rust-peg VS rust

And some related parser tools: - https://github.com/kevinmehall/rust-peg - https://github.com/pest-parser/pest - https://github.com/lalrpop/lalrpop

Rust is a very nice langage for implementing compilers, and has a nice ecosystem for it (logos, rust-peg, lalrpop, astmaker -- this one is mine --, etc...).

My peg crate is a parser generator that supports arbitrary token types as input. See https://github.com/kevinmehall/rust-peg/blob/master/tests/run-pass/tokens.rs for an example.

The one rust parser-generator I used is PEG

The two parser generators that I am aware of are lalrpop and PEG. There both great, and have seen some use by languages that have been written in Rust.

rust-peg

I wanted to create a parser for Apertium Stream. In 2014, I used Whittle in Ruby. If this year were 2001, I would use Lex/Yacc. Anyway, this year is 2021. I wanted to create this parser in Rust. I tried to find what is similar to Lex/Yacc. I found Rust-Peg. I found a link to Nom from Rust-Peg's document. My first impression was Nom example is easy to read. At least, its document claimed Nom is fast.

The peg crate has a resolved issue about this.

I don't really know that much about parsing and grammars, other than what I've learned about regular languages and expressions and context-free languages in a standard Theory of Comp course from my university. I basically just learned peg by reading the Wikipedia article on PEGs, reading the crate documentation to understand the syntax, and then looking at some of the peg examples on their GitHub to understand how it works in practice.

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.