frank VS jellylanguage

For the curious, "do be do be do" is a seminal paper in the literature on algebraic effects that introduces _frank_, quirky little language that has algebraic effects but not handlers, at least in the traditional sense.

Traditionally, an effect handler is an interpreter for a stream of commands, conforming to a specific interface. Generally, handlers surface in languages as a sort of generalized try/catch mechanism, that receive a "callback" to resume the "exception" that produced the command. In frank, not so.

Frank is based around the idea of _operators_, which generalize functions with the capability of interpreting multiple streams of commands. A plain function can be seen, in fact, as the special case of an operator that interprets no commands.

Operators are organized around ports and pegs. Pegs are the set of side effects that a computation needs. Each port is an offer to extend that set for downstream callers. Instead of building up a union of effects that each function needs, Frank propogated ambient ability inwards. Operators can then be composed based on the ports and pegs they offer.

operator: X → [peg]Y

This works partially because operators are shallow handlers and not deep handlers. Handlers interpret commands: if the handler itself is in scope when interpreting a command, then the language is said to have deep handlers. Frank has shallow handlers, meaning that commands are interpreted in an environment without the handling operator present. Shallow handlers give greater control to the programmer with respect to how commands are interpreted.

(This is a bad explanation because you already need to know what I'm talking about to understand what I'm talking about, but oh well.)

My one critism of frank is that the effect model is kinda hard for the working programmer to understand. I can explain Koka effects as "exceptions plus multiple resumption". I don't really have a categorical phrase for frank, and that's its innovation. This isn't so much a criticism but a plea for the pedagogical ramp to this research to improve.

do be do be do.

If you're still curious, check out the compiler github repo:

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

And if anything is wrong in the above explanation, please correct me, because we all benefit from Cunningham's Law in the end. Allow me to be the fool.

How does this compare to other effect-oriented languages like Koka, Frank, and Eff?

I've been doing some work with Koka lately, but I briefly looked into the other three (including Effekt) and it mostly came down to, 'Koka seems most active in development'[1] and 'Koka had the easiest to use documentation for me'[2].

[1] E.g. https://github.com/effekt-lang/effekt had its last commit back in June; https://github.com/frank-lang/frank last commit last year; but https://github.com/koka-lang/koka last update was Oct 15. Effekt seems semi-active, at least, compared to Frank. While stability is good, I wouldn't expect it in a language actively being used for research.

[2] Comparing https://koka-lang.github.io/koka/doc/book.html and https://effekt-lang.org/docs/ and https://www.eff-lang.org/learn/

Frank's effect handling. "A strict functional programming language with a bidirectional effect type system designed from the ground up around a novel variant of Plotkin and Pretnar's effect handler abstraction. ... Frank [is different from other PLs with effect type systems in that it is based on] generalising the basic mechanism of functional abstraction itself. A function is simply the special case of a Frank operator that interprets no commands. Moreover, Frank's operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. Effect typing in Frank employs a novel form of effect polymorphism which avoid mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards."

At least on the Code Golf Stack Exchange, I see a lot of people using esolangs for golfing (two random examples: Jelly [1] and O5AB1E [2]). I expect that it could be a line or two shorter at least with a change of language. As I recall some of the golfing langs also have pretty sophisticated compression techniques for strings, although they might be optimized for dictionary words. Careful distinction: they are all optimizing for bytes used, not characters used.

I don't want to neglect your shameless plug, but I struggle enough to find a solution to some of the puzzles I wrote (hence the undo), so finding the shortest path is a little daunting.

[1] https://github.com/DennisMitchell/jellylanguage

[2] https://github.com/Adriandmen/05AB1E

ADDITIONAL COMMENTS: I am also solving most of these problems in Jelly, a recreational language designed for code-golf. They are in the same repository under the jelly folder.

Jelly (put the input in the first command line argument):

Yes it is totally possible, Batch script is Turing complete afterall. Since you found Python tutorials, you can just apply the same concepts in Batch. The difficulty depends on the complexity of the language you're trying to make. I would recommend trying to make a stack-based language first, with the syntax similar to golfing languages (ie, one character is one "command", check out https://github.com/DennisMitchell/jellylanguage), since that would be the easiest. But obviously if you're up to it you could make a fully fledged programming language.

This is a basic version of many commonly used ideas for string compression in golfing languages. Jelly [0] is a good example of a more practical and versatile approach that builds on ideas such as this.

[0] https://github.com/DennisMitchell/jellylanguage/wiki/Tutoria...

(As an aside, some people "stop" here and then make programming languages based on this - because that is a simple interpreter... you could write a compiler for this language, or extend it - and the great golfing languages take that starting spot and keep going - don't worry about trying to replicate it, it takes some insanity to go that far - the point is that a stack based language is the starting spot for some impressive systems... like the JVM itself)

If you like code to be as short and unreadable as possible, try out Jelly.

Arguably, however, if you think about "High Level" in terms of "how many keystrokes do you need to do X complex task" (kinda like some mean komolgorov complexity measure over a set of tasks) then code golf languages could probably be the most "high level". Take Jelly for instance. Incomprehensible garbage when written, but goddamn if it isn't character efficient.

I am waiting for a time when we get Angular or React in Jelly [1]

[1] https://github.com/DennisMitchell/jellylanguage/wiki/Tutoria...

Being honest with naming things is also a great roundabout way to ensure you write maintainable, readable code. If the name is honest and it feels awkward, it's a good red flag that there might be a problem with the approach you're taking. I think code golf languages (a-la [0]) are a good example of this approach as well, when your language is as terse as possible, giving very deep consideration to what the language actually does is crucial.

[0] https://github.com/DennisMitchell/jellylanguage/wiki/Atoms