A really powerful outworking of it is seen in the Rayon crate, where you can change a sequential iterator into a parallel iterator just by adding the crate, importing the trait and changing `iter` to `par_iter`. If it’s not thread-safe to do, then it won’t compile. (That’s the big difference from C++.) If it is, it will, and it’ll be smart about how it runs, spreading the load across all available cores pretty much optimally, or not bothering with multiple threads if it’s not going to be worth it (e.g. single-threaded, or only one item in the iterator). And all that with close enough to no overhead.

Basically, Rayon makes data parallelism really easy in a way that few if any other languages do. I’d love to have an equivalent in Python or Node, but it’s just not possible to achieve such a thing in most languages—even if you ignore the thread safety aspect.

Parallelism hasn’t seen a great deal of use until it’s urgently needed, because it’s hard to get right in most environments, and you normally need to substantially refactor code to make it happen. My hope is that with the likes of Rayon, parallelism can be a much more natural thing that people that care even a little about performance will just do, because it’s so easy to do.

https://crates.io/crates/rayon