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James Balamuta

@coatless.bsky.social

Nothing makes you feel vintage like your license getting moved to the retirement home directory. GNU put GPL 2.0 in /old-licenses/ causing #rstats packages to throw URL warnings. Somewhere a CRAN maintainer is rubbing their hands together, ready to trigger 847 email requests...

Screenshot of a code diff showing line 10 being updated. The removed line (red) shows a GPL 2.0 license URL pointing to gnu.org/licenses/gpl-2.0.html, while the added line (green) shows the same URL updated to point to gnu.org/licenses/old-licenses/gpl-2.0.html, indicating the license documentation has been moved to an 'old-licenses' directory.

September 26, 2025 at 6:12 PM

James Balamuta

@coatless.bsky.social

macOS 26 Tahoe + R 4.5.1: Keeps #rstats moving along on #macOS. Upgrade confidently, just remember to update Xcode CLI afterwards if using stan & compiled code.

A screenshot showing R 4.5.1 working under RStudio 2025.9.0.387 on macOS Tahoe (26.0.0) with a call to compiled code requiring gfortran through RcppArmadillo.

A screenshot showing R 4.5.1 working under Positron 2025.9.0 (Universal) on macOS Tahoe (26.0.0) with a call to compiled code requiring gfortran through RcppArmadillo.

September 16, 2025 at 12:39 AM

James Balamuta

@coatless.bsky.social

R that travels light on #Linux: Portable R AppImages.

Now working everywhere: your Ubuntu, friend's Fedora, cousin's Arch setup (btw)

No sudo, no tears, just base R science ✨

(package support coming soon!)

#RStats #AppImage #DataScience

Terminal session showing the download and execution of an R AppImage from GitHub releases. The commands show wget downloading the ARM64 AppImage built on Ubuntu 24.04, making it executable with chmod +x, and then launching it to run R statistical analysis including a linear regression model with income vs age data, demonstrating the workflow from GitHub release to running statistical computations.

VS Code showing the successful completion of an R AppImage build process. The terminal displays the build summary indicating a 76MB minimal R 4.5.1 AppImage for ARM64 architecture with package installation disabled (immutable). The output shows usage examples and confirms the build completed successfully, with R actually running at the bottom showing the standard R startup message and executing system environment commands, demonstrating the fully functional portable R installation.

VS Code terminal showing R 4.5.1 running from an AppImage on ARM64 architecture. The file explorer shows the typical AppImage directory structure with usr/bin, usr/lib, and usr/share folders, demonstrating the self-contained portable nature of the R installation.

September 15, 2025 at 6:37 PM

James Balamuta

@coatless.bsky.social

Linux support 🐧

Same #rshiny → desktop workflow on #Fedora 42 aarch64:

shinyelectron::export() → #rshinylive → #AppImage → portable #Linux app

Plot twist: no more "go buy yourself a real computer" moments - you get zero #rstats dependencies too! The condescending Unix users have won this round.

September 10, 2025 at 5:49 AM

James Balamuta

@coatless.bsky.social

Core Shiny Application (Shinylive Layer): 61.9 MB

This represents the base Shiny application code and dependencies

Platform-Specific Packaging Overhead (ARM64):

Windows: 300.1 MB
macOS: 264.1 MB
Linux: 304.9 MB

Total Application Size by Platform:

Windows: 362 MB
macOS: 326.4 MB
Linux: 366.8 MB

Windows 11 File Explorer displaying the Programs folder with properties dialogs open for "My-App-Title," showing the application size as 362 MB (379,900,896 bytes) in the Local Programs directory, demonstrating the Windows build footprint.

macOS Finder window showing the contents of an "electron-app" folder with various build artifacts from running {shinyelectron} to create a standalone R Shiny App, highlighting the "converted-app" executable file sized at 326.4 MB, representing the packaged macOS application bundle.

