I ofc have to finish this in 30 days while I also have two class projects due in 20 days plus studying for my finals. I love having to do the same work as PHD and post grad students for less pay
TLDR; !linuxchads !fosstards !biology Despite having cowtools to create instantly deployable exact decency loaders via docker or GUIX scientists can apparently pass unreplicatable and hardcoded code past reviewers.
Pip3 download speeds are prob butt (like 600 kb/s) because there is one gorillion AWS and Azure vms for ML trying to set up at the same time and amazon and Microsoft cant arsed to use their billions of dollars to make their own mirrors so they just leach off FOSS projects
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As much as I like to shit on sexy Indian dudes and webshit devs, reading code from researchers is next level heck. Kinda messed up that he's asking you to pad his own work, I don't know much about submitting research papers, is that common?
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This is a chink researcher ofc. And yeah this is pretty common in the tech side of biology. Since its "easy" reviewers will demand you benchmark every tool against every other tool in existence ignoring how temperamental and poorly documented all these POS are.
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They didn't know a lot about what you were talking about and this was a way to make them seem smart.
It's the nerd version of hazing.
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the fricking absolute state of academia
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This guy is holding my paper hostage presumably so he can eek one more citation from this POS.
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You should try (and fail) to replicate his work and publish that, spite is good
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What do you mean? It's all right there... In the excel workbook
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I know a couple CS professors, at their school every single person involved went straight into academia when they finished their own education. One of them didn't finish his PhD untill he was already teaching. None of them have a single lick of real world experience, they don't know what's actually useful or being used these days. Anything slightly newish like Docker is not only foreign and unknown to them but totally uninterests them. Lack of curiosity defines their computer use. They don't really seem to know jack shit about linux and 90% of their work appears to be done in Visual Basic via a VM from a MacBook. I can't imagine the situation where computers meet applied sciences can be good.
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I do all my work on a macbook ssh'd into a linux enterprise machine and code everything in nano (no syntax highlighting) . Comp sci cels cant even provide the version of python they used at minimum so I have to guess what exact version works with the unearthly dependency chain.
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Please use vscode remote instead
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That's the fricking problem I always had with LISP-y languages. They always came from the fricking ivory towers of academia and lacked so many real world utilities.
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This is why I love stata. All of its models and commands are designed by professors (economists) who painstakingly write out the documentation. The problem with python cowtools is that you don't know which method and which underlying assumptions are at play (because the !fosstards who wrote it have no idea either). Must be heck using it for anything involving serious statistics.
!codecels, bring out the pythonistas. I want to wring your necks!
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I unironically love Python
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The sooner D replaces python the better
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frick you
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I love Haskell, I think it hits an amazing mix of functional purity and a deeply expressive type system.
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assert.isTrue(true)
100% coverage achieved.
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Another place had freak out over a possible disappearing crystal contamination. HUGE drive to triple check everything over the next few days make sure nothing is fricked.
https://www.chemistryworld.com/news/the-mystery-of-the-disappearing-crystals/3003967.article
!chuds required reading
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Science is epic
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Dogshit code is a part of the field. I do enjoy the silly design decisions you encounter when dealing with it.
Pip speeds are crappy because pypi was never intended for large wheels. Unfortunately the big ml packages shit all over the normal rules and have everyone downloading gigabyte Nvidia silo binaries for no good reason.
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I have just never seen anything this hard coded . Like as a reviewer you think question 1 would be "can this code be tested on other data". Like what is the point of publishing an ML model which works on only two datasets
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It's pretty common. I often see models so overfitted that it's basically a top hat filter. "It works well on my data" is all these researchers understand
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I have to download this 4gb file to show a 15 second video of a black guy making a joke but it's somehow for "research".
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Just dont lmao. The editor will understand if you explain it to them. Which to be fair is only true if the editor is not r-slurred.
And unless you are going for a top tier journal (which you shouldnt because effort risk funding connections etc) submit it to multiple journals at the same time. If an editor finds out and calls you out on it just say it was an accident and apologize.
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Sorry, ML "algorithm" for spatial transcriptomics? What is it really?
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No idea its what the phd students are doing. I just touch the benchmarking of other algorithms for the paper . From what I understand it's an ML algorithm to find the boundaries of cell types in spatial transcription data in cancer patients. As rn cancer research is on fire with cell-to-cell communications research of reach spatial analysis is a large part.
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It'd be absolutely wild if you knew this guy I used to know.
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You seem to be quite the GUIX fanboy as of late. Why should I use it over Nix?
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No particular reason other than it has a bunch of biology based packages and I personally don't like NIX's custom scripting language.
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I mean truth be told it kind of does make more sense to use a lisp dialect for scripting in general since it's the only lang off the top of my head where knowing one means you know them all, etc etc
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i only worked with bioinformatics once and they had done their work in julia. That was ~10 years ago, I hate them so much.
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Juilia was basically killed when python got faster. Only positive of Julia is that it can work with gpus without the mess that is cuda Nvidia slop.
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is..is that....dare i say, S-S-S-SOVL?????????????????
uhhh ughhh UGHHHH SSOUVL!!!!
aaaaaAAAAAaaaAAAAAAAAAAAAaAAAAaaaa SSSSOOOOVLLLLLLLL SOVL SOVL SOVL SOVL!!!!!!!!!!!!!!!
ohh! OHHH OHHH GOD Im SOVVVLLINGGG!!!!!!
SOVL!
OU
L!
SOVL!
OU
L!
SOVL!
OU
L!
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Most research scientists aren't even enlightened enough to do this!
If you can keep your dependencies managed entirely by Pip (and don't have to shoot yourself by touching Conda), definitely use one of the dependency managers with a lockfile like PDM (best) or Poetry. Installs go like 5-10x faster because you're not fighting dependency resolution at every step, and you have a reference of every version of every dependency in the lockfile. Also works really well if you're building a Docker image.
But yeah you can't truly hate Python until you read researcher code. I'm convinced many of them don't even understand data types; total dynamic typing death please.
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If you want a package manager try uv. It came out recently and blows everything else out of the water for performance and ease of use
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Oh nice, will have to look at uv. They made ruff too, which also blows all of the other linters/formatters out of the water in both performance and usability. The Python Packaging Authority should kill themselves for being outdone by another group of randos for the THIRD time.
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AL ML/AI in biology is useless and so is transcriptomics.
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wait i thought ai solved biotech already, why are u still doing "research"
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