The gh package provides a minimalistic R client for accessing GitHub’s REST and GraphQL APIs. It allows you to interact with GitHub programmatically from R using simple function calls.
The package converts GitHub API endpoints directly into R function calls, making it easy to query repositories, manage issues, create releases, and perform other GitHub operations. It handles authentication through Personal Access Tokens stored in the git credential store or environment variables, and automatically converts JSON responses into R objects. The straightforward syntax lets you copy API endpoints from GitHub’s documentation and paste them directly into your code with minimal modification.
Contributors#
Resources featuring gh#
What R We Counting? (Ben Arancibia, GSK) | posit::conf(2025)
What R We Counting?
Speaker(s): Ben Arancibia
Abstract:
GSK Biostatistics mandates that all new tools be written using open-source languages and open-source code achieve parity with proprietary software by the end of 2025. Given this ambitious timeline, someone might ask, “How is the open-source adoption going?” This seemingly simple question involves complexities: What metrics do you track? How to measure success? How to show progress? GSK addressed these by leveraging our internal GitHub data, using open-source R packages like {gh}, scheduling our data pipeline on Posit Connect, and generating diverse reports/dashboards. We’ll share our journey of transitioning to R and other open-source tools, offering insights on scaling full enterprise open-source adoption. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Carson Sievert - Supercharge Your Shiny (for Python) App: Unleashing Interactive Jupyter Widgets
Most Python packages that provide interactive web-based visualizations (e.g., altair, plotly, bokeh, ipyleaflet, etc.) can render in Jupyter notebooks via the ipywidgets standard. The shinywidgets package brings that ipywidgets standard to Shiny, enabling the use of 100s of Jupyter Widgets as Shiny outputs. In this talk, you’ll not only learn how to render Jupyter Widgets in Shiny to get interactive output, but also how to leverage user interaction with widgets to create delightful and bespoke experiences.
Talk by Carson Sievert
Slides: https://talks.cpsievert.me/20240814/ GitHub Repo: https://github.com/cpsievert/talks/tree/gh-pages/20240814
Ask Hadley Anything
A unique opportunity to gain insights directly from a leading expert in open source data science and a driving force behind many popular R packages like ggplot2 and dplyr.
Links from the Q&A: gh-action webscraping demo: https://github.com/hadley/cran-deadlines tidyverse devday 2024: https://www.tidyverse.org/blog/2024/04/tdd-2024/
For the 3 questions on moving from SAS to R in Pharma: Posit and Atorus have partnered on a Posit Academy training: https://posit.co/blog/upskill-to-r-programming-with-posit-and-atorus-research/ And at least 3 pharma companies have shared resources to help people on the transition from statistical programming in SAS, to data science in R: Pfizer exercises: https://github.com/pfizer-opensource/pharma-hands-on-exercises Bayer SAS to R: https://bayer-group.github.io/sas2r/ Roche Coursera course: https://www.coursera.org/learn/making-data-science-work-for-clinical-reporting
Capacity Planning for Microsoft Azure Data Centers | Using R & RStudio Connect
Capacity Planning for Microsoft Azure Data Centers | An Explainable Data Science Workflow using R & RStudio Connect | Presented by Paul Chang
2:12 - Start of presentation 47:43 - Start of Q&A session
Thank you for watching! Here are a few helpful links:
- Link to Paul’s slides: https://lnkd.in/gh-hGScE
- More information on RStudio Connect: https://www.rstudio.com/products/connect/
- How to open an Azure account: https://azure.microsoft.com/en-us/
- Getting started with SAML authentication on RStudio Connect: https://support.rstudio.com/hc/en-us/articles/360022321494-Getting-Started-with-SAML-in-RStudio-Connect
- pins package: https://pins.rstudio.com/
- plumber package: https://www.rplumber.io/
- Upcoming events: rstd.io/community-events
- Chat with our team to start an RStudio Connect evaluation: rstd.io/chat-with-rstudio
Abstract: The Long Range Capacity Planning team at Microsoft is responsible for producing plans for expanding Microsoft Azure Data Centers around the world. These are multi-billion dollar plans that enable the full suite of IaaS and PaaS cloud offerings for our customers, over a 5+ year time horizon. In this talk, we will present the data science software stack that we have built using RStudio Connect and Azure, for producing these data center capacity plans. We will discuss how RStudio Connect has empowered our data scientists to connect more directly with internal stakeholders and decision makers, and how RStudio Connect has enabled us to streamline our data science and business processes.
Speaker Bio: Paul Chang, Senior Data & Applied Scientist, Microsoft
Paul Chang is the Systems Architect of the Long Range Capacity Planning team for Microsoft Azure Data Centers. He received his Applied Math PhD from Simon Fraser University and has worked in a variety of fields including Applied Functional Analysis, Hydrogen Fuel Cell modeling, and A.I. Applications in Vehicular Traffic Engineering. He was also a software engineer in SQL Azure for a couple of years.
Thank you for joining us!
- If you ever have suggestions or general feedback, please let us know! Here’s an anonymous google form: rstd.io/meetup-feedback
- We’d love to hear from you too! Here’s a talk submission form as well: rstd.io/meetup-speaker-form
- If you’d like to learn more about RStudio Connect: https://www.rstudio.com/products/connect/
- If you’re just starting to advocate for data science in general or RStudio tools: rstudio.com/champion