Ice and fire vibes #notGenerative
Made with #rstats {rdeck}
#rstats VSCode productivity tip: assign keybindings to workbench.action.terminal.scrollDown and workbench.action.terminal.scrollUp so you can move though console output without having to switch back and forth from the terminal or use your mouse.
When you take advantage of {dplyr} groups for mutating or filtering you DON’T get the helpful warning about sticky groups as per summarise(). This red flag I put into {paint} has saved me twice in 2 days! #rstats
New in {rmdocs} 0.2.0:
You get an Rmd verison of the dev help for your package when it detects {devtools} is loaded. #rstats
Something in prod bombed over the weekend. I had logged the #rstats {targets} build output so I knew which target. I pulled the dependencies from the cache stepped through the target code interactively until I found the bomb. Data source schema change ofcourse. Took about ~10 minutes to pin down the field and record in the cached data and fire off the email to upsream team. Prod without a target graph and a cache? I can’t even.
Setup
In response to a Twitter question from Jared Lander, here is my logging setup:
Top level file is a .cmd - yes we’re on Windows Server Data Centre.
pushd $~dp0
Rscript.exe the_script.R > log.txt 2>&1
Roughly translated to:
- set the working dir to the scipt’s location.
- pipe the std output and std error of running the_script.R to log.txt
Here is the_script.R:
capsule::run({
targets::tar_invalidate(source_file)
targets::tar_make(output)
})
Which translates to:
- within my {capsule} ({renv}):
- invalidate the source data (so it will be refreshed)
- build the output (this plan has multiple outputs on different schedules)
To do interactive diagnostics with cached targets, I run capusle::repl() to switch my R REPL over to the capsule environment.
After 7 days of dogfooding, the addition of a test suite, documentation, and 1 confirmed user, {paint} is now v0.1.0 #rstats
Happy Friday #rstats! This week’s diversion is alternative print() methods for data rectangles. Here’s {paint}, highly experimental, works on my machine stage:
Bit of a scraping project on that’s going to sip thousands of xml files over the next couple of days. Using #rstats {targets} dynamic branching each xml file is a cached target. The advantage of this is that if the process is interrupted at any time for any reason it can be resumed with a simple tar_make(). Niiiiiiice.