I’m not sure I would consider the scientific computing that Julia targets a “tiny” niche. It’s worth remembering that Python is 30 years older than Julia, and Julia has only been in a really usable state for 4 or 5 years. You can’t expect it to displace Numpy/Scipy/etc overnight. Especially if you include machine learning, where there’s just huge momentum with large corporations having massively invested in Python frameworks for at least 10 years. Subjectively, I’m seeing quite a lot of growth in Julia. It’s certainly a much stronger language than the Python/C++ combination that currently has the biggest market share in that area.

Also, there’s nothing wrong with niches. Julia is undoubtedly less of a general-purpose language like Python, but it very much shines in its domain.

> I certainly consider Julia to be a Lisp

Can you elaborate some more on this? My worldview assumed that a lisp used a list as a primary code/data structure and Julia doesn't seem to be doing that... Of course it does provide a way to manipulate code and data because of its macros. But what makes a lisp a lisp?

I think the commenter refers to the fact that in Julia, code is data, even if it is not represented as lists. This allows the existence of macros, which are syntactic sugar to functions modifying code. Also that most (all?) lisps have multiple dispatch as a fundamental part of the language, and Julia does too.

Every time this pops up, I feel compelled to point out how different Julia macros look like from regular Julia code, especially once the macros get complicated.

"Code as data" is not quite the same thing as homoiconicity, which I feel is Julia's missing piece.

Here's a meme that might help: https://www.reddit.com/r/LispMemes/comments/irkm5m/nobody_li...