So.. In the meantime our new contributor Matt implemented the move and we
are merging it https://github.com/apache/airflow/pull/7456 as we have
already several approvals. I hope it will help us to move faster a bit :)
We might have another discussions on the models __init__.py stuff removal
and pl
Hi all,
We are using Airflow to put batch ML models in production (only the
prediction is done).
[image: image.png]
Above is an example of a DAG we are using to execute an ML model written in
Python (scikit learn)
1. At first, data is extracted from BigQuery. The SQL query is on a DS
owned
Here is the link to the AIP for folk's convenience:
https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-31%3A+Airflow+functional+DAG+API
The proposal and this all looks really good to me :)! I do want to call out
to others that it's important we get the interface 95%+ right from the
get-go sin
Hi everyone,
Sending a new message to everyone to gather feedback on the AIP-31 about
Airflow functional DAG API. This was initially discussed and proposed in
[DISCUSS] Airflow functional DAGs. After leaving open a small doc to iterate on
the proposal for a couple weeks, I decided to move forw
Any more comments for system tests? I would love to vote on the AIP-4 and
my current proposal would be :
1) Let's try to automate system test execution (starting with GCP as it is
close to be ready). That would most likely be with Github Actions -
details to be worked on.
2) We can do it to automa
