______________________

                      LANGUAGES POPULARITY

                          Nicolas Herry
                     ______________________


                           2017/03/31





1 Languages popularity
======================

 [An article posted on monday on Revolution Analytics] echoes the
 latest report published by Redmonk, which shows which programming
 languages are most popular. In this report, Python climbed to
 position #3 and R registered a slight step back, to #14. So, what
 does it tell us?  Well, not much, I'm afraid.


[An article posted on monday on Revolution Analytics]
<http://blog.revolutionanalytics.com/2017/03/redmonk-jan-2017.html>

1.1 Useful information
~~~~~~~~~~~~~~~~~~~~~~

 Of course, the first thing is that putting all languages in one
 bag seems a bit silly, to say the least. How often do you
 hesitate between C and Javascript? And why is the popularity
 contest run every six months by Redmonk and every month by TIOBE?
 How does that relate to anything in the real world?

 But it's not just the methodology I have a problem with. I
 believe the value of any piece of information is directly
 proportional to the value of the decisions you can make based on
 it. So, what decision can we make based on the knowledge that
 [Redmonk] or [TIOBE] reports that some language (let's call it
 "wiggly") that used to be #11 is now #15, for example?
 - Shut down all projects written in wiggly
 - Shut down all future plans to write anything in wiggly
 - Convert all projects written in wiggly to a language in the top
   10
 - Organise trainings for all wiggly people willing to evolve to
   something more fashionable and fire all those who won't

 Well, I guess we can agree all the above seems a bit over the
 top. But if you were to make such a decision, what would you do
 if in the next report, dear wiggly was to climb back to #8? And
 if you aren't to make any such decision, exactly what kind of
 decision can you make based on the report?

 Well, since this is not about the technical merits of the
 languages themselves, maybe it's about the market. So, what does
 it say about the market? Not much. We get a picture of how much
 activity GitHub and StackOverflow see for these forty
 languages. It doesn't say anything about the value of mastering
 these languages on the market and it doesn't tell anything about
 the value generated by these languages on the market either.

 So, if it's not about the technologies themselves, not about the
 value of the skills, the size of the market or what technology is
 right, then what is it about? I guess the answer is that it
 reflects trends and fashions, and I'm not sure I want to make any
 decision based solely on that.


[Redmonk] <https://www.redmonk.com>

[TIOBE] <https://www.tiobe.com/tiobe-index/>


1.2 Making decisions
~~~~~~~~~~~~~~~~~~~~

 So, if these kinds of reports aren't of any help in making
 decision, then what is?  What should we be considering? I'm not
 stupid enough to believe I hold the definitive answer to that
 question, but to me, there are a few things that you must take
 into account, always.


1.2.1 The team
--------------

 A project is first and foremost made up of the people involved in
 it. Besides being all sweet and cute, this sentence should act as
 a reminder that to get a project done, you need people with the
 right skills. So, whenever I need to decide on some technology, I
 first ask myself what these people know already. Especially when
 a project is about exploring new grounds, it's better to do it
 with a toolset you already master. Starting a new project, in a
 new domain, in a new language and possibly with new people seems
 a little risky to me. This is not to say that any novelty should
 be ruled out from the start: introducing new languages and
 technologies is healthy and useful, but I believe it should be
 done while keeping in mind a clear career path for the people on
 the team. In other words, this is long-term thinking, not
 something you revise entirely every month or even twice a
 year. As a side effect, not jumping on everything new and shiny
 can help getting a product well written, easy to maintain (or
 rather, not completely horrible to maintain, since you are less
 likely to discover unexpected shortcomings with the technology)
 and with a better time to market as a result.


1.2.2 Community and ecosystem
-----------------------------

 If the reports from Redmonk and TIOBE give some idea about the
 size of the respective communities behind the different
 languages, they tell nothing about the culture their programmers
 evolve in. Are they a good match to yours? Is there enough
 documentation available on your favourite support, be it books,
 forums, tutorials, mailing lists or IRC channels? Or are there
 enough open source code you can study, if this is how your team
 likes to learn about technology? Also, are there enough libraries
 available so you won't be pioneering your field in a language new
 to you? Another thing is that a large community is not always a
 good thing: as a community grows, the average skill of potential
 hires you can get from it gets lower and lower. This may or may
 not be a problem, depending on the project or the sector, but it
 is important to factor this in the equation.


1.2.3 Cost
----------

 The two considerations above already cover this item to a great
 extent, so no need to rehash everything I already said. The
 question remains the same I ask myself with any project decision:
 how much does introducing a new technology cost in short term and
 in the long run?  It's not much of a surprise, but no popularity
 contest can provide a proper answer to that question.

 So, in conclusion, I really can't see the point of these
 reports. In the latest TIOBE Index for March 2017, the star is
 Swift, which is entering the top 10. Who would have guessed
 programming on the iPhone, with the technology stack actively
 pushed by Apple is a popular thing do? I certainly didn't, but
 I'm not losing anymore time; I already started rewriting all my
 MATLAB code in wiggly.