R and Rstudio Install, setup and Package Management

R
RStudio
Install
Rpackages
How to install and upgrade R and RStudio
Author

Marcelo Rosales

Published

March 24, 2023

Installing/Upgrading R and RStudio

References Pages to visit first:
Painless way to install a new version of R?
How to migrate Rstudio files and installed packages ( by version to a new computer )
An efficient way to install and load R packages
Loading packages: the difference between R’s library() and require() functions
Bioconductor
Install/Update R and R packages
restore all R packages after installing a new version of R?
How to Upgrade R Without Losing Your Packages
Upgrade R Without Losing Your Packages
Update and migrate R
Profiles package
Rprofile.site file example for Startup customization
Managing R with .Rprofile, .Renviron, Rprofile.site, Renviron.site, rsession.conf, and repos.conf
How to Create Directory and File If It doesn’t Exist in R

Trick for doing the upgrade, from installing the software to copying all the settings/packages over?First you install the new version, then run this in the old version:

Stack Overflow

Run in the old version of R

setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")

Followed by this in the new version:

Run in the new version

setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)

For windows

Using Installr

#From https://stackoverflow.com/questions/1401904/painless-way-to-install-a-new-version-of-r

# Run in the old version of R (or via RStudio)
setwd("C:/Temp/") 
packages <- installed.packages()[,"Package"] 
save(packages, file="Rpackages") 

# INSTALL NEW R VERSION
if(!require(installr)) { install.packages("installr"); require(installr)} #load / install+load installr
# See here for more on installr: https://www.r-statistics.com/2013/03/updating-r-from-r-on-windows-using-the-installr-package/  

# step by step functions:
check.for.updates.R() # tells you if there is a new version of R or not.
install.R() # download and run the latest R installer... This install.R seems to be a windows only command. 

# Install library - run in the new version of R. This calls package names and installs them from repos, thus all packages should be correct to the most recent version
setwd("C:/Temp/") 
load("Rpackages") 
for (p in setdiff(packages, installed.packages()[,"Package"])) 
install.packages(p) 

# Installr includes a package migration tool but this simply copies packages, it does not update them
copy.packages.between.libraries() # copy your packages to the newest R installation from the one version before it (if ask=T, it will ask you between which two versions to perform the copying)

R-bloglers

How to Upgrade R Without Losing Your Packages

  1. Before you upgrade, build a temp file with all of your old packages. Files saved as .rda files.
tmp <- installed.packages()
installedpkgs <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
save(installedpkgs, file="installed_old.rda")

  1. Install the new version of R and let it do it’s thing.

  2. Once you’ve got the new version up and running, reload the saved packages and re-install them from CRAN.

load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
install.packages(missing)
update.packages()

Note: If you had any packages from BioConductor, you can update those too!

#Update: 'biocLite' is not available for new versions of R

source("http://bioconductor.org/biocLite.R")
chooseBioCmirror()
biocLite()
load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
for (i in 1:length(missing)) biocLite(missing[i])
About bioLite package

Update: ‘biocLite’ is not available for new versions of R

install.packages("biocLite") # Warning in install.packages : package ‘biocLite’ is not available for this version of R

BiocLite is not a thing anymore, it was used in the old versions of Bioconductor to install packages, now you can directly use BiocManager::install().

For example:

BiocManager::install("limma")

Save files as csv or excel .xlsx

csv files

write.csv(data_frame, 'path/to/forder/and/file_name.csv') # or set wd and just type file_name.csv

excel files

Convert first to a data frame.

install.packages("writexl")
library("writexl")
the_dataframe_name <- as.data.frame(data)
write_xlsx(the_dataframe_name,"path/to/folder/and/file_name.xlsx")

Upgrading R on Windows and Mac

https://www.r-statistics.com/tag/installr/

Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code in Rgui:

install.packages("installr") # install 
setInternet2(TRUE) # only for R versions older than 3.3.0
installr::updateR() # updating R.
# If you wish it to go faster, run: installr::updateR(T)

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.). There is also a step by step tutorial (with screenshots) on how to upgrade R on Windows, using the installr package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).

