rust VS too-many-lists

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.

To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.

Another week, another dive into Rust. This time, we're delving into structs. Structs bear resemblance to interfaces in TypeScript, enabling the grouping of intricate data sets within an object, much like TypeScript/JavaScript. Rust also accommodates functions within these structs, offering a semblance of classes, albeit with distinctions. Let's delve into this topic.

There’s also other reasons. For example, take binary search:

* prefetch + cmov. These should be part of the STL but languages and compilers struggle to emit the cmov properly (Rust’s been broken for 6 years: https://github.com/rust-lang/rust/issues/53823). Prefetch is an interesting one because while you do optimize the binary search in a micro benchmark, you’re potentially putting extra pressure on the cache with “garbage” data which means it’s a greedy optimization that might hurt surrounding code. Probably should have separate implementations as binary search isn’t necessarily always in the hot path.

* Eytzinger layout has additional limitations that are often not discussed when pointing out “hey this is faster”. Adding elements is non-trivial since you first have to add + sort (as you would for binary search) and then rebuild a new parallel eytzinger layout from scratch (i.e. you’d have it be an index of pointers rather than the values themselves which adds memory overhead + indirection for the comparisons). You can’t find the “insertion” position for non-existent elements which means it can’t be used for std::lower_bound (i.e. if the element doesn’t exist, you just get None back instead of Err(position where it can be slotted in to maintain order).

Basically, optimizations can sometimes rely on changing the problem domain so that you can trade off features of the algorithm against the runtime. These kinds of algorithms can be a bad fit for a standard library which aims to be a toolbox of “good enough” algorithms and data structures for problems that appear very very frequently. Or they could be part of the standard library toolkit just under a different name but you also have to balance that against maintenance concerns.

You seem to have a preset opinion, and I'm not sure you are interested in re-evaluating it. So this is not written to change your mind.

I've developed production code in C, C++, Rust, and several other languages. And while like pretty much everything, there are situations where it's not a good fit, I find that the solutions tend to be the most robust and require the least post release debugging in Rust. That's my personal experience. It's not hard data. And yes occasionally it's annoying to please the compiler, and if there were no trait constraints or borrow rules, those instances would be easier. But way more often in my experience the compiler complained because my initial solution had problems I didn't realize before. So for me, these situations have been about going from building it the way I wanted to -> compiler tells me I didn't consider an edge case -> changing the implementation and or design to account for that edge case. Also using one example, where is Rust is notoriously hard and or un-ergonomic to use, and dismissing the entire language seems premature to me. For those that insist on learning Rust by implementing a linked list there is https://rust-unofficial.github.io/too-many-lists/.

Advent of Code was okay until I encounterd a problem that required a graph, tree or linked list to solve, where I hit a wall. Most coding exercises are similar--those requiring arrays and hashmaps and sets are okay, but complex data structures are a PITA. (There is an online course dedicated to linked lists in Rust but I couldn't grok it either). IMO you should simply skip problems that you can't solve with your current knowledge level and move on.

I feel obligated to point to the original cannon literature: https://rust-unofficial.github.io/too-many-lists/

I started learning Rust and like how the compiler is fussy about things. My plan was to implement the data structures I knew, but I got stuck at the singly linked list's remove() method. I've read the book as well, but I have no clue how to simplify this further:

My impression from the article is that Zig provides several different hashtables and not all of them are broken in this way.

This reminds me of Aria's comment in her Rust tutorial https://rust-unofficial.github.io/too-many-lists/ about failing to kill LinkedList. One philosophy (and the one Rust chose) for a stdlib is that this is only where things should live when they're so commonly needed that essentially everybody needs them either directly or to talk about. So, HashTable is needed by so much otherwise unrelated software that qualifies, BloomFilter, while it's real useful for some people, not so much. Aria cleaned out Rust's set of standard library containers before Rust 1.0, trying to keep only those most people would need. LinkedList isn't a good general purpose data structure, but, it was too popular and Aria was not able to remove it.

Having multiple hash tables feels like a win (they're optimized for different purposes) but may cost too much in terms of the necessary testing to ensure they all hit the quality you want.

> Cyclic references can be dealt with runtime safety checks too - like Rc and Weak.

Indeed. Starting out with code sprinkled with Rc, Weak, RefCell, etc is perfectly fine and performance will probably not be worse than in any other safe languages. And if you do this, Rust is pretty close to those languages in ease of use for what are otherwise complex topics in Rust.

A good reference for different approaches is Learn Rust With Entirely Too Many Linked Lists https://rust-unofficial.github.io/too-many-lists/

Second, once you've finished something introductory like The Book, read Learning Rust With Entirely Too Many Linked Lists. It really helped me to understand what ownership and borrowing actually mean in practical terms. If you don't mind paying for learning materials, a lot of people recommend Programming Rust, Second Edition by Blandy, Orendorff, and Tindall as either a complement, follow-up, or alternative to The Book.

Learning Rust With Entirely Too Many Linked Lists which highlights a lot of the differences with how you need to structure your code in Rust compared to other languages.