@kupac @aRubes did yiu give a go to nvim-R https://github.com/R-nvim/R.nvim if yes what didn't you like?
@statquant
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@defuneste
I can tell you what we did: we built a way to drive jupyterlab from neovim so you write everything from neovim in a proper dev env and jupyterlab becomes your "gui"
I can tell you what we did: we built a way to drive jupyterlab from neovim so you write everything from neovim in a proper dev env and jupyterlab becomes your "gui"
@defuneste
I think because you end up with one file for everything because people won't store functions away, it's bad as a development environment, it consumes more resources than it should.
I think because you end up with one file for everything because people won't store functions away, it's bad as a development environment, it consumes more resources than it should.
@sirwumpus
Nope ce serait à Montréal. Bonne chance pour la recherche du coup 💪
Nope ce serait à Montréal. Bonne chance pour la recherche du coup 💪
@sirwumpus
Bonjour, intéressé par travailler en finance ?
Bonjour, intéressé par travailler en finance ?
I have no experience with target specifically bytva lot with paralelism in #rstats and it's very bad...
Which backend do you endup using (local like multicore, multiprocess or distributed like slurm)?
Which backend do you endup using (local like multicore, multiprocess or distributed like slurm)?
@tangming2005 you might as well call this best tidyverse practices...
coolbutuseless#RStats Rainy Day Dev Diary
Progress on {zap} - bespoke serialization infrastructure for R
Writing to file a 255-level factor with 10% NAs. N = 10000 random values
* faster than writing uncompressed 'saveRDS()'
* more compressed than saveRDS('xz') (just by a smidge!)
* 10x faster than writing saveRDS(xz)
@coolbutuseless I did not know about qs2. I always seems to learn about cool stuff incidentally
@plantarum data.table::fread and data.table::fwrite works and are probably much faster