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#reproducible

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We just added a #reproducible example for large-scale #metabolomics data preprocessing using the @bioconductor #xcms package to @phili 's #Metabonaut tutorials resource! 💪

rformassspectrometry.github.io

runs also on a standard 💻 - thanks to the new memory-saving processing in #xcms

using the largest (n=4000) data set from MetaboLights

rformassspectrometry.github.ioLarge Scale Data Preprocessing with xcms

We are celebrating 10 years of #reproducible builds in #FDroid this year, and we are overhauling the way the build server works.

Thanks to the funding from #NLnet, #NGI #NGI0 part of #HorizonEurope, and your donations, our work is intended to power the future of #FDroid for the next ten and more.

Dig deeper for the why and the how in this 15 mins post: f-droid.org/2025/05/21/making-

f-droid.orgMaking reproducible builds visible | F-Droid - Free and Open Source Android App RepositoryOur lives are moving into the digital realm, our private data flows throughall sorts of software. As software controls more and more of our lives, itis becom...

Reproducible Research: Make your work stand the test of time

If you ran your code in a year, would it still work? 🤔

In this session, we teach you how to make your research #reproducible — so your results can be trusted and built upon.

📅 Join our workshop: coderefinery.github.io/2025-03

coderefinery.github.ioCodeRefinery workshop March 25-27 and April 1-3, 2025Free workshop on git, testing, documentation, and more in a workshop - for researchers and scientists.

The #guix survey also showed that our users are knowledgeable #Linux people. Almost 50% are experts/advanced and 47% are intermediate!

A lot of the attraction is the #nix value of declarative configuration and reproducibility. Users also identified that Scheme, Guile and Lisp are cool! Perhaps the overlap of two different communities! That was my path from #clojure and #ubuntu /#debian

See Q1 in the post:

guix.gnu.org/en/blog/2025/guix

#scheme#emacs#guile

Things you should describe in your study if you need to process data with an #AI tool in order to make it #reproducible as much as possible according to @bortzmeyer :
- software used (easiest part)
- training set (hard to find, even for so-called "open source" LLM
- training parameters (weight...)
- hardware (GPU type and core number)
- durability (this LLM won't be available on huggingface forever, is there an alternative and more durable deposit somewhere?

Wanted to share that [Stageˣ] is now full source bootstrapped, 100% reproducible, signed by 2-3 independent reviewers/reproducers on every release, and can build itself.

It can be the base of reproducible build containers for most projects written in c, c++, nodejs, go, php, ocaml, rust, or zig.

I am thankful for the efforts of our team, and the patient advice and tireless debugging of people in the #reproducible-builds and #bootstrappable projects <3

codeberg.org/stagex/stagex

Codeberg.orgstagexA container-native, full-source bootstrapped, and reproducible toolchain to build all of the things

Very happy with this visualisation, not just because it's neatly presents results of our network simplification methods (which it does), but also because it was produced automatically in our workflow, which re-generates the results of our paper with every 'commit' to GitHub 🎉 Watch this space for associated #reproducible paper with #RStats and #Python code 🚀

I'm currently working on a new npm package that will replace deltachat-node (which is still based on the cffi and NAPI).
The new npm package will make use of the #reproducible buildable deltachat-rpc-server binaries, which will make cross compiling much easier.

A nice side-effect to this is that the new npm packet is even somewhat compatible with #deno
Nice work on the part of Deno for their node compatibility!

Let me know If you would be interested in writing #deltachat #bots with #deno