[jira] [Commented] (AIRFLOW-4830) Timezone ignored if default_args used for multiple dags

["Abhishek Ray (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/AIRFLOW-4830?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16879495#comment-16879495 ] 

Abhishek Ray commented on AIRFLOW-4830:
---------------------------------------

I think this issue should be fixed by this pull request:
[https://github.com/apache/airflow/pull/5277]

> Timezone ignored if default_args used for multiple dags
> -------------------------------------------------------
>
>                 Key: AIRFLOW-4830
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-4830
>             Project: Apache Airflow
>          Issue Type: Bug
>          Components: DAG
>    Affects Versions: 1.10.3
>            Reporter: Dean
>            Priority: Major
>         Attachments: Screen Shot 2019-06-20 at 4.43.16 PM.png, Screen Shot 2019-06-20 at 4.45.15 PM.png
>
>
> I created a {{default_args}} dict and passed it to two different dags. In the first dag, the job was scheduled for 'America/Los_Angeles' as specified in the dict, but for the second it was in 'UTC' (it should also be 'America/Los_Angeles'.
> {code:python}
> from airflow import DAG
> from airflow.operators.python_operator import PythonOperator
> from datetime import datetime
> import logging
> from pendulum import timezone
> def msg(s, **kwargs):
>     logging.info('{}: {}'.format(s, str(kwargs['execution_date'])))
> default_args = {
>     'start_date': datetime(2018, 1, 1, tzinfo=timezone('America/Los_Angeles'))
> }
> dag1 = DAG('tz_test_shared_1',
>            default_args=default_args,
>            catchup=True,
>            schedule_interval='0 0 * * *')
> t1 = PythonOperator(
>     task_id='t1',
>     provide_context=True,
>     op_args=['t1'],
>     python_callable=msg,
>     dag=dag1)
> dag2 = DAG('tz_test_shared_2',
>            default_args=default_args,
>            catchup=True,
>            schedule_interval='0 0 * * *')
> t2 = PythonOperator(
>     task_id='t2',
>     provide_context=True,
>     op_args=['t2'],
>     python_callable=msg,
>     dag=dag2)
> {code}
> See the resulting task execution times in Screen Shot 2019-06-20 at 4.45.15 PM.png. One job happens at 08:00 UTC (as expected), but the other at 00:00 UTC.
> Compare that to this version, the only difference is the dag names and {{default_args}} is repeated:
> {code:python}
> from airflow import DAG
> from airflow.operators.python_operator import PythonOperator
> from datetime import datetime
> import logging
> from pendulum import timezone
> def msg(s, **kwargs):
>     logging.info('{}: {}'.format(s, str(kwargs['execution_date'])))
> default_args = {
>     'start_date': datetime(2018, 1, 1, tzinfo=timezone('America/Los_Angeles'))
> }
> dag1 = DAG('tz_test_1',
>            default_args=default_args,
>            catchup=True,
>            schedule_interval='0 0 * * *')
> t1 = PythonOperator(
>     task_id='t1',
>     provide_context=True,
>     op_args=['t1'],
>     python_callable=msg,
>     dag=dag1)
> default_args = {
>     'start_date': datetime(2018, 1, 1, tzinfo=timezone('America/Los_Angeles'))
> }
> dag2 = DAG('tz_test_2',
>            default_args=default_args,
>            catchup=True,
>            schedule_interval='0 0 * * *')
> t2 = PythonOperator(
>     task_id='t2',
>     provide_context=True,
>     op_args=['t2'],
>     python_callable=msg,
>     dag=dag2)
> {code}
> See the resulting task execution times in Screen Shot 2019-06-20 at 4.43.16 PM.png. Both happen at 08:00 UTC (as expected).



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