Did #julialang end up kinda stalling or at least plateau-ing lower than hoped?
I know it’s got its community and dedicated users and has continued development.
But without being in that space, and speculating now at a distance, it seems it might be an interesting case study in a tech/lang that just didn’t have landing spot it could arrive at in time as the tech-world & “data science” reshuffled while julia tried to grow … ?
Can a language ever solve a “two language” problem?
IMO Julia just had way too many big issues to gain critical mass:
Copied 1-based indexing from MATLAB. Why? We’ve known that’s the worse option for decades.
For ages it had extremely slow startup times. I think because it compiles everything from C, but even cached it would take like 20s to load the plotting library. You can start MATLAB several times in that time. I believe they improved this fairly recently but they clearly got the runtime/compile time balance completely wrong for a research language.
There’s an article somewhere from someone who was really on board with Julia about all the issues that made them leave.
I still feel like there’s space for a MATLAB replacement… Hopefully someone will give it a better attempt at some point.
GNU Octave?
https://en.wikipedia.org/wiki/GNU_Octave
The only benefit Octave has over MATLAB is that it’s free. Which is something I guess, but in practice it is MATLAB without the benefits of MATLAB.
It’s plotting functionality sucks as much as anything else, it has fairly good toolkit support but not remotely like MATLAB, and it still has the mediocre MATLAB language. Worse - with custom incompatible extensions!
@FizzyOrange
Yea I remember reading about some deeper issues with the language (Dan Luu was quite dark on it I think) and that more or less turned me off. At the time I would have had to have been amongst some dedicated users urging me on to consider adoption.