SMT
pp0196.bsky.social
SMT
@pp0196.bsky.social
420 followers 670 following 360 posts
Sequences and consequences. Credit Pic : Cellular landscape cross-section through a eukaryotic cell, by Evan Ingersoll
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I put out a patch release of mirai today. Version 2.5.2 really improves the OpenTelemetry integration so you can more easily see into your async workflows. Other key ecosystem packages will roll out with this enabled - next up: Shiny!

mirai.r-lib.org

#Rstats
Minimalist Async Evaluation Framework for R
Designed for simplicity, a mirai evaluates an R expression asynchronously, locally or distributed over the network. Built on nanonext and NNG for modern networking and concurrency, scales efficiently ...
mirai.r-lib.org
rixpress is a R based proposition for so called multilingual pipelines (in reality most of the time why not just wrap what is needed via reticulate or similar for other languages) brodrigues.co/posts/2025-1...
Orchestrating Polyglot, Reproducible Data Science with Nix and {rixpress} – Econometrics and Free Software
brodrigues.co
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Any examples of fitting a graph convolution network in {torch} or {luz} folks are aware of? #rstats
Sometimes one need more control than just letting lexical scoping rule, one reason would be to avoid size effects in caller environment (using `source` with an environment parameter). Other than the more general questions around environment and Namespaces henrikbengtsson.github.io/environments...
How objects are found by package functions
henrikbengtsson.github.io
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We recently checked out tidySingleCellExperiment at the R Stats Club @libdrstats.bsky.social, an R package part of a broader effort to bring tidy coding to genomics. Pretty useful!

youtu.be/ob_SQY4-YjQ?...

#RStats
[2025-07-11] Tidy manipulation of SingleCellExperiment objects
YouTube video by Leonardo Collado Torres
youtu.be
As it happens, there is a R level equivalent of the C API finalization registration mechanism stat.ethz.ch/R-manual/R-d...
Never saw it in the wild, but it looks like some CRAN packages use it (expectedly lot of these packages manage external processes)
github.com/search?q=org...
#Rstats
R: Finalization of Objects
stat.ethz.ch
If you add to this the terrible docs you can understand the nihilist and p(y)edantic (pun intended) type annotations drive
Use any python library and you quickly find yourself buried under layers upon layers of encapsulated OOP inheritance crap, the tracebacks are order of magnitude worse than tidyverse NSE tracebacks before the rlang package (this is when the module author allows you to see traces)
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R version 4.5.2 "[Not] Part in a Rumble" (source version) has been released. (You can find it in cran.r-project.org/src/base/R-4/, or wait for CRAN to be updated.)
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luz v0.5.1 is now on #rstats CRAN. Just a small bug fix related to forwarding `predict` parameters to the model. I also added a new Variational Autoencoder example to our examples gallery: mlverse.github.io/luz/articles...
Examples
mlverse.github.io
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A significant OpenZL theme is genomic data compression. Users are eager for benchmarks against CRAM, FASTA, FASTQ, SAM, and VCF. It shows promise for tackling large datasets, especially challenging nanopore data. #Genomics 2/5
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R^4 post #054: Faster r-ci Contimuous Integration via r2u Container
Accelerating Continous Integration at GitHub Actions
dirk.eddelbuettel.com/blog/2025/10...
#rstats
#mojo vs #C in the #RStats convolve classic benchamrk. Looks like mojo goes brrr
github.com/sounkou-bioi...
is there some container setup to test reticulate against specific CPython builds (i can see that the libpython is linked against in src) ? Disclosure i am not a (direct) reticulate even though i should become one pretty soon :D
My template for any #RStats package that used LLM tools and hopefully somebody should trigger some lawsuit to enforce this interpretation in any project out there that uses LLM tools
how does the python so called free threading interact with R ?
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BioProBench: Comprehensive Dataset and Benchmark in Biological Protocol Understanding and Reasoning arxiv.org/abs/2505.07889 🧬🖥️🧪
Code: github.com/YuyangSunshi...
Data: huggingface.co/datasets/Bio...
je ne sais pas pourquoi, mais j ai l impression que c'est fait avec litedown
Il manque plus que des diagrammes pour les personnes qui sont plus dans le visuel (comme moi)
Where are the (vendor agnostic) #Rstats case studies, packages, books, CRAN task views on Data engineering and ETL ? Maybe I am uninformed, but if I am not this gap is not sustainable : cannot expect people to go along with the instable equilibrium that is programming Diglossia (a.k.a "polyglot")
We should really not leave data engineering to the snake side. The snake creep is both from the ETL and Data warehouse side, sandwiching the poor Rstat data analyst, not sustainable long term. We have similar issue in my field (Bioinformatics) where R is getting reduced to plotting for papers lol