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.
Related
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.
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: ')
)
}
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.
I tried to use get_rollit_source from the RcppRoll package as follows:
library(RcppRoll)
get_rollit_source(roll_max,edit=TRUE,RStudio=TRUE)
I get an error:
Error in get("outFile", envir = environment(fun)) :
object 'outFile' not found
I tried
outFile="C:/myDir/Test.cpp"
get_rollit_source(roll_max,edit=TRUE,RStudio=FALSE,outFile=outFile)
I get an error:
Error in get_rollit_source(roll_max, edit = TRUE, RStudio = FALSE, outFile = outFile) :
File does not exist!
How can fix this issue?
I noticed that the RcppRoll folder in the R library doesn't contain any src directory. Should I download it?
get_rollit_source only works for 'custom' functions. For things baked into the package, you could just download + read the source code (you can download the source tarball here, or go to the GitHub repo).
Anyway, something like the following should work:
rolling_sqsum <- rollit(final_trans = "x * x")
get_rollit_source(rolling_sqsum)
(I wrote this package quite a while back when I was still learning R / Rcpp so there are definitely some rough edges...)
For a corporate environment, I want our R users to use our local repository only. I have made corresponding required changes to Rprofile.site, .Rprofile, and repositories files as suggested by other posts and it works fine for changing the repository option only to the local one. However, a user is still able to select a CRAN mirror by selecting "Set CRAN Mirror" from the menu or by running "chooseCRANmirror()" command and when she does either of these, it will add standard CRAN repository as a repository option again. What can I do so that users don't see/get the default options for CRAN mirrors and as a result can no way change the local repository?
EDIT: As #Dason says, I don't want to stop the expert user from changing the repository option or others. I want to disable choosing mirrors just to ensure that users will not be able to access remote repositories (and download a package from there) by mistake.
Looks like in utils/R/packages.R source code, chooseCRANmirros() calls the function getCRANmirrors(all = FALSE, local.only = FALSE) and it does the following:
getCRANmirrors <- function(all = FALSE, local.only = FALSE)
{
m <- NULL
if(!local.only) {
## try to handle explicitly failure to connect to CRAN.
con <- url("http://cran.r-project.org/CRAN_mirrors.csv")
m <- try(open(con, "r"), silent = TRUE)
if(!inherits(m, "try-error")) m <- try(read.csv(con, as.is = TRUE))
close(con)
}
if(is.null(m) || inherits(m, "try-error"))
m <- read.csv(file.path(R.home("doc"), "CRAN_mirrors.csv"),
as.is = TRUE)
if(!all) m <- m[as.logical(m$OK), ]
m
}
So, it has a hard-coded value for the CRAN url if local.only is FALSE. Hence, I guess we have to set local.only to TRUE and then change the local CRAN_mirrors.csv file.