Programming-Language-Benchmark VS ripgrep

I found Zig implementation of json parsing is interesting. The code is free from hidden control flow !.

https://github.com/hanabi1224/Programming-Language-Benchmark...

It appears helloworld is the only test with any repeats, and it only has 5 repeats. https://github.com/hanabi1224/Programming-Language-Benchmark...

Here's the measurement code, it appears to be significantly more complicated than a simple fork/exec/wait loop but that could just be all the C# getting in the way: https://github.com/hanabi1224/Programming-Language-Benchmark... Nevertheless you are probably right that the bulk of this 1.8ms is in the executable under test, and it truly is just bloat. Running `hyperfine ./empty-main-function` from rustc on my Mac gives 0.8ms.

Is faster... on code that has been optimized to hell and back 5 times over and no longer resembles anything like normal code written in the language.

Seriously, this is the code for the top program. I'm reasonably sure 99% of C++ programmers could not decipher it without spending significant amounts of time on google: https://github.com/hanabi1224/Programming-Language-Benchmark...

I appreciate that fair benchmarks across languages are a hard problem, but this is not a good solution to it. Any reference to this data as a comparison between "programming languages and compilers" needs to come with a giant disclaimer that it's comparing them at something you almost certainly don't use them for, and is very far from their main use case.

I also appreciate that this is a repetitive comment the likes of which always come up when this benchmark is mentioned... but I really don't see another way to avoid people misinterpreting it. Very few people are going to spontaneously click through to the code.

ripgrep - https://github.com/BurntSushi/ripgrep

Basic code searching skills seems like something new developers are never explicitly taught, but which is an absolutely crucial skill to build early on.

I guess the knowledge progression I would recommend would look something kind this:

- Learning about Ctrl+F, which works basically everywhere.

- Transitioning to ripgrep https://github.com/BurntSushi/ripgrep - I wouldn't even call this optional, it's truly an incredible and very discoverable tool. Requires keeping a terminal open, but that's a good thing for a newbie!

- Optional, but highly recommended: Learning one of the powerhouse command line editors. Teenage me recommended Emacs; current me recommends vanilla vim, purely because some flavor of it is installed almost everywhere. This is so that you can grep around and edit in the same window.

- In the same vein, moving back from ripgrep and learning about good old fashioned grep, with a few flags rg uses by default: `grep -r` for recursive search, `grep -ri` for case insensitive recursive search, and `grep -ril` for case insensitive recursive "just show me which files this string is found in" search. Some others too, season to taste.

- Finally hitting the wall with what ripgrep can do for you and switching to an actual indexed, dedicated code search tool.

live grep: ripgrep

The world has moved on though to opinionated tools, and Rust isn't even the furthest in that direction (That would be Go). The equivalent of those two lines in Cargo.toml would be this example of a basic configuration from the jacoco-maven-plugin: https://www.jacoco.org/jacoco/trunk/doc/examples/build/pom.x... - That's 40 lines in the section to do the "defaults".

Yes, you could add a load of config for files to include/exclude from coverage and so on, but the idea that that's a norm is way more common in Java projects than other languages. Like here's some example Cargo.toml files from complicated Rust projects:

Servo: https://github.com/servo/servo/blob/main/Cargo.toml

rust-gdext: https://github.com/godot-rust/gdext/blob/master/godot-core/C...

ripgrep: https://github.com/BurntSushi/ripgrep/blob/master/Cargo.toml

socketio: https://github.com/1c3t3a/rust-socketio/blob/main/socketio/C...

I'm not clear on why you're seeing the results you are. It could be because your haystack is so small that you're mostly just measuring noise. ripgrep 14 did introduce some optimizations in workloads like this by reducing match overhead, but I don't think it's anything huge in this case. (And I just tried ripgrep 13 on the same commands above and the timings are similar if a tiny bit slower.)

[1]: https://github.com/radare/ired

[2]: https://github.com/BurntSushi/ripgrep/discussions/2597

Explore o Ripgrep no repositório oficial: https://github.com/BurntSushi/ripgrep

🔎🗃️ ripgrep or ugrep (search fast, use regex patterns or fuzzy search, pipe output to bash/zsh shell for further processing V coloring)