colinfay/memoise

Easy memoisation for R

memoise

Memoization

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)  # FALSE

Installation

devtools::install_github("r-lib/memoise")

External Caches

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
• cache_gcs() allows caching on Google Cloud Storage
• cache_mongo() allows caching on MongoDB GridFS

AWS 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

Filesystem

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.

Google Cloud Storage

cache_gcs saves the cache to Google Cloud Storage. It requires you to authenticate by downloading a JSON authentication file, and specifying a pre-made bucket:

library(googleCloudStorageR)
# Set GCS credentials.
Sys.setenv("GCS_AUTH_FILE"="<google-service-json>",
           "GCS_DEFAULT_BUCKET"="unique-bucket-name")

gcs <- cache_gcs()
mrunif <- memoise(runif, cache = gcs)
mrunif(10) # First run, saves cache
mrunif(10) # Loads cache, results should be identical

Mongo GridFS

cache_mongo() allows to store cache on a MongoDB back-end, using the GridFS API. You will first need to create a connection using mongolite::gridfs()

library(mongolite)
mongo_grid <- gridfs(
  db = "memoize",
  prefix = "memoize"
)

mong <- cache_mongo(mongo_grid)
mem_runif <- memoise(runif, cache = mong)

mrunif(10) # First run, saves cache
mrunif(10) # Loads cache, results should be identical