bitvec VS crates.io

I was also under the false impression that bitwise encoding was slow. When I first implemented bitcode with bitvec I got performance 20x worse than bincode. After writing my own implementation I was able to get much better performance.

interesting; i'll have to compare this to my rust counterpart. your numbers indicate some clever implementations i'd love to read

Not to mention having a lackluster std which causes you to use nonstardard not so well documented crates and a 40K LoC library to do "bit-twiddling" (the lib, https://github.com/bitvecto-rs/bitvec the blog that says "twiddle bits" https://blog.adamchalmers.com/making-a-dns-client/ and for crying out loud the blogger also used the language the author mentioned and I quote "ergonomics AND speed AND correctness")

https://github.com/bitvecto-rs/bitvec/issues/135 is a very funny read about how to perform inttoptr with provenance retention

Technically #135 gives me license to yank affected crates, but since the only exploit is "Miri crashes exactly one test out of the suite" it's not really worth it to be a stickler. Call it a truce

My friend Nika wrote a macro that packs a sequence of 1, 0, … tokens into a correctly structured bit-buffer, adaptable over any register type or bit-ordering, at compile time. It's now basically this whole file

if you are interested in a user manual, you can use mdbook as well. for an example, my bitvec project uses mdbook (book.toml) and a github action (.github/workflows/gh-pages.yml) to compile the guide and host it as a github pages website. it's slightly more complicated, and i'd like docs.rs to follow hexdoc.pm's example of hosting both api docs and prose, but until then this is a pretty reasonable solution.

the first one

i would browse the standard library, tower, nom, or my own bitvec to see layout and trait/record separation. in particular, std::io and std::net may be of use: io::Read and io::Write are pervasive examples of implementing unixy file-descriptor-like behavior in the type system

Rust has a rich ecosystem of frameworks and libraries that let you read, parse, and manipulate text files, interact with cloud services and databases, and perform any other job that your project's development workflow may require. And because of its strong typing and tight memory management, you are much less likely to write programs that behave unexpectedly in production.

All the code discussed in this article can be accessed through this repository. For integration with existing projects consider using keyword_extraction crate available on crates.io.

So, be sure to double-check your critical libraries and be sure their alternatives exist in the Rust ecosystem. There’s a good chance the crates you need are available in Rust's crates.io repository.

The previous section was very simple, this section is also very simple but introduces us to cargo which is Rust's package manager, as a JS dev my mind goes straight to NPM.

Now, there has to be a place where all these packages come from. Similar to npmjs registry, where all node packages are registered, stored and retrieved, Rust also has something called crates.io where many helpful packages and dependencies are registered.

Before proceeding, let's check https://crates.io/, the official Rust package registry.

The most thrilling aspect has been the joy of writing the backend. It's like every struct, enum, and method in Rust forms this interconnected Multiverse of code , which you can see in crates.io which is best Documentation experience I Ever Had.

5. Crates.io

When using crates from eg. crates.io, and also things like std and core

Vendoring your packages was very tedious to even remotely get to work with Cargo. I spent a very long time getting Cargo to work together with cargo-local-registry. We vendor crates from crates.io and a custom internal registry.