magicl
py4cl
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magicl | py4cl | |
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14 | 21 | |
225 | 221 | |
0.4% | - | |
5.4 | 2.3 | |
6 months ago | 6 months ago | |
Common Lisp | Common Lisp | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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.
magicl
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A tutorial quantum interpreter in 150 lines of Lisp
(Link didn't work for me)
https://github.com/quil-lang/magicl/blob/master/src/high-lev...
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Why Lisp?
use MAGICL. [1] It is optionally and transparently accelerated by BLAS/LAPACK.
[1] https://github.com/quil-lang/magicl/blob/master/doc/high-lev...
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How fast can you multiply matrices using only common lisp?
Maybe have a look at how magicl does this?
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A software engineer's circuitous journey to calculate eigenvalues
This is essentially the first option, which is already supported by MAGICL by loading MAGICL/EXT-LAPACK [1].
[1] https://github.com/quil-lang/magicl#extensions
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Uncle Stats Wants You
I think what the magicl team has done is brilliant - allowing multiple implementations is awesome.
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Good Lisp libraries for math
Second up is magicl, especially useful if performance is a concern. This might not be as extensive as numcl, but it's been battle tested in the industry over the last decade or so. Because this uses generic functions, so long as you are using not-very-small arrays, performance should not be a concern for you. And even if you are, you could write your own functions that use the low-level functions that magicl's backends define. Otherwise performance can be at par with numpy.
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Why is python numpy *so* much faster than lisp in this example?
This Dev How-To describes (I hope in enough detail) how to add these specialized routines to MAGICL.
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CL-AUTOWRAP generated (C)BLAS wrapper in QUICKLISP
I agree... and I do don't want be the person who has not rallied. I just took a look at guicho's issue from 2019. And here, you yourself have admitted that the high level interface is less than ideal and needs more work. However, the very point that magicl is an industry standard could imply that potentially radical backward-incompatible changes can be hard. But, honestly, I want to discuss this, time permitting!
- Fast and Elegant Clojure: Idiomatic Clojure without sacrificing performance
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Anybody using Common Lisp or clojure for data science
Common Lisp is a great language to build new tools for data science, but currently has pretty awful library support existing data science workflows. Common Lisp is sorely lacking in high-quality statistics, plotting, and sparse arrays. There’s been a long work-in-progress library to bring flexible and high-performance linear algebra to Lisp, but it needs more contributors.
py4cl
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Need recommendation for IPC with Go
py4cl and cl4py rely on uiop:launch-program and python's subprocess respectively. These are portable to the extent uiop and subprocess are portable and do not require any additional installation.
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Lisp-Stick on a Python
If you want to use Python libs from CL, see py4cl: https://github.com/bendudson/py4cl the other way around, calling your efficient CL library from Python: https://github.com/marcoheisig/cl4py/ There might be more CL libraries than you think! https://github.com/CodyReichert/awesome-cl (or at least a project sufficiently advanced on your field to join forces ;) )
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The German School of Lisp (2011)
FYI you can call Python from CL: https://github.com/bendudson/py4cl and CL from Python: https://github.com/marcoheisig/cl4py/
If you don't know Emacs, see other editors: https://lispcookbook.github.io/cl-cookbook/editor-support.ht... If you want the more Smalltalk-like experience I'd go with the free LispWorks version: it has many GUI panes that allow to watch and discover the state of the program.
I personally couldn't stay long with Hylang. You won't get CL niceties: more language features, performance, standalone binaries, interactive debugger (all the niceties of an image-based development)…
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Plotting
I ended up using a fair bit of matplotlib through college and with colleagues. I too don't want to use python, but I also don't like throwing away its libraries, and I'm too lazy to invest in other* plotting ecosystems. In effect, I use up using matplotlib through py4cl/2.
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numericals - Performance of NumPy with the goodness of Common Lisp
Note that it is not my aim to replace the python ecosystem; I think that is far too lofy a goal to be of any good. My original intention was to interoperate with python through py4cl/2 or the likes, but felt that one needs a Common Lisp library for "small" operations, while "large" operations can be offloaded to python libraries through py4cl/2.
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Good Lisp libraries for math
If performance is absolutely not a concern, then third option is using python libraries through py4cl/2. To put it differently, if calling python from lisp is not the bottleneck, then this is a feasible option.
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Why Hy?
I encourage people to try out Common Lisp because, unlike with Hy, you will get: speed, ability to build binaries, truly interactive image-based development (yes, more interactive than ipython), more static type checks, more language features (no closures in Hy last time I checked), language stability… To reach to Python libs, you have https://github.com/bendudson/py4cl My comparison of Python and CL: https://lisp-journey.gitlab.io/pythonvslisp/
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Tutorial Series to learn Common Lisp quickly
> Not sure if such a thing already exists for CL
couple of solutions exist for this
https://github.com/bendudson/py4cl
https://github.com/pinterface/burgled-batteries
- Calling Python from Common Lisp
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(define (uwu) (display "nya~\n"))
Ahh, makes sense. Well, if you ever wanna steal some of python's thunder, libpython-clj worked great for me lol. Supposedly py4cl fills a similar role in Common Lisp.
What are some alternatives?
lisp-matrix - A matrix package for common lisp building on work by Mark Hoemmen, Evan Monroig, Tamas Papp and Rif.
py4cl2 - Call python from Common Lisp
criterium - Benchmarking library for clojure
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
Petalisp - Elegant High Performance Computing
hy - A dialect of Lisp that's embedded in Python
hash-array-mapped-trie - A hash array mapped trie implementation in c.
libpython-clj - Python bindings for Clojure
april - The APL programming language (a subset thereof) compiling to Common Lisp.
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
skiko - Kotlin MPP bindings to Skia
racket - The Racket repository