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CONTRIBUTING.md

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Contributing to target

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.

Table of Contents

Branches and branch prefixes

The package is developed on dev while the latest stable release is made available on main. Releases follow a frequency of about 12 weeks, except for hotfixes or when larger features become available. All feature branches should be created of dev. Branches containing hotfixes should contrary be created of main to avoid merging unfinished features from dev into main.

Branch prefixes

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.

Pull requests

All pull requests (PRs) must be made on dev. 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 dev.

Continuous integration

A variety of continuous integration tests are set up in .github/workflows to mitigate the risk of committing malfunctioning code.

R package development

Style guide

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 testing

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.

Attribution

This guide is based on the contributing.md. Make your own!