logica
dex-lang
logica | dex-lang | |
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19 | 25 | |
1,683 | 1,538 | |
- | 0.5% | |
9.1 | 8.8 | |
22 days ago | 7 days ago | |
Jupyter Notebook | Haskell | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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logica
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Prolog language for PostgreSQL proof of concept
If you're interested in this I would also recommend you check out Logica[0], which is a datalog-like language that is explicitly made to compile to SQL queries.
0: https://logica.dev/
- Logica
- New welcome page for Logica language
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Introduction to Datalog
> I guess the intention is to be better than SQL but then I was left with "under which circumstances?"
Excellent question.
Two of the most common use cases for databases are "transactional processing" (manipulating small numbers of rows in real time) and "analytical processing" (querying enormous numbers of rows, typically in a read-only fashion).
SQL is generally fine for transactional workloads.
But analytical queries sometimes involve multi-page queries, with lots of JOINs and CTEs. And these queries are often automatically generated.
And once you start writing actual multi-page "programs" in SQL, you may decide that it's a fairly clunky and miserable programming language. What Datalog typically buys you is a way to cleanly decompose large queries into "subroutines." And it offers a simpler syntax for many kinds of complex JOINs.
Unfortunately, there isn't really a standard dialect of Datalog, or even a particular dialect with mainstream traction. So choosing Datalog is a bit of a tradeoff: does it buy you enough, for your use case, that it's worth being a bit outside the mainstream? Maybe! But I'd love to see something like Logica gain more traction: https://logica.dev/
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Mangle, a programming language for deductive database programming
Interesting; a Google engineer previously published a Datalog variant for BigQuery: https://logica.dev/
This new language seems similar to differential-Datalog (which is sadly in maintenance mode): https://news.ycombinator.com/item?id=33521561
- Show HN: PRQL 0.2 – Releasing a better SQL
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Show HN: PRQL – A Proposal for a Better SQL
Looks pretty cool. I'd be interested if the README had a comparison with Google's Logica (https://github.com/EvgSkv/logica)
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PathQuery, Google's Graph Query Language
Oh wow that is neat!
And yes, this kind of thing is why datalog is a lot more amenable to fast query plans & runtimes than prolog. This part is especially cool: https://github.com/EvgSkv/logica/blob/main/compiler/dialects...
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Thought about Logica: Google new programming language that compiles to SQL ?
Google new programming Language that compiles to SQL (Support BigQuery and Postgres) feels very exciting. Blog: https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html Github: https://github.com/EvgSkv/logica
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Google Logica Aims To Make SQL Queries More Reusable and Readable
Going to be? It already is. In fact, one thing the article misses is right there at the bottom of the project page:
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?
scryer-prolog - A modern Prolog implementation written mostly in Rust.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
ungoogled-chromium-archlinux - Arch Linux packaging for ungoogled-chromium
futhark - :boom::computer::boom: A data-parallel functional programming language
malloy - Malloy is an experimental language for describing data relationships and transformations.
julia - The Julia Programming Language
prql - PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
hasktorch - Tensors and neural networks in Haskell
differential-datalog - DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. A DDlog programmer does not write incremental algorithms; instead they specify the desired input-output mapping in a declarative manner.
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