numcl | hissp | |
---|---|---|
9 | 29 | |
627 | 333 | |
0.3% | - | |
0.0 | 9.1 | |
7 months ago | 4 months ago | |
Common Lisp | Python | |
GNU General Public License v3.0 or later | Apache 2.0 |
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numcl
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How fast can you multiply matrices using only common lisp?
Is it me or numcl is faster than magicl? Matrix multiplication on magicl with pure lisp backend is
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Rewrite Your Scripts In LISP - with Roswell
Interesting, I will, thanks! I am aware of numcl for CL, but I don't think it is "there" yet :).
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Good Lisp libraries for math
The first that comes to mind is numcl. This works if (i) performance is not seriously a concern, (ii) you are not annoyed by julia-like JIT/JAOT compilation delays, (iii) copy-based slicing won't be a performance issue for you. To be fair, limitation (i) might be overcome by writing a better (simd-based) backend for numcl. numcl is fast, it compiles to fairly good code, but simd can boost the performance by another 4-8 times or so.
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Efficiently/easily sample from a list - any existing alternative?
am I missing something that already exists (numcl / Alexandria / core language, etc?)
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Lisp as an Alternative to Java (2000)
>Either implement numpy equivalent on your own or half of your code is data massaging data between libraries
I haven't tested this but here you go:
https://github.com/numcl/numcl
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Machine Learning in Lisp
Personally, I've been relying on the stream-based method using py4cl/2, mostly because I did not - and perhaps do not - have the knowledge and time to dig into the CFFI based method. The limitation is that this would get you less than 10000 python interactions per second. That is sufficient if you will be running a long running python task - and I have successfully run trivial ML programs using it, but any intensive array processing gets in the way. For this later task, there are a few emerging libraries like numcl and array-operations without SIMD (yet), and numericals using SIMD. For reasons mentioned on the readme, I recently cooked up dense-arrays. This has interchangeable backends and can also use cl-cuda. But barring that, the developer overhead of actually setting up native-CFFI ecosystem is still too high, and I'm back to py4cl/2 for tasks beyond array processing.
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cbaggers/rtg-math - a selection of the math routines most commonly needed for making realtime graphics in lisp (2, 3 and 4 component vectors, 3x3 and 4x4 matrices, quaternions, spherical and polar coordinates). [2019]
numcl - Numpy clone in Common Lisp. [LGPL3][9].
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SBCL: New in Version 2.1.0
[3] https://github.com/numcl/numcl
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?
What are some alternatives?
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
hy - A dialect of Lisp that's embedded in Python
april - The APL programming language (a subset thereof) compiling to Common Lisp.
hy-lisp-python - examples for my book "A Lisp Programmer Living in Python-Land: The Hy Programming Language"
lisp-matrix - A matrix package for common lisp building on work by Mark Hoemmen, Evan Monroig, Tamas Papp and Rif.
libpython-clj - Python bindings for Clojure
Petalisp - Elegant High Performance Computing
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
cl-containers - Containers Library for Common Lisp
femtolisp - a lightweight, robust, scheme-like lisp implementation
magicl - Matrix Algebra proGrams In Common Lisp.
incanter - Clojure-based, R-like statistical computing and graphics environment for the JVM