posit::glimpse() Newsletter

Welcome to our newsletter, posit::glimpse(). If you’re currently reading this on our blog, consider subscribing to Stories on our subscription page to receive this newsletter directly in your inbox.

We’re back with our newsletter! posit::glimpse() is the same glimpse of our tools and how to use them, but now with our new name. In this edition: Learn how to position text and images in Shiny apps, work on your data science compositions in Quarto, and transpose data with tidyverse. Additionally, new releases of our pro tools make it easier to create composite R and Python tools with your data science teams. We posit you’ll find something useful, and positive you’ll learn something new!

Roundup

• • Join us at posit::conf(2023) in Chicago or online September 17-21! There’s talks, workshops, a chance to get together with other data science folks, and of course, stickers. Discover what makes posit::conf() special from Hadley, Mine, Curtis, and Rachael. Visit our website to register and stay up-to-date on all conference details. 
  • Shiny for Python ready for production work. We are thrilled to announce that Shiny for Python has moved from the alpha stage to general availability! With Shiny for Python, data scientists can build interactive web applications with the expressiveness and power of reactive programming, and combine that with the extensive array of data analysis tools and visualization libraries in Python. It’s the perfect balance between simplicity and power. 
  • R in the browser! webR 0.1.0 has been released! In his blog post, George Stagg introduces webR, and demonstrates some of the possibilities that running R in a web browser brings, including how to include webR in your own TypeScript or JavaScript web applications. There’s already so many amazing developments with webR in the community! 
  • Too many new features in dplyr to count. In his blog post series, Davis Vaughn shares about all the new features and updates in dplyr 1.1.0. There’s joins, per-operation grouping, various updates to vectors functions, two new verbs, pick() and reframe(), along with some changes to arrange() that improve both reproducibility and performance. 
  • Cherry blossom release of RStudio IDE and Posit Workbench. It’s not just cherry blossom season for trees. This release of the IDE and Workbench includes support for R-4.3.0, improvements to auto-completion, updates to user guides, and more. This release also adds configurable locations for Jupyter Lab and VS Code, to ensure the right installation is run, especially in complex, contained-based environments such as Kubernetes.
  • {purrr} now at 1.0.0! This is a big release, adding some long-needed functionality (like progress bars!) as well as really refining the core purpose of {purrr}. Hadley Wickham shares about these updates in the release video. Whether you’re a “cat”-egorical beginner or a seasoned functional programming “purr”-fessional, {purrr} has something to offer. So why not “pounce” on the opportunity to try it out.

   

  Learn. Teach. Share.

  • Quarto 1.3 release is coming soon! Charlotte Wickham highlights some of the new features coming in Quarto 1.3, including code annotation, multi-format publishing, Jupyter notebook cell embedding, and publishing from Quarto to Confluence. No need to wait! You can try any of these features now by downloading and installing the pre-release.  
  • Shiny and Pharma, better together. Thanks to cross-organizational collaboration, R and Shiny are being used to help the FDA quickly and accurately assess the efficacy of new medical products. Eric Nantz, Director of the Statistical Innovation Center at Eli Lilly and Company, shares how he has seen Shiny create value in the clinical trials process.
  • Deep learning and scientific computing with R torch. Sigrid Keydana’s book on this topic is now available! It introduces torch basics, shows various deep-learning use cases, and how to use torch for more general topics. Also learn about de-noising diffusion with torch and group-equivariant convolutional neural networks.
  • Evaluating the MLOps readiness of your team. MLOps are a set of practices to deploy and maintain machine learning models in production. Isabel Zimmerman shares some considerations for assessing whether your team needs MLOps.
  • Approaches for deploying your Shiny apps. Shiny has many deployment options to choose from! Seamless and quick deployment helps you focus on building apps rather than trying to deploy them. Vedha Viyash shares some approaches, including git-backed deployment on Posit Connect and Ryan Johnson shares how to leverage pins with Connect.

   

  Selected Releases

  • Shiny: In the new release of the ShinyUIEditor, bslib cards provide an easy-to-use and attractive way to wrap related content in your app. 
  • Modeling: {vetiver} 0.2.0 and {pins} 1.1.0 releases help with model deployment. {torch} 0.10.0 upgrades the underlying LibTorch, and adds support for Automatic Mixed Precision. {luz } 0.4.0, a high-level interface for {torch}, is now on CRAN. 
  • Tidyverse: {dtplyr} 1.3.0, {dplyr} 1.1.1, {dbplyr} 2.3.0, {tidyr} 1.3.0, {purrr} 1.0.0,  and {forcats} 1.0.0 were all released to CRAN. With the release of tidyverse 2.0.0, {lubridate} is now a core member of the tidyverse! 
  • Tidymodels: Tidymodels is getting faster and {censored 0.2.0} has been released.
  • R Markdown: New releases of {knitr} include the ability to specific a custom progress bar. {gt} releases are packed with features. Rich Iannone highlights some in his {gt} 0.8.0 release video and shares about formatting functions in {gt} 0.9.0.  
  • Pro: Posit Connect 2023.03.0 now supports Voilà and Jupyter Widgets for adding interactive elements to a Jupyter Notebook.

   

  Wrapping Up

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