Anybody using Common Lisp or clojure for data science

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/lisp

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  • magicl

    Matrix Algebra proGrams In Common Lisp.

    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.

  • numcl-benchmarks

    benchmarks against numpy, julia

    For example, numcl aims to be a clone of numpy. The published benchmarks are not impressive. My aim is not to second guess the author or belittle his project and effort.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • burgled-batteries

    A bridge between Python and Lisp (FFI bindings, etc.)

    burgled batteries

  • py4cl

    Call python from Common Lisp

    py4cl

  • CLPython

    An implementation of Python in Common Lisp

    cl-python

  • qvm

    The high-performance and featureful Quil simulator.

    Yes, simulator, compiler, paper is some of it.

  • quilc

    The optimizing Quil compiler.

    Yes, simulator, compiler, paper is some of it.

  • SonarQube

    Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.

  • hissp

    It's Python with a Lissp.

    Hissp is an option. It's a Lisp that compiles to Python expressions. One of the data science guys here said he liked it better than Hy.

  • dtype-next

    A Clojure library designed to aid in the implementation of high performance algorithms and systems.

    There are some interesting efforts concurrent with scicloj work by Chris Nuernberger specifically dtype-next, and the earlier tech-jna stuff. It's the same stuff underlying libpython-clj and libjulia-clj. recent talk.

  • neanderthal

    Fast Clojure Matrix Library

    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.

  • clusters

    Variety of clustering tools for the Common Lisp

    Yeah, I use CL for data science, despite lack of suitable tools. I even ended up writing my own: https://github.com/sirherrbatka/clusters https://github.com/sirherrbatka/vellum https://github.com/sirherrbatka/vellum-plot https://github.com/sirherrbatka/statistical-learning

  • vellum

    Data Frames for Common Lisp

    Yeah, I use CL for data science, despite lack of suitable tools. I even ended up writing my own: https://github.com/sirherrbatka/clusters https://github.com/sirherrbatka/vellum https://github.com/sirherrbatka/vellum-plot https://github.com/sirherrbatka/statistical-learning

  • vellum-plot

    Yeah, I use CL for data science, despite lack of suitable tools. I even ended up writing my own: https://github.com/sirherrbatka/clusters https://github.com/sirherrbatka/vellum https://github.com/sirherrbatka/vellum-plot https://github.com/sirherrbatka/statistical-learning

  • statistical-learning

    Statistical learning models for the Common Lisp

    Yeah, I use CL for data science, despite lack of suitable tools. I even ended up writing my own: https://github.com/sirherrbatka/clusters https://github.com/sirherrbatka/vellum https://github.com/sirherrbatka/vellum-plot https://github.com/sirherrbatka/statistical-learning

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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