symreg VS coalton

Well, I wrote a genetic programming library, and it was fun to parse a Lisp-like representation from Python. You still have recursion and everything (albeit no tail call optimization).

Here, `_from_source` goes from a plain array of tokens to a nested one (tree), depending on their arity:

https://github.com/danuker/symreg/blob/7c6593d3046f6c52dfb92...

Lisp is almost valid Python. The exception is the single-element tuple which needs a comma: (x,)

But I still preferred to use Python as a programming language, and Lisp as a sort of AST. It's just easier. I am curious what roadblocks you faced in your ASCII delimited parsing.

Do you by any chance still have the two parsers? I'd love to see them. If you are worried about your anonymity, you can find my website on my HN profile, and my e-mail on my website. I promise not to disclose your identity publicly.

If interpretability is sufficiently important, you could straight-up search for mathematical formulae.

My SymReg library pops to mind. I'm thinking of rewriting it in multithreaded Julia this holiday season.

https://github.com/danuker/symreg

Indeed, I ran face-first into Python's GIL that prevents any useful CPU-bound multithreading, with my symbolic regression library.

If you like type safety, this project would be perfect for using https://coalton-lang.github.io/ so your REPL supported Common Lisp out of the gate.

Agree that you can use types to express and prove logical properties via compiler; it can be a fun way to solve a problem though too much of it tends to frustrate coworkers. It's also not exactly "low cost"; here's an old quip I have in my quotes file:

"With Scala you feel smart having just got something to work in a beautiful way but when you look around the room to tell your clojure colleague how clever you are, you notice he left 3 hours ago and there is a post-it saying use a Map." --Daniel Worthington-Bodart

> On the contrary, they're still the most effective technique we've found for improving program correctness at low cost.

This is not borne out by research, such as there is any of any quality: https://danluu.com/empirical-pl/ The best intervention to improve correctness, if not already being done, is code review: https://twitter.com/hillelogram/status/1120495752969641986 This doesn't necessarily mean dynamic types are better, just that if static types are better, they aren't tremendously so to obviously show in studies, unlike code review benefit studies.

My own bias is in favor of dynamic types, though I think the way Common Lisp does it is a lot better than Python (plus Lisp is flexible enough in other ways to let static type enthusiasts have their cake and eat it too https://github.com/coalton-lang/coalton), and Python better than PHP, and PHP better than JS. Just like not all static type systems are C, not all dynamic type systems are JS. Untyped langs like assembly or Forth are interesting but I don't have enough experience.

I don't find the argument that valuable though, since I think just focusing on dynamic vs static is one of the least interesting division points when comparing languages or practices, and if we're trading experience takes I think Clojure's immutable-by-default prevents more bugs than any statically typed language that is mutable by default. It's not exactly a low cost intervention though, and when you really need to optimize you'll be encouraged by the profiler to replace some things with Java native arrays and so on. I don't think changing to static types would make a quality difference (especially when things like spec exist to get many of the same or more benefits) and would also not be a low cost intervention.

Last quip to reflect on. "What's true of every bug found in the field? ... It passed the type checker. ... It passed all the tests. Okay. So now what do you do? Right? I think we're in this world I'd like to call guardrail programming. Right? It's really sad. We're like: I can make change because I have tests. Who does that? Who drives their car around banging against the guardrail saying, "Whoa! I'm glad I've got these guardrails because I'd never make it to the show on time."" --Rich Hickey (https://www.infoq.com/presentations/Simple-Made-Easy/)

> Lisps can be very flexible, but they usually lack static type safety, opening a wide and horrible door to run-time errors.

People should do basic research before writing something silly like this. Qualifying your statement with 'usually' is just a chicken sh*t approach. Common Lisp and Racket have optional strong typing, leaving the responsibility and choice to the developer. Common Lisp is great for implementing compilers. You also have thing like Typed Racket and Coalton. The latter is comletely statically typed ala MLTON

https://github.com/coalton-lang/coalton

Coalton doesn't actually work: https://github.com/coalton-lang/coalton/issues/84?s=09

This is why it's important to always look at the issues on a repo instead of just believing what's in the README. It fails to detect type errors in some of the most basic situations

> static strong typing

Alright, here is it: https://github.com/coalton-lang/coalton/

> small efficient native binaries

The numbers are: with SBCL's core-compression, a web app with dozens on dependencies will weight ±30 to 40MB. This includes the compiler, the debugger, etc. Without core compression, we reach ±150MB.

> The actor runtime?

the actor library: https://github.com/mdbergmann/cl-gserver

> couldn't find a way to make money with it. I suspect many other programmers are in my boat.

Alright. Some do, that's life. Yes, some companies go with CL even in 2023 (https://lisp-journey.gitlab.io/blog/lisp-interview-kina/, they released https://github.com/KinaKnowledge/juno-lang lately; Feetr (finance): https://twitter.com/feetr_io/status/1587182923911991303)

https://github.com/azzamsa/awesome-lisp-companies/

> Give us an HTTP (1.x & 2.0) and WebSockets libraries

How so? We have those libraries. HTTP/2: https://github.com/zellerin/http2/

https://github.com/CodyReichert/awesome-cl

1. There are functional dependencies and multi-parameter type classes. No GADTs (yet?) or existential types (yet?).

2. Records are being implemented but it's far from being a dealbreaker, in the sense that thousands of production lines of Coalton have been built without needing them. It's just not ergonomic to shuffle around and pattern match against record-like data. With pattern matching in function arguments, things are at least easier.

3. All Coalton functions compile to Lisp functions. There's a guide that describes what is promised about interop (https://github.com/coalton-lang/coalton/blob/main/docs/coalt...).

4. Since Coalton functions are Lisp functions, you can call (unconstrained) functions directly. However there's a lot of room for improvement. There's an open issue to make a dedicated Coalton REPL that can show types and not require COALTON to be typed.

5. Coalton is developed as an open source project to build tools at HRL Laboratories, so it does receive sponsorship. Yes, HRL is hiring. Feel free to send me an email to the address in my profile.

Coalton [1] is a dialect of ML with S-expression syntax and integrates into Common Lisp. It works, and is used "in production" by its developers, but it's still being developed into a 1.0 product.

Coalton made a lot of design decisions that resonate with this post.

- Coalton dispensed with structures, signatures, and functors. No doubt a beautiful concept, and sometimes satisfying to write, but almost always unsatisfying to use. Like the author suggests, the "interface-style" of type classes, traits, and interfaces have always felt more intuitive, and that different interfaces should require different types. Coalton uses type classes.

- Coalton has S-expression syntax. No indent rules. No precedence rules. No expression delimiters. All of the "tradition" of ML syntax is dispensed with into something that is a lot easier to write.

- It should be no surprise that with S-expressions, you get Lisp-style macros. Macros in Coalton are just Common Lisp macros. No separate pre-processors. No additional language semantics to deal with.

- Because it's built on Common Lisp, Coalton gets something few (if any?) other ML-derivatives get: Truly incremental and interactive development. You can re-compile types, functions, etc. and try them out immediately. There's no separate "interpreter mode"; just a Lisp REPL.

Coalton's language features are still settling (e.g., records are being implemented) and the standard library [2] is still evolving. However, it's been used for "serious" applications, like implementing a compiler module for quantum programs [3].

[1] https://github.com/coalton-lang/coalton

[2] https://coalton-lang.github.io/reference/

[3] https://coalton-lang.github.io/20220906-quantum-compiler/

Is Malli for clojure what coalton is for common lisp?

If proper abstraction, type safety, as well as performance is important, then you might want to try out Coalton.