Error when trying to deploy to shinyapps.io: Application depends on package "package" but it is not - r

My server.R contains the following code for dynamically installing packages when needed:
package <- input$chip
if (!require(package, character.only=T, quietly=T)) {
source("https://bioconductor.org/biocLite.R")
biocLite(package, ask = F, suppressUpdates = T, suppressAutoUpdate = T)
library(package, character.only=T)
}
ui.R has a select input element where the user can select one of the following bioconductor packages:
selectInput(inputId = 'chip', label='Chip', choices=c('Mouse Gene 1.0'='mogene10sttranscriptcluster.db',
'Mouse Gene 2.0'='mogene20sttranscriptcluster.db',
'Human Gene 1.0'='hugene10sttranscriptcluster.db',
'Human Genome U133A 2.0'='hgu133a2.db'))
So, based on what chip the user selects, the corresponding annotation package should get loaded, and if it is not already installed, it should install it.
This works on my local machine. But when I try to deploy my app on shinyapps.io. I get the following error:
Error:
* Application depends on package "package" but it is not installed. Please resolve before continuing.
I know that it is unable to recognize the package in biocLite(package, ask = F, suppressUpdates = T, suppressAutoUpdate = T). The deployment process thinks that package is a library name and not a variable and is unable to evaluate its value.
Is there any way to resolve this? Or do I have to explicitly load all required packages? The problem with explicitly loading the annotation packages is that these packages are so big they take up a lot of memory, which is why I wanted to load these packages only when required.
An alternative is to make an if-else loop or switch statement to install packages based on the condition:
package <- function(input$chip) {
switch(input$chip,
'mogene10sttranscriptcluster.db' = 'mogene10sttranscriptcluster.db',
'mogene20sttranscriptcluster.db' = 'mogene20sttranscriptcluster.db',
'hugene10sttranscriptcluster.db' = 'hugene10sttranscriptcluster.db',
'hgu133a2.db' = 'hgu133a2.db')
}
library(package)
But even in this case, the deployment process won't be able to evaluate the package value.
Thanks!
UPDATE:
Taking Yihui's suggestion, I modified my code to:
package <- input$genome
if(!do.call(require, list(package = package, character.only = T, quietly = T))){
do.call(biocLite, list(pkgs = package, ask = F, suppressUpdates = T, suppressAutoUpdate = T))
do.call(library, list(package = package, character.only = TRUE))
}
The application is able to deploy now, but it throws me this error:
Error: unable to install packages

Unfortunately, you have to fool the shinyapps (or rsconnect) package a bit so that it does not detect package as a literal package name. For example, you may use do.call():
do.call(library, list(package = package, character.only = TRUE))
The ShinyApps.io server does not allow you to install packages on the fly (strictly speaking, this is not true, but I don't want to show you how). You have to declare all packages you need in the app as dependencies beforehand. Again, it is a hack:
if (FALSE) {
library(mogene10sttranscriptcluster.db)
library(mogene20sttranscriptcluster.db)
library(hugene10sttranscriptcluster.db)
library(hgu133a2.db)
}
Then ShinyApps.io will detect these packages as dependencies and pre-install them for you. What you need to do in your app is simply load them, and you don't need to install them by yourself.

