
Compute/Visualize Drive Space Consumption of Your Installed R Packages
The fs
package makes it super quick and easy to find out just how much “package hoarding” you’ve been doing:
library(fs)
library(ggalt) # devtools::install_github("hrbrmstr/ggalt")
library(igraph)
library(ggraph) # devtools::install_github("thomasp85/igraph")
library(hrbrthemes) # devtools::install_github("hrbrmstr/hrbrthemes")
library(tidyverse)
installed.packages() %>%
as_data_frame() %>%
mutate(pkg_dir = sprintf("%s/%s", LibPath, Package)) %>%
select(pkg_dir) %>%
mutate(pkg_dir_size = map_dbl(pkg_dir, ~{
fs::dir_info(.x, all=TRUE, recursive=TRUE) %>%
summarise(tot_dir_size = sum(size)) %>%
pull(tot_dir_size)
})) %>%
summarise(
total_size_of_all_installed_packages=ggalt::Gb(sum(pkg_dir_size))
) %>%
unlist()
## total_size_of_all_installed_packages
## "1.6 Gb"
While you can modify the above and peruse the list of packages/directories in tabular format or programmatically, you can also do a bit more work to get a visual overview of package size (click/tap the image for a larger view):
installed.packages() %>%
as_data_frame() %>%
mutate(pkg_dir = sprintf("%s/%s", LibPath, Package)) %>%
mutate(dir_info = map(pkg_dir, fs::dir_info, all=TRUE, recursive=TRUE)) %>%
mutate(dir_size = map_dbl(dir_info, ~sum(.x$size))) -> xdf
select(xdf, Package, dir_size) %>%
mutate(grp = "ROOT") %>%
add_row(grp = "ROOT", Package="ROOT", dir_size=0) %>%
select(grp, Package, dir_size) %>%
arrange(desc(dir_size)) -> gdf
select(gdf, -grp) %>%
mutate(lab = sprintf("%s\n(%s)", Package, ggalt::Mb(dir_size))) %>%
mutate(lab = ifelse(dir_size > 1500000, lab, "")) -> vdf
g <- graph_from_data_frame(gdf, vertices=vdf)
ggraph(g, "treemap", weight=dir_size) +
geom_node_tile(fill="lightslategray", size=0.25) +
geom_text(
aes(x, y, label=lab, size=dir_size),
color="#cccccc", family=font_ps, lineheight=0.875
) +
scale_x_reverse(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0)) +
scale_size_continuous(trans="sqrt", range = c(0.5, 8)) +
ggraph::theme_graph(base_family = font_ps) +
theme(legend.position="none")
Challenge
Do some wrangling with the above data and turn it into a package “disk explorer” with @timelyportfolio’s d3treeR
package.
*** This is a Security Bloggers Network syndicated blog from rud.is authored by hrbrmstr. Read the original post at: https://rud.is/b/2018/04/01/compute-visualize-drive-space-consumption-of-your-installed-r-packages/