[eggy]

I use Mathematica, and it's great strength is the curated data available for doing exploratory work. You can link to data with Python, but you need to set it up, but in Mathematica it's there from the installation. There are more things you can pay for and add, but the base installation is cohesive and powerful. Mathematica's notebook preceded Jupyter and is still better. I use the Home edition that I pay for. If I get work that uses Mathematica, I will buy the full version. I tried to use Octave as a substitute for Matlab but wound up moving to Julia. The code is very similar and easy to jump between the two sans the Matlab add-ons, however, Julia is developing a Symlink alternative.

My aversion to Python is a personal bias. It is an easy language to pick up and has won its place. I just don't like it. I was using Lush back in the day (Yann LeCun was one of the creators), and I wish it had won over Python due to my Lisp predilection [1]. It is a Lisp-like syntax that compiles to C.

[1] https://lush.sourceforge.net/

[actinium226]

What's the Julia Simulink alternative called? In Googling it I found sims.jl which isn't quite a simulink alternative so I wonder if you're talking about something else?

[ChrisRackauckas]

ModelingToolkit.jl, a comparison is given here: https://docs.sciml.ai/ModelingToolkit/dev/comparison/#Compar... . A showcase from one of the library's users, demonstrating a 15,000x acceleration, was given at a SIAM conference and the recording can be found here: https://www.youtube.com/watch?v=tQpqsmwlfY0

[eggy]

<<was given at a SIAM conference and the recording can be found here: https://www.youtube.com/watch?v=tQpqsmwlfY0>>

At 14:00, the interactive slider exploration due to the speed is amazing. Over 500 Monte Carlo simulations in less than 60ms.