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Technical decisions should not be made on "which technology sounds cool on CV" basis.

Unless there is strong reason, codebase should be in one language. Having it in multiple languages makes learning curve for newcommers unnecessary steep, especially if the company is willing to hire juniors. It also makes maintenance more difficult and expensive. Too many languages will also force your people to have very shallow knowledge.

We are going to do this one module in python should be done either cause you consider to move to python altogether or because the usual language is really bad fit. "Someone wants to learn it" is both bad reason and unprofessional.



> Too many languages will also force your people to have very shallow knowledge.

I spent the last 10 years learning programming languages and PLT; it's a hobby of mine and I put quite a lot of effort behind it. While I certainly forget some things I learned (I regret not using C on a daily basis and not keeping with C++ advancements), at any given time during those past ten years I was fluent in at least 3-4 languages. Without needing a refresher, right now I can speak and I really know in depth the following languages: JavaScript, OCaml, Erlang, Racket, Python, LiveScript and Pharo Smalltalk. I have about 20 other languages I could become similarly fluent in with a week's effort. It's not shallow knowledge, it's just 10 years of work. There is really nothing to force you not to have deep understanding of many different languages and technologies.

On the professional side - I have quite big system under my care which is mixed Python, JavaScript, Ruby and Erlang, not to mention bits of C, shell scripts and Makefiles and two compile-to-JS languages, some compile-to-CSS and compile-to-HTML languages. The system works - and believe it or not, working on it is a pleasure and using the right tool for the job really feels liberating. It let's me move twice as quickly with twice as good results than I'd get trying to do for example fault tolerant, concurrent backend service in Python instead of Erlang (or quick data mining script in Erlang instead of Python for that matter).

I believe using the right tool for the job is the very definition of professional. Of course, the learning curve is probably steeper for newcomers, but for professionals above a certain level language specifics are rather easy to grok and becoming fluent in a language takes a few weeks tops. Besides, it's not like every team member is required to know every technology used in a project - there's a tech lead for this and I wouldn't want to work with one who can't easily convert iterative algorithms to tail-recursive ones and switch from algol-like to prolog-like to python(-like) syntax on the fly.

Anyway, I know what I know and I know what I do and you're basically saying that these skills are irrelevant and using them would be unprofessional. In short, what I'm saying in response is: bullshit.




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