README.md

In slagtermaarten/serializer: serializeR, automatically cache results of statement if required and read from cache if possible

serializeR

Wrapper around existing serialization infrastructure in R (writeRDS) that obviates typical associated boilerplate code. This project is premeaturely published, so use at your own risk and convenience. I'm considering a migration to an OOP design using R's reference classes.

Usage example

First create a serializer function

serializer <- gen_serializer()

The cache folder is set to saved-objects in the current working directory of the R session by default.

Example of a long running function whose results you would want to store to save future CPU time

longComputingFunc <- function() {
  # Wait 2 seconds
  Sys.sleep(2)
  return("return value")
}
a <- longComputingFunc()

The first time you run this, the function call will be evaluated. The second time, the evaluated expression in the right hand side of the assignment will have been stored on disk using saveRDS and will be assigned to a

serializer(a <- longComputingFunc())
print(a)
# [1] "return value"

Remove the value to illustrate starting out a new session with regards to a

rm(a)

This time the RHS of the assignment will be read from memory

serializer(a <- longComputingFunc())
print(a)
# [1] "return value"

To remove a stored object - for instance because the upstream code has changed and you want this to be reflected in the object - you can do the following:

clear_object(a)
# alternative
clear_object(a <- longComputingFunc())

The inclusion of this functionality in the serializeR package illustrates the difference between serializeR and knitR caching. Unlike in knitR caching, upstream code changes will not break the stored result but rather only variable name change on the LHS of assignments will accomplish this. For my own purposes, this is a great time saver as I often make small stylistic changes to long running code that I know will not affect the returned value. Be mindful of this difference and do use knitr caching if you would rather always be on the safe side!

To clear all objects and remove the cache folder in its entirety

clear_all_objects()

Known issues

Data.table objects don't like to be wrapped using the functionality in this package, YMMV.

slagtermaarten/serializer documentation built on May 30, 2019, 3:04 a.m.