Related

How to manage dependencies with renv explicitly

I would prefer to have a config file and list the packages within it which are needed for the project, rather than relying on renv::init() to scrape the project and find all which I need (it often can't).
So my question is - how do I explicitly tell renv which packages are required for a project, an example would be appreciated.
The renv package does all sorts of fancy things: installing from several different locations, setting up a project-specific library so that you can control the versions for a project, etc. If you need that stuff, I think you're out of luck. As far as I can see it has no way to pass in a list of dependencies, it needs to scan your source to find them. I suppose you could include a function like
loadPackages <- function() {
requireNamespace("foo")
requireNamespace("bar")
...
}
to make it easier for renv to find your required packages, but if it's failing in some other way (e.g. you have incomplete files that don't parse properly), this won't help.
If you don't need all that fancy stuff, you could use the function below:
needsPackages <- function(pkgs, install = TRUE, update = FALSE,
load = FALSE, attach = FALSE) {
missing <- c()
for (p in pkgs) {
if (!nchar(system.file(package = p)))
missing <- c(missing, p)
}
if (length(missing)) {
missing <- unique(missing)
if (any(install)) {
toinstall <- intersect(missing, pkgs[install])
install.packages(toinstall)
for (p in missing)
if (!nchar(system.file(package = p)))
stop("Did not install: ", p)
} else
stop("Missing packages: ", paste(missing, collapse = ", "))
}
if (any(update))
update.packages(oldPkgs = pkgs[update], ask = FALSE, checkBuilt = TRUE)
for (p in pkgs[load])
loadNamespace(p)
for (p in pkgs[attach])
library(p, character.only = TRUE)
}
which is what I've used in one project. You call it as
needsPackages(c("foo", "bar"))
and it installs the missing ones. It can also update, load, or attach them. It's just using the standard function install.packages to install from CRAN,
no fancy selection of install locations, or maintenance of particular package versions. If you do use something simple like this, you should run sessionInfo() afterwards to record package version numbers, in case you need to return to the same state later. (Though returning to that state will probably be painful!)
There are two possible ways forward here:
Configure renv to use "explicit" snapshots, as described in https://rstudio.github.io/renv/reference/snapshot.html#snapshot-type -- this workflow requires that you list your package requirements in your DESCRIPTION file;
Manually use renv::init(bare = TRUE) + renv::install(<packages>) (or your own package installation functions) to install the packages you need for your project, building the list of <packages> from some separate source that you maintain.
If you have specific workflow that you wish renv would make possible, then you could consider filing a feature request at https://github.com/rstudio/renv/issues.

how to add new R packages in azure machine learning for time series anomaly detection

I am trying to find out time series anomaly detection in which i need to install new R packages. In this i m following https://github.com/business-science/anomalize site. In this i needed to install 2 packages: tidyverse and anomalize.
can anyone help me on installing package mentioned above as I am getting
error "package or namespace load failed for tidyverse"
Also while adding zip of tidyverse and anomalize do I need to add any other packages and dependencies in that as I am adding only those 2 packages thinking there r no other dependencies I needed for those 2?
you can see in code that I created R_Package.zip and put tidyverse.zip and anomalize.zip in that that
dataset1 <- maml.mapInputPort(1)
data.set <- data.frame(installed.packages())
#install.packages(“src/R_Package/tidyverse_1.2.1.zip”, lib = “.”,
repos = NULL, verbose = TRUE);
#library(tidyverse, lib.loc=”.”, verbose=TRUE);
install.packages("src/tidyverse.zip",lib=".",repos=NULL,verbose=TRUE)
library(R_package, lib.loc = ".", verbose=TRUE);
install.packages("src/anomalize.zip",lib=".",repos=NULL,verbose=TRUE)
library(R_package, lib.loc = ".", verbose=TRUE);
#success <- library("tidyverse", lib.loc = ".",
logical.return = TRUE, verbose = TRUE)
#library(tidyverse)
maml.mapOutputPort("dataset1");
Regarding the error message, notice that it may take some time for the installed packages to become actually available; quoting from Adding R Packages In Azure ML blog post:
Note: In one instance, we ran into an issue where the package was not
loaded into the workspace immediately. We had to wait about half an
hour before we could use the package. You may be running into this
issue as well if you see a message that looks something like this
and you’ve used the above method to check which packages are in your
workspace and the package in question appears on that list. If this is
the case, we suggest waiting a bit before running your experiment
again.
AFAIK yes, you also need to add the package dependencies; the SO thread Install R Packages in Azure ML contains some useful hints.