Also chekck the video:

Mac

If you are using Mac you can easily upgrade to the latest version of R using Andrea Cirillo’s updateR package. The package is not on CRAN, so you’ll need to run the following code in Rgui:

install.packages("devtools")
devtools::install_github("AndreaCirilloAC/updateR")
updateR(admin_password = "PASSWORD") # Where "PASSWORD" stands for your system password

MBP15 The downloaded source packages are in “/private/var/folders/xc/rxn5vywj3lvd_qt78ss92cc80000gn/T/Rtmp8TJvA5/downloaded_packages” MBP20 The downloaded binary packages are in /var/folders/1v/nbx_5tgn553dq8s639lyln5c0000gn/T//Rtmp8AkWwy/downloaded_packages /private/var/folders/1v/nbx_5tgn553dq8s639lyln5c0000gn/T/RtmpP5nIXV/downloaded_packages

Option 1

Painless way to install a new version of R?

Files are .rda

#--run in the old version of R
setwd("C:/Temp/")
packages <- installed.packages()[,"Package"]
save(packages, file="Rpackages")

#--run in the new version
setwd("C:/Temp/")
load("Rpackages")
for (p in setdiff(packages, installed.packages()[,"Package"]))
install.packages(p)


#-----

# Just for completeness, you can save your packages in another directory on your computer.
install.packages("thepackage",lib="/path/to/directory/with/libraries")
#You can change the default .Library value using the function .libPaths too
.libPaths("/path/to/directory/with/libraries")

# -----

#Finally, You can also include a small code in my Rprofile.site allowing  to reinstall all packages when installing a new R version. You just have to list them up before you update to the new R version by using an .RData file containing an updated list with all packages.

library(utils)

## Check necessary packages
load("G:\Setinfo\R\packagelist.RData") # includes a vector "pkgs"
installed <- pkgs %in% installed.packages()[, 'Package']
if (length(pkgs[!installed]) >=1){
  install.packages(pkgs[!installed])
}
# I make the packagelist.RData by specifying .Last() in my Rprofile.site. This updates the package list if I installed some :

.Last <- function(){
  pkgs <- installed.packages()[,1]
  if (length(pkgs) > length(installed)){
    save(pkgs,file="G:\Setinfo\R\packagelist.RData")
  }
}

Option 2:
How to migrate Rstudio files and installed packages ( by version to a new computer )

Save as .csv files.
Or .xlsx files.

getwd()
setwd()
# /Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/file_name.csv  

installed <- as.data.frame(installed.packages())
write.csv(installed, 'installed_previously.csv') # Path/to/folder/installed_previously.csv 
installedPreviously <- read.csv('installed_previously.csv') # Path/to/folder/installed_previously.csv 
baseR <- as.data.frame(installed.packages())
toInstall <- setdiff(installedPreviously, baseR)

# the first thing to do would be to make sure that the set of currently installed packages is up-to-date. 

update.packages(checkBuilt=TRUE, ask=FALSE)  #check spelling of arguments
  new_pacs <- paste( setdiff( installedPreviously$Package, baseR$Package), 
                       collapse=",")
  install.packages( new_pacs, dependencies=TRUE)

# For excel files, requires: 
install.packages("writexl")
library("writexl")
write_xlsx(the_dataframe_name,"path/to/folder/file_name.xlsx")

An efficient way to istall and load R packages

An efficient way to install and load R packages

Inefficient way to install and load R packages:

# Installation of required packages
install.packages("tidyverse")
install.packages("ggplot2")
install.packages("readxl")
install.packages("dplyr")

# Load packages
library("tidyverse")
library("ggplot2")
library("readxl")
library("dplyr")

More efficient way

# Package names
packages <- c("ggplot2", "readxl", "dplyr", "tidyr", ...)

# Install packages not yet installed
installed_packages <- packages %in% rownames(installed.packages())
if (any(installed_packages == FALSE)) {
  install.packages(packages[!installed_packages])
}

# Packages loading
invisible(lapply(packages, library, character.only = TRUE))

Most efficient way

{pacman} package
After this article was published, a reader informed me about the {pacman} package. After having read the documentation and try it out myself, I learned that the function p_load() from {pacman} checks to see if a package is installed, if not it attempts to install the package and then loads it. It can also be applied to several packages at once, all this in a very condensed way:

install.packages("pacman")

pacman::p_load(ggplot2, tidyr, dplyr)

## Make sure your current packages are up to date
update.packages()
## devtools is required
library(devtools)
install_github("trinker/pacman")

Find more about this package on CRAN. Introduction to the pacman Package in R (3 Examples)

{librarian} package
Like {pacman}, the shelf() function from the {librarian} package automatically installs, updates, and loads R packages that are not yet installed in a single function. The function accepts packages from CRAN, GitHub, and Bioconductor (only if Bioconductor’s Biobase package is installed). The function also accepts multiple package entries, provided as a comma-separated list of unquoted names (so no “” around package names).

