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Co-dfns Alternatives
Similar projects and alternatives to Co-dfns
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zig
General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Nim
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
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InfluxDB
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tigerbeetle
Discontinued A distributed financial accounting database designed for mission critical safety and performance. [Moved to: https://github.com/tigerbeetledb/tigerbeetle] (by coilhq)
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cloc
cloc counts blank lines, comment lines, and physical lines of source code in many programming languages.
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medley
The main repo for the Medley Interlisp project. Wiki, Issues are here. Other repositories include maiko (the VM implementation) and Interlisp.github.io (web site sources) (by Interlisp)
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The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Co-dfns alternative or higher similarity.
Co-dfns reviews and mentions
Posts with mentions or reviews of Co-dfns.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-02-24.
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Tacit Programming
And if anyone wants an absolute masterclass in tacit programming, have a look at Aaron's Co-dfns compiler. The README has extensive reference material. https://github.com/Co-dfns/Co-dfns/
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YAML Parser for Dyalog APL
I don't put a lot of stock in the "write-only" accusation. I think it's mostly used by those who don't know APL because, first, it's clever, and second, they can't read the code. However, if I remember I implemented something in J 10 years ago, I will definitely dig out the code because that's the fastest way by far for me to remember how it works.
This project specifically looks to be done in a flat array style similar to Co-dfns[0]. It's not a very common way to use APL. However, I've maintained an array-based compiler [1] for several years, and don't find that reading is a particular difficulty. Debugging is significantly easier than a scalar compiler, because the computation works on arrays drawn from the entire source code, and it's easy to inspect these and figure out what doesn't match expectations. I wrote most of [2] using a more traditional compiler architecture and it's easier to write and extend but feels about the same for reading and small tweaks. See also my review [3] of the denser compiler and precursor Co-dfns.
As for being read by others, short snippets are definitely fine. Taking some from the last week or so in the APL Farm, {⍵÷⍨+/|-/¯9 ¯11+.○?2⍵2⍴0} and {(⍸⍣¯1+\⎕IO,⍺)⊂[⎕IO]⍵} seemed to be easily understood. Forum links at [4]; the APL Orchard is viewable without signup and tends to have a lot of code discussion. There are APL codebases with many programmers, but they tend to be very verbose with long names. Something like the YAML parser here with no comments and single-letter names would be hard to get into. I can recognize, say, that c⌿¨⍨←(∨⍀∧∨⍀U⊖)∘(~⊢∊LF⍪WS⍨)¨c trims leading and trailing whitespace from each string in a few seconds, but in other places there are a lot of magic numbers so I get the "what" but not the "why". Eh, as I look over it things are starting to make sense, could probably get through this in an hour or so. But a lot of APLers don't have experience with the patterns used here.
[0] https://github.com/Co-dfns/Co-dfns
[1] https://github.com/mlochbaum/BQN/blob/master/src/c.bqn
[2] https://github.com/mlochbaum/Singeli/blob/master/singeli.bqn
[3] https://mlochbaum.github.io/BQN/implementation/codfns.html
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HVM updates: simplifications, finally runs on GPUs, 80x speedup on RTX 4090
This always seemed like a very interesting project; we need to get to the point where, if things can run in parallel, they must run in parallel to make software more efficient on modern cpu/gpu.
It won't attract funds, I guess, but it would be far more trivial to make this work with an APL or a Lisp/Scheme. There already is great research for APL[0] and looking at the syntax of HVM-core it seems it is rather easy to knock up a CL DSL. If only there were more hours in a day.
- Co-Dfns
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APL: An Array Oriented Programming Language (2018)
There are many styles of APL, not just due to its long history, but also because APL is somewhat agnostic to architecture paradigms. You can see heavily imperative code with explicit branching all over the place, strongly functional-style with lots of small functions, even object-oriented style.
However, given the aesthetic that you express, I think you might like https://github.com/Co-dfns/Co-dfns/. This is hands-down my favorite kind of APL, in which the data flow literally follows the linear code flow.
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Franz Inc. has moved the whole Allegro CL IDE to a browser-based user interface. Incl. all their Lisp development tools. One can check that out with their Allegro CL Express Edition.
Which is, as far as I know, unused. (Similarly the gpu compiler.)
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What would make you try a new language?
You might be familiar with iKe (grahics), SpecialK (GLSL) and Co-dfns. Also, I am working on bastardized APL for GPU – Fluent. Fluent 1 had backend implemented through Apple Metal Performance Shaders Graph and Fluent 2 has TensorFlowJS backend for now. I care more about having auto differentiation in the lang than running on GPU and do graphics, to be honest.
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APL9 from Outer Space
Not that I am aware of. I think the closest project is co-dfns[1] which is being developed by Aaron Hsu (he did a presentation as well). It aims to compile a subset of APL so that it can be executed on GPUs for instance, possibly with other backends. I imagine an XLA backend could be possible there.
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Who is researching array languages these days?
Aaron hsu did his dissertation on this topic (compiler, thesis), at indiana university in the us.
- Researchers Develop Transistor-Free Compute-in-Memory Architecture
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A note from our sponsor - SaaSHub
www.saashub.com | 19 Apr 2024
Stats
Basic Co-dfns repo stats
19
642
9.6
1 day ago
Co-dfns/Co-dfns is an open source project licensed under GNU Affero General Public License v3.0 which is an OSI approved license.
The primary programming language of Co-dfns is APL.
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