[Lyngbakr]

I only used Julia for a short time, but I didn't see the blazing fast speeds I was promised. I've seen the benchmarks, of course, on which the claims are founded, but the C-like speeds weren't obvious to me in everyday data science workflows. In the end, there wasn't sufficient motivation for me to switch to Julia as my weapon of choice. I do like Pluto[0], though...

[0]https://plutojl.org/

[BrandonS113]

If doing data science, I find Julia's tools to be inferior to Python and R. But in my work, when it comes to long computations, not only does Julia usually vastly outperform both, we write Julia code faster with fewer errors.

[thejosh]

What kind of questions are you trying to answer?

What's the area for the long computations you're doing?

Just curious :)

[rightbyte]

You need to know how the compiler propagates types in detail to write performant code. It is quite hard.

[CyberDildonics]

It's not 'quite hard' you just need to put types on your variable and function declarations.

If you leave them off you can make a function generic but you need to make sure you don't have multiple returns that could each return different types.