A few years ago I wasn’t sure, who was going to win, Golang seemed to be popular, and still is for that matter. When I first wrote a little Golang (~2+ years ago) I was just trying to see what the hype was all about. The funny thing is, at the time, and today, it seems like the Golang syntax is much simpler than Rust, easier to learn and pick up by far.

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Photo by Thomas Schweighofer on Unsplash

I’m not sure if DataFrames in Golang were created by Gandalf or by Saruman, it is still unclear to me. I mean, if I want a DataFrame that bad … why not just use something normal like Python, Spark, or pretty much anything else but Golang. But, I mean if Rust gets DataFusion, then Golang can’t be left out to dry, can it!? I mean I guess if you’re hardcore Golang and nothing else will do, and you’re playing around with CSV files, then maybe? Seems like kind of a stretch. But, I have a hard time saying no to Golang, it’s just so much fun. Kinda like when Gandalf told them little hobbits and dwarfs to not stray from the path going through Fangorn Forest, those little buggers did it anyways. Code available on GitHub.

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I’ve always been a firm believer in using the right tool for the job. Sometimes I look at a piece of code … and ask … why? I mean just because you can do something doesn’t mean that you should. I see a lot of my job as someone who writes code … as not just my ability to write code, but the ability to reason about problems and design simple and elegant solutions that solve the problem at hand.

I try not to let my love of a tool, language, or package color my view of the world as it is. In fact, there is wisdom to be found in being critical of those languages and tools you love the most. Be aware of their shortcomings and failures. This leads to better software and architecture designs, and less complexity. Too often I’ve seen folks picking their tool of choice and then sticking with it till the bitter end, and it usually is bitter. There is more to life than writing obtuse Scala code that is illegible for some mundane task.

This sort of thing is a blight on everyone and every system. Now I must descend from my high horse and join the peasants on the dusty road of life. Today I want to look at some very common Data Engineering tasks, namely cloud storage, and what it is like to do such a thing with Golang, Rust, and Python. I will let you draw your own conclusions. Maybe. Code available on GitHub.

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Image: Saint Augustine of Hippo | Line engraving by P. Cool after M. de Vos | Wellcome Images

I’ve always enjoyed reading Mr. Augustine of Hippo, particularly “Confessions.” Ahead of his time in many ways. Although, you have to be into that sort of thing to find such topics interesting. It can be sort of dry, drawn out, verbose, and not for the faint of heart. Much like learning new programming languages. I’ve been messing with Golang off and on and here and there. Recently I added Rust to that list, more out of curiosity and to see what’s new in the world.

I’ve spent a lot of time thinking about the theology of programming in the space of Data Engineering. It’s such a wide area that encompasses so many different skills, Data Engineering that is. Why do we do what we do, write what we write? Like Augustine I see both old and new all around me, some things change, but many things stay the same.

People find hills like Python, Scala, Golang, Rust, and then promptly decide to die on them. I enjoy different things simply because of the way they teach you things about yourself and the world.

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Photo by Nik Shuliahin 💛💙 on Unsplash

I’ve been playing with Golang off and on for a few weeks, when I find the time, which is every few weeks between kids and fishing. I have become a little bit of a fan, wishing for more projects to take on with Go. It seems like a fairly straightforward language to pick up, the learning curve isn’t that bad, and it’s fast and powerful. I’ve found it a little more intuitive than Scala for example. I mean don’t get me wrong, nothing will take the place of Python in my life, but there’s always room for one more.

That being said, “But I have this against you…” when it comes to Go, and it has to do with JSON. All code is on GitHub.

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I periodically try to pick up a new programming language on my journey through Data Engineering life. There are many reasons to do that, personal growth, boredom, seeing what others like, and helping me think differently about my code. Golang has been on my list for at least a year. I don’t hear much about it in the Data Engineering world myself, at least in the places I haunt like r/dataengineering and Linkedin.

I know tools like Kubernetes and Docker are written with Go, so it must be powerful and wonderful. But, what about Data Engineering work … and everyday Data Engineering work at that, is Go useful as an everyday tool for everyday simple Data Engineering tasks? Read on my friend.

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