3 ms·
There were some problems during the transition between 0.6 and 1.0 but that was kinda expected. After 1.0 it's been pretty breezy. Good IDE support (juno). Jul
by adamnemecek 8y ago
There were some problems during the transition between 0.6 and 1.0 but that was kinda expected. After 1.0 it's been pretty breezy.
Good IDE support (juno). Julia is fast. Numpy is actually c, julia is just julia.
You have an amazing interop that just works. With python, matlab, c,c++,etc etc.
https://github.com/JuliaPy/PyCall.jl https://github.com/JuliaPy/PyCall.jl
Package manager just works.
The language is a lot more powerful. Diffeq is around 1000 lines of code which is nuts.
- ChrisRackauckas 8y agoDiffEq is a lot more than a 1000 lines of code. By now it's about 75 git repo and some of those repos are themselves >10,000 lines of code. And there is a single file in the test suites that is 10,000 lines defining mathematical constants for 200 Runge-Kutta tableaus. So it's way way more, and actually quite large by now. However, we still get a lot of feature bang for our lines of code buck.
- adamnemecek 8y agoLol. I think I looked at it a while back.