R.cache: Fast and Light-Weight Caching (Memoization) of Objects and Results to Speed Up Computations

Memoization can be used to speed up repetitive and computational expensive function calls. The first time a function that implements memoization is called the results are stored in a cache memory. The next time the function is called with the same set of parameters, the results are momentarily retrieved from the cache avoiding repeating the calculations. With this package, any R object can be cached in a key-value storage where the key can be an arbitrary set of R objects. The cache memory is persistent (on the file system).

Version: 0.12.0
Depends: R (≥ 2.5.0)
Imports: utils, R.methodsS3 (≥ 1.7.0), R.oo (≥ 1.19.0), R.utils (≥ 2.1.0), digest (≥ 0.6.8)
Published: 2015-11-12
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb at braju.com>
BugReports: https://github.com/HenrikBengtsson/R.cache/issues
License: LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2.1)]
URL: https://github.com/HenrikBengtsson/R.cache
NeedsCompilation: no
Materials: README NEWS
In views: ReproducibleResearch
CRAN checks: R.cache results


Reference manual: R.cache.pdf
Package source: R.cache_0.12.0.tar.gz
Windows binaries: r-devel: R.cache_0.12.0.zip, r-release: R.cache_0.12.0.zip, r-oldrel: R.cache_0.12.0.zip
OS X El Capitan binaries: r-release: R.cache_0.12.0.tgz
OS X Mavericks binaries: r-oldrel: R.cache_0.12.0.tgz
Old sources: R.cache archive

Reverse dependencies:

Reverse imports: aroma.affymetrix, aroma.cn, aroma.core, fulltext, PSCBS, R.filesets, R.rsp, repmis, scholar, stepR
Reverse suggests: ragtop


Please use the canonical form https://CRAN.R-project.org/package=R.cache to link to this page.