Biobase: Base functions for Bioconductor DOI: 10.18129/B9.bioc.Biobase
Installation:
To install this package, start R (version “4.2”) and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("Biobase")

Last but not least, the {librarian} package allows to load packages automatically at the start of every R session (thanks to the lib_startup() function) and search for new packages on CRAN by keywords or regular expressions (thanks to the browse_cran() function).

Here is an example of how to install missing packages and load them with the shelf() function:

# From CRAN:
install.packages("librarian")

librarian::shelf(ggplot2, DesiQuintans / desiderata, pander)

For CRAN packages, provide the package name as normal without “” and for GitHub packages, provide the username and package name separated by / (i.e., UserName/RepoName as shown for the desiderata package).

Find more about this package on CRAN.

Stack Overflow 2

Every time I upgrade R using homebrew I need to install most packages again

Before install:

1. Update all R packages

Ref: https://www.neonscience.org/resources/learning-hub/tutorials/packages-r

# list all packages where an update is available
old.packages()

# update all available packages
update.packages()

# update, without prompts for permission/clarification
update.packages(ask = FALSE)

# update only a specific package use install.packages()
install.packages("plotly")

2. Backup current package list.

tmp <- installed.packages()
installedpkgs <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
save(installedpkgs, file="installed_old.rda")

3. Backup your preferences file

# Copy a file
source_path <- "/Users/marcelorosales/.config/rstudio/rstudio-prefs.json"
destination_path <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/RS_preferences/"

file.copy(source_path, destination_path, overwrite = FALSE)

# If: [1] TRUE, file was copied
# If: [1] FALSE, file was not copied, error might be that the file already exists (change overwrite = TRUE, or paths not correct.)

# Check if the copy was successful. This does not really work. 
if (file.exists(destination_path)) {
  print("File copied successfully!")
} else {
  print("File copy failed.")
}

Another way to do it:

# identify the folders
source_path <- "/Users/marcelorosales/.config/rstudio/"
destination_path <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/RS_preferences/"
file <- "rstudio-prefs.json"

# find the files that you want

list.files(source_path)

list.of.files <- list.files(source_path, file)
list.of.files

# copy the files to the new folder
file.copy(list.of.files, destination_path)

Ref:
- https://fs.r-lib.org/reference/copy.html
- https://www.r-bloggers.com/2014/11/copying-files-with-r/
- https://r-lang.com/how-to-copy-a-file-in-r/***
- https://stat.ethz.ch/R-manual/R-devel/library/base/html/files.html

Install new version of R

brew upgrade r
brew upgrade rstudio

Reload packages from CRAN

load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
install.packages(missing)
update.packages()

Reload packages from BioConductor

# Update2022: 'biocLite' is not available for new versions of R

chooseBioCmirror()
biocLite()
load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
for (i in 1:length(missing)) biocLite(missing[i])

Location of the R packages

terminal
#| eval: false

# MBP15: The downloaded source packages are in:
open /private/var/folders/xc/rxn5vywj3lvd_qt78ss92cc80000gn/T/Rtmp8TJvA5/downloaded_packages 

# MBP20: The downloaded binary packages are in:
# old: open /private/var/folders/1v/nbx_5tgn553dq8s639lyln5c0000gn/T/Rtmp8AkWwy/downloaded_packages 
open /private/var/folders/1v/nbx_5tgn553dq8s639lyln5c0000gn/T/RtmpP5nIXV/downloaded_packages

Comparing files

To compare and find whether two files differ and where, there are a few packages.

