I am trying to wrap my head around how DAGs should actually be executed in docker compose environment, when they are dependent on other service (separate python venv) defined in the compose file.
I have setup airflow via docker compose as mentioned in official documentation. Also, I have added a Django service, which has its own dependencies.
Now, i would like to have a DAG, that executes python script using that Django's service python environment (It also uses Django's models. Not sure if that's relevant).
The only way I see it working is with DockerOperator as described here. I managed to setup and execute the test DAG mentioned there, however when I try to run the real task, it fails due to networking issues. Iam quite confident i can solve that issue, but setting everything this way just seems like way too much hassle.
So, in the end I guess Iam wondering what the ideal architecture should when using Airflow via compose? Should the base airflow image be extended with my Django service (creating one hell of a big image) or is there a better way?