If a function is called multiple times with the same input, you can
often speed things up by keeping a cache of known answers that it can
retrieve. This is called memoisation http://en.wikipedia.org/wiki/Memoization.
The memoise package provides a simple syntax
mf <- memoise(f)to create mf(), a memoised wrapper around f(). You can clear mf's
cache with
forget(mf)and you can test whether a function is memoised with
is.memoised(mf) # TRUE
is.memoised(f) # FALSEdevtools::install_github("hadley/memoise")
memoise also supports external caching in addition to the default in-memory caches.
cache_filesystem()allows caching using files on a local filesystem. You can point this to a shared file such as dropbox or google drive to share caches between systems.cache_s3()allows caching on Amazon S3
Use cache_s3() to cache objects using s3 storage. Requires you to specify
a bucket using cache_name. When creating buckets, they must be unique among
all s3 users when created.
Sys.setenv("AWS_ACCESS_KEY_ID" = "<access key>",
"AWS_SECRET_ACCESS_KEY" = "<access secret>")
mrunif <- memoise(runif, cache = cache_s3("<unique bucket name>"))
mrunif(10) # First run, saves cache
mrunif(10) # Loads cache, results should be identical
cache_filesystem can be used for a file system cache. This is useful for
preserving the cache between R sessions as well as sharing between systems
when using a shared or synced files system such as Dropbox or Google Drive.
fc <- cache_filesystem("~/.cache")
mrunif <- memoise(runif, cache = fc)
mrunif(20) # Results stored in local file
dbc <- cache_filesystem("~/Dropbox/.rcache")
mrunif <- memoise(runif, cache = dbc)
mrunif(20) # Results stored in Dropbox .rcache folder which will be synced between computers.
gdc <- cache_filesystem("~/Google Drive/.rcache")
mrunif <- memoise(runif, cache = gdc)
mrunif(20) # Results stored in Google Drive .rcache folder which will be synced between computers.