Coconut
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Coconut | jax | |
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27 | 82 | |
3,926 | 27,509 | |
- | 3.8% | |
9.4 | 10.0 | |
5 days ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Coconut
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Mojo is now available on Mac
> to be part of the Python ecosystem
I'd rather use Python if I'm in the Python ecosystem. So many attempts were made in the past to make a new language compatible with the Python ecosystem (look up hylang and coconu -- https://github.com/evhub/coconut). But at the end of the day, I'd come back to Python because if there's one thing I've learnt in recent years it's this:
minimize dependencies at all costs.
- I modified and hacked away xonsh source code
- Show HN: I mirrored all the code from PyPI to GitHub
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Leaving Haskell Behind
Have you had a look at Coconut? I don't know if it'll push all your buttons but whenever I hear someone who's reasonably content with Python but wants more FP goodies I always think of it. https://github.com/evhub/coconut . It's basically a superset of Python3 that transpiles into Python3 and is compatible with MyPy. I don't think I'd code Python w/o it ever again assuming I had the choice. The biggest negative for me is that there's no IDE support for the language last I looked, though of course you can work with the transpiler output (plain Python) in your favorite Python IDE. It might be fun to play around with, I know that I really enjoyed it but then I got spoiled by the language+tooling of Scala3, but if you don't have that option ...
- Codon: A high-performance Python compiler
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[2022 Day 1-7] Going for 1 language per day, looking good so far
If you're looking for suggestions I want to put forward zig lang if you like C/C++ and Coconut Lang if you like Python!
- Show HN: Programming Google Flutter with Clojure
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What is your favourite programming language? (other than Scala)
F# and also the fun, compile-to-Python, functional language called Coconut.
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Top Python Coding Repos
requests - A simple, yet elegant, HTTP library. sanic - Next generation Python web server/framework | Build fast. Run fast. click - Python composable command line interface toolkit elasticsearch-dsl-py - High level Python client for Elasticsearch panel - A high-level app and dashboarding solution for Python internetarchive - A Python and Command-Line Interface to Archive.org coconut - Simple, elegant, Pythonic functional programming
- Dogelang – it's a Python No, it's a Haskell
jax
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The Elements of Differentiable Programming
The dual numbers exist just as surely as the real numbers and have been used well over 100 years
https://en.m.wikipedia.org/wiki/Dual_number
Pytorch has had them for many years.
https://pytorch.org/docs/stable/generated/torch.autograd.for...
JAX implements them and uses them exactly as stated in this thread.
https://github.com/google/jax/discussions/10157#discussionco...
As you so eloquently stated, "you shouldn't be proclaiming things you don't actually know on a public forum," and doubly so when your claimed "corrections" are so demonstrably and totally incorrect.
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Julia GPU-based ODE solver 20x-100x faster than those in Jax and PyTorch
On your last point, as long as you jit the topmost level, it doesn't matter whether or not you have inner jitted functions. The end result should be the same.
Source: https://github.com/google/jax/discussions/5199#discussioncom...
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Apple releases MLX for Apple Silicon
The design of MLX is inspired by frameworks like NumPy, PyTorch, Jax, and ArrayFire.
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MatX: Efficient C++17 GPU numerical computing library with Python-like syntax
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Are they even comparing apples to apples to claim that they see these improvements over NumPy?
> While the code complexity and length are roughly the same, the MatX version shows a 2100x over the Numpy version, and over 4x faster than the CuPy version on the same GPU.
NumPy doesn't use GPU by default unless you use something like Jax [1] to compile NumPy code to run on GPUs. I think more honest comparison will mainly compare MatX running on same CPU like NumPy as focus the GPU comparison against CuPy.
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JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation
Actually that never changed. The README has always had an example of differentiating through native Python control flow:
https://github.com/google/jax/commit/948a8db0adf233f333f3e5f...
The constraints on control flow expressions come from jax.jit (because Python control flow can't be staged out) and jax.vmap (because we can't take multiple branches of Python control flow, which we might need to do for different batch elements). But autodiff of Python-native control flow works fine!
Development seems not to have dropped at all from the contributions page: https://github.com/google/jax/graphs/contributors
Don’t know about usage and uptake though.
You're right! Maybe we should revise that... I made https://github.com/google/jax/pull/17851, comments welcome!
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Julia and Mojo (Modular) Mandelbrot Benchmark
For a similar "benchmark" (also Mandelbrot) but took place in Jax repo discussion: https://github.com/google/jax/discussions/11078#discussionco...
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Functional Programming 1
2. https://github.com/fantasyland/fantasy-land (A bit heavy on jargon)
Note there is a python version of Ramda available on pypi and there’s a lot of FP tidbits inside JAX:
3. https://pypi.org/project/ramda/ (Worth making your own version if you want to learn, though)
4. For nested data, JAX tree_util is epic: https://jax.readthedocs.io/en/latest/jax.tree_util.html and also their curry implementation is funny: https://github.com/google/jax/blob/4ac2bdc2b1d71ec0010412a32...
Anyway don’t put FP on a pedestal, main thing is to focus on the core principles of avoiding external mutation and making helper functions. Doesn’t always work because some languages like Rust don’t have legit support for currying (afaik in 2023 August), but in those cases you can hack it with builder methods to an extent.
Finally, if you want to understand the middle of the midwit meme, check out this wiki article and connect the free monoid to the Kleene star (0 or more copies of your pattern) and Kleene plus (1 or more copies of your pattern). Those are also in regex so it can help you remember the regex symbols. https://en.wikipedia.org/wiki/Free_monoid?wprov=sfti1
The simplest example might be {0}^* in which case
0: “” // because we use *
- Codon: Python Compiler
What are some alternatives?
Numba - NumPy aware dynamic Python compiler using LLVM
functorch - functorch is JAX-like composable function transforms for PyTorch.
julia - The Julia Programming Language
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Cython - The most widely used Python to C compiler
jax-windows-builder - A community supported Windows build for jax.
Toolz - A functional standard library for Python.
mesh-transformer-jax - Model parallel transformers in JAX and Haiku
dex-lang - Research language for array processing in the Haskell/ML family
tensorflow - An Open Source Machine Learning Framework for Everyone
Pyrsistent - Persistent/Immutable/Functional data structures for Python
fn.py - Functional programming in Python: implementation of missing features to enjoy FP