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Re:Julia 1.5 Highlights by eigenspace on Monday August 03, 2020 @03:56PM (#24042582)
Most people who advocate anything have never built production ready systems because that's not a thing most people do. There are important and knowledgeable people in the Julia community who build production ready systems as their full time jobs though.

What is your point?

Re:Julia 1.5 Highlights by fermienrico on Monday August 03, 2020 @04:32PM (#24043026)
I disagree. If a language is positioning itself as a python alternative, it needs to handle production readiness. If I were to guess, python is used in more production environments than in prototyping environments, but I don't have data to prove. What's most likely true is that production systems aren't a minuscule portion of a language's application - it is a significant chunk and Julia just isn't there yet. Hopeful though.
Re:Julia 1.5 Highlights by eigenspace on Monday August 03, 2020 @04:49PM (#24043217)
> If I were to guess, python is used in more production environments than in prototyping environments.

Then you have a stunning misunderstanding of Python's demographics.

Re:Julia 1.5 Highlights by fermienrico on Monday August 03, 2020 @09:23PM (#24045522)
I’d be curious if you have data. 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”?

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

Re:Julia 1.5 Highlights by eigenspace on Monday August 03, 2020 @09:46PM (#24045657)
> I’d be curious if you have data.

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...

Re:Julia 1.5 Highlights by sannee on Tuesday August 04, 2020 @09:42AM (#24049847)
Julia positions itself not as a Python alternative, but as a Matlab alternative. People also sometimes use Python as a Matlab alternative and hence would use Julia as an alternative to Python only by transitivity.