maru
femtolisp
Our great sponsors
maru | femtolisp | |
---|---|---|
6 | 10 | |
180 | 1,550 | |
- | - | |
2.7 | 0.0 | |
6 months ago | about 4 years ago | |
Common Lisp | Scheme | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
maru
-
C Is Not a Low-level Language – Your computer is not a fast PDP-11
Well Forth is possibly the most minimal VM over a platform, as evidenced by openfirmware.
It does have problems scaling though, in that if you've seen one Forth, you've seen one Forth ie. The variations required to fit a platform make them semi-incompatible.
That's not to say that a more lispy Forth wouldn't be useful though, in that a concatenative syntax allows us to pass custom datastructures around like APL, and CPS (delimited continuations with lexically scoped dynamic binding would come from the lisp side (see https://github.com/manuel/wat-js).
Memory management in Forth can handle multiple memory types eg. https://flashforth.com/ so adding something like ref counting (https://github.com/zigalenarcic/minilisp/blob/main/main.c) to handle the dynamic list side of things might mesh well.
In any case, if you're looking for a self hosting lisp that runs on bare metal, https://github.com/attila-lendvai/maru has been out for a few years.
- Maru - a tiny self-hosting lisp dialect. Developed as part of Alan Kay's Fundamentals of New Computing.
-
About making a self hosting programming language
Take a look at Maru. The github project has links to other similar projects.
-
Why can't there be a LISP dialect/system that directly translates to optimal machine code?
That's the idea behind the Maru Project. It's a really cool concept and more people should know about it.
- lisp but small and low level?Does it make sense?
-
SubX: A minimalist assembly language for a subset of the x86 ISA
Here's another interesting one I just noticed:
https://github.com/attila-lendvai/maru/blob/maru.10/source/a...
femtolisp
- Petalisp: Elegant High Performance Computing
- fe: A tiny, embeddable language implemented in ANSI C
-
From Common Lisp to Julia
> In short, Julia is very similar to Common Lisp, but brings a lot of extra niceties to the table
This probably because Jeff Bezanson, the creator of Julia, created a Lisp prior to Julia, which I think still exists inside Julia in some fashion
https://github.com/JeffBezanson/femtolisp
-
Modern Python Performance Considerations
Well let's flip this around: do you think you could write a performant minimal Python in a weekend? Scheme is a very simple and elegant idea. Its power derives from the fact that smart people went to considerable pains to distill computation to limited set of things. "Complete" (i.e. rXrs) schemes build quite a lot of themselves... in scheme, from a pretty tiny core. I suspect Jeff Bezanson spent more than a weekend writing femtolisp, but that isn't really important. He's one guy who wrote a pretty darned performant lisp that does useful computation as a passion project. Check out his readme; it's fascinating: https://github.com/JeffBezanson/femtolisp
You simply can't say these things about Python (and I generally like Python!). It's truer for PyPy, but PyPy is pretty big and complex itself. Take a look at the source for the scheme or scheme-derived language of your choice sometime. I can't claim to be an expert in any of what's going on in there, but I think you'll be surprised how far down those parens go.
The claim I was responding to asserted that lisps and smalltalks can only be fast because of complex JIT compiling. That is trueish in practice for Smalltalk and certainly modern Javascript... but it simply isn't true for every lisp. Certainly JIT-ed lisps can be extremely fast, but it's not the only path to a performant lisp. In these benchmarks you'll see a diversity of approaches even among the top performers: https://ecraven.github.io/r7rs-benchmarks/
Given how many performant implementations of Scheme there are, I just don't think you can claim it's because of complex implementations by well-resourced groups. To me, I think the logical conclusion is that Scheme (and other lisps for the most part) are intrinsically pretty optimizable compared to Python. If we look at Common Lisp, there are also multiple performant implementations, some approximately competitive with Java which has had enormous resources poured into making it performant.
-
CppCast: Julia
While it uses an Algol inspired syntax, it has the same approach to OOP programing as CLOS(Common Lisp Object System), with multi-methods and protocols, it has a quite powerfull macro system like Lisp, similar REPL experience, and underneath it is powerered by femtolisp.
- Julia and the Incarceration of Lisp
-
What is the smallest x86 lisp?
For a real answer, other replies have already mentioned KiloLisp, but there's also femtolisp. Also, not exactly what you're asking for, but Maru is a very compact and elegant self-hosting lisp (compiles to x86).
-
lisp but small and low level?Does it make sense?
Take a look at femtolisp It has some low level features and is quite small. There is also a maintenance fork at lambdaconservatory
-
Lispsyntax.jl: A Clojure-like Lisp syntax for julia
A fun Julia easter egg I recently discovered.
Running 'julia --lisp' launches a femtolisp (https://github.com/JeffBezanson/femtolisp) interpreter.
-
Wisp: A light Lisp written in C++
Reminds me of the femtolisp README :)
Almost everybody has their own lisp implementation. Some programmers' dogs and cats probably have their own lisp implementations as well. This is great, but too often I see people omit some of the obscure but critical features that make lisp uniquely wonderful. These include read macros like #. and backreferences, gensyms, and properly escaped symbol names. If you're going to waste everybody's time with yet another lisp, at least do it right damnit.
https://github.com/JeffBezanson/femtolisp
What are some alternatives?
Carp - A statically typed lisp, without a GC, for real-time applications.
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
clasp - clasp Common Lisp environment
julia - The Julia Programming Language
flpc - Forth Lisp Python Continuum: A small highly dynamic self-bootstrapping language
sectorlisp - Bootstrapping LISP in a Boot Sector
Fennel - Lua Lisp Language
cosmopolitan - build-once run-anywhere c library
mu - Soul of a tiny new machine. More thorough tests → More comprehensible and rewrite-friendly software → More resilient society.
hissp - It's Python with a Lissp.