How to add code coverage (codecov) to your R package?

June 24, 2017
By

[This article was first published on R-bloggers – Eryk Walczak, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

During the development of another R package I wasted a bit of time figuring out how to add code coverage to my package. I had the same problem last time so I decided to write up the procedure step-by-step.

Provided that you’ve already written an R package, the next step is to create tests. Luckily, devtools package makes setting up both testing and code coverage a breeze.

Let’s start with adding an infrastructure for tests with devtools:
library(devtools)
use_testthat()

Then add a test file of your_function() to your tests folder:
use_test("your_function")

Then add the scaffolding for the code coverage (codecov)
use_coverage(pkg = ".", type = c("codecov"))

After running this code you will get a code that can be added to your README file to display a codecov badge. In my case it’s the following:
[![Coverage Status](https://img.shields.io/codecov/c/github/erzk/PostcodesioR/master.svg)](https://codecov.io/github/erzk/PostcodesioR?branch=master)

This will create a codecov.yml file that needs to be edited by adding:
comment: false
language: R
sudo: false
cache: packages
after_success:
- Rscript -e 'covr::codecov()'

Now log in to codecov.io using the GitHub account. Give codecov access to the project where you want to cover the code. This should create a screen where you can see a token which needs to be copied:

Once this is completed, go back to R and run the following commands to use covr:

install.packages("covr")
library(covr)
codecov(token = "YOUR_TOKEN_GOES_HERE")

The last line will connect your package to codecov. If the whole process worked, you should be able to see a percentage of coverage in your badge, like this:

Click on it to see which functions are not fully covered/need more test:

I hope this will be useful and will save a lot of frustrations.

To leave a comment for the author, please follow the link and comment on their blog: R-bloggers – Eryk Walczak.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)