library(tools)
md5sum("path/to/file1") == md5sum("path/to/file2")

library(diffobj)
diffFile("path/to/file1", "path/to/file2")   # or `diffChr` if you data is in R already

library(diffr)
diffr("path/to/file1", "path/to/file2")

ses(readLines("path/to/file1"), readLines("path/to/file1"))

packages <- installed.packages()
structure(packages)

Summary

recap core shell outline synopsis

Update 20230522

Saved installed packages

# Run in the old version of R

# ------
# 1. Before you upgrade, update all old packages.
# ------

# A. Update current packages.
update.packages(checkBuilt=TRUE, ask=FALSE)  #check spelling of arguments

# B. Upgrade packages of Bioconductor
# Install packages from a newer version of Bioconductor.
# https://www.bioconductor.org/install/ 

if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
BiocManager::install(version = "3.16") # Or the newest version

# ------
# 2. Before you upgrade: 1. build and save a file with all current packages (old packages) and 2. Backup your rstudio preferences files.  
# ------

# MBP15: setwd("/Users/Marcelo-Rosales/Box Sync/Github/RStudio_shared/R_packages/")
# MBP20: setwd("~/Box Sync/Github/RStudio_shared/R_packages/")

getwd()

# Variables for generic code:

## Create a new folder for packages files
new_folder <- "Rpkgs230522/" # <----------------change folder name here, don't forget the "/".
folder <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/"
dir.create(paste0(folder,new_folder)) #use paste0(), paste() inserts a space between obj.

## Create the packages list files
file_name <- "Rpkgs_MBP20_230522" # <------------change file name here.
rda <- ".rda"
csv <- ".csv"
df <- "_df"
xlsx <- ".xlsx"

file1 <- paste0(folder,new_folder,file_name) 
file2 <- paste0(folder,new_folder,file_name,rda)
file3 <- paste0(folder,new_folder,file_name,csv)
file4 <- paste0(folder,new_folder,file_name,df,csv)
file5 <- paste0(folder,new_folder,file_name,xlsx)

file1
file2
file3
file4
file5

# Generic code: I use this method because it is easy to change the names of the variables in one place once.

## No extension
Rpkgs <- installed.packages()[,"Package"] # This is a temp file. 
save(Rpkgs, file= file1) 
load(file1) # load as values (vector?)

## As .rda file
tmp <- installed.packages() # save in environment as data (dataframe?)
Rpkgs_rda<- as.vector(tmp[is.na(tmp[,"Priority"]), 1]) # save as vector package names.
save(Rpkgs_rda, file= file2)
load(file2)

## As .csv file requires a dataframe.  
### 1. Only the Package column variable (as vector?), or 2. as full csv data frame.  
Rpkgs_csv <- installed.packages()[,"Package"] 
Rpkgs_df <- as.data.frame(installed.packages()) 
write.csv(Rpkgs_csv, file= file3)
write.csv(Rpkgs_df, file= file4)

## As as excel files also requires a dataframe (df)
### install.packages("writexl")
library("writexl")
Rpkgs_df <- as.data.frame(installed.packages()) # same as in df_csv
write_xlsx(Rpkgs_df, file5)



# Specific code: I do not use this method because requires changing the name of the folder and file in each instance, and paths are also troublesome.

Rpkgs_MBP20_230329 <- installed.packages()[,"Package"] # save as vector values?
save(Rpkgs_MBP20_230329, file="/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329") # Or Rpkgs_MBP20_230329.rda
load("/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329.rda") # load as values (vector?)

## As .rda file
Rpkgs_MBP20_230329 <- as.vector(tmp[is.na(tmp[,"Priority"]), 1]) # save as vector package names.
save(Rpkgs_MBP20_230329, file="/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329.rda") # save as vector .rda; names... environment: installedpkgs, file: installed_old.rda, but when loaded in environment is back to installedpkgs.  
load("/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/installed_old.rda") # In environment is back to installedpkgs.  

