femtolisp
foth
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femtolisp | foth | |
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10 | 9 | |
1,550 | 69 | |
- | - | |
0.0 | 5.1 | |
about 4 years ago | 2 months ago | |
Scheme | Go | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 only |
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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.
femtolisp
- Petalisp: Elegant High Performance Computing
- fe: A tiny, embeddable language implemented in ANSI C
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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
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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.
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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
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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).
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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
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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.
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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
foth
- Show HN: Writing a simple FORTH-like system, in simple steps
- Show HN: Implementing a simple FORTH, inspired by a Hacker News thread
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Byte Magazine: The FORTH programming language
I hacked up a simple forth-like system in golang, by following the overview posted in this hackernews comment-chain:
https://news.ycombinator.com/item?id=13082825
The result is here:
https://github.com/skx/foth
It's not real, but it was a pretty fun experiment regardless.
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Jonesforth – A sometimes minimal FORTH compiler and tutorial (2007)
Here's one of the many forks that brings it up to 64-bit:
https://github.com/matematikaadit/jombloforth
If you like forth there's an awesome series of comments here on hacker news on building a simple variant in a few simple steps:
https://news.ycombinator.com/item?id=13082825
I took that, and built a simple forth-like system, in golang following the original recipe and breaking it down into simple steps for learning-purposes:
https://github.com/skx/foth
- Forth control flow execution steps.
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ColorForth (2009)
I'll always vote up submissions referencing anything FORTH related. For me FORTH is as much fun as lisp appears to be for others. I've never really done much with it, but I always like the simplicity and the ability to reason about it.
Sure FORTH has problems of its own, but it's always nice to use. I've hacked up a couple of simple FORTH-like systems over the years, most recently this one which was inspired by a thread on this site:
https://github.com/skx/foth
A lot of people go through guides of writing a lisp, I'd love to urge people to try writing a simple FORTH interpreter instead, or even something somewhat related such as TCL.
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Lang Jam: create a programming language in a weekend
There's even a recipe posted in a couple of comments here:
https://news.ycombinator.com/item?id=13082825
I followed that guide to implement a simple FORTH-like system in golang:
https://github.com/skx/foth
As I was following the implementation recipe I broke it down into "educational steps". Although it isn't a true FORTH it is pretty easy to understand and useful enough to embed inside other applications.
Now and again I consider doing it again, but using a real return-stack to remove the hardcoded control-flow words from the interpreter, but I never quite find the time.
- Tutorial-style FORTH implementation written in Golang
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Wisp: A light Lisp written in C++
I actually hacked up a simple forth-like system, after reading a brief howto here on hackernews:
https://github.com/skx/foth/
Here's the thread which has the barebones overview which inspired me:
https://news.ycombinator.com/item?id=13082825
I could have taken it further, but the implementation there is not "real" in the sense that there is no real return-stack, so you can't implement IF-statements using the lower-level primitives.
That said it is a good starting point, and I had some fun doing it. I'd guesstimate it is more of a single weekend project though, rather than longer.
What are some alternatives?
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
wisp - A little Clojure-like LISP in JavaScript
julia - The Julia Programming Language
rustc_codegen_cranelift - Cranelift based backend for rustc
Carp - A statically typed lisp, without a GC, for real-time applications.
cling - The cling C++ interpreter
Fennel - Lua Lisp Language
sectorlisp - Bootstrapping LISP in a Boot Sector
factor - Factor programming language
hissp - It's Python with a Lissp.
zForth - zForth: tiny, embeddable, flexible, compact Forth scripting language for embedded systems