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Me a couple years ago: Hah there's no efficient implementations of a rope in rust. I'll port my C rope impl over - oh wait, rust is hard. Me now: Hah yeah C code working! Oh wait, there's lots of amazing implementations in cargo. ... They're better than mine, too! O_opic.twitter.com/Ij8lpWMqPR
This is made with criterion, which if its not obvious is *amazing*. https://github.com/japaric/criterion.rs … I said before rust/etc > JS but npm > all, and that matters more. Now ... http://crates.io . Y'all are kind of killing it
Explorable report here: https://josephg.com/ropereport/report/ … Comparing random insert / delete operations (weighted to inserts) in a string of size X. Check this out - this is the same test run on a dedicated machine vs my laptop. You can see the laptop thermal throttling in the spread!pic.twitter.com/WnAaKnoVeK
Code: https://github.com/josephg/rustrope … Report generated with `cargo run --release` in the bench/ directory, using rust 1.31.0-nightly.
Alright one more cool thing:
I don't know what data structure an-rope is using, but its getting less efficient over time. In comparison you can see how the skip list in my jumprope library gives much less predictable perf, but is much more stable.
stats!pic.twitter.com/sicsfLI4bn
Bahahaha this is a chart of O(n) vs O(log n) algorithms. Red line is the naive memcpy based implementation. Everything else stacks along the bottom of this chart. I'm leaving this here for next time I teach algorithms.pic.twitter.com/wP1fcXtD24
What did you use to draw those charts?
Criterion (the rust benchmarking crate) draws them, calling gnuplot behind the scene for the charts. https://crates.io/crates/criterion …
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