This R package offers a minimal approach to cache R objects. It is offers similar functions to rlang::hash(), cachem::cache_mem(), and cachem::cache_disk().

The usage is quite elemental. While this package was create to cache summary tables obtained from large 'SQL' tables, it works with arbitrary R objects, such as linear models.

Here is an example of how to cache results for an lm() output:

library(tinycache)
fit_model <- function(n, cache) {
  key <- hash(n)
  cached <- cache$get(key)
  if (!is.key_missing(cached)) {
    return(cached)
  }
  set.seed(123)
  mydata <- data.frame(x = seq_len(n), y = seq_len(n) * 2 + rnorm(n))
  mycoef <- coef(lm(y ~ x, data = mydata))
  cache$set(key, mycoef)
  mycoef
}
cache <- dcache(dir = tempdir())
fit_model(5e7, cache) # computed and cached
fit_model(5e7, cache) # reused from disk, no recomputation
cache <- mcache()
fit_model(5e7, cache) # computed and cached
fit_model(5e7, cache) # reused from memory, no recomputation

How to check that it works:

cache <- mcache()
# 1st run
system.time(fit_model(5e7, cache))
# > system.time(fit_model(5e7, cache))
#    user  system elapsed 
#  10.088   1.289   8.278
# 2nd run
system.time(fit_model(5e7, cache))
# > system.time(fit_model(5e7, cache))
#    user  system elapsed 
#   0.000   0.000   0.001