kotlingrad
uiua
| kotlingrad | uiua | |
|---|---|---|
| 3 | 22 | |
| 546 | 2,128 | |
| 0.0% | 1.2% | |
| 3.7 | 9.9 | |
| over 1 year ago | 8 days ago | |
| Kotlin | Rust | |
| Apache License 2.0 | MIT License |
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kotlingrad
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Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
and that there is a mature library for autodiff https://github.com/breandan/kotlingrad
- Show HN: Shape-Safe Symbolic Differentiation with Algebraic Data Types
- Kotlinā: Type-safe Symbolic Differentiation for the JVM
uiua
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Mastering Dyalog APL
I am really surprised that no-one mentioned https://www.uiua.org/ yet. If you like APL/BQN/K/L, look at Uiua! You're going to love it! It's very ergonomic, and has awesome and fun facilities for audio and video rendering!
- A Letter from Dijkstra on APL
- GPT-5.3-Codex
- In Praise of APL (1977)
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Advent of Code 2025
For those who think this is a typo, uiua [1] (pronounced "wee-wuh") is a stack-based array programming language.
I solved a few problems last year, and it is amazing how compact the solutions are. It also messes with your head, and the community surrounding it is interesting. Highly recommended.
[1] https://www.uiua.org/
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Array Programming the Mandelbrot Set
You should definitely check out uiua (https://www.uiua.org/)! Array programming can certainly be intimidating, but I think it's worth doing for a few reasons:
- The "array"-ish solution to a problem is usually a very data-oriented solution. Even if you aren't working in an array-oriented language (and just to be clear, I'm not advocating that people write production code in array languages), "thinking in arrays" helps me come up with more elegant solutions.
- Learning array programming is a little like learning to program all over again. If you really enjoyed the process of learning to program, it lights up those same brain circuits, which I found really enjoyable.
- If you ever want to do any graphics programming the mental model can be very helpful. Array programming really helped me wrap my mind around how shader programs are executed.
Uiua is little unique in that it is also a stack-based language, so learning both paradigms at the same time can definitely be a little challenging, but I think it's well worth it.
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Dijkstra On the foolishness of "natural language programming"
> APL is another example of dense languages that (some) people like to work in.
I recently learn an array programming language called Uiua[0] and it was fun to solve problems in it (I used the advent of code's ones). Some tree operation was a bit of a pain, but you can get very concise code. And after a bit, you can recognize the symbols very easily (and the editor support was good in Emacs).
[0]: https://www.uiua.org/
- Uiua ā A stack-based array programming language
- Uiua: A stack-based array programming language
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Advent of Code on the Nintendo DS
I struggled with APL last year. This year Iāve been enjoying trying to solve the problems in uiua (āwee-whaā). Itās a symbol-based array language like APL, with a wonderful online editor and code formatter (also command line), that formats on each run, and lets you type in English keywords that it converts into symbols, so you donāt have to hunt and peck through the virtual keyboard or remember a bunch of arbitrary chords.
Thereās a decent VSCode plugin but I mostly use the online pad because itās such a rich environment. Very active Discord, with an AoC channel for help and sharing solutions - the maintainer actively iterates on the language to help them solve AoC problems.
https://www.uiua.org/
(I also fall back to Clojure when Iām struggling to come up with a uiua solution or banging my head against the stack, I kinda wish I had uiua-in-Clojure like how April is APL-in-CL)
What are some alternatives?
lets-plot-kotlin - Grammar of Graphics for Kotlin
BQN - An APL-like programming language
kmath - Kotlin mathematics extensions library
cognate - A human readable quasi-concatenative programming language
kotlindl - High-level Deep Learning Framework written in Kotlin and inspired by Keras
sqlite-vss - A SQLite extension for efficient vector search, based on Faiss!