mlton
chumsky
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mlton | chumsky | |
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9 | 54 | |
916 | 3,316 | |
0.8% | - | |
8.3 | 9.0 | |
15 days ago | 17 days ago | |
Standard ML | Rust | |
GNU General Public License v3.0 or later | MIT License |
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mlton
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Flunct: Well-typed, fluent APIs in SML
https://github.com/MLton/mlton/issues/473
Is there sufficient use of MLTon "native" backend out there to consider it mature? or Do people prefer the LLVM or C backend instead in general?
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Simple JSON parser in c++, rust, ocaml, standard ml
Once I got the parser ready in OCaml, I thought I port it to Standard ML, since it belong to the same ML language family. I was also curious on how well mlton could optimise it. The language lacks custom let bindings, so I resorted to use Result.bind manually. This makes code much less readable and more verbose. The standard library also lacks result type, so I had to come up with my own simple implementation. There's also a lack of any hash map in the standard library, so I just used a list of key-value pairs. This isn't correct, but it's the closest I could get without inventing my own hash map. MLton's compile times are slow. It also lacks interactive REPL. Because of that I used alternative Standard ML implementation for interactive usage: PolyML. Debugging MLton binaries is also pretty hard. gdb doesn't work and there's no bundled debugger. I had to resort to debugging facilities built into PolyML. Valgrind doesn't work with mlton binaries, as it doesn't report any memory allocations. Looks like mlton uses mmap for allocation memory. Surprisingly, performance is not the best. This might be due to heavy usage of my custom Result type and bind calls. Exceptions seem to be a more natural choice for error reporting in Standard ML. I tried to make such a change, but this didn't improve the performance much.
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old languages compilers
MLton
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Modules: Overcoming Stockholm and Duning-Kruger
Something I’d highly recommend you do before concluding that SML’s module system is the best is to go through and read the MLton Basis library. MLton uses the module system extremely heavily in its definition of the standard, and I think it’s extremely important to understand what you may be getting yourself into when you add those features, and what you may lose in return.
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Ante: A low-level functional language
If you’re fine with tracing GC (which depends on the situation, of course), Standard ML is a perfectly boring language (that IIUC predated and inspired Caml) and MLton[1] is a very nice optimizing compiler for it. The language is awkward at times (in particular, the separate sublanguage of modules can be downright unwieldy), and the library has some of the usual blind spots such as nonexistent Unicode support (well, not every language WG is allocated a John Cowan).
Speaking of, Scheme can also be a delightful unexciting static language; consider for example the C-producing implementation Chicken[2]. The pattern-matching / algebraic-datatype story was still rather unsatisfying last I checked, but there are other situations where it shines—it’s complementary to SML in a way.
You’re not going to be writing a kernel or a real-time renderer in either (though I’m certain people have taken that as a challenge), they son’t afford the flashy EDSLs of Tcl, Ruby, or Racket, and I can’t say I can prototype in them like I do in Python or sh+tools, but there is a comfortable middle ground where they fit well. (I hear others use Go in what seem like the same places, but to me it feels so thin and devoid of joy that I can’t really compare.)
The FFI tools in both of the mentioned implementations are excellent, though not quite at the “type in C declarations” level of LuaJIT and D.
[1] http://mlton.org/
[2] https://call-cc.org/
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Write your own programming language in an hour with Chumsky
Unfortunately, I haven't found a ton of "easily-digestible" and, at the same time, comprehensive guides on compiling functional languages. Generally you'll find a mix of blog posts/class notes/papers covering a single step.
Some resources I like:
- Andrew Kennedy's 2007 paper Compiling with Continuations, Continued [1]. This one is the most clear IMO
- Andrew Appel's Compiling with Continuations book (a bit outdated though... assembly code is for VAX)
- Matt Might's series [2]
- MLton's source and documentation [3]
[1] https://www.microsoft.com/en-us/research/wp-content/uploads/...
[2] https://matt.might.net/articles/closure-conversion/
[3] http://mlton.org/
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Why are imperative programs considered faster than their functional counterparts?
More broadly, they can be fast even without such extensions if they aggressively pursue optimization opportunities afforded by static typing, like MLton for example, but that also impacts compilation performance negatively.
- Coalton: How to Have Our (Typed) Cake and (Safely) Eat It Too, in Common Lisp
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Are there any efficient key-value map/dictionary implementations in SML?
https://github.com/MLton/mlton/blob/master/lib/mlton/basic/hash-set.sig https://github.com/MLton/mlton/blob/master/lib/mlton/basic/hash-table.sig
chumsky
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Lezer: A Parsing System for CodeMirror, Inspired by Tree-Sitter
I attempted to use this but was disheartened but the fact that it doesn't statically type node names. Tree Sitter doesn't either but it has much more of an excuse given that it targets C.
https://github.com/lezer-parser/lezer/issues/8
The dev seems mildly hostile to outside involvement too, so I moved on. These days I use Chumsky which is Rust rather than Typescript, but also way more awesome, if you can deal with the often incomprehensible compilation errors at least!
https://github.com/zesterer/chumsky
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nom > regex
there’s also chumsky: https://github.com/zesterer/chumsky
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Writing an Equation Solver
We are using technique called parser combinator. And we are using a library chumsky to write parser combinators.
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loxcraft: a compiler, language server, and online playground for the Lox programming language
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.
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Examples of function-based parsers in chumsky? Examples of unit tests?
The examples that come with chumsky and the chumsky tutorial and guide all define their parsers using closures.
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Flamingo - A start: the syntax, a soon-to-be-built keyword-less lang with flavoured code blocks. Seeking help and advice please :)
Parser: https://crates.io/crates/chumsky
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pep-508 v0.2.1 - Zero copy Python dependency parser written with chumsky
chumsky's zero-copy rewrite has reached its first alpha release, and I have migrated my pep-508 parser to it, as suggested in my last announcement.
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winnow = toml_edit + combine + nom
On my side, nom is still advancing well and a new major version is in preparation, with some interesting work a new GAT based design inspired from the awesome work on chumsky, that promises to bring great performance with complex error types. 2023 will be fun for parser libraries!
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Rust implementation of Python dependency parser for PEP 508
I am using chumsky because I like the API, but it doesn't support zero copy at the moment. Although efficiency is good to have, it is not my primary good. This will probably get supported once chumsky implements support for it (see upstream issue).
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Question about lexer and parser generators in Rust
Checkout https://github.com/zesterer/chumsky or https://github.com/rust-bakery/nom
What are some alternatives?
LunarML - The Standard ML compiler that produces Lua/JavaScript
nom - Rust parser combinator framework
typed-racket - Typed Racket
pest - The Elegant Parser
sml-parseq - parallel sequences library in Standard ML
pom - PEG parser combinators using operator overloading without macros.
seL4 - The seL4 microkernel
lalrpop - LR(1) parser generator for Rust
tao - A statically-typed functional language with generics, typeclasses, sum types, pattern-matching, first-class functions, currying, algebraic effects, associated types, good diagnostics, etc.
combine - A parser combinator library for Rust
smlfmt - A custom parser/auto-formatter for Standard ML
instaparse