OS-independent way to select directory interactively in R

I would like users to be able to select a directory interactively in R. The solution needs to work on different platforms (at least on Linux, Windows and Mac machines that have a graphical desktop environment). And it needs to be robust enough to work on a variety of computers. I've run into problems with the variants I know of:
file.choose() unfortunately only works for files - It won't allow to select a directory. Other than this limitation, file.choose is a good example of the type of solution I'm looking for - it works across platforms and does not have external dependencies that may not be available on a particular computer.
choose.dir() Only works on Windows.
tk_choose.dir() from library(tcltk) was my preferred solution until recently. But I've had users report that this throws an error
log4cplus:ERROR No appenders could be found for logger (AdSyncNamespace).
log4cplus:ERROR Please initialize the log4cplus system properly.
which we tracked back to Autodesk360 software being installed, which for some reason interferes with tcltk. So this is not a suitable solution unless there is a fix for this. (the only solution I've found by googling is to uninstall Autodesk360, which won't be a solution for users who installed it because they actually use it).
This answer suggests the following as a possible alternative:
library(rJava)
library(rChoiceDialogs)
jchoose.dir()
But, as an example of the sort of thing that can go wrong with this, when I tried to install.packages("rJava") I got:
checking whether JNI programs can be compiled... configure: error:
Cannot compile a simple JNI program. See config.log for details.
Make sure you have Java Development Kit installed and correctly
registered in R. If in doubt, re-run "R CMD javareconf" as root.
ERROR: configuration failed for package ‘rJava’
* removing ‘/home/dominic/R/x86_64-pc-linux-gnu-library/3.3/rJava’ Warning in install.packages : installation of package ‘rJava’ had
non-zero exit status
I managed to fix this on my own machine (linux running openJDK) by installing the openjdk compiler using the linux package manager then running sudo R CMD javareconf. But I can't expect random users with varying levels of computer expertise to have to jump through hoops just so that they can select a directory. Even if they do manage to fix it, it will look bad when every other piece of software they use manages to open a directory-selection dialogue without any problems.
So my question: Is there a robust method that can reliably be expected to "just work" (like file.choose does for files), on a variety of platforms and makes no expectation of the end user being computer literate enough to solve these kinds of issues (such as incompatabilities with Autodesk360 or unresolved Java dependencies)?
In the time since posting this question and an earlier version of this answer, I've managed to test the various options that have been suggested on a range of computers. This process has converged on a fairly simple solution. The only cases I have found where tcltk::tk_choose.dir() fails due to conflicts are on Windows computers running Autodesk software. But on Windows, we have utils::choose.dir available instead. So the answer I am currently running with is:
choose_directory = function(caption = 'Select data directory') {
if (exists('utils::choose.dir')) {
choose.dir(caption = caption)
} else {
tk_choose.dir(caption = caption)
}
}
For completeness, I think it is useful to summarise some of the issues with other approaches and why they do not meet the criteria of being generally robust on a variety of platforms (including robustness against potentially unresolved external dependencies that can't be fixed from within R and that that may require administrator privileges and/or expertise to fix):
easycsv::choose_dir in Linux depends on zenity, which may not be available.
rstudioapi::selectDirectory requires that we are in RStudio Version greater than 1.1.287.
rChoiceDialogs::rchoose.dir requires not only that java runtime environment is installed, but also java compiler must be installed and configured correctly to work with rJava.
utils::menu does not work if the R function is run from the command line, rather than in an interactive session. Also on Linux X11 it frequently leaves an orphan window open after execution, which can't be readily closed.
gWidgets2::gfile has external dependency on either gtk2 or tcltk or Qt. Resolving these dependencies was found to be non-trivial in some cases.
Archived earlier version of this answer