## Save as csv requires a dataframe (df)
Rpkgs_MBP20_230329 <- installed.packages()[,"Package"] # save only the Package (name) variable as vector values?, still can be save as csv
write.csv(Rpkgs_MBP20_230329, '/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329.csv')

## Or df with all the info of packages
Rpkgs_MBP20_230329df1 <- as.data.frame(installed.packages())
write.csv(Rpkgs_MBP20_230329df1, '/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329df1.csv')

# As excel file also requires a dataframe (df)
# install.packages("writexl")
library("writexl")
write_xlsx(Rpkgs_MBP20_230329df1,"/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329df1.xlsx")


# Copy/Paste Rstudio global settings and preferences (~/.config/rstudio/rstudio-prefs.json)

## Open folder 
folder_path <- "~/.config/rstudio/"  # seems like "~/path" does not work on rstudio. 
folder_path <- "/Users/marcelorosales/.config/rstudio/"

system(paste("open", shQuote(folder_path)))

## Copy a file (direct).
source_path <- "/Users/marcelorosales/.config/rstudio/rstudio-prefs.json"
destination_path <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/RS_preferences/"

file.copy(source_path, destination_path, overwrite = FALSE)

## Copy a file (indirect). Find the file(s) first.
file <- "rstudio-prefs.json"

list.files(folder_path) # list all files in folder
find.files <- list.files(folder_path, file) # select a specific file
find.files

## copy the files to the new folder
file.copy(find.files, destination_path, overwrite = FALSE)

# If: [1] TRUE, file was copied
# If: [1] FALSE, file was not copied, error might be that the file already exists (change overwrite = TRUE, or paths not correct.)
# Another way to do it, see Stack overflow 2 section. 

# Check if the copy was successful (THis code does not work properly, is )

if (file.exists(paste0(destination_path, file))) {
  print("File copied successfully!")
} else {
  print("File copy failed.")
}


# ------
# 3. Install the new version of R (use homebrew). See Brew cask upgrade below.
# ------

#　4. Once the new version up and running, reload the saved packages and re-install them from CRAN.

# run in the new version
# MBP20: setwd("/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/")

load("/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230329/Rpkgs_MBP20_230329.rda")  

for (p in setdiff(RSpacks230324MBP15, installed.packages()[,"Package"]))
  install.packages(p)

Copy/Paste Rstudio global settings and preferences if necessary.

Terminal
#| eval: false

# Copy/Paste Rstudio global settings and preferences.. 
open ~/.config/rstudio

# Search and Copy file to same place as packages files. 
rstudio-prefs.json
open ~/.config/rstudio
# Open folder 
folder_path <- "~/.config/rstudio/"  # seems like "~/path" does not work on rstudio. 
folder_path <- "/Users/marcelorosales/.config/rstudio/"  

system(paste("open", shQuote(folder_path)))

# Copy a file
source_path <- "/Users/marcelorosales/.config/rstudio/rstudio-prefs.json"
destination_path <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/RS_preferences/"

file.copy(source_path, destination_path)


# Check if the copy was successful
if (file.exists(destination_path)) {
  print("File copied successfully!")
} else {
  print("File copy failed.")
}

Brew cask upgrade R and Rstudio.

Terminal
# Upgrade R and rstudio
brew update
brew upgrade --cask r
# password
#`brew cleanup` has not been run in the last 30 days, running now...

# Upgrade RStudio
brew upgrade --cask rstudio

# Copy paste the `rstudio-prefs.json` if needed, usually it still remains after upgrade. 
rstudio-prefs.json

Errors and trouble shooting.

non-UTF8 locale error in R

WARNING: You’re using a non-UTF8 locale

When opening R new version… an error message is displayed.

error message
#| code-block-bg: false
#| code-block-border-left: "#31BAE9"
#| eval: false

During startup - Warning messages:
1: Setting LC_CTYPE failed, using "C" 
2: Setting LC_COLLATE failed, using "C" 
3: Setting LC_TIME failed, using "C" 
4: Setting LC_MESSAGES failed, using "C" 
5: Setting LC_MONETARY failed, using "C" 
[R.app GUI 1.79 (8198) x86_64-apple-darwin17.0]

WARNING: You're using a non-UTF8 locale, therefore only ASCII characters will work.
Please read R for Mac OS X FAQ (see Help) section 9 and adjust your system preferences accordingly.

A solution: For english:
- Installing R on Mac - Warning messages: Setting LC_CTYPE failed, using “C”
- For Japanese:.

