wahsmail opened a new issue #15752:
URL: https://github.com/apache/airflow/issues/15752
**Apache Airflow version**: 2.0.1
**Environment**:
- **OS** (e.g. from /etc/os-release): CentOS Linux 7 (Core)
- **Kernel** (e.g. `uname -a`): Linux 3.10.0-957.27.2.el7.x86_64
- **Install tools**: conda install airflow airflow-with-ldap psycopg2
sqlalchemy=1.3
**What happened**:
When I want to backfill tasks using only the UI, I usually pick how far I
want to backfill to, mark as failed with the "future" option selected, then
clear with the "future" option selected (with various dependency options as
well). After upgrading our production server to 2.x, the "Wait a minute prompt"
only shows the selected task when there are multiple executions dates following
it.
One interesting thing to note is that this behavior works as expected when
**clearing** tasks, just not marking success/failure.
**What you expected to happen**:
I expected all the task instances for on and after the selected execution
dates to be affected. Instead I have to manually fail each task-date or find
another workaround, but this is how our non-power-users have been backfilling
processes.
**How to reproduce it**:
We created a fresh conda environment with Python 3.8, ran `conda install
airflow airflow-with-ldap psycopg2 sqlalchemy=1.3` and continued the setup for
the scheduler and webservice. Python package environment is airflow-centric,
not much else in there. We are using the default timezone "America/Chicago" and
cron expression schedules "0 0 * * *" to ensure our dags run every night at
midnight local time, instead of 11pm/12am/1am depending on daylight savings
time / start_date. For the DAG/task start_date I have tried passing a naive
datetime.datetime, a datetime.datetime object with
tzinfo=pedulum.timezone("America/Chicago"), a pendulum.datetime object with
tz="America/Chicago", and a airflow.utils.timezone.datetime object. All suffer
from the same issue. Here is an example DAG suffering from this:
`
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from airflow.utils.timezone import datetime
default_args = {
'owner': 'wahsmail',
'depends_on_past': False,
'start_date': datetime(2021, 3, 1),
'email_on_failure': False,
'email_on_retry': False,
'retries': 0,
}
dag = DAG('test_dag', default_args=default_args, schedule_interval='0 0 * *
*', catchup=True)
def print_stuff_func(**context):
print('---- airflow macros ----')
print(str(context).replace(',', ',\n'))
print_stuff = PythonOperator(
task_id='print_stuff',
python_callable=print_stuff_func,
dag=dag
)
`
**Anything else we need to know**:
Step 1:
Step 2:
Step 3:
Step 4:
Actually in this example, not even the selected date itself was marked as
failed... not sure what's going on here.
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