I have a simple, linear DAG(created using Airflow 2.0) with two tasks. I have custom operators for each of the task which extend over BaseOperator
. Following is the code for dag and operators:-
class Operator1(BaseOperator):
@apply_defaults
def __init__(self, **kwargs) -> None:
super().__init__(**kwargs)
def execute(self, context):
...
logging.info('First task')
context['task_instance'].xcom_push(key="payload", value=data)
return data
class Operator2(BaseOperator):
@apply_defaults
def __init__(self, **kwargs) -> None:
super().__init__(**kwargs)
def execute(self, context):
...
logging.info("context is ", context)
parameters = context['task_instance'].xcom_pull(key="payload", value=data)
with DAG('dag_1', default_args=DEFAULT_ARGS, schedule_interval=None) as dag:
TASK_1 = Operator1(
task_id='task_1',
do_xcom_push=True)
TASK_2 = Operator2(
task_id='task_2',
do_xcom_push=True)
TASK_1 >> TASK_2
When I run the DAG, I find that context
which is used for getting xcom
values is empty. I have searched a lot of answers on stackoverflow and tried the way mentioned in them but they didn't work.
Would really appreciate some hint over the issue - how to push and pull xcom values in custom operators?
I took your code and run it, the first problem was that start_date
wasn't defined, so it ended up in an exception:
Exception has occurred: AirflowException (note: full exception trace is shown but execution is paused at: _run_module_as_main)
Task is missing the start_date parameter
Also, in Operator1
class, data
variable is not defined. I guess maybe you missed them when you made the code example.
Other than that the code worked, but I think you should consider defining the task_id
parameter when doing the xcom_pull operation.
From TaskInstance
xcom_pull
method description:
:param task_ids: Only XComs from tasks with matching ids will be pulled. Can pass None to remove the filter.
Here is the code of a working example, note that I use two equivalent methods to perform the XComs
operations:
from airflow import DAG
from airflow.utils.dates import days_ago
from airflow.utils.decorators import apply_defaults
from airflow.models import BaseOperator
class Operator1(BaseOperator):
@apply_defaults
def __init__(self, *args, **kwargs) -> None:
super(Operator1, self).__init__(*args, **kwargs)
def execute(self, context):
print('First task')
data = "valuable_data"
more_data = "more_valueable_data"
context['task_instance'].xcom_push(key="payload", value=data)
self.xcom_push(context, "more_data", more_data)
return data
class Operator2(BaseOperator):
@apply_defaults
def __init__(self, *args, **kwargs) -> None:
super(Operator2, self).__init__(*args, **kwargs)
def execute(self, context):
# print(f"context is {context}")
data = context['task_instance'].xcom_pull(
"task_1",
key="payload")
more_data = self.xcom_pull(context, "task_1", key="more_data")
print(f"Obtained data: {data}")
print(f"Obtained more_data: {more_data}")
with DAG('dag_1',
default_args={'owner': 'airflow'},
start_date=days_ago(1),
catchup=False,
schedule_interval=None) as dag:
TASK_1 = Operator1(
task_id='task_1'
)
TASK_2 = Operator2(
task_id='task_2'
)
TASK_1 >> TASK_2
Log from Task_2:
[2021-06-15 12:55:01,206] {taskinstance.py:1255} INFO - Exporting the following env vars:
AIRFLOW_CTX_DAG_OWNER=airflow
AIRFLOW_CTX_DAG_ID=dag_1
AIRFLOW_CTX_TASK_ID=task_2
AIRFLOW_CTX_EXECUTION_DATE=2021-06-14T00:00:00+00:00
AIRFLOW_CTX_DAG_RUN_ID=backfill__2021-06-14T00:00:00+00:00
Obtained data: valuable_data
Obtained more_data: more_valueable_data
[2021-06-15 12:55:01,227] {taskinstance.py:1159} INFO - Marking task as SUCCESS. dag_id=dag_1, task_id=task_2, execution_date=20210614T000000, start_date=20210615T120402, end_date=20210615T125501
Side notes: I changed the __init__
method in order to accept *args as well. I'm using print
but It could be done using Airflow logger as self.log.info('msg')
.
Let me know if that worked for you!
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