The REDCapSync package benefits from storing/caching information
about your different projects. The two most important pieces of
information is the project_name and directory
where it’s stored. This is enough information to be able to find where
you have chosen to securely store your files, load what has already been
collected, and then communicate with R to fetch any new updates.
REDCapSync’s ability to store your projects in a standardized directory
is what allows for powerful pipeline tasks. Importantly, no direct
project data or tokens are stored in the cache!
library(REDCapSync) # don't forget to load the packageUsing the hoadr package, R finds the standard location
where R typically stores cahced package data. For example, on Mac the
location might look like,
“/Users/yourmacname/Library/Caches/R/REDCapSync”.
Location
Your exact path can be found for any R package with
rappdirs::user_cache_dir("R"). The only thing that
REDCapSync stores in this cache is the projects data.frame, which can be
loaded with projects <- get_projects().
user_cache_location <- rappdirs::user_cache_dir("R")
redcapsync_cache_location <- file.path(user_cache_location, "REDCapSync")
redcapsync_cache_location
# launch the folder on your computer
utils::browseURL(redcapsync_cache_location)Clearing
You can clear the entire cache or only delete specific projects. This will only delete REDCapSync’s “knowledge” of project information and location; it will not delete any files from any project directories. If you want to delete files, please do so using your own methods.
# clear entire cache (all projects)
cache_clear()
# clear specific project
cache_clear("OLD_PROJECT1")
# clear specific project1
cache_clear(c("OLD_PROJECT2", "OLD_PROJECT3"))Projects
If you setup and subsequently sync/save a project, it will appear using the code below. If you haven’t setup any projects, it will be an empty data.frame.
projects <- get_projects()
print.data.frame(projects)