rust-toolchain VS flamegraph

I currently use dtolnay/rust-toolchain to install the Rust toolchain instead

FYI, I'm fairly sure actions-rs is basically unmaintained. The maintainer hasn't been seen on GitHub for a couple years now. I would instead try using dtolnay's toolchain action instead, which is IMO much simpler to use anyway.

I already had some experience with GitHub Actions (their native CI/CD framework) and after finding rust-toolchain I wanted to experiment with whether it'd be feasible to use Actions as a compute service.

I've migrated to https://github.com/dtolnay/rust-toolchain for managing rustup, and https://github.com/Swatinem/rust-cache for caching

I would also not want to maintain 1000s of lines of JavaScript and TypeScript with an eye-watering 693 dependencies. ... https://github.com/dtolnay/rust-toolchain which is 54 lines

You can install cargo-flamegraph with cargo install flamegraph. There are some underlying requirements to be able to use cargo-flamegraph; you will want to take a look at the repo here to make sure you have the right dependencies.

I tried to diagnose the issue with flamegraph, but unfortunately the flamegraph didn't show anything beyond the next call for some reason

having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go)

I'm currently implementing a solution for the first part of the day 16. It work but it is really slow... I'd like to : - understand why - having some tools to identify slowness origins (flamegraph is one... but not sure it's the way to go) - eventually have some clue/solution/idea - have general feedback on what in my "coding style" is not appropriate for rust (I come from java/kotlin/ts even if I've already coded a bit in c/c++) : for example I love iterator & sequence but i feel they are not really suited to overuse in rust (mostly because of async & result).

Use a profiler. Flamegraph is a good way to visualise profiler output. This lets you identify which functions are taking up a large amount of time - and hence helps you identify where to focus your optimisation efforts.

You tried trying to see what takes the most time under load via flames? https://github.com/flamegraph-rs/flamegraph

Well, in cases like that the answer is straight forward, use a profiler like https://github.com/flamegraph-rs/flamegraph

I don't see any obvious problems with your algorithm. I've had luck using cargo-flamegraph to identify the slow parts of my code. That's going to show you which parts to focus on improving the performance of!

From the readme of cargo flamegraph: