Assignment B2: Making an R Package

Due: Wednesday November 17, 2026 at 11:59pm

Total Points: 100

In Assignment B-1, you practiced writing a function. This time, we’ll be evaluating your ability to wrap that function (or something else!) in an R package.

Need some help? Checkout chapter 2 of the “R packages” book.

Options for what function to wrap into a package

Option 1: The function you made in Assignment B1

You can turn the function you made in Assignment B1 into a package for Assignment B2.

The work in Assignment B1 was deliberately designed to make it easier for you to convert it into a package down the line.

However, note that the deadlines for Assignments B1 and B2 are close together as they are on sequential topics, and so you are not guaranteed feedback before the B2 deadline.

Option 2: “Pre-baked” function

A documented function with tests written by the instructional team will be released to Canvas; you can choose to make that into a package for Assignment B2.(Note that the download links on that page won’t work until after the Assignment B1 deadline.)

The pre-baked function is available on Canvas under Assignment B2.

Note: If you take this option, then you may modify the documentation or the tests in any way you see fit. This “pre-baked” function is simply intended to serve as a clean starting point for this assignment that doesn’t depend on your personal success level in Assignment B1.

Option 3: Something new!

If you like, you can choose to write a new function - not used in Assignment B1 - for Assignment B2.

Setup

1. Create a new repository in our organization https://github.com/UBC-STAT545-F2026. Set the owner as UBC-STAT545-F2026 and name your repository assignmentB2FirstnameLastname. YOU CANNOT ADD HYPHENS OR UNDERSCORES IN THE PACKAGE NAME! Make it public.

2. Open an RStudio session

   1. Run library(devtools) in the console

   2. Run create_package("path/assignmentB2FirstnameLastname") replacing “path” with the path to where you’d like your package to live on your computer, and “package_name” with the name of your package.

3. Initialize Git

   1. In the RStudio window that just opened, run git init in your Terminal

4. Connect to GitHub

   1. In the Terminal, run git remote add origin [LINK] replacing the [LINK] with the link to your repository URL (you can find this on the green CODE button on your repository)

   2. Stage, commit, and push the changes to GitHub from RStudio. In the Terminal, run:

      • git add .

      • git commit -m "initial commit"

      • git push origin main (OR git push origin master if an error occurs)

Your files should now appear on GitHub, and you can commit and push changes as you work through the project.

Exercise 1: Function(s) (20 points)

Include a function in your package (see above options).

You should include documentation for the:

• title

• description

• parameter descriptions

• outputs

• examples

Be sure to also include the @export tag to make your function(s) available to users (unless you want the function to be strictly internal)

Render the documentation for all of the functions/objects in your package using document().

Hint: if you’re using the same function as in Assignment B-1, you should only need to put your function in an R script in the R/ folder with the specified additions to your roxygen2 documentation. Then, run document() after loading the devtools package.

What we’re looking for:

• You followed the above instructions.

• You should have .Rd files automatically generated in your man/ folder. Don’t touch these files.

• Functions intended to be used by a package user are deliberately listed under “exports” in the NAMESPACE file (this should happen automatically after running document() and having @export tags with your functions).

• Documentation for each function should load after executing ?function after loading your package.

Exercise 2: High-level documentation (20 points)

Create documentation for your R package at a high level.

1. Fill out a README.Rmd file, being sure to include the package description, installation instructions, and demonstrated usage. Build the README.md file.

2. In the DESCRIPTION file, update the package title and description fields (you can use the same description as you did in your README).

Tips:

• When writing your description, imagine coming across the package on CRAN, and evaluating whether the package is relevant to you based solely on this description. It should be concise and informative.

• To generate the README, use a function that will generate it for you (see lecture notes).

• Installation instructions: should be as simple as running, for example, install_github("org/repo", ref = "0.1.0") (change the version number to your own).

What we’re looking for:

• The above instructions were followed.

• The documentation is clear, simple, and effective.

Exercise 3: DESCRIPTION file (20 points)

1. Ensure a license is in place, and found in the DESCRIPTION file. We suggest usethis::use_mit_license() as an open-source-friendly license.

2. Ensure package dependencies are listed in the DESCRIPTION file, and are effectively chosen (probably listed under “Imports”).

   • If your function relies on other packages, like dplyr, they should be included here

   • If your function relies on a dataset from another package (like steamgames from datateachr, include them here)

   • Packages that come pre-loaded upon opening R are candidates to be listed here, too, such as the datasets and stats packages (but not the base package).

   • If your package does not rely on anything

3. Ensure all calls to functions from external packages are called using the form package::function() (only in very rare situations will you not need to use ::).

4. Ensure all other mechanical structure of the DESCRIPTION file is in place, i.e., passes a check().

Exercise 4: Tests (20 points)

Create unit tests for your package using use_testthat() (see lecture notes)

Hint: if you’re using the same function as in Assignment B-1, you should only need to copy and paste your test_that calls after creating a test file using usethis::use_test(...).

What we’re looking for:

• The extent of testing should match that of Assignment B-1. So, you may not need to add any more tests if your tests were sufficient, but this is an important note if you plan on adding more functions / objects to your R package.

• Your tests should all pass after running devtools::test().

• All tests use testthat

• If you create an object in a test script, you clean up after yourself using rm('name_of_object') (not needed if the objects are created within a test_that() function.)

Repository Visability

Ensure your repository is public at this stage! Go to the settings, scroll down to the “danger zone”, and change it to public.

Tidy Submission (20 points)

Follow these steps once you’re ready to submit your work.

1. Increase the version number in the DESCRIPTION file, using semantic versioning conventions. You should not have a trailing .9000.

   • Summary of convention: MAJOR.MINOR.PATCH, where initial development starts at 0.1.0, and then increment the minor version for each subsequent release

     • Only release 1.0.0 if your package is being used in production and ready for public use.

     • e.g., 0.1.0 -> 0.1.1 -> 0.1.X -> 1.0.0 -> 1.0.1 -> 1.0.X -> 1.1.0

   • Your release versioning is especially important if you will be choosing to develop your package further.

2. Tag a release in your GitHub repository corresponding to your submission before the deadline, using the package version as your tag.

3. Grab the URL corresponding to your tagged release, and submit that to canvas

See Rubric on Canvas for more details on how the package will be graded.