First off, thanks for taking the time to contribute! ❤️
All types of contributions are encouraged and valued. See the Table of Contents for details about how to contribute code to this project. Please make sure to read the relevant section before making your contribution. It will make it a lot easier for us maintainers and smooth out the experience for all involved.
We currently maintain a single active development branch develop.
We use prefixes to label branches. A meaningful short description follows the
prefix and hyphens (-) are used for separation. For example,
feature/new-ml-model-interface is a valid feature branch name.
feature/: Branches for developing new features.
bugfix/: Branches for fixing non-critical bugs.
hotfix/: Branches for fixing critical bugs.
docs/: Branches for writing, updating, or fixing documentation.
All pull requests (PRs) must be made on develop.
The title of the PR should follow the format of
conventional commits and a
summary of the proposed changes must be provided in the body of the PR. This
makes it easier for maintainers as title and body can be reused once all commits
are squashed before merging the feature branch into develop.
A variety of continuous integration tests are set up in .github/workflows to mitigate the risk of committing malfunctioning code.
Contributors should set up their development environment to comply with the
project specified editorconfig configuration and
lintr static code analysis tool. We follow to the
largest extent the
tidyverse style guide, which is
checked via the code linter. A notable difference is that we use dots for long
argument names of functions. For example, instead of predict_args we use
predict.args. We remain using snake case for names of functions and R6 class
methods.
Unit tests are written using the
tinytest
framework and go into the inst/tinytest directory. Tests which
take considerable time to complete (more than a few seconds) go into
inst/slowtest. These tests are not performed when checking with
package with R CMD check. The organization of test files should match the
organization of R files. That is, tests for a function in R/cate.R go into
inst/tinytest/test_cate.R.
Tinytest does not make internal functions directly callable like some other
unit testing packages do. Thus, testing internal functions requires using :::
inside the test files like
output <- targeted:::some_internal_function(1)
expect_equal(output, 2)
More information about unit testing with tinytest is provided in this vignette.
This guide is based on the contributing.md. Make your own!