mangle
dex-lang
mangle | dex-lang | |
---|---|---|
9 | 25 | |
1,038 | 1,539 | |
0.9% | 0.5% | |
6.7 | 8.5 | |
22 days ago | 2 days ago | |
Go | Haskell | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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mangle
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Learn Datalog Today
Mangle https://github.com/google/mangle is an open-source implementation in golang, it was an explicit goal to make it easy to learn. Meaning: it is easy to recognize the pure datalog part, the syntax is following the good old course material.
It was discussed here: https://news.ycombinator.com/item?id=33756800
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Prolog for Data Science
Logic programming offers a good foundation for anything that people call "rule engines." Within logic programming, there is some variation on the degree of declarativeness.
Datalog is arguably the minimal core logic programming, similar to what the lambda calculus achieves for functional programming. Unfortunately, it has been forgotten outside of database and query processing realm. A resurgence has happened in recent years, as PL researchers and also industry have discovered the virtues of datalog (e.g. Flix, DataFun). My own attempt at making this more widely known is here https://github.com/google/mangle, a language from the datalog family and its implementation as a go library.
As the example shows: plain "rules" (or: plain datalog) is rarely enough to capture everything that one wants to express: the question then is, how to combine a pure declarative "kernel" with more general purpose programming (e.g. mapping a list).
PROLOG offered one answer, already in the 1980s, but I fully reject it: the fact that the writing a program in the wrong order with negation and recursion makes it non-terminating is not something we'd want everyone to deal with. Datalog with stratified recursion is somewhat better, as "layers of rules" is a concept that is easy to understand.
In mainstream programming languages, the possibility of writing non-terminating programs also exists, but is rarely an issue. That is why I believe a good combination of declarative and general-purpose has to make it really easy to recognize which parts of a program are in the declarative, terminating, safe kernel and which parts require more attention from the programmer.
- Maps and structs in Mangle datalog
- Mangle, a programming language for deductive database programming
- Mangle: Programming language for deductive database programming
dex-lang
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Thinking in an Array Language
A really nice approach to this I've seen recently is Google's research on [Dex](https://github.com/google-research/dex-lang).
- Function Composition in Programming Languages – Conor Hoekstra – CppNorth 2023 [video]
- Dex Lang: Research language for array processing in the Haskell/ML family
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[D] Have their been any attempts to create a programming language specifically for machine learning?
Dex
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[D] PyTorch 2.0 Announcement
Have you tried Dex? https://github.com/google-research/dex-lang It is in a relatively early stage, but it is exploring some interesting parts of the design space.
- Mangle, a programming language for deductive database programming
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Looking for languages that combine algebraic effects with parallel execution
I think [Dex](https://github.com/google-research/dex-lang) might be along the lines of what you're looking for, although its focus is on SIMD GPU-style parallelism rather than thread-level parallelism.
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“Why I still recommend Julia”
Dex proves indexing correctness without a full dependent type system, including loops.
See: https://github.com/google-research/dex-lang/pull/969
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Haskell for Artificial Intelligence?
In case you want to see one research direction that's combining practical machine learning and functional programming, one of the authors of JAX (and the main author of its predecessor, Autograd) is writing Dex (https://github.com/google-research/dex-lang), a functional language for array processing. The compiler itself is written in Haskell. JAX is one of the most popular libraries for doing a lot of machine learning these days, along with Tensorflow and PyTorch. You might also want to see the bug in the JAX repo about adding Haskell support, for some context: https://github.com/google/jax/issues/185
What are some alternatives?
biscuit-go
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
pengine - pengines (SWI Prolog) client for Go
futhark - :boom::computer::boom: A data-parallel functional programming language
go - Trealla Prolog embedded in Go using WASM
julia - The Julia Programming Language
OPA (Open Policy Agent) - Open Policy Agent (OPA) is an open source, general-purpose policy engine.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
logica - Logica is a logic programming language that compiles to SQL. It runs on Google BigQuery, PostgreSQL and SQLite.
hasktorch - Tensors and neural networks in Haskell
wuffs - Wrangling Untrusted File Formats Safely
CIPs