Build robust and maintainable software with object-oriented design patterns in R. Design patterns abstract and present in neat, well-defined components and interfaces the experience of many software designers and architects over many years of solving similar problems. These are solutions that have withstood the test of time with respect to re-usability, flexibility, and maintainability. R6P provides abstract base classes with examples for a few known design patterns. The patterns were selected by their applicability to analytic projects in R. Using these patterns in R projects have proven effective in dealing with the complexity that data-driven applications possess.

I worked on a refactor of an R package at work the other day. Here’s some notes about that after doing the work. This IS NOT a best practices post - it’s just a collection of thoughts. For context, the package is an API client. It made sense to break the work for any given exported function into the following components, as applicable depending on the endpoint being handled (some endpoints needed just a few lines of code, so those funtions were left unchanged):

Swagger is a collection of HTML, Javascript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API. - rstudio/swagger

R-hub API client. Contribute to r-hub/rhub development by creating an account on GitHub.

:cloud: R interface to the Dark Sky API [APPLE IS SHUTTING DOWN THE API 2021-12-31] - hrbrmstr/darksky

Tools to work with the Google DNS over HTTPS API in R - hrbrmstr/gdns

🐦 R client for interacting with Twitter's [stream and REST] APIs - ropensci/rtweet

:hash: A package to send webhook API messages to Slack.com channels/users from R - hrbrmstr/slackr

Package to call the todoist API. Manage your ToDo lists with todoist from R. - ThinkR-open/rtodoist

R interface to todoist.com. Contribute to emitanaka/rtodoist development by creating an account on GitHub.