Everything runs in one process, so you can put a breakpoint in your IDE, and configure it to run airflow dags test then debug code! Auto tailing task logs in the Grid view
#Airflow 2.0 code#
it gets to running the task code so much quicker)Ĭ. It is about an order of magnitude quicker to run the tasks than before (i.e. Task logs are visible right there in the console, instead of hidden away inside the task log filesī. This airflow subcommand has been rethought and re-optimized to make it much easier to test your DAGs locally - the major changes are:Ī. Greatly improved airflow dags test command When we released Dataset aware scheduling in September we knew that the tools we gave to manage the Datasets were very much a Minimum Viable Product, and in the last two months the committers and contributors have been hard at work at making the UI much more usable when it comes to Datasets.īut we we aren’t done yet - keep an eye out for more improvements coming over the next couple of releases too. Usability improvements to the Datasets UI
This quicker release cadence is a departure from our previous habit of releasing every five-to-seven months and was a deliberate effort to listen to you, our users, and get the changes and improvements into your workflows earlier. 🐳 Docker Image: docker pull apache/airflow:2.5.0 Apache Airfow 2.5 has just been released, barely two and a half months after 2.4!
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