Package Development

Developing R Packages with usethis and GitLab CI: Part II

This post, the second part in a series that covers R package development, will define the important concept of continuous integration (CI) and demonstrate the advantages of using CI within GitLab. The version control code repository, GitLab, offers many services to its users, including the ability to set up CI services to R programmers and software developers in private repositories for free. GitLab’s built-in CI service is easy to utilize and can be set up with an R package relatively quickly.
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Developing R Packages with usethis and GitLab CI: Part I

The best way to share your R code with others is to create a package. Whether you want to share your functions with team members, clients, or all interested R users, bundling up your functions into a package is the way to go. Luckily, there are great tools available that make this process relatively smooth and easy. This series of posts aims to walk through the process of setting up an R package and sharing it on the version control code repository, GitLab.
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Pytesting your python package

Most software developers understand the advantages of packaging up their code: it makes their functions testable, reliable and reusable. Not to mention making their future work much easier and more efficient. Here at Methods, we have realized the benefits of building R and Python packages to bundle up and test our code for collaboration both internally and with clients. This post will help readers in the data science community see how easy it is to get started developing and testing their own Python package using the pytest framework and GitLab CI.
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