Terminal
defaults write org.R-project.R force.LANG en_US.UTF-8  # 英語表示
defaults write org.R-project.R force.LANG ja_JP.UTF-8  # 日本語表示

There is already an App… (legacy)

Error: It seems there is already an App at ‘/Applications/Rstudio’
is it possible to override the legacy app when install using brew

Some times is not possible to install, re-intall or upgrade a program via brew because first installation was made manually (downloaded zip or tar files).
This leaves a “legacy” app. To fix it use the --force attribute while installing

brew install --cask rstudio --force

Other relevant files

how to find out R library location in Mac OSX?

With .Library you get your default library location With .libPaths(“your/path”) you can also get/set you library trees (see ?.libPaths) and with getwd() resp. setwd(“your/path”) you get/set your working-directory

.Library  
.libPaths()

Loading packages: the difference between R’s library() and require() functions{target= “_blank”}

Shell

# Run in the old version of 

# ===== Before upgrade =====

# ------1. Update all old packages ----------

# Check R version or session info.
R.Version()  
sessionInfo()

# A. Update current packages.
update.packages(checkBuilt=TRUE, ask=FALSE)  #check spelling of arguments
## 20230608: The downloaded binary packages are in:  /var/folders/1v/nbx_5tgn553dq8s639lyln5c0000gn/T//Rtmpt7WwKz/downloaded_packages

# B. Upgrade packages of Bioconductor
# Install packages from a newer version of Bioconductor https://www.bioconductor.org/install/ 
if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
# BiocManager::install(version = "3.17") # Or the newest version
BiocManager::install("Biobase")
BiocManager::install("BiocGenerics")

# if error,  re-install: 'Biobase'Old packages: 'learnr'
install.packages("learnr")

# ------ 2. Save backup of old packages and preferences ----
# 2. Before you upgrade: 1. build and save a file with all current packages (old packages) and 2. Backup your rstudio preferences files.  

# ---- 2.1 Variables / info ----
# Run paths and pc`s info
# ~/path/to/folder "~" doesn't work?

pdir <- "/Box Sync/Github/RStudio_shared/R_packages/" # Path to directory
pth15 <- "/Users/Marcelo-Rosales" # MBP15
pth20 <- "/Users/marcelorosales"  # MBP20
pc15 <- "MBP15"
pc20 <- "MBP20"

p15 <- paste0(pth15,pdir)  # MBP15 destination folder
p20 <- paste0(pth20,pdir)  # MBP20 destination folder

rpref <- "/.config/rstudio/rstudio-prefs.json" # ~ Location of preferences.json
# rprefd <- "/Box Sync/Github/RStudio_shared/RS_preferences/" # destination folder
pref15 <- paste0(pth15,rpref)
pref20 <- paste0(pth20,rpref)

# Run paths and pc`s info
#--- 2.2 Variables manual imput ----
library(stringr)
Sys.Date()
Sys.time()
gsub("-","",Sys.Date())
str_sub(gsub("-","",Sys.Date()), 3, -1) # https://youtu.be/343VCX3ynOA

date <- "230608"   # <--------------------- change date (file name) here (manual).
date <- str_sub(gsub("-","",Sys.Date()), 3, -1)   # date auto.
folder <- p20      # <--------------------- change destination folder (path) here.
pc <- pc20         # <--------------------- change PC (device name) here.
rs_pref <- pref20  # <--------------------- change r prefs location here.

new_folder <- paste0("Rpkgs",date,"/")   
file_name <- paste0("Rpkgs_",pc,"_",date)   
rda <- ".rda"
csv <- ".csv"
df <- "_df"
xlsx <- ".xlsx"

rpref.json <- paste0("rstudio-prefs_", pc,"_", date, ".json") # .json file name
source_path <- paste0(rs_pref)
destination_path <- paste0(folder,new_folder,rpref.json)  # Place after the creation of the folder var.


system(paste("open", shQuote(folder)))


## Check Destination folder
date
folder
new_folder
file_name
pc
rs_pref

## Create a new folder for packages files... use paste0(), paste() inserts a space between obj.
dir.create(paste0(folder,new_folder)) 

