Data scientists using Macs for everything and sometimes needing to run Linux in a container to get work done is more common than you might think.

    brew install coreutils

For instance, on a mac the 'sed' command doesn't understand the difference between space and tab

https://stackoverflow.com/questions/40311339/using-sed-on-ma...

Running a docker container, regardless of what it does under the hood, is extremely easy on a mac. You install a program then do "docker run ...".

    "Able to install packages"

There's something to be said for the cool-new-tech driven approach, when it comes to resume building.

That isn't to say that the Unix utilities are without merit. I have used them extensively for similar tasks. That being said, it is in environments where everyone used some version of Unix (typically Linux, Solaris, or Mac OS X).

Because then you're also looking at getting people using the same version of python and your dependencies - and it's likely slower.

> That being said, it is in environments where everyone used some version of Unix (typically Linux, Solaris, or Mac OS X).

If only there was a technology aimed at sharing an exact same version for easy use ;)

Sure, this case where it's just coreutils + csvlookup, the benefit for the added abstractions isn't so great. Using docker like this makes more sense if there are more dependencies. (Maybe it's just easier to say "use docker" than to explain how to install a dependency on different OSs?).

In general, I think it's fine for people to be able to solve problems without having a full understanding of the mechanisms involved in getting the tool to work. If they need to know it later, they'll learn it then. This is a top-down approach -- But, naturally, there'll be some awkward solutions on the way.

The whole point of my post is that running a container otecshstration system to accomplish any of this, for someone new, is insane. It is absolutely 100% only adding complexity and making things more confusing. How many people will not realize these utilities are on every computer they use? How long until someone poisons these repacked uselessly opaque versions? This makes things easier for no one and only furthers to complicate things by adding unnecessary complexity.

If someone is on a Mac, then they are now running a Linux VM, then running containers, then logging into said fucked up environment and then finallly... running... awk?

macOS -> Linux -> Container Runtime -> SSH-> finally use awk, sed, head, or anything else. Why stop there? We can probably then start up Qemu from a container, boot MacOS, and then simply repeat the process for maximum usefulness.

Err, no, they are not doing this. That's not how it's working for a start (there's no SSH here) but the user experience is literally

Install a standard application, downloaded like any other.

Open terminal.

Run "docker run ..."

That's it.

> It is absolutely 100% only adding complexity and making things more confusing. How many people will not realize these utilities are on every computer they use?

They aren't on every computer, and they are different on different computers. A point the author not only talks about in the linked explanation but describes how that bit them.

In the context of making things hard for a tutorial or complex for a beginner, it not being visible is the key point. Just like the complexities of how your CPU actually works aren't relevant for this tutorial.

This is a tutorial and set of examples, and it comes with a fully working environment with example data exactly setup to work. No difference between gsort and sort, no version issues or whether someone is using brew or macports or anything else. No python environment problems or pip Vs pip3 or whatever other random crap you need to deal with when trying to do something simple with lots of varied setups people have.

You are entirely free to not use docker.

> In order to use GNU/Linux one must

Nope. You can. You don't have to.

The point is invalid and clearly untrue.

> This is a tutorial and set of examples, and it comes with a fully working environment with example data exactly setup to work. No difference between gsort and sort, no version issues or whether someone is using brew or macports or anything else. No python environment problems or pip Vs pip3 or whatever other random crap you need to deal with when trying to do something simple with lots of varied setups people have.

I really don't see how having to get Docker going is alleviating any of the above headaches but I'm far removed from these tools being "new to me." Setting up virtualization to run a process on my local machine which I can run without virtualization or containerization the very same way seems crazy to me. It seems like an awful amount of complexity to push onto beginners for what is likely to be zero benefit and gives them only what they had at the start...

> You are entirely free to not use docker. >> In order to use GNU/Linux one must > Nope. You can. You don't have to.

Yeah that's my point exactly... you don't have to at all in fact, Docker offers most literally nothing but opaque complexity. I was saying you MUST have Linux if you want containers because containers are a Linux feature and DNE on MacOS but all them sweet utilities are already there save the weird csv tool. I don't think the complexity of Docker is warranted for simply handling a CSV tool and I find it to be a disservice to anyone who is learning.

/shrug

> I really don't see how having to get Docker going is alleviating any of the above headaches

Because it is a single thing to get working that then leaves all users of your tutorial on all major platforms dealing with the exact same environment. Have you ever tried to work with getting end users up to speed only to discover that one is using python2.7, another has anaconda but pip is pointing to the wrong place, pip3 is required for someone else and one user has mac so needs to install brew then replace every standard call to sort with gsort. Then dateutils appears as some conflicted dependency...

> Setting up virtualization to run a process on my local machine which I can run without virtualization or containerization the very same way seems crazy to me

Then don't, you don't have to. Go and setup an identical environment. For those that have docker this becomes a single command to run, and those that don't can get setup quickly. If they're heading into data science they're likely to benefit from having at least a basic understanding of docker.

> It seems like an awful amount of complexity to push onto beginners for what is likely to be zero benefit and gives them only what they had at the start...

It doesn't give zero benefit, it removes a whole bunch of differences in setup that are entirely irrelevant to the tutorial.

> Docker offers most literally nothing but opaque complexity.

It offers a standard environment that puts all users in the same place.

> but all them sweet utilities are already there save the weird csv too

No they are not, not on a mac and not on windows.

> I don't think the complexity of Docker is warranted for simply handling a CSV tool

What complexity? 'docker run --rm -it X bash' is literally all I need to do.

Also "kids these days" all reach for docker. Otherwise any sane person would have just used cat instead of csvlook.

Upvoted the kid's article, because command line text cleaning is of TOWERING IMPORTANCE to any DS person worth their salt. But he is definitely an inexperienced kid.