I personally did one project with PyO3 and it was a breeze.
For data analysis I initially implemented my physics model in python (say f=m*a), but during a fitting procedure (what is “a”, given a measured “m” and “f”?) this part of the code is called thousands of times.
Writing such a simple function is rust (twi numbers in (m and a guess for a), one number out (predicted f)) was easy. Since there are no complex data structures involved the borrow checker was happy the whole way through. Rust has bindings for numpy with the ndarray crate/library, so even that was simple.
Simply writing the numerics in rust gave a 40x speedup in my case. I got another 2.5x by making the main loop of my calculation parallel. With the rayon crate this is again a single line change, turning for x in array {...} into for x in array.par_iter() {...}
I can’t recommend it enough. If you have a single hot spot in your python code, this is the way to go, even if you are new to rust.
You are not logged in. However you can subscribe from another Fediverse account, for example Lemmy or Mastodon. To do this, paste the following into the search field of your instance: !programming@programming.dev
Welcome to the main community in programming.dev! Feel free to post anything relating to programming here!
Cross posting is strongly encouraged in the instance. If you feel your post or another person’s post makes sense in another community cross post into it.
Hope you enjoy the instance!
Rules
Rules
Follow the programming.dev instance rules
Keep content related to programming in some way
If you’re posting long videos try to add in some form of tldr for those who don’t want to watch videos
Interesting stuff, might give me an excuse to look into rust in the future. Thanks!
I personally did one project with PyO3 and it was a breeze.
For data analysis I initially implemented my physics model in python (say f=m*a), but during a fitting procedure (what is “a”, given a measured “m” and “f”?) this part of the code is called thousands of times.
Writing such a simple function is rust (twi numbers in (m and a guess for a), one number out (predicted f)) was easy. Since there are no complex data structures involved the borrow checker was happy the whole way through. Rust has bindings for numpy with the ndarray crate/library, so even that was simple.
Simply writing the numerics in rust gave a 40x speedup in my case. I got another 2.5x by making the main loop of my calculation parallel. With the rayon crate this is again a single line change, turning
for x in array {...}intofor x in array.par_iter() {...}I can’t recommend it enough. If you have a single hot spot in your python code, this is the way to go, even if you are new to rust.