## Create file names (only), extensions and path to folder. 
file1 <- paste0(folder,new_folder,file_name) 
file.rda <- paste0(folder,new_folder,file_name,rda)
file.csv <- paste0(folder,new_folder,file_name,csv)
file.csv2 <- paste0(folder,new_folder,file_name,df,csv)
file.xlsx <- paste0(folder,new_folder,file_name,xlsx)

file1
file.rda
file.csv
file.csv2
file.xlsx

#--------- 2.3 Create files ----------

# Ways to create and save Packages (old Rpkgs)
tmp <- installed.packages()                         # <--- Matrix
temp2 <- installed.packages()[,"Package"]           # <--- Vector
temp3 <- as.vector(tmp[is.na(tmp[,"Priority"]), 1]) # <--- Vector
temp4 <- as.data.frame(installed.packages())        # <--- Dataframe
temp5 <- as.data.frame(installed.packages()[,"Package"])

# Which script to use?...
# 1.  
as.vector(tmp[is.na(tmp[,"Priority"]), 1]) # Is currently the most common script.
# a) is.na(tmp[,"Priority"]) checks for missing or NA (Not Available) values in the "Priority" column. Returns a logical "vector" where TRUE = NA values and FALSE = non-NA values.
# b) It will return only NA rows. 
# b) Non-NA rows are the default installed packages at clean/new start of program. 
# c) Is NOT very good for comparing files good.

# 2. 
as.data.frame(installed.packages()[,"Package"]) # Vector of only the packages column
# a) It will return a df of only the packages column, but will include all packages
# b) DF can be saved as csv files, very easy to compare with VS code "File: Compare..."


#=====2.3.1 PASTE FILE NAME!!! to each file type.====
print(file_name)
# [1] "Rpkgs_MBP15_230612" <-----------------------------Copy/Paste from console.

## No extension
Rpkgs_MBP20_230612 <- installed.packages()[,"Package"] # This is a temp file. 
save(Rpkgs_MBP20_230612, file= file1) 

## As .rda file
tmp <- installed.packages() # save in environment as data (dataframe?)
Rpkgs_MBP20_230612_rda<- as.vector(tmp[is.na(tmp[,"Priority"]), 1]) # save as vector package names.
save(Rpkgs_MBP20_230612_rda, file= file.rda)

tmp2 <- as.vector(installed.packages()[,"Package"])
tmp3 <- as.data.frame(installed.packages()[,"Package"])


## As .csv file requires a dataframe.  
### 1. Only the Package column variable (as vector?), or 2. as full csv data frame.  
Rpkgs_MBP20_230612_csv <- installed.packages()[,"Package"] 
Rpkgs_MBP20_230612_df <- as.data.frame(installed.packages()) 
write.csv(Rpkgs_MBP20_230612_csv, file= file.csv)
write.csv(Rpkgs_MBP20_230612_df, file= file.csv2)

## As as excel files also requires a dataframe (df)
### install.packages("writexl")
library("writexl")
Rpkgs_MBP20_230612_df <- as.data.frame(installed.packages()) # same as in df_csv
write_xlsx(Rpkgs_MBP20_230612_df, file.xlsx)

# Copy/Paste Rstudio global settings and preferences (~/.config/rstudio/rstudio-prefs.json)

## Open folder 
folder
new_folder
system(paste("open", shQuote(folder))) # seems like "~/path" does not work on rstudio. 
system(paste("open", shQuote(paste0(folder, new_folder))))

## Copy a file (direct).

file.copy(source_path, destination_path, overwrite = FALSE) # overwrites old file.

# If: [1] TRUE, file was copied
# If: [1] FALSE, file was not copied, error might be that the file already exists (change overwrite = TRUE, or paths not correct.)
# Another way to do it, see Stack overflow 2 section. 

# ------ 3. Install the new version of R (use homebrew).------

# Close R and Rstudio!! RUN in terminal better.

# {bash filename="Terminal"}
#| eval: false 

# Upgrade R and rstudio
brew update
brew upgrade --cask r
brew reinstall --cask r  

system("brew update")
system("brew update", intern = TRUE) # Setting intern = TRUE captures the output of the command and returns it as a character vector in R. 
# password
#`brew cleanup` has not been run in the last 30 days, running now...

