Comment by abdullahkhalids
1 day ago
The reason is quite simple. Julia is a language designed for scientific computation. Numpy is a library frankenstein-grafted onto a language that isn't really designed for scientific computation.
We can only hope that Julia somehow wins and those of forced to work in python because of network effects can be freed.
Julia really needs to generalize and clarify its deployment story before it could possibly take off. It was built with a promise of generality but its tethered packaging is an albatross.
Nah, because "Python is second-best at everything" and has more libraries than the Galactic Federation, that will never happen.
This has me wondering, if not that, then what is python designed for?
To be general purpose with a very large package ecosystem so that you can get just about anything started pretty quickly. It is relatively easy to do things that aren't performance critical with python, which is great if you want an MVP to grow off of or if you're messing around with something and want to make a little flask server for it, or maybe run some image recognition, or a little anything. It's really just insanely flexible and puts a lot of the cognitive load in libraries so you can get straight to doing stuff, again, often at the cost of performance.
I've been hoping this for 15 years, but so far I still use Python for everything.