That's a very good point. Julia's debugger and profiler are both horrifyingly bad.
https://groups.google.com/forum/#!topic/julia-dev/-LTsBVRv1d...
You figure out who's who.
I was merely trying to understand why thebooktocome thought the profiler was so bad.
Have a nice day.
Also your words with the easy usage of "stupid" led me - wrongly! - into the direction that you might not be interested in understanding why users prefer Matlab, but more in expressing your opinion about the topic.
And to be frank, again perhaps due to my weak understanding of English, your usage of "You figure out who's who." and "Have a nice day" to me do not sound as the intention of trying to understand things but more on making clever remarks. But as I've pointed out, this might be due to the fact that English is not my native tongue.
In my experience (15 years), Matlab has been the best for exploratory data analysis. If you change a script, you don't need to worry about re-importing issues like in python; you can even change code DURING a debugging session, EVEN with GUIs. I have been using python+numpy+pandas for a few years now, and python just feels like there is an impedance there that I don't get from Matlab, primarily with graphics/matplotlib. But, deploying and sharing python is easier. I admit it could just be my experience with Matlab that biases me. I usually find that people bitching about Matlab don't like the language, and that is usually because they are viewing Matlab AS the language (like python), and not as a data exploration and analysis environment.
Relevant to the topic at hand, Julia does have that functionality already, and it in fact (afaik) uses the same engine that's behind iPython, the Jupyter environment. There's even a web-based community version for people to try stuff out: https://www.juliabox.org/
If you mean a packaged script more like a mathematica notebook, I don't believe so.
I don't have much to offer to Julia on technical terms. Octave's codebase started as pre-standard C++, and it's been a long and arduous job to very slowly modernise it. Julia has the advantage of starting modern.
I think the biggest lesson I've learned is, don't underestimate Matlab. It may be old, it may be an ugly language, but it also is gigantic, very well-funded, and everywhere. Julia and Octave are approaching Matlab from different angles, Julia by providing a better language and Octave by providing a free drop-in replacement, but ultimately we are both trying to replace Matlab.
Matlab users greatly value having a complete package with an editor, debugger, visualiser, profiler, and system modeller all in one. They don't generally see Simulink or the symbolic toolbox as being separate components, or indeed, as the completely separate programs that they really are. For the devout Matlab users, these conveniences greatly outweigh a better programming language. Going further, many Matlab users don't even consider their activity "programming" at all, and in recent years Matlab even writes the code for you if you just push a few buttons.
We're seeing some academics slowly switching over to Julia. This is great. The Mathworks knows very well that captivating young, malleable minds in university is how you get loyal paying customers, namely, the future bosses of these newly-molded minds. Julia is doing a good job appealing to profs. I am optimistic that within five years or so, new generations of Julia-trained graduates will slowly spread the love of the new language.