Sounds like a hard thing to measure, but I'm sure someone has good estimates.

> Also, if we define execution of a Python line as a metric: Instagram alone will dwarf all prototypers in Python. What would be a good metric to indicate “popularity”?

Code cycles isn't really what I would mean by language use, but if we go by that metric Julia's production code also dwarfs non-production code cycles.

The Celeste project alone was running at petaflops[1] at it's peak, that is 10^15 floating point operations per second. One of the biggest targets for Julia is deploying it at scale on super-computing clusters. There are almost surely many more CPU cycles being devoted to production scale julia code than random repl code, but that's got to be true for almost any language being used at scale.

Also, counting Python line executions in production code is a little squirreley, because almost surely those lines are really just a thin wrapper around a big hunk of C code if it's a production system.

> If it’s number of installs, then Python tinkerers would win and I agree with you.

I'd also say just number lines written or projects started, the tinkerers win hands down.

[1] https://www.hpcwire.com/off-the-wire/julia-joins-petaflop-cl...