[jhoechtl]

I personally find the syntax of the language and quality of the current implementation (speed!) excellent. However, it doesn't experience the marketing languages like Rust or Golang receive.

What I personally also find worrisome is the perception (at least for me) that Julia is confined to scientific computing whereas I find it should really be a general purpose language.

[plinkplonk]

There is no technical reason that Julia can't be used for general purpose computing. (Well personally, I'd like nested namespaces, but) it is an amazing language. Just a matter of someone putting in the time to build the required libraries and glue code. Which will happen in time.

[elcritch]

The lack of AOT has been the main thing holding me back from adopting it for more general purpose computing. Now with AOT I can "compile" the code and get some reasonable expectation of performance and ease of deployment. I'm probably going to start using Julia and (hopefully) extending the web server packages. Basically it feels similar enough to JavaScript for web development but with more expressiveness, so I'm pretty excited by the prospect.

Now this turns up a terrible delima, do I try to use Julia or Rust for writing embedded controllers? Rust has macros and direct memory control, but the article mentions. :)

I also think the more of us that recommend Julia for general compute, the more likely it'll get used that way.

[z92]

I am all for replacing Python with Julia.

[pjmlp]

Me too, maybe this will pressure more adoption of PyPy.

[pwang]

Can you elaborate on this?

[pjmlp]

For the majority of people without CS background Language == Implementation.

So if the reference implementation is a bare bones interpreter, even though there are JIT and AOT compilers tp choose from, they will say language X is interpreted.

Which in Python's case means many ignore the existence of PyPy, given that the language designers don't want to change the nature of CPython.

[tavert]

PyPy's adoption problem is not that it isn't the reference implementation. It's that it is incompatible with a huge body of Python modules that rely on C extensions. If you're going to lose access to libraries, may as well not make the same exact semantic decisions for a JIT-oriented language implementation that you made for an interpreted implementation.

[vmorgulis]

> ... that Julia is confined to scientific computing whereas I find it should really be a general purpose language.

It is intentional. Julia could be the new Fortran like Rust could be the new C++.

[renox]

> What I personally also find worrisome is the perception (at least for me) that Julia is confined to scientific computing whereas I find it should really be a general purpose language.

With 1-based array indexing? Very unlikely.