If you're working with data pipelines, you definitely need to give Apache Airflow a look.

This pure Python workflow framework is one of the most popular and capable out there.

You create your workflows by writing Python code using clever language operators,

and then you can monitor them and even debug them visually once you get them started.

So stop writing manual code or cronjob-based code to create data pipelines and check out Airflow.

And to do that, we have three great guests from the Airflow community, Yarek Potech, Taxil-Nike, and Leia Cole.

This is Talk Python to Me, episode 330, recorded August 5th, 2021. Welcome to Talk Python to me, a weekly podcast on Python, the language, the libraries, the

ecosystem, and the personalities. This is your host, Michael Kennedy.

Follow me on Twitter where I'm at M. Kennedy, and keep up with the show and listen to past

episodes at talk python.fm and follow the show on Twitter via at Doc Python.

This episode is brought to you by us over at Talk Python Training, and the transcripts

are brought to you by Assembly AI.

Leah, Yarek, Axel, welcome to Talk Python.

It's good to have you all here.

Thanks for having us.

Thank you.

Yeah. It's really fun to be talking about Airflow.

These are the types of tools that I think they don't get that much awareness, but they're the kind of thing that can be the real backbone of a lot of teams,

a lot of organizations, and so on. So I think that'll be super fun to dive into and we'll all

learn a lot. And I suspect a lot of people listening and will realize, oh, here's a whole class

of tools. I didn't even realize I should have considered to solve my problems. Before we get

down to that, let's start with your stories.

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