numericals
CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental] (by digikar99)
py4cl2
Call python from Common Lisp (by digikar99)
numericals | py4cl2 | |
---|---|---|
6 | 11 | |
47 | 39 | |
- | - | |
7.7 | 5.6 | |
about 1 month ago | 7 days ago | |
Common Lisp | Common Lisp | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
numericals
Posts with mentions or reviews of numericals.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-02.
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numericals - Performance of NumPy with the goodness of Common Lisp
How about the semantics? Nevermind, I looked -- utter nonsense, just like numpy.
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Good Lisp libraries for math
Then there is a question - do you actually need these libraries? You can optimize code in Common Lisp (type declarations, usage of appropriate data structures, SIMD instructions etc). See this: https://github.com/digikar99/numericals/tree/master/sbcl-numericals <- SIMD instructions used from SBCL (on x86; these are processor-family specific so Apple M1 will have different ones).
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Image classification in CL? Help with starting point
*I have not; I have a couple of WIP/alpha-stage libraries like dense-arrays and numericals that could be useful; once I find the time, I want to think about if these or its dependencies can be integrated into the existing libraries including antik mentioned by awesome-cl.
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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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polymorphic-functions - Possibly AOT dispatch on argument types with support for optional and keyword argument dispatch
I made this while running into code modularity issues with the numericals project I attempted last year; I did discover specialization-store, but found its goals in conflict with what I wanted to achieve; so I ended up investing in this.
py4cl2
Posts with mentions or reviews of py4cl2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-05.
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An Idea for Piggybacking Python (language) ecosystem
I... recently got that working: https://github.com/digikar99/py4cl2/tree/master/cffi - Yes, CFFI! Yes, passing CL array data by reference!
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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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interested in learning lisp, (specifically for games, but also for everything else including tui and gui applications for linux. currently have next to no programming knowledge, can i get forwarded some resources and some tips on what exactly i should do? any videos i should watch?
Python: Blender and Panda3D (game engine used for Disney's Toontown way back when) are both scriptable with Python. I've been able to successfully call Panda from Py4CL2 (thanks digikar for the help with that), but I have not tried with Blender yet. I think it's doable.
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Rewrite Your Scripts In LISP - with Roswell
While you are at it I may as well mention https://github.com/digikar99/py4cl2
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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.
- Using Lisp as a Dynamic Library
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What are the advantages of Hy/Hissp over python bindings for CL/Clojure?
py4cl2 (not py4cl!) author here. From the v2.9.0 docs:
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Design patterns for Lisp interop with other languages?
py4cl and py4cl2 represent a fairly pragmatic example of method 1, using an OS child process to communicate back and forth with your python code. Python is fairly popular and well-enabled with libraries, so you can delegate things to python that leverage those libraries.
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Image classification in CL? Help with starting point
If you can structure your code so that data de/serialization is not a bottleneck, then you could access the python libraries using py4cl/2.
What are some alternatives?
When comparing numericals and py4cl2 you can also consider the following projects:
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
py4cl - Call python from Common Lisp
specialization-store - A different type of generic function for common lisp.
numcl - Numpy clone in Common Lisp
Petalisp - Elegant High Performance Computing
farolero - Thread-safe Common Lisp style conditions and restarts for Clojure(Script) and Babashka.
dense-arrays - Numpy like array object for common lisp
vega-lite - A concise grammar of interactive graphics, built on Vega.
specialized-function - Julia-like dispatch for Common Lisp