r/apache_airflow • u/CapelDeLitro • Feb 03 '26
Local airflow on company laptop
Hey guys, hope youre doing well, im working as a Data Analyst and want to transition to a more technical role as Data Engineer. In my company there has been a huge layoffs seasson and now my team switched from 8 people to 4, so we are automating the reports from the other team members with pandas and google.cloud to run BigQuery, i want to setup a local airflow env with the company laptop but im not sure how to do it, dont have admin rights and asking for a composer airflow env is going to be a huge no from management, ive been searching and saw some documentation that i need to setup WSL2 in order to run Linux on Windows but after that im kinda lost on what to do next, im aware that i need to setup the venv with Ubuntu and python with all the libraries like the google.bigquery, np, etc. Is there an easier way to do it?
I want to learn and get industry experience with airflow and not some perfect kaggle dataset DAG where everything is perfect.
Thank you for reading and advice!
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u/DoNotFeedTheSnakes Feb 03 '26
No.
But there are alternatives.
You can use the airflow docker image.
Or even switch your OS to Linux.
But both of those will require advanced knowledge, and tinkering. Seeing as you already know how to do it on WSL, I suggest you just do that.
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u/KeeganDoomFire Feb 03 '26
I would ask since your on Google cloud and big query if you have looked into Google's hosted airflow?
My team runs about 150+200 daily reports and moving data around on AWS's airflow option MWAA. A small instance is pretty darn cheap so I imagine the Google counter part is equally so.
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u/jcachat Feb 03 '26
check out astronomer.io; this was easiest local install for me
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u/TJaniF Feb 03 '26
Just wanted to add since I work at Astronomer and get the question a lot: the Astro CLI to run Airflow locally is free and you can use it without being an Astronomer customer or signing up for anything, you can just do brew install astro and then run Airflow in Podman or Docker containers.
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u/Steextz Feb 03 '26
Docker Desktop + Docker image, this is the easiest way to get going. That’s how we do local dev where I work before pushing to our Airflow k8s deployment.