Collaborate Disseminate
The last post showed how to work with the macOS mdls command line XML output, but with {swiftr} we can avoid the command line round trip by bridging the low-level Spotlight API (which mdls uses) directly in R via Swift. If you’ve already played with {s… Continue reading Avoiding The mdls Command Line Round Trip With swiftr::swift_function()
(reminder: Quick Hits have minimal explanatory blathering, but I can elaborate on anything if folks submit a comment). I’m playing around with Screen Time on xOS again and noticed mdls (macOS command line utility for getting file metadata) has a -plist… Continue reading Quick Hit: Processing macOS Application Metadata Weirdly Fast with mdls and R
Horrible puns aside, hopefully everyone saw the news, earlier this week, from @thomasp85 on the evolution of modern typographic capabilities in the R ecosystem. Thomas (and some cohorts) has been working on {systemfonts}, {ragg}, and {textshaping} for … Continue reading Getting Into the Rhythm of Chart Typography with {ragg} and {hrbragg} (a.k.a. It’s {ragg}-time}
💙 Expand for EKG code library(hrbrthemes) library(elementalist) # remotes::install_github(“teunbrand/elementalist”) library(ggplot2) read_csv( file = “~/Data/apple_health_export/electrocardiograms/ecg_2020-09-24.csv”, # this is extracted below skip = 1… Continue reading Extracting Heart Rate Data (Two Ways!) from Apple Health XML Export Files Using R (a.k.a. The Least Romantic Valentine’s Day R Post Ever)
Presented without much commentary since I stopped once {ggrepel} and {graphlayouts} failed (RStudio doesn’t support it yet, either, which I knew). The following steps will get you a fully working and STUPID FAST fully native ARM64 M1/Apple Silicon R se… Continue reading Fully Native M1/Apple Silicon R Setup
If you’ve been following me around the internets for a while you’ve likely heard me pontificate about the need to be aware of and reduce — when possible — your personal “cyber” attack surface. One of the ways you can do that is to install as few applic… Continue reading Getting a Handle on macOS App Entitlements with R
I was chatting with a fellow Amazon Athena user and the topic of using Presto functions such as approx_distinct() via {d[b]plyr} came up and it seems it might not be fully common knowledge that any non-already translated function is passed to the desti… Continue reading Amazon Athena {dbplyr} Implicit Usage of Presto Functions and Making JSON Casting Great Again
The past two posts have (lightly) introduced how to use compiled Swift code in R, but they’ve involved a bunch of “scary” command line machinations and incantations. One feature of {Rcpp} I’ve always 💙 is the cppFunction() (“r-lib” zealots have a simil… Continue reading Making It Easier To Experiment With Compiled Swift Code In R
The previous post introduced the topic of how to compile Swift code for use in R using a useless, toy example. This one goes a bit further and makes a case for why one might want to do this by showing how to use one of Apple’s machine learning librarie… Continue reading Calling [Compiled] Swift from R: Part 2
I’ve been on a Swift + R bender for a while now, but have been envious of the pure macOS/iOS (et al) folks who get to use Apple’s seriously ++good machine learning libraries, which are even more robust on the new M1 hardware (it’s cool having hardware … Continue reading SwiftR Switcheroo: Calling [Compiled] Swift from R!