Screenshot of RStudio IDE on Ubuntu 24.04 showing R code in the editor and a system file browser dialog displaying the "linux-arm64-unpacked" folder containing 76 items with a total size of 366.8 MB, representing the Linux build of the standalone R Shiny application created using {shinyelectron} with shinylive.

macOS Finder window displaying the contents of the "converted-app" folder with the "shinylive-app" subfolder selected and its info panel open, showing the Shiny application components (app.json, index.html, shinylive folder, and shinylive-sw.js) with a total size of 61.8 MB (244 items). This is the core Shinylive layer footprint shared across applications.

September 9, 2025 at 9:25 PM

James Balamuta

@coatless.bsky.social

By request: Same #rshiny app → native #electron desktop app workflow now on #Windows11

shinyelectron::export() → #rshinylive → installer → app.exe

[Worth the Parallels license to record this from my Mac]

Still no #rstats dependencies for end users. Living the cross-platform life (virtually).

September 7, 2025 at 5:57 AM

James Balamuta

@coatless.bsky.social

Prototyping #rshiny apps to native #electron desktop apps:

shinyelectron::export() → #rshinylive conversion → .dmg → Native Mac app

Zero #rstats dependencies for end users! Early days but promising 👀

September 4, 2025 at 7:35 AM

James Balamuta

@coatless.bsky.social

I think that covers SciServer Essentials v1.0. There are 4 different versions. The latest has software at #rstats 4.2.2 and #Python 3.9 inside of #JupyterLab.

The R+RStudio image has R 4.2.1 and RStudio Build 2022.07.2.

Maybe raise a ticket to update the underlying suites?

Screenshot of JupyterLab launcher interface showing the main dashboard with two sections: "Notebook" and "Console". Each section displays kernel options for Python 3.9 (py39) and R 4.2.2 with their respective icons. The left sidebar contains a file browser showing "Storage" and "Temporary" folders, both modified "a minute ago", with a search filter box at the top. The interface includes typical JupyterLab navigation elements and is running on sciserver.org as shown in the browser tab.

August 28, 2025 at 4:45 PM

James Balamuta

@coatless.bsky.social

TIL about SciServer.org: Free scientific computing platform with persistent accounts (#NSF-funded). All the power of #JupyterHub without the setup hassle. Focus on building great teaching + research notebooks, not infrastructure! #OpenScience

Screenshot of SciServer's Education page with the same blue header design. The main content shows "Education" as the page title, followed by explanatory text about using SciServer to teach data science. The page includes sections on "How to Teach with SciServer" with detailed instructions, and an "Examples" section featuring astronomy course examples from University of St Andrews and University of North Carolina Asheville, with links to GitHub repositories containing sample notebooks.

August 28, 2025 at 3:08 PM

James Balamuta

@coatless.bsky.social

Request fulfilled! Converted {macrtools::openmp_*()} #OpenMP suite into standalone shell scripts for #macOS:

🎯 Auto Xcode detection & OpenMP library mapping
🔬 Diagnostics tests
🧹 Safe uninstall

📦 Repo: github.com/coatless-she...
📝 Post: blog.thecoatlessprofessor.com/programming/...

The toolkit consists of three focused shell scripts: install-openmp.sh handles automatic Xcode version detection and downloads official CRAN binaries; check-openmp.sh performs diagnostics across five categories; and uninstall-openmp.sh provides safe removal with confirmation prompts and cleanup guidance.

August 27, 2025 at 2:27 AM

James Balamuta

@coatless.bsky.social

After my 6th cup of coffee, I've officially entered the owl dimension. My empty mugs have finally summoned their nocturnal overlord. We communicate only in hoots and caffeine-induced anxiety now. 🦉☕

A collection of bright green coffee mugs arranged on a white kitchen counter. In the foreground is a light green mug filled with black coffee, featuring a decorative blue and green owl design with large eyes. Behind it are six empty matching bright green mugs.

August 22, 2025 at 2:21 PM

James Balamuta

@coatless.bsky.social

Finally, your R packages on #macOS can disappoint all your cores instead of just one of them at a time 😅

{macrtools} now installs & configures OpenMP with:

`openmp_install()` and you're done! ⚡️

mac.thecoatlessprofessor.com/macrtools/re...

