Imagine spending a lot of time on learning Julia, then imagine you want to do web dev, then imagine your favorite language is Julia, and you don't want to use time on learning something else? So why not I guess. From reading the landing page, I don't see a compelling reason to use it unless you are already in the ecosystem, which is fair.
Frameworks are helpful when a community would benefit by having a bit less variety in how things are done. Even if it's sub-optimal for most individual use cases, having a standard way of building applications in a community makes it easier to construct and maintain projects.
People are free to use their time & energy to develop interesting things in whatever language/toolchain/techstack they like and share with the community.
That is how ecosystems evolve, expand, and new ecosystems emerge.
We don't want to be locked into incumbent solutions forever.
Not everything needs to have corporate support or large scale use from day one. It doesn't even have to be useful at all on day one, or ever for that matter.
Julia is a fairly elegant nice language and multiple dispatch makes a lot of sense in all sorts of places.
I don't really get why Julia is pigeon-holed for numerics. I prefer its syntax to Python and would consider it for scripting applications where I use Julia now.
I also think Julia is a very nice language and I prefer its syntax over Python.
However, I can understand why Julia is "pigeon-holed for numerics". It started as a language for scientific computing. Today, it promotes itself as a general-purpose language suitable for any task - not just for scientific tasks. Only time will tell if perception of the language will shift. As this discussion shows though, the association with scientific computing remains strong.
“We want a language that's open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that's homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled.”
The language may have been intended to be a general-purpose language from the beginning, but my recollection is that the focus was firmly on scientific computing (and remains the principal sphere of activity). The quote you shared also seems to hint at that focus.
