storr

Simple object cacher for R. storr acts as a very simple key-value store (supporting get/set/del for arbitrary R objects as data and as keys). The actual storage can be transient or persistent, local or distributed without changing the interface. To allow for distributed access, data is returned by content rather than simply by key (with a key/content lookup step) so that if another process changes the data, storr will retrieve the current version.

• Cached in-memory copies that might be faster to retrieve than on-disk/database copies
• Content-addressable storage, storing and retrieving potentially fewer copies of identical data (useful if lookup is slow or over a network) and to make the system somewhat robust in the face of multiple accessing processes
• Fetch from an external source (e.g. website) if a key is not found locally
• Pluggable storage backends - currently
  • environment (memory)
  • rds (disk)
  • Redis (http://redis.io) (via redux & RedisAPI)
  • rlite (via rrlite & RedisAPI)
• Future backends might include
  • git via git2r
  • leveldb via RcppLevelDB
  • dat

storr always goes back to the common storage (database, filesystem, whatever) for the current object -> hash mapping but when retrieving the data given a hash hash we can often do that without accessing the underlying storage. This means that repeated lookups happen quickly while still being able to reflect changes elsewhere.

Installation

From CRAN

install.packages("storr")

or install the development version with

devtools::install_github("richfitz/storr")

Documentation

storr comes with three vignettes:

• storr vignette("storr") outlines basic use and core implementation details.
• external vignette("external") shows how to use storr to cache external resources such as files, web resources, etc, using the storr_external object.
• drivers vignette("drivers") shows how to create new drivers for storr, illustrated by implementing a naive driver for DBI/SQLite.