {{ ti. The return type if you use dynamic mapping and expand in Airflow is the return type changes to _LazyXComAccess which is . Is there any way in Airflow to create a workflow such that the number of tasks B. class When a task pushes an XCom, it makes it generally available to other tasks. The following parameters are supported in Docker Task decorator. For example, INFO - Task exited with return code 1 or INFO - Task exited with return code 0 or INFO - Process psutil. If you return a value from a function, this value is stored in xcom. If it is not, the set_return_value task is called with the value False. The same context dictionary is used for pre_execute, post_execute, on_execute_callback, and execute() itself. If you’re out of luck, what is always left is to use Airflow’s Hooks to do the job. get_records method (i am returning a small amount of kines - usually a single cell). airflow dynamic task group range creation. Chaining tasks with return values is a powerful feature In simple terms, PythonOperator is just an operator that will execute a python function. I have a workflow like below, Task2 generates a list and saves it to airflow variable "var1". Share. And when you use result of such @task decorated method you actually get not the actual result - but XComArg representation of the XCom saved result (also@task decorator will take care about that). the output varies on each execution. def get_job_dts(**kwargs): #Do something to determine the appropriate job_start_dt and job_end_dt #Package up as a list as inputs to other PythonCallables using op_args job_params = [job_start_dt, job_end_dt] # Push job_params airflow task INFO - Task exited with return code -9. xcom_push(key='return_value', value=full_paths) Code: from airflow. A dictionary key under the check name must include check_statement and the value a SQL statement that resolves to a boolean (this can be any string or int that resolves to a boolean in airflow. sql. example_dags. In your case, you could access it like so from The returned value, which in this case is a dictionary, will be made available for use in later tasks. db import provide_session dag = DAG() @provide_session def get_files_list(session): execution_date = dag. py:1395} INFO - Marking task as UP_FOR_RETRY. Reload to refresh your session. Airflow PythonOperator task fail - TypeError: The key has to be a string. Note that these tasks are defined programmatically, therefore I cannot simply use xcom_pull(task_id="some_task") because the tasks are defined in a loop (as shown below): I have a python callable process_csv_entries that processes csv file entries. When a task pushes an XCom, it makes it generally available to other tasks. @task def push_task(): return "value_to_pass" @task def pull_task(data): However, when people begin using both together, one common question that comes up is how to pass data between traditional operators and TaskFlow API tasks. now()) // Find previous task instance: ti The below code works but my requirement is to pass totalbuckets as an input to the function as opposed to global variable. Dict will unroll to xcom values with keys as keys. Instead, you can use the new concept Dynamic Task Mapping to create multiple task at runtime. Airflow - select bigquery table data into a dataframe. 1 json serializer function that serialized datetime objects as ISO format and all other non-JSON-serializable to null. virtualenv(show_return_value_in_logs=False) – Matthias. Versioning is required. 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. 3 if that makes a difference. This virtualenv or system python can also have different set of custom libraries installed and must be made available in all workers that can execute the Additional/less values can be returned by DB in each call. 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 insted of xcom_push=True , try do_xcom_push=True, It will bring all the stdout to the xcom with key return_value. In Airflow, a DAG – or a Directed Acyclic Graph – is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies. python_callable (python callable) – A reference to an object that is callable. Python command for executing functions How to dynamically create tasks based on xcom value of previous task or airflow variable in airflow? Ask Question Asked 2 years ago. models. Stack Overflow. Instead I got from DAGR 3. issue with passing return value from a task as an argument to another task. base import PokeReturnValue from airflow xcom_value=operator_return_value) # Print Sensor's Value @task 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 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 Parameters. 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. base. For example, use conditional logic to determine task behavior:. The issue here is what do you expect the status of task1 to be when you do return False. kwbf qomjs igialj hgneai zodlhg siukwo emm dbuujdh nmqp ybjylxc