cat in your python packages • he/him
Joined July 2013
- Tweets417
- Following100
- Followers237
- Likes1.5K
you can solve sudokus in python packaging
not python code, python packaging
[project]
name = "sudoku"
version = "1.0.0"
dependencies = [
"sudoku_3_1 == 2",
"sudoku_5_7 == 6",
"sudoku_0_7 == 5"
...
]
github.com/konstin/sudoku-in…
konsti retweeted
Announcing the Astral OSS Fund.
We're giving > $3,000 per Astral team member per year to open source projects, maintainers, and foundations, inspired by @getsentry's OSS Pledge.
astral.sh/blog/astral-oss-fu…
konsti retweeted
But our goal is to evolve uv into a "Cargo for Python": a comprehensive project and package manager that's fast, reliable, and easy to use, wrapped in an opinionated workflow.
Think: a single static binary that bootstraps everything you need to be productive with Python.
konsti retweeted
Announcing uv: an extremely fast Python package installer and resolver, written in Rust.
uv is designed as a drop-in replacement for pip, pip-tools, and virtualenv.
astral.sh/blog/uv
I've started a company, Astral, to continue building high-performance developer tools for the Python ecosystem.
We're going to keep building Ruff, and build more Ruff-like things.
We've raised a seed round led by @Accel.
I'm extremely excited :)
astral.sh/blog/announcing-as…
1
1
437
i've reimplemented PEP 440 (the python version standard) and wrote about the depths of PEP 440 and how to evolve it for the future cohost.org/konstin/post/5148…
konsti retweeted
Hi #bioinformatics! With the developers at #PyO3 (#Python to #Rust bindings), we are working on a paper manuscript to make it easier to cite the library when it's used to do #science. Do you know published projects using #PyO3 to support our statement of need?
It's a bit shame to tweet this because I've been away from OSS recently... but we are preparing to submit #PyO3 paper to JOSS (joss.theoj.org/)! If you work on or know a cool scientific project that uses PyO3, please let us know at github.com/PyO3/pyo3/pull/26… or reply😉
i've made a proof of concept for using python packages without virtualenv, or really any explicit installing at all: github.com/konstin/poc-monot…
no virtualenv/pip/pyenv/conda, just ´monotrail run python` and it will set everything up
there's still a lot missing and many things are broken, e.g. non-linux is badly tested, only pypi is supported, startup is slow, only some requirements.txt syntax is supported, some mysterious failures in jupyter/colab, windows scripts are wonky, etc.
1
incidentally, i've also written a wheel installer that's faster than pip's singlethreaded (e.g. 5.8s vs. 7.6s for plotly on my laptop) and can additionally be multithreaded, if somebody is interested in reusing that github.com/konstin/poc-monot…
1
So what happens when you replace BLAST/MMseqs2 with embedding/language model based search?
The latest generation of protein language models (ProtT5/ESM) is really good at remote homology, but there are also a bunch of catches
Nearest neighbor search on embeddings rapidly identifies distant protein relations biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
While those two are big caveats for general purpose knn homology search, this may not apply to your specific problem, e.g. knn beast BLAST for GO term prediction (nature.com/articles/s41598-0…) and supervised finetuning can help (doi.org/10.1093/nargab/lqac0…)