rdata, a package from Carlos Ramos Carreño, is a pure Python implementation that offers a lightweight way to import R datasets/objects stored in the “.rda” and “.rds” formats into Python!
@joranelias nay. i barely had time to get that plot up (and I also broke it + filed an issue :-) the wrapping is one of the things I 💙 about {ggtext} and hoping it's even better in this, tho it seems to have similar glyph spacing foibles.
Check it out, the #Shiny extension for #VSCode now supports both Shiny for R apps and Shiny for Python apps in everyone's second favorite IDE!
Along with the updates come a few neat features for deploying your Shiny apps as serverless ShinyLive apps using https://shinylive.io, or for saving a ShinyLive app as local #RStats or #Python files.
I have an #RStats {httr2} question: I'm about to make a bajillion requests to the same server. Can I use the server's keep-alive capability to batch these more efficiently? I'm not finding any info on this online or in the docs.
@gaborcsardi I'm looking at the code in R/sequential.R and it's just looping through requests like I would. Do you (or anyone reading this!) happen to know if this is using deeper magic to keep the TCP/IP connection alive between requests? I see that it's doing stuff with {curl} handles but haven't dug into that yet.
We are thrilled to introduce {keras3}, the next version of the Keras R package. {keras3} is a ground-up rebuild of {keras}, maintaining the beloved features of the original while refining the API based on valuable insights gathered over the past few years.
Introducing get_provider_meta_data() in the healthyR.data package! Perfect for healthcare datasets, it offers easy metadata fetching and filtering from CMS.
Highlights:
Customizable Filtering by identifier, title, description, keyword, dates, theme, and media type.
Tidy Tibble Output with detailed metadata, including download URLs and contact info.
Efficient Data Processing for clean and ready-to-use data.
📦 Generalizing OOP in R core @R_Foundation
🏨 Visualizing overture map buildings data @kyle_e_walker
📝 Refactoring a test file (part 2) @maelle
You'll see awesome new features in our show like custom chapter images and boosting directly to your hosts with a modern podcast app available at https://newpodcastapps.com/
@hrbrmstr@smach It's actually much slower than I expected :) I briefly tried to render one of my previous books and it took 3 whole seconds! My expectation was at most half a second. I haven't profiled the code yet, but I guess I won't be able to optimize it much at the R level.
Today's Computing Infrastructure package is outcomerate
AAPOR (American Association of Public Opinion Research) Survey Outcome Rates
🙏 Maintained by Rafael Pilliard Hellwig
📝 https://docs.ropensci.org/outcomerate/