hissp
femtolisp
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hissp | femtolisp | |
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29 | 10 | |
331 | 1,550 | |
- | - | |
9.1 | 0.0 | |
3 months ago | about 4 years ago | |
Python | Scheme | |
Apache 2.0 | BSD 3-clause "New" or "Revised" License |
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hissp
- Hissp
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2 line tic tac toe
Hissp is a Python library that can compile a whole program into one Python expression.
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What's the most hilarious use of operator overloading you've seen?
If you want Python to be as customizable as Lissp, check out Hissp (and Hebigo).
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Pythoneers here, what are some of the best python tricks you guys use when progrmming with python
Hissp is really cool for metaprogramming Python. There's also macropy, but it's harder to use.
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Lush – Lisp-like language for deep learning designed by Yann LeCun
I prefer https://github.com/gilch/hissp, where Hy has to use shims to pretend statements are expressions, Hissp just targets the expression subset in the first place. (though as you mentioned, hy has a lot of literature and support around it, where as you're going to have to find your own way around hissp)
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A Python-compatible statically typed language erg-lang/erg
No shortage of options, e.g. Dg, Mochi, Coconut, and Hebigo (based on Hissp[1]).
[1]: https://github.com/gilch/hissp
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Other than having a wider range of libraries and beingthus being more "general purpose" and "practical" is there anything that makes Python an intrinsically better programming language than Lisp?
If you want Lisp metaprogramming plus Python ecosystem, check out Hissp
- Lisp.py
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What are some amazing, great python external modules, libraries to explore?
Hissp is really interesting. Read through the docs and you'll understand Python more deeply. It works well with Toolz and Pyrsistent.
- Why Hy?
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
What are some alternatives?
hy - A dialect of Lisp that's embedded in Python
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
hy-lisp-python - examples for my book "A Lisp Programmer Living in Python-Land: The Hy Programming Language"
julia - The Julia Programming Language
libpython-clj - Python bindings for Clojure
Carp - A statically typed lisp, without a GC, for real-time applications.
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
Fennel - Lua Lisp Language
incanter - Clojure-based, R-like statistical computing and graphics environment for the JVM
sectorlisp - Bootstrapping LISP in a Boot Sector
lisp-rosetta-stone - A lisp rosetta stone to demonstrate modern language features
awesome-lisp-companies - Awesome Lisp Companies