Finally, an earlier version of this answer contained some longer code that tries out several possible solutions to find one that works. Although I have settled on the simple version above, I leave this version archived here in case it proves useful to someone else.
What it tries:
Check whether the function utils::choose.dir exists (will only be available on Windows). If so, use that
Check whether the user is working from within RStudio version 1.1.287 or greater. If so use the RStudio API.
Check if we can load the tcltk package and then open and close a tcltk window without throwing an error. If so, use tcltk.
Check whether we can load gWidgets2 and the RGtk2 widgets. If so, use gWidgets2. I don't try to load the tcltk widgets here, because if they worked, presumably we would already be using the tcltk package. I also do not try to load the Qt widgets, as they seem somewhat unmaintained and are not currently available on CRAN.
Check if we can load rJava and rChoiceDialogs. If so, use rChoiceDialogs.
If none of the above are successful, use a fallback position of requesting the directory name at the console.
Here's the longer version of the code:
# First a helper function to load packages, installing them first if necessary
# Returns logical value for whether successful
ensure_library = function (lib.name){
x = require(lib.name, quietly = TRUE, character.only = TRUE)
if (!x) {
install.packages(lib.name, dependencies = TRUE, quiet = TRUE)
x = require(lib.name, quietly = TRUE, character.only = TRUE)
}
x
}
select_directory_method = function() {
# Tries out a sequence of potential methods for selecting a directory to find one that works
# The fallback default method if nothing else works is to get user input from the console
if (!exists('.dir.method')){ # if we already established the best method, just use that
# otherwise lets try out some options to find the best one that works here
if (exists('utils::choose.dir')) {
.dir.method = 'choose.dir'
} else if (rstudioapi::isAvailable() & rstudioapi::getVersion() > '1.1.287') {
.dir.method = 'RStudioAPI'
ensure_library('rstudioapi')
} else if(ensure_library('tcltk') &
class(try({tt <- tktoplevel(); tkdestroy(tt)}, silent = TRUE)) != "try-error") {
.dir.method = 'tcltk'
} else if (ensure_library('gWidgets2') & ensure_library('RGtk2')) {
.dir.method = 'gWidgets2RGtk2'
} else if (ensure_library('rJava') & ensure_library('rChoiceDialogs')) {
.dir.method = 'rChoiceDialogs'
} else {
.dir.method = 'console'
}
assign('.dir.method', .dir.method, envir = .GlobalEnv) # remember the chosen method for later
}
return(.dir.method)
}
choose_directory = function(method = select_directory_method(), title = 'Select data directory') {
switch (method,
'choose.dir' = choose.dir(caption = title),
'RStudioAPI' = selectDirectory(caption = title),
'tcltk' = tk_choose.dir(caption = title),
'rChoiceDialogs' = rchoose.dir(caption = title),
'gWidgets2RGtk2' = gfile(type = 'selectdir', text = title),
readline('Please enter directory path: ')
)
}
Here is a simple directory navigation menu (using menu{utils}):
d=1
while(d != 0) {
a = getwd()
a = strsplit(a, "/")
a = unlist(a)
b = list.dirs(recursive = F, full.names = F)
c = paste("..", a[length(a) - 1], a[length(a)], sep = "/")
d = menu(c("..", b), title = c, graphics = T)
if(d==1){
e=paste(paste(a[1:(length(a)-1)],collapse = '/',sep = ''),'/',sep = '')
#print(e)
setwd(e)
}else{
e=paste(paste(a,collapse = '/',sep = ''),'/',b[d-1],sep='')
#print(e)
setwd(e)
}
}
Note: I did not (yet) test it under different systems. Here is what the documentation says:
If graphics = TRUE and a windowing system is available (Windows, macOS or X11 via Tcl/Tk) a listbox widget is used, otherwise a text menu. It is an error to use menu in a non-interactive session.
One limitation: The title = can only be a single line.
you can use the choose_dir function from easycsv.
it works on Windows, Linux and OSX
easycsv::choose_dir() # can be run without parameters to prompt a folder selection window
for some use cases a little trick might be to use dirname() around file.choose()
dir <- dirname(file.choose())
this will return the directory. It does however require at least one file to be present in the directory
Suggestion for adaption of choose_directory() as mentioned in my comment (06.09.2018 RFelber):
choose_directory <- function(ini_dir = getwd(),
method = select_directory_method(),
title = 'Select data directory') {
switch(method,
'choose.dir' = choose.dir(default = ini_dir, caption = title),
'RStudioAPI' = selectDirectory(path = ini_dir, caption = title),
'tcltk' = tk_choose.dir(default = ini_dir, caption = title),
'rChoiceDialogs' = rchoose.dir(default = ini_dir, caption = title),
'gWidgets2RGtk2' = gfile(type = 'selectdir', text = title, initial.dir = ini_dir),
readline('Please enter directory path: ')
)
}

