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Contributing Guidelines

Source: CONTRIBUTING.md

Repository structure

This repository is structured as a standard R package following the conventions outlined in the Writing R extensions manual. A few additional files are provided that are not part of the built R package and are listed in .Rbuildignore, such as the docs/ folder contents, which contains the package website’s html and Javascript data.

Documentation

All of the function documentation is generated automatically. Please do not edit any of the documentation files in man/ or the NAMESPACE. Instead, construct the appropriate roxygen2 documentation in the function files in R/ themselves. The documentation is then generated by running the document() function from the devtools package. Please consult the Advanced R programming guide if this workflow is unfamiliar to you. Note that functions should include examples in the documentation. Please use \dontrun for examples that take more than a few seconds to execute or require an internet connection.

Likewise, the README.md file in the base directory should not be edited directly. This file is created automatically from code that runs the examples shown, helping to ensure that they are functioning as advertised and consistent with the package README vignette. Instead, edit the README.Rmd source file in manuscripts and run make to build the README.

Fixing typos

You can fix typos, spelling mistakes, or grammatical errors in the documentation directly using the GitHub web interface, as long as the changes are made in the source file. This generally means you’ll need to edit roxygen2 comments in an .R, not a .Rd file. You can find the .R file that generates the .Rd by reading the comment in the first line.

Code

All code for this package is found in R/, (except compiled source code, if used, which is in /src). All functions should be thoroughly documented with roxygen2 notation; see Chapter 8: Object documentation in R Packages (2e). Code should conform to our rOpenSci Style Guide

If you want to make a bigger change, it’s a good idea to first file an issue and make sure someone from the team agrees that it’s needed. If you’ve found a bug, please file an issue that illustrates the bug with a minimal reprex (this will also help you write a unit test, if needed). See our guide on how to create a great issue for more advice.

  • Fork the package and clone onto your computer. If you haven’t done this before, we recommend using usethis::create_from_github("{{github_spec}}", fork = TRUE).

  • Install all development dependencies with devtools::install_dev_deps(), and then make sure the package passes R CMD check by running devtools::check(). If R CMD check doesn’t pass cleanly, it’s a good idea to ask for help before continuing.

  • Create a Git branch for your pull request (PR). We recommend using usethis::pr_init("brief-description-of-change").

  • Make your changes, commit to git, and then create a PR by running usethis::pr_push(), and following the prompts in your browser. The title of your PR should briefly describe the change. The body of your PR should contain Fixes #issue-number.

  • For user-facing changes, add a bullet to the top of NEWS.md (i.e. just below the first header). Follow the style described in https://style.tidyverse.org/news.html.

Code style

  • New code should follow the tidyverse style guide. You can use the styler package to apply these styles, but please don’t restyle code that has nothing to do with your PR.

  • We use roxygen2, with Markdown syntax, for documentation.

  • We use testthat for unit tests. Contributions with test cases included are easier to accept.

Testing

Any new feature or bug-fix should include a unit-test demonstrating the change. Unit tests follow the testthat framework with files in tests/testthat. Please make sure that the testing suite passes before issuing a pull request. This can be done by running check() from the devtools package, which will also check for consistent documentation, etc.

This package uses the AppVeyor continuous testing mechanism for R to ensure that the test suite is run on each push to Github. An icon at the top of the README.md indicates whether or not the tests are currently passing.

This package also uses codecov.io to measure test coverage. While not all code can be covered by automated tests (in particular, functions involving user prompts), try to avoid decreasing coverage by writing unit tests for any contributed code. Codecov.io will flag PRs that decrease coverage.

General Development Goals & Guidelines

  1. Not having too many high-level functions,
  2. Using sensible defaults, (driven by use cases).
  3. Docs should point advanced users to the lower-level API when they need special cases.
  4. Maintain a consistent user-facing API.
  5. Maintain consistency with sensible RDF definitions.

Code of Conduct

Please note that the creation of the dataset package as a project is released with a Contributor Code of Conduct. By contributing to this project you agree to abide by its terms.