covr is an R package that tracks test coverage for R packages and generates coverage reports. It can display results locally or upload them to services like Codecov or Coveralls.
The package works by modifying package code to add tracking calls, measuring coverage for both R and compiled code. It supports flexible exclusion of files, functions, or individual lines from coverage analysis using various methods including special comments, configuration files, and function arguments. covr integrates with any R testing framework and includes an RStudio addin for convenient access during development.
Contributors#
Resources featuring covr#
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
Covr Test Coverage | RStudio Webinar - 2016
This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/web … . We try to host a couple each month with the goal of furthering the R community’s understanding of R and RStudio’s capabilities.
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