# Cache

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 package

Using the `hoadr` package, R finds the standard location where R typically stores cached 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$load("PROJECT")`.

    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)
    # can modify with config options
    config$cache.dir()

# 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.

    print.data.frame(projects$df)