#rstats #hpc

$RStudio screenshot showing OpenMP-enabled R code with parallel processing functions like openmp_enabled() and openmp_limits(). The editor displays a timesTwo() function using OpenMP pragmas for parallel execution. The right panel shows macrtools documentation for OpenMP installation functions, with the console confirming OpenMP detection and showing results from querying OpenMP functions. Code: #include <Rcpp.h> #ifdef _OPENMP #include <omp.h> #endif // [[Rcpp::export]] Rcpp::IntegerVector openmp_limits() { Rcpp::IntegerVector limit_data(3, NA_INTEGER); #ifdef _OPENMP limit_data[0] = omp_get_num_procs(); limit_data[1] = omp_get_max_threads(); limit_data[2] = omp_get_thread_limit(); #endif return limit_data; } // [[Rcpp::export]] bool openmp_enabled() { bool enabled = false; #ifdef _OPENMP enabled = true; #endif return enabled; } // [[Rcpp::export]] std::vector<double> timesTwo(std::vector<double> x) { #pragma omp parallel for for (size_t i = 0; i < x.size(); ++i) { x[i] *= 2; } return x ; } /*** R openmp_enabled() openmp_limits() timesTwo(42) */$ R Console on macOS displaying the automated OpenMP installation process. Shows successful download and installation of OpenMP binaries (613 KB), automatic configuration of compiler flags in ~/.R/Makevars, and confirmation that macrtools::is_openmp_installed() returns TRUE, indicating a successful setup without manual toolchain configuration.

R Console on macOS displaying the automated OpenMP installation process. Shows successful download and installation of OpenMP binaries (613 KB), automatic configuration of compiler flags in ~/.R/Makevars, and confirmation that macrtools::is_openmp_installed() returns TRUE, indicating a successful setup without manual toolchain configuration.

August 9, 2025 at 8:45 AM

James Balamuta

@coatless.bsky.social

Step 1: Write R code
Step 2: Share it
Step 3: Spend 2 hours helping someone install R and troubleshoot their environment

OR

Step 1: Write R code
Step 2: webR sharelink

webr.r-wasm.org/latest/?mode...

Step 3: Profit ✨

#rstats #webr

Screenshot showing Firefox browser displaying a webR REPL interface in the foreground, with an RStudio session visible in the background. The webR interface shows decoded R files (main.R, functions.R, config.R, sample_data.csv) that were embedded in a shareable URL. The RStudio console in the background displays the encoded webR sharelink URL that packages all the local files. On the right side, R documentation is open showing help for the 'Create WebR REPL sharelink for multiple files' function. This demonstrates the workflow of encoding local R project files into a URL that can be shared and automatically reconstructed in a browser-based R environment.

July 18, 2025 at 8:26 AM

James Balamuta

@coatless.bsky.social

Yes, through input$map_bounds. c.f.

shinylive.io/r/editor/#co...

A screenshot of a Shiny web application demonstrating spatial data filtering with Leaflet maps. The left panel shows R code in an editor, including library imports for shiny, leaflet, sf, and DT packages, along with server-side logic for filtering spatial data based on map bounds. The right panel displays the running application titled "Filtering Spatial Data by Leaflet bbox" with an interactive map. The map is populated with hundreds of blue circular markers representing spatial data points that change when the bounding box is updated to new locations through a mouse drag event.

July 13, 2025 at 9:13 AM

James Balamuta

@coatless.bsky.social

What is this? An R editor for ants?

@examplesWebR now goes full-screen because your data viz deserves better than a cramped iframe!

Click "Full-width" → no more squinting

Try it: rd.thecoatlessprofessor.com/webr-in-pkgd...

#rstats #webr

July 13, 2025 at 8:51 AM

James Balamuta

@coatless.bsky.social

Saturday morning hacking on {quarto-assign} that takes

One file → multiple outputs (assignment/solution/rubric)

Coming soon:

✨ Auto-numbering with {#exr-} integration
📦 Solutions in callouts

#quarto #rstats #python

Split screen showing a code editor on the left with R code and a rendered homework assignment webpage on the right. The assignment page displays "Homework Assignment" as the title with three exercises: Exercise 1 asks to create a vector with 5 different integers, Exercise 2 requests calculating mean and standard deviation from Exercise 1's vector, and Exercise 3 involves creating a histogram of the mtcars$mpg variable. A "Standalone Example" section appears at the bottom.