# Upgrade RStudio
brew upgrade --cask rstudio

# ------ After upgrade -----

# 4. Once the new version up and running, reload the saved packages and re-install them from CRAN

# run in the new version/device

#--- 4. Reload Variables and files ------

pdir <- "/Box Sync/Github/RStudio_shared/R_packages/" # Path to directory
pth15 <- "/Users/Marcelo-Rosales" # MBP15
pth20 <- "/Users/marcelorosales"  # MBP20
pc15 <- "MBP15"
pc20 <- "MBP20"

p15 <- paste0(pth15,pdir)  # MBP15 destination folder
p20 <- paste0(pth20,pdir)  # MBP20 destination folder

rpref <- "/.config/rstudio/rstudio-prefs.json" # ~ Location of preferences.json
# rprefd <- "/Box Sync/Github/RStudio_shared/RS_preferences/" # destination folder
pref15 <- paste0(pth15,rpref)
pref20 <- paste0(pth20,rpref)

# Run paths and pc`s info
## Variables:
date <- "230609"   # <--------------------- change date (file name) here.
date <- str_sub(gsub("-","",Sys.Date()), 3, -1)   # date auto.
folder <- p20      # <--------------------- change destination folder (path) here.
pc <- pc20         # <--------------------- change PC (device name) here.
rs_pref <- pref20  # <--------------------- change r prefs location here.

new_folder <- paste0("Rpkgs",date,"/")   
file_name <- paste0("Rpkgs_",pc,"_",date)   
rda <- ".rda"
csv <- ".csv"
df <- "_df"
xlsx <- ".xlsx"

rpref.json <- paste0("rstudio-prefs_", pc,"_", date, ".json") # .json file name
source_path <- paste0(rs_pref)
destination_path <- paste0(folder,new_folder,rpref.json)  # Place after the creation of the folder var.

# file1 <- paste0(folder,new_folder,file_name) 
file.rda <- paste0(folder,new_folder,file_name,rda)
# file.csv <- paste0(folder,new_folder,file_name,csv)
# file.csv2 <- paste0(folder,new_folder,file_name,df,csv)
# file.xlsx <- paste0(folder,new_folder,file_name,xlsx)

# file1
file.rda
# file.csv
# file.csv2
# file.xlsx

#---- 5. Load old packages list ------

system(paste("open", shQuote(folder)))

#---- 5.1 "new" (base) vs "old" (backup) pkgs differences installation----

#load(installedpkgs_old)

file.rda
file_name_rda <- paste0(file_name,"_rda")
file_name_rda

load(file.rda) # will load as Rpkgs_MBP20_230612_rda

installedpkgs_old <- Rpkgs_MBP20_230612_rda # .rda

tmp <- installed.packages()
installedpkgs_new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs_old, installedpkgs_new)
missing
install.packages(missing)
update.packages()


#------ 5.2 "pc1" vs "pc2" pkgs differences install ----

file.rda　# pc1.
load(file.rda) # will load as Rpkgs_MBP20_230612_rda

pc2 <- "/Users/marcelorosales/Box Sync/Github/RStudio_shared/R_packages/Rpkgs230612/Rpkgs_MBP15_230612.rda"
load(pc2) # will load as Rpkgs_MBP15_230612_rda

missing2 <- setdiff(Rpkgs_MBP20_230612_rda, Rpkgs_MBP15_230612_rda)
missing2
# [1] "Biobase"      "BiocGenerics"

rm(Rpkgs_MBP15_230612_rda)
rm(Rpkgs_MBP20_230612_rda)


#----- 5.3 Install "Bioconductor" packages -----

## Packages from Bioconductor (before or after Rpackages install?)
## Install packages from a newer version of Bioconductor https://www.bioconductor.org/install/
if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
# BiocManager::install(version = "3.17") # Or the newest version
BiocManager::install("Biobase")
BiocManager::install("BiocGenerics")

# if error,  re-install: 'Biobase'Old packages: 'learnr'
install.packages("learnr")


#----- 5.4 Install packages short code

# for (p in setdiff(installedpkgs_old, installed.packages()[,"Package"]))
#   install.packages(p)




#-----6. Compare csv files -----

# 6.1 Open csv files in VS code
path_csv <- paste0(p20, new_folder)
system(paste("open", shQuote(path_csv)))

# Select csv for pc1 and pc2 > drag to VS code icon > ....[]... will open in VS code
# In VS code: Select pc1 > cmd + p ...[]... > File: Compare Active File With...


# ------ 7. copy paste preferences. -------