![]() ![]() ![]() If you are interested in using the RSPM in your own organisation, give us a shout - we’re RStudio Partners.There are few different OSs available for RSPM.If you are using 18.04 bionic, then change in the obvious way The above code is for Ubuntu 16.04 Xenial.If you use GitHub Actions, then this has already been implemented. The above is an incredibly easy way to speed-up your CI steps and works with other CI systems. These few lines cut the travis build time from around 12 minutes to under 4 minutes. ![]() Rprofile to enable packages that are installed via Rscript to also use the binary package versions. The first line adds the RStudio binary package repository to the. While looking complicated, it is actually fairly simple. Paste(getRversion(), R.version, R.version, R.version), echo "options(HTTPUserAgent = paste0('R/', getRversion(), ' R (', echo "options(repos = c(CRAN = ''))" > ~/.Rprofile.site The second job had same two lines, but also an additional before_install: line before_install: The total time for this travis job was around twelve minutes. Imports: tidyverse in the DESCRIPTION file. To test this I made a simple package, with no functions, but a dependency on the. RSPM provides precompiled binaries for CRAN packages, which should ensure a faster install. The RStudio package manager is perhaps the easiest way of speeding up your CI process. In this post, we’ll discuss leveraging some of those techniques for our CI pipeline.ĭo you use Professional Posit Products? If so, checkout out our managed Posit services In a recent post, we showed the different ways of speeding up package installation (worth checking this out if you find package installation/updating slow). One obvious bottle neck is the “install your R package” step, as any R package may have a large number of dependencies. Start a VM, install your R package, then run a bunch of checks. If you are using R, then the current most popular CI pipeline is Travis CI, but there’s also Jenkins, GitHub Actions, GitLab CI, Circle CI and a few others. It protects us from ourselves! However this process can become slow, as typically the CI process starts with a blank virtual machine (VM). We push a change to the server, and a process is spawned that checks we haven’t done something silly. Continuous integration is an amazing tool when developing R packages. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |