lalrpop VS pom

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

rust-langdev has a lot of libraries for building compilers in Rust. Perhaps you could use these to make your implementation easier, and revisit it later if you want to build things from scratch. I'd suggest logos for lexing, LALRPOP / chumsky for parsing, and rust-gc for garbage collection.

Hi! For one of my projects I am currently using lalrpop (https://github.com/lalrpop/lalrpop/tree/master/doc/calculator/src), which is far from complete, but has the basic syntax I was looking for. I took some examples and worked around some lexer stuff but I’m currently happy with it. If you use it and have Intellij stuff installed, you can also use a plug-in for highlighting and SOMETIMES error checking. Otherwise, even VSCode had a great plug-in for highlighting!

How would you compare and contrast this with, say, lalrpop?

lalrpop is great. It's a completely different approach from nom, but for parsing a programming language, I would at least consider it. RustPython uses it.

I presume LALRPOP handles left recursion just fine.

I wanted to share an experimental side project I have been working on for some time. I constantly use commands like `jq` and `yq` for processing structured data in my day job and I was curious if a similar idea could be applied to images.

Another goal of mine was to get some exposure to with rust. I discovered the LALRPOP parser generator which really helped moved the project along (https://github.com/lalrpop/lalrpop)

The key point here is that we are going to depend on the lalrpop library to generate the parser based on the formal grammar we define. Note that we have it as part of the [build-dependencies] section and we only depend on a tiny utility crate called lalrpop-util at runtime. The reason for that is the main lalrpop "magic" would happen during the crate compilation (in the build.rs file) when lalrpop would generate the deterministic pushdown automaton based on our grammar. The code generation logic is not required to be part of our interpreter, we only need a few utility methods from the lalrpop-util for the automaton to operate. You might have noticed that we also enable the lexer feature of lalrpop, because we are going to use lexer provided by lalrpop as well (please refer to the Part I if you do not know what the lexer is).

pom

Maybe a parser combinator library is not what you want? One alternative might be writing an expression parser without a library at all: https://matklad.github.io/2020/04/13/simple-but-powerful-pratt-parsing.html (Depending on the grammar you are parsing a Pratt parser might actually be a good fit!) A PEG might also be more suitable for your use case, like pom.

I saw the performance comparison against pom, pom is unfortunately quite slow compared to an handwritten parser as it boxes most (all?) parsers so you may want to compare against a handwritten parser, or at least something in the same ballpark (for reference, combine's json benchmark on the same data is about 6x faster with "good errors", when optimized to work on &str-like input it is about 12x faster, nom or a hand written parser may be another 10-20% faster than that, if I remember correctly.) From a brief skim of the code, I don't see anything that would hinder it from at least closing that gap however.

Everyone on this sub seems to be using nom. In my experience I find pom to be intuitive and have to write less code. Maybe it's just me I'm having a hard time understanding nom which has a lot of function calls rather than less.If you compare both the json examples on both projects, the pom example is a lot clearer to read and a lot shorter.