neanderthal
hissp
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neanderthal | hissp | |
---|---|---|
5 | 29 | |
1,043 | 331 | |
0.1% | - | |
7.0 | 9.1 | |
about 1 month ago | 3 months ago | |
Clojure | Python | |
Eclipse Public License 1.0 | Apache 2.0 |
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.
neanderthal
- AI’s compute fragmentation: what matrix multiplication teaches us
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Having trouble setting up Neanderthal.
There is the official Hello World https://github.com/uncomplicate/neanderthal/tree/master/examples/hello-world
- Da li u Srbiji , generalno prostoru balkana , ima "Ozbiljnih" Open source kreatora?
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Anybody using Common Lisp or clojure for data science
Did you have any occasion to evaluate neanderthal during your research? People seem to prefer it over core.matrix because it focus on primitive speed and sticking to BLAS idioms (as well as offering a decent api for working with GPU backends via cuda and opencl). I am curious to see if you did and found anything lacking there. I have a project on the backburner to try and target neanderthal for local search stuff, expressing problems in a high-level API that can then be baked into some numerically-friendly representation for efficient execution. It's often easier (trivial) to express solution representations, neighborhood functions, and objectives/constraints in a general purpose language, of which none of the things we like (sparse data structures, dynamically allocated stuff) are amenable to the contiguous memory, primitive numeric model that the hardware wants.
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I want to quit my data analyst job and learn and become a Clojure developer
Do clojure as a side gig or in free time. Let day job pay the bills. If you can, maybe incorporate clojure into work job to solve small problems (https://github.com/clj-python/libpython-clj and https://github.com/scicloj/clojisr provide bridges to/from python and r). There is a lot of effort going into the data science side as well; the scicloj effort has resulted in a lot of growth over the last 2 years. tech.ml.dataset, tech.ml (now scicloj.ml). Dragan has a bunch of excellent stuff in neanderthal and deep diamond. There are also bindings to other jvm libraries from multiple languages.
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?
dtype-next - A Clojure library designed to aid in the implementation of high performance algorithms and systems.
hy - A dialect of Lisp that's embedded in Python
libpython-clj - Python bindings for Clojure
hy-lisp-python - examples for my book "A Lisp Programmer Living in Python-Land: The Hy Programming Language"
deep-diamond - A fast Clojure Tensor & Deep Learning library
numcl-benchmarks - benchmarks against numpy, julia
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
magicl - Matrix Algebra proGrams In Common Lisp.
femtolisp - a lightweight, robust, scheme-like lisp implementation
qvm - The high-performance and featureful Quil simulator.
incanter - Clojure-based, R-like statistical computing and graphics environment for the JVM