Re: programmatically creating and airflow quirks
I think this is what is going on. The dags are picked by local variables.
I.E. if you do
dag = Dag(...)
dag = Dag(...)
Only the second dag will be picked up.
On Thu, Nov 22, 2018 at 2:04 AM Soma S Dhavala <soma.dhavala@xxxxxxxxx>
> Hey AirFlow Devs:
> In our organization, we build a Machine Learning WorkBench with AirFlow as
> an orchestrator of the ML Work Flows, and have wrapped AirFlow python
> operators to customize the behaviour. These work flows are specified in
> We drop a DAG loader (written python) in the default location airflow
> expects the DAG files. This DAG loader reads the specified YAML files and
> converts them into airflow DAG objects. Essentially, we are
> programmatically creating the DAG objects. In order to support muliple
> parsers (yaml, json etc), we separated the DAG creation from loading. But
> when a DAG is created (in a separate module) and made available to the DAG
> loaders, airflow does not pick it up. As an example, consider that I
> created a DAG picked it, and will simply unpickle the DAG and give it to
> However, in current avatar of airfow, the very creation of DAG has to
> happen in the loader itself. As far I am concerned, airflow should not care
> where and how the DAG object is created, so long as it is a valid DAG
> object. The workaround for us is to mix parser and loader in the same file
> and drop it in the airflow default dags folder. During dag_bag creation,
> this file is loaded up with import_modules utility and shows up in the UI.
> While this is a solution, but it is not clean.
> What do DEVs think about a solution to this problem? Will saving the DAG to
> the db and reading it from the db work? Or some core changes need to happen
> in the dag_bag creation. Can dag_bag take a bunch of "created" DAGs.