fabruic VS tokei

For today, I've chosen to use my best guess as to the best type of blocking wrapper for each type of operation, but the long-term goal is utilizing a new async executor that Daxpedda is working on. It's compatible with tokio, but it already has a concept named block_on_blocking, which is an optimized version of blocking designed to more fairly block without needing to adopt a 'static lifetime requirement due to using spawn_blocking. He's about to resume working on the executor, but he was responsible for the QUIC-based networking stack PliantDB is using and is wrapping up a few last requests before moving on.

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.

cloc repalcement - Tokei

Not sure if anyone mentioned tokei yet but it’s excellent

My approach would be to use Tokei to count LOC and cargo-tree(1) to find dependencies. You can then locate the dependencies in the registry and count each of their LOC, then combine the results.

However, considering File Content Indexing is enabled, I should look at how much text data it has to index, so I did it, I used tokei to count the LOCs of my development directories, these are the results: ```