femtolisp
yaegi
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femtolisp | yaegi | |
---|---|---|
10 | 39 | |
1,550 | 6,574 | |
- | 2.3% | |
0.0 | 5.6 | |
about 4 years ago | 16 days ago | |
Scheme | Go | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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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
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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.
yaegi
- Traefik/Yaegi: Yaegi Is Another Elegant Go Interpreter
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Go: What We Got Right, What We Got Wrong
Yes. There are long standing feature requests for (e.g.) the reflect package that simply don't get done because they'd break this assumption and/or force further indirection in hot paths to support "no code generation at runtime, ever".
Packages like Yaegi (that offers an interpreted Go REPL) have "know limitations, won't be addressed" also because of these assumptions.
https://github.com/golang/go/issues/4146
https://github.com/golang/go/issues/16522
https://github.com/traefik/yaegi?tab=readme-ov-file#limitati...
- Fourteen Years of Go
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Gojekyll – 20x faster Go port of jekyll
There is always https://github.com/traefik/yaegi - a Go interpreter written to make it easy to write plugins.
- Jacobin: Minimal JVM written in Go and capable of running Java 17 classes
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Can Go run statements in cmd like Python?
I think https://github.com/traefik/yaegi comes as close as using the python interpreter in you CLI, but for Go
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Can Go files be compiled by themselves?
There's a go interpreter: https://github.com/traefik/yaegi It could run programs without compiling them, but there're some limitations.
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referencing packages on the internet and using go plugin
I'd recommend looking into a different approach for plugins such as hashicorp/go-plugin (which uses multiple process PIDs and RPC communication between them) or traefik/yaegi (which implements a Go-compatible scripting language that can be interpreted at runtime and which still supports most Go modules).
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Mun v0.4.0: a statically-typed scripting language like Rust, written in Rust
Why do we need a language like Rust when we have Rust. Why not just create a Rust interpreter. (There's such an interpreter for Go, BTW, https://github.com/traefik/yaegi )
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Plugo - A plugin library for Go.
A cool solution I saw was Traefik's yaegi module. They basically created an interpreted scripting language with Go compatible syntax (turning Go into an interpreted, not compiled, language). I haven't tried this but it sounds like it brings the better parts of dynamic languages like Python's plugin support to Go - plugin writers can still write "Go" code, which can load dynamically.
What are some alternatives?
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
golive - ⚡ Live views for GoLang with reactive HTML over WebSockets 🔌
julia - The Julia Programming Language
gomacro - Interactive Go interpreter and debugger with REPL, Eval, generics and Lisp-like macros
Carp - A statically typed lisp, without a GC, for real-time applications.
grule-rule-engine - Rule engine implementation in Golang
Fennel - Lua Lisp Language
gobook - Simple in Pure Go in Browser Interactive Interpreter
sectorlisp - Bootstrapping LISP in a Boot Sector
scriggo - The world’s most powerful template engine and Go embeddable interpreter
hissp - It's Python with a Lissp.
gophernotes - The Go kernel for Jupyter notebooks and nteract.