Split screen showing the same code editor on the left and a solutions page on the right displaying "Exercise 2." The solutions are presented in green-bordered callout boxes containing R code and outputs, including vector creation (x <- c(1L, 2L, 3L, 4L, 5L)), mean calculation showing "Mean: 3", standard deviation calculation showing "Standard Deviation: 1.58113883", and summary statistics displaying a table with Min, 1st Qu., Median, Mean, 3rd Qu., and Max values.

July 12, 2025 at 6:44 PM

James Balamuta

@coatless.bsky.social

New in {rocleteer}: @examplesWebR tag lets you add interactive #rstats examples to your #pkgdown documentation with #webr!

📦 Pkg: github.com/coatless-rpk...
🎯 Demo pkgdown repo: github.com/coatless-r-n...
🌐 pkgdown website: rd.thecoatlessprofessor.com/webr-in-pkgd...

July 9, 2025 at 9:25 AM

James Balamuta

@coatless.bsky.social

Shoutout to @gws.phd for another #rstats #webR REPL update:

1. Shared code now auto-runs when you click links (by adding &a parameter to end of code=)
2. Choose your view: editor, plot, terminal, or files with ?mode='editor-plot'

Try it yourself: webr.r-wasm.org/latest/?mode...

Screenshot of webR REPL application running in a web browser. The interface is split into two panels: on the left is a code editor containing the R command 'plot(1:10)', and on the right is the resulting scatter plot visualization showing 10 points plotted from coordinates (1,1) to (10,10). The plot has 'Index' labeled on the x-axis and values from 0 to 10 on the y-axis. The browser interface shows typical web app controls including Run, Save, and Share buttons at the top.

July 9, 2025 at 6:10 AM

James Balamuta

@coatless.bsky.social

Experimenting with `@examplesWebR` - a new roxygen2 tag that makes R package examples interactive!

Instead of static code blocks, users get "View in webR REPL" buttons that open examples in their browser or the embedded webR REPL. No R installation needed!

🧵1/2 #rstats #webR

RStudio interface demonstrating WebR REPL link inclusion functionality. The left pane shows R source code with roxygen2 documentation for "Test WebR REPL Link Inclusion." The right pane displays package documentation with a blue "View in webR REPL" button. A firefox browser window is open showing the WebR REPL interface with simple R code (1 + 1) and R session information including details about contributors, demos, and help functions. The interface shows the same rocletter package documentation as the first image.

RStudio interface showing R package documentation with embedded WebR REPL functionality. The left pane contains R source code with roxygen2 comments, including a @examplesWebR tag and demo functions. The right pane displays package documentation for "Test WebR REPL Embedded Inclusion" with an embedded WebR REPL interface showing a ggplot2 example. The WebR interface contains code (library(ggplot2), ggplot(mtcars, aes(mpg, wt)) + geom_point() + theme_minimal()) and displays a scatter plot visualization. The bottom shows an R console with package loading messages in red text.

July 8, 2025 at 7:42 AM

James Balamuta

@coatless.bsky.social

#webR now has shareable links! Just like #Shinylive's editor, you can instantly share #rstats code snippets with colleagues.

Thanks to @gws.phd (webR creator) for adding this awesome feature to webR Latest (0.5.4-dev)!

Try it out with this demo snippet: webr.r-wasm.org/latest/#code...

Screenshot of webR REPL in a web browser showing R code for creating a scatter plot analyzing car weight vs fuel efficiency. The left panel contains ggplot2 code using the mtcars dataset, with points colored by cylinder count and a trend line. The right panel displays the resulting scatter plot with a clear negative correlation between weight and MPG. A modal dialog box is overlaid in the center showing "Share URL (765 bytes)" with a long encoded URL and a blue "Copy URL" button, demonstrating the new share link feature.

