>Eventually, the code gets a speedup only after significant and non-obvious tuning that requires a lot of Julia experience I wouldn't say it's non-obvious: the

>Eventually, the code gets a speedup only after significant and non-obvious tuning that requires a lot of Julia experience I wouldn't say it's non-obvious: the things you have to do would be obvious to any programmer who's written code in something like C++. The problem usually tends to be that MATLAB, R, and Python tend to train people to want to use sub-optimal programming styles, like something heavy on array allocations, even if writing a function that does a loop is perfectly optimal. If someone is always told that mapping one function at a time ("vectorization") is the optimal way to do things, then they will try it when they go to a more optimal language. So it's really just a re-education issue.