There are very real pain points in Python, too. Developers tend to internalize these pain points to the extent that they’re completely blind to them, and that limits innovation. Not all interesting and fast algorithms can be vectorized. The idea behind Julia is that you can write code that should be fast, like loops, and it will be. You don’t have to bend over backwards to jam your algorithm into a C wrapper. It’s fair to question whether the trades with things like JIT compilation were worth it in Julia, but it should also be understood that NumPy is insufficient for supporting all of the interesting things you can do with arrays of numbers on a computer.
