Since `depends_on_past` allows for `skipped` status, it seems like ` wait_for_downstream` should have the same behavior.
I think it's just a matter of changing this line: https://github.com/apache/incubator-airflow/blob/master/airflow/models.py#L990 to TaskInstance.state.in_(State.SUCCESS, State.SKIPPED), This, and writing a test or two for it and making this clear in the documentation. I'd approve this PR if no one opposes it. Max On Thu, Sep 1, 2016 at 1:24 AM, Greg Lira <[email protected]> wrote: > Hi, > > For some of our DAGs [where we clear and re-import the staging tables], > having wait_for_downstream on the tasks is very important. > However, we have a BranchPythonOperator for happy and error path, so if > the flow has successfully completed, the tasks of the error path as marked > as skipped. > It seems that it doesn't work well with wait_for_downstream, where > airflow checks for the task instances with SUCCESS state only. > Is this 'by design'? > How can we handle sequential execution of the DAGs then? Should we > completely re-design the workflow or there is a way to do that with airflow > configuration settings? > > Thanks, > Greg >
