genemichaels VS tokei

Python and JavaScript have similarly good formatters (as long as your idiot colleagues don't insist on using yapf instead of Black, despite yapf producing non-deterministic output!). In fact I would say Rust is probably behind Prettier in terms of auto formatting. The rustfmt output is less pretty (subjective I know), the devs have made several strange decisions and it seems to be semi-abandoned (maybe partly because the devs were ... shall we say not as friendly and welcoming as the Rust community likes to bleat on about).

There are a couple of alternative formatters:

* https://github.com/andrewbaxter/genemichaels

There are alternatives to rustfmt: Prettier Rust and genemichaels

Gene Michaels, code formatter

I think we should all take inspiration from Gene Michaels and just start naming crates after random people.

So If we would only count code and not comments, it is only 9489 LoC Rust. Which would be about 0.03% and if we take all lines and not only LoC it would be around 0.05%

[0] https://github.com/XAMPPRocky/tokei

[1] https://github.com/torvalds/linux/commit/b401b621758e46812da...

thirdly: found this (https://github.com/XAMPPRocky/tokei) and wanted to analyze languages used on my system, didn't see a package manager (apt) for it that I had. So i installed cargo via apt-get rustup. Added the bin folder to $PATH via PATH=$PATH:~/.cargo/bin. But did not make it permanent. And stupidly rand tokei on "/", realizing how long and unhelpful that would be killed it. Then ran it in a dump folder with some very nested repo dumps, and tons of wolfram.nb files. After killing that too, and attempting to kill via system monitor. Still have two of those as zombie processes.

tokei

For what it's worth, tokei seems to be named after tokei.

BTW, for more info on how it is done, you can check out tokei which is the library use by onefetch for code statistics.

With pytokei you can count code quickly using all the power from tokei, but from python.

Tokei is a nice utility to count lines and stats of code. It is very fast, accurate, and has a nice output. It supports over 150 languages and can output in JSON, YAML, CBOR, and human-readable tables.