If I open script.R in RStudio and try and load the library this is the expected behaviour: > library (stringr )Įrror in library (stringr ) : there is no package called ‘stringr’
> system ( "echo 'library(stringr)' >| script.R" ) You should also notice the RStudio integration in the packages area, where it will show your project version against that which Packrat has the binary for and the source of that binary:įor test purposes I created script.R with only one package. "/Users/lukesingham/Projects/testpackrat2" To double check packrat has been initialised properly run: # Check I am in the right directory R will restart once this process is finished. This runs the packrat::init() function to enter packrat mode, takes a snapshot of the package dependencies (of which there are currently none) and places the binaries in the project folder under testpackrat2/packrat/src/ finally init() runs restore() to apply the latest snapshot to the project folder. I've created a new project /testpackrat2 and with the latest RStudio you should be able to select both git and packrat to be initialised. To get the RStudio niceties/integrations it seems neccessary to treat your project folder as an R Project. "isolated, portable, and reproducible way." Getting Started # "Description: Manage the R packages your project depends on in an" "Title: A Dependency Management System for Projects and their R Package" Packrat # > readLines (system.file ( "DESCRIPTION", package = "packrat" ) ) If you are an organisation heavily using R, you have a lot of productivity to gain from the adoption of package management by your R developers. In the data science world, I attribute this difference between the R and Python communities to Python coming out of the computer science discipline and R coming from the statistics discipline. In contrast to the Python community who seem very familiar with their virtualenv package management, the R community doesn't seem to have widely adopted the practice. R scripts breaking over time is annoying for anyone, but it's worth highlighting that organisations using proper package management will significantly decrease their costs in the form of maintenance time spent by developers, data scientists and data analysts fixing projects broken due to changes in package dependencies.
Packrat removal code#
Now you come to 2016 and you want to re-run the code in the 2014project, but you find a bunch of errors because in 2015 dplyr had those syntax changes, such that the syntax you used in 2014 no longer computes. Over time packages get updated, sometimes changing syntax and function names, let's say some major syntax changes occurred in 2015 to dplyr and you used the latest version of dplyr in other projects in 2015. The problem: Let's say you coded a project in R in 2014 using the package dplyr and you called the project 2014project.
Packrat removal how to#
How to Stop R Projects and Scripts BreakingĪ how-to in getting started with Package Management in R How to Stop R Projects and Scripts Breaking Luke Singham
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