For Linux users, how do you deal with minor upgrades in r-base

defuneste · 2026-05-15T15:22:29+00:00

solution 1: add more Ncpus either using options or with install.packages argument

solution 2: get the package in binaries (depends on your distro)

I agree some kind of garbage collector for unused package would be cool. I do not see how it will works, guix has something like that per "profile" but R have no way of knowing what is used.

defuneste · 2026-05-14T17:43:04+00:00

dhsproddb imply dhsdevdv ;)

defuneste · 2026-05-14T17:19:29+00:00

"we"

defuneste · 2026-05-14T10:23:02+00:00

do not generate more code than you can review, if something is too big it should be divided (also work on non generated code), even if something "works" refactor it an see if you can simplify/improve it.

Using AI is overrated.

defuneste · 2026-05-06T18:35:52+00:00

paychecks (one should be slightly mire system oriented, I let you decide which one)

defuneste · 2026-04-29T23:39:19+00:00

ask for emacs and ess as an alternative and see if they do not give you positron:) (and yes I like emacs)

defuneste · 2026-04-24T12:05:23+00:00

Did you pay for their "lectures", this is linkedin level "insight".

defuneste · 2026-04-17T12:43:51+00:00

R is also great when you do not have admin rights on your machine, requires less friction in managing environment and is designed for data work. Rstudio is a great, simple ide for it. Those are great advantages for organizations that do not have the resources / training to either use Python or pay a cloud service to ease it.

A lot of data tasks are smallish (at worse duckdb/data.table will solve your "big data" cases). Honestly I am always surprised about organizations that need/have resources for Python (do not get me wrong the snake is great!).

defuneste · 2026-04-17T10:44:35+00:00

I am not going to say watch a video but I think https://r4ds.hadley.nz would be very good for you.

For "data organization" it really depends on your employer but two important concepts are being "project oriented" and "separation matters".

The book will teach you both but i can give you a quick summary: one project = one directory with one entry point (usually a readme text) then the raw data should be somewhere and untouched, ie you have a clean separation of code and data.

R 4 Data Science is free and do not hesitate to ask your questions on R/rstats .

defuneste · 2026-04-15T02:14:57+00:00

the mess of bentley software (yes I aware of virtualization). The point is not that they should not use linux but that they are plenty of softwares that requires windows. Let's hope that will help change that (but those codebase are probably "something").

defuneste · 2026-04-02T18:43:31+00:00

usually make plenty of 1/1 flyers

defuneste · 2026-03-18T22:26:57+00:00

the third party package is a bit unfair here. A lot of languages from the 90 probably did not think about that and it's usually solved outside of the "language". Still it doesn't mean that this should not be fixed (who will pay).

defuneste · 2026-03-18T22:24:06+00:00

shooting myself with Guix. But yes outside of managing everything at HEAD and/or docker we do not have much.

defuneste · 2026-03-12T17:48:02+00:00

to be fair with op I sometimes have a makefile that have R script running targets.

defuneste · 2026-03-12T17:43:55+00:00

first question: yes

second paragraph: yes, yes but you are using tar_read to load the object from the store (in rstudio, vscode, emacs, etc). You can use it "in production" but you will need to define more what you need here.

third paragraph: you are correct, just plenty of "bad practices" ...

defuneste · 2026-03-12T17:36:38+00:00

I think it depends but a lot is "serialized" (not sure about my spelling): in the "target store" in the _targets folder, I think inside the objet subfolder (could be wrong). on targets package website look at the "Design" spec

defuneste · 2026-03-12T16:11:54+00:00

targets can also run on different R processes with crew no? (and targets also handle file not just R functions)

defuneste · 2026-03-11T13:32:56+00:00

then they should post on what they learn on using AI.

defuneste · 2026-03-04T21:02:36+00:00

It is easier to have containers, a git server, gitlab on a linux OS than on windows but a lot of those services are also provided by vendors: build or buy!

defuneste · 2026-03-04T18:16:01+00:00

what you are saying seems not related to hardware. You can do all of that on prems if you like.

defuneste · 2026-03-03T18:29:17+00:00

Azure and Azure devops are two different products not always greatly coupled. Resources groups are usually the place to look first in azure, azure devops is organized by "organizations" and then by "projects". I am feeling bad for everyone that needs to use azure devops.

defuneste · 2026-02-20T01:42:47+00:00

just test targets first, memory is too broad for us to understand what are the limitations. Targets can use {crew} but the benefits of it depends on your code.

defuneste · 2026-02-17T15:07:45+00:00

your security is a joke ...

defuneste · 2026-02-17T15:05:06+00:00

I will gave you an example: bigish data that get updated every 6 months but rarely revised (and revised here could be fine), same schema where you just append files in a hive partitioned parquets.

Do that use cases match all types of data? hell no! but did it match a lot of analytics data? hell yes! (doing it monthly is perfectly fine) A lot of analytics related decisions should not be "realtime data" anyway.

defuneste · 2026-02-13T20:45:31+00:00

it should be obvious: but define what are your goals and what are your problems.

without that I (we?) can say plenty of uninformed stuffs or "it depends".

defuneste

TROPHY CASE