procs VS tokei

You can have a look at this repo for some inspiration, since it's mostly cross platform. It uses the winapi crate for Windows and the procfs for Unix.

procs is a ps replacement. It provides colorized human-readable output, multi-column search, more information than ps, docker support, paging, watch mode, and tree view. It is a much more user-friendly and modern alternative to ps. You can filter by name and PID and use logical and/or operators to combine multiple filters. It also has a tree view which is very useful for seeing the process hierarchy. It can also show docker container names for the process running docker containers.

ps replacement - Procs

prox: A modern replacement for ps written in Rust.

For example, add the below entry to the TOML config file if you want to download the procs tool as well.

Preview process trees (using procs)

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.