How to list and remove lazyData of R package? - r

Question

I want to write a package with internal data, and my method is discribe here
My DESCRIPTION file is:
Package: cancerProfile
Title: A collection of data sets of cancer
Version: 0.1
Authors#R: person("NavyCheng", email = "navycheng2020#gmail.com", role = c("aut", "cre"))
Description: This package contain some data sets of cancers, such as RNA-seq data, TF bind data and so on.
Depends: R (>= 3.4.0)
License: What license is it under?
Encoding: UTF-8
LazyData: true
and my project is like this:
cancerProfile.Rproj
NAMESPACE
LICENSE
DESCRIPTION
R/
data/
|-- prad.rna.count.rda
Then I install my package and load it:
> library(pryr)
> library(devtools)
> install_github('hcyvan/cancerProfile')
> library(cancerProfile)
> mem_used()
82.2 MB
> invisible(prad.rna.count)
> mem_used()
356 MB
> ls()
character(0)
> prad.rna.count[1:3,1:3]
TCGA.2A.A8VL.01A TCGA.2A.A8VO.01A TCGA.2A.A8VT.01A
ENSG00000000003.13 2867 1667 3140
ENSG00000000005.5 6 0 0
ENSG00000000419.11 1354 888 1767
> rm(prad.rna.count)
Warning message:
In rm(prad.rna.count) : object 'prad.rna.count' not found
My question is why I can't 'ls' and 'rm' prad.rna.count and how can I don this?

Answer 1

In your case you couldn't ls() or rm() the dataset because you never put it in your global environment. Consider the following:
# devtools::install_github("hcyvan/cancerProfile")
library(cancerProfile)
library(pryr)
mem_used()
#> 31.8 MB
data(prad.rna.count)
mem_used()
#> 32.2 MB
ls()
#> [1] "prad.rna.count"
prad.rna.count[1:3,1:3]
#> TCGA.2A.A8VL.01A TCGA.2A.A8VO.01A TCGA.2A.A8VT.01A
#> ENSG00000000003.13 2867 1667 3140
#> ENSG00000000005.5 6 0 0
#> ENSG00000000419.11 1354 888 1767
mem_used()
#> 305 MB
rm(prad.rna.count)
ls()
#> character(0)
mem_used()
#> 32.5 MB
Created on 2019-01-15 by the reprex package (v0.2.1)
Since I used data() rather than invisible(), I actually put the data into the global environment, allowing me to see it via ls() and remove it via rm(). The way I loaded the data (data()) didn't increase memory usage because it just returns a promise, but when I evaluated the promise via prad.rna.count[1:3,1:3], the memory usage shot up. Luckily, since I had a name pointing to the object by using data() rather than invisible(), when I used rm(prad.rna.count), R recognized there was no longer a name pointing to that object and released the memory. I'd check out http://adv-r.had.co.nz/memory.html#gc and http://r-pkgs.had.co.nz/data.html#data-data for more details.