If I'm writing a game I care about what's most popular with games. If I'm writing an enterprise reservation system, I care about that.
These languages really live in completely different universes and I think it's time we acknowledge that. The one-size-fits-all survey of this sort feels like a holdover of a time when software development was far more homogeneous.
It's yet another example of how the entire profession is getting more specialized. You used to be a "programmer". Now you're a data engineer, ops engineer, front-end engineer, back-end/full-stack engineer, ios/android/react, system/OS programmer, etc. These are becoming entirely different jobs with little crossover between them, just like family law vs. criminal law vs. estate law vs. corporate law.
https://blog.shortbar.com/the-end-of-the-country-developer-7...
I still wonder when there's actually going to be official training in these specialties, that counts as credentials when seeking employment. As far as I know (and I could be wrong), traditional education tends to be somewhat general.
Which specialty you're qualified for seems to have more to do with what job you happened to hold when the specialization split began, rather than something you deliberately decided to study.
(Okay, I'll admit that there are training courses in all manner of things, but they don't seem like a formal course of study you can actually put on a resume.)
The split started to happen about 5 years ago and it's really picked up velocity in the last year or two, to where it's getting hard to "jump" if you want to change. It's one of those slow, long-term things that's easy to miss if you aren't paying attention.
I think Udacity has a good model for this. I'm a generalist dev who has let curiosity drive my career more than anything else and feel I'm paying the penalty for it. Most places seem to want 5+ years specialization in whatever you're applying for if you're coming in at the senior level.
It's getting harder asking people to trust you if your resume isn't properly "tracked" into one specialty. I think that's a huge loss in terms of diversity and cross-skilling but perhaps necessary given the immense amount of sheer knowledge there is in each area, e.g. the entire iOS or Android API set.
This is just a return to the norm.
Just a thought
Actually a better question might be "What proportion of good programmers I interview will know a language in five years".
But within that market it's further divided, if you're looking for non-game related Objective-C developers you'd probably be in trouble and so on...
It really is a super complex question, but that's the sort of ranking vector I'd be more interested as opposed to "How quickly do stackoverflow questions get accepted answers?" and I am under no illusion that it'd be super hard to measure.
I ended up finding C#/.NET was listed on 33/50 recent job listings, Java was on 30/50 (some jobs had multiple languages listed), and other languages cropped up between 1-20 times or so.
So in my market, if I want a job where I don’t relocate (with a 3 year old and a baby and a wife who chooses not to work non-remote SV jobs are out), I’d better get to learning C#.
Even so, this article is also pretty bad. Nowhere does the author define what he means by "popularity", which is one of the key problems all of these popularity contests suffer.
If we say "Language X is more popular than language Y?" What does that mean? Answers could be any of:
* Total extant corpus of X is larger than Y.
* Number of people who know X is larger than Y.
* Amount of open source code in X is greater than Y.
* Number of people currently writing X (how much?) is greater than Y.
* Number of people who want to be writing X is greater than Y.
* Number of jobs available for writing X is greater than Y.
* Number of people talking about X is greater than Y.
These are all wildly different metrics but all have reasonable claims to represent "popularity" and/or are what some of these rankings claim to show.
To do anything useful, you really need to know what problem the reader is trying to solve and pick a metric that helps that problem. Is the reader trying to decide what language to learn to find a job today? To get ahead of the curve and be an expert in five years? To discover a new exciting language? To choose a language to use for a large, conservative project? A small ambitious one?