lintr is a static code analysis tool for R that checks code for style adherence, syntax errors, and potential semantic issues. It identifies problems and reports them so developers can fix issues before runtime.
The package provides configurable linters that can be run on individual files, projects, or entire R packages. It integrates with CI/CD workflows and popular editors for automated checking. lintr complements the styler package, which automatically fixes formatting issues, while lintr focuses on detection and reporting of a broader range of code quality problems.
Contributors#
Resources featuring lintr#
Jim Hester | It depends: A dialog about dependencies | RStudio (2019)
Software dependencies can often be a double-edged sword. On one hand, they let you take advantage of others’ work, giving your software marvelous new features and reducing bugs. On the other hand, they can change, causing your software to break unexpectedly and increasing your maintenance burden. These problems occur everywhere, in R scripts, R packages, Shiny applications and deployed ML pipelines. So when should you take a dependency and when should you avoid them? Well, it depends! This talk will show ways to weigh the pros and cons of a given dependency and provide tools for calculating the weights for your project. It will also provide strategies for dealing with dependency changes, and if needed, removing them. We will demonstrate these techniques with some real-life cases from packages in the tidyverse and r-lib.
VIEW MATERIALS https://speakerdeck.com/jimhester/it-depends
About the Author Jim Hester Jim is a software engineer at RStudio working with Hadley to build better tools for data science. He is the author of a number of R packages including lintr and covr, tools to provide code linting and test coverage for R