Refreshing sysdata.rda after reinstalling R package

I'm developing a package in R (3.3.2) that has internal data. The data is added to ./R/sysdata.rda via
devtools::use_data(dataset, pkg = 'pkgName', internal = TRUE, overwrite = TRUE)
Within the package I've added and exported a simple function:
show.R
show = function() {
print(dataset)
)
I'm installing the package locally:
devtools::install(pkg = 'pkgName',
args = paste('--library=', installLocation, sep = ''),
reload = TRUE,
local = FALSE)
Finally, I can call show without problems:
library(pkgName, lib.loc = installLocation)
show()
# ...output as expected
I'm running into trouble when I change the data in sysdata.rda. No matter what I try the ONLY way I can get the new data to load from the installed package is on the initial library() load after I restart R.
I have tried:
detach('package:pkgName', unload = TRUE)
unloadNamespace(pkgName)
remove.packages(pkgName, lib = installLocation)
I have also confirmed that the data in the source location has updated:
load(sysdata.rda) # looks good
Where does internal sysdata get cached and how can I clear it or at least force a refresh?
You need to document and install the package in a clean R session for sysdata.rda to be properly refreshed.
Answering as I had the same problem just now and arrived at this page when looking for a solution.

Check if R package is installed then load library

Our R scripts are used on multiple users on multiple computers and hence there are deviations in which packages are installed on each computer. To ensure that each script works for all users I would like to define a function pkgLoad which will first test if the package is installed locally before loading the library with suppressed startup messages. Using Check for installed packages before running install.packages() as a guide, I tried
pkgLoad <- function(x)
{
if (!require(x,character.only = TRUE))
{
install.packages(x,dep=TRUE, repos='http://star-www.st-andrews.ac.uk/cran/')
if(!require(x,character.only = TRUE)) stop("Package not found")
}
#now load library and suppress warnings
suppressPackageStartupMessages(library(x))
library(x)
}
When I try to load ggplot2 using pkgLoad("ggplot2") I get the following error message in my terminal
Error in paste("package", package, sep = ":") :
object 'ggplot2' not found
> pkgLoad("ggplot2")
Loading required package: ggplot2
Error in library(x) : there is no package called ‘x’
> pkgLoad("ggplot2")
Error in library(x) : there is no package called ‘x’
Any why x changes from ggplot2 to plain old x?
I wrote this function the other day that I thought would be useful...
install_load <- function (package1, ...) {
# convert arguments to vector
packages <- c(package1, ...)
# start loop to determine if each package is installed
for(package in packages){
# if package is installed locally, load
if(package %in% rownames(installed.packages()))
do.call('library', list(package))
# if package is not installed locally, download, then load
else {
install.packages(package)
do.call("library", list(package))
}
}
}
The CRAN pacman package that I maintain can address this nicely. Using the following header (to ensure pacman is installed first) and then the p_load function will try to load the package and then get them from CRAN if R can't load the package.
if (!require("pacman")) install.packages("pacman"); library(pacman)
p_load(qdap, ggplot2, fakePackage, dplyr, tidyr)
Use library(x,character.only=TRUE). Also you don't need the last line as suppressPackageStartupMessages(library(x,character.only=TRUE)) already loads the package.
EDIT: #LarsKotthoff is right, you already load the package inside of the if brackets. There you already use option character.only=TRUE so everything is good if you just remove last to lines of your function body.
Have a look at this nice function:
klick
The following can be used:
check.and.install.Package<-function(package_name){
if(!package_name%in%installed.packages()){
install.packages(package_name)
}
}
check.and.install.Package("RTextTools")
check.and.install.Package("e1071")
Though #maloneypatr function works fine, but it is quite silent and does not respond on success of packages loaded. I built below function that does make some checks on user entry and also respond on the number of packages being successfully installed.
lubripack <- function(...,silent=FALSE){
#check names and run 'require' function over if the given package is installed
requirePkg<- function(pkg){if(length(setdiff(pkg,rownames(installed.packages())))==0)
require(pkg, quietly = TRUE,character.only = TRUE)
}
packages <- as.vector(unlist(list(...)))
if(!is.character(packages))stop("No numeric allowed! Input must contain package names to install and load")
if (length(setdiff(packages,rownames(installed.packages()))) > 0 )
install.packages(setdiff(packages,rownames(installed.packages())),
repos = c("https://cran.revolutionanalytics.com/", "http://owi.usgs.gov/R/"))
res<- unlist(sapply(packages, requirePkg))
if(silent == FALSE && !is.null(res)) {cat("\nBellow Packages Successfully Installed:\n\n")
print(res)
}
}
Note 1:
If silent = TRUE(all capital silent), it installs and loads packages without reporting. If silent = FALSE, it reports successful installation of packages. Default value is silent = FALSE
How to use
lubripack(“pkg1","pkg2",.,.,.,.,"pkg")
Example 1: When all packages are valid and mode is not silent
lubripack(“shiny","ggvis")
or
lubripack(“shiny","ggvis", silent = FALSE)
Output
Example 2: When all packages are valid and mode is silent
lubripack(“caret","ggvis","tm", silent = TRUE)
Output 2
Example 3: When package cannot be found
lubripack(“shiny","ggvis","invalidpkg", silent=FALSE)
Output 3
How to Install Package:
Run below code to download the package and install it from GitHub. No need to have GitHub Account.
library(devtools)
install_github("espanta/lubripack")

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