Screenshot of the same webR REPL interface after the share dialog has been closed. The left panel shows the same R code for the car efficiency analysis, and the right panel displays the identical scatter plot visualization. The console output shows package loading messages and the correlation result (-0.868). This demonstrates the clean interface without the share modal overlay.

July 7, 2025 at 11:45 PM

James Balamuta

@coatless.bsky.social

Scattered links 🔗 driving you crazy in a post?

The linkate Quarto extension automatically collects every URL and creates a tidy "Links" section at the bottom. Just add one line to your YAML!

📚 Docs: quarto.thecoatlessprofessor.com/linkate/
💻 Repo: github.com/coatless-qua...

#quarto

July 6, 2025 at 8:58 AM

James Balamuta

@coatless.bsky.social

Congratulations to Posit on the Positron IDE exiting beta!

This is huge for #python and #rstats data scientists - having a unified, modern IDE that speaks both languages fluently. Can't wait to see how this accelerates data science workflows!

Try it out here: positron.posit.co/download.html

Screenshot of Positron documentation page showing release notes with "Positron is out of beta!" headline, featuring highlights about stable releases, daily builds, migration guides, and Positron Assistant AI integration features.

GitHub pull request page titled "Bump to FIRST STABLE RELEASE 🎉 #108" showing a merged pull request with deployment preview information and contributor activity timeline.

July 3, 2025 at 5:09 AM

James Balamuta

@coatless.bsky.social

Struggling with $ signs breaking your #Typst templates in #Quarto? 🤯

Standard escaping doesn't work, but hex escape sequences do: \u{24}

Wrote up a quick note with Typst's ASCII table tool for finding any character's hex code.

blog.thecoatlessprofessor.com/programming/...

Screenshot of Typst's ASCII table tool showing the full character grid. The dollar sign ($) is highlighted with a blue border in the table, displaying its hex code 0x24 and decimal value 36. The table shows various ASCII characters organized in rows, including control characters (NUL, SOH, STX, etc.) and printable characters (letters, numbers, and symbols like !, ", #, $, %, &).

June 20, 2025 at 4:15 AM

James Balamuta

@coatless.bsky.social

After disrupting the notebook world, #marimo is expanding to markdown with a new #Quarto extension (WIP)!

marimo-team.github.io/quarto-marimo/

What's marimo? Reactive #jupyter -like notebooks that automatically run cells when code changes. marimo islands is making this tech portable everywhere 🏝️

Screenshot of the marimo-quarto documentation website showing a browser window with the URL marimo-team.github.io/quarto-marimo/. The page displays "marimo + quarto" as the main heading, with a left sidebar navigation containing tutorial sections including Intro, Dataflow, UI, Markdown, Plots, Layout, and Fileformat. The main content area features explanatory text about integrating Quarto with marimo, followed by a blue-highlighted interactive example box titled "Hello from marimo!" that demonstrates a reactive Python cell. Below this is visible Python code using mo.md() function, and a "What?" section that begins explaining marimo and the qmd format. The page has a clean, documentation-style layout with syntax highlighting for the code examples.

May 30, 2025 at 2:10 AM

James Balamuta

@coatless.bsky.social

Nothing says 'modern CI/CD' like using R to install Python packages because {reticulate} said so 🙃 #rstats

$Screenshot of the code diff change from needing just a quick: # Install python dependencies - name: "Install python dependencies" run: | pip install -r docs/requirements.txt To needing to use: # Setup Python for reticulate - uses: actions/setup-python@v5 with: python-version: "3.x" # Install python dependencies for reticulate - name: Setup r-reticulate venv shell: Rscript {0} run: | path_to_python <- reticulate::virtualenv_create( envname = "r-reticulate", python = Sys.which("python"), requirements = "docs/requirements.txt" ) writeLines(sprintf("RETICULATE_PYTHON=%s", path_to_python), Sys.getenv("GITHUB_ENV"))$

May 29, 2025 at 3:44 AM

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