I am trying to work my way through an R htmlWidgets tutorial and I am occuring what seems to be a bug related to Windows 10.
The code below works on my Windows 7 machine but not my Windows 10 machine:
# libpath
.libPaths("C:/R/R-3.2.4revised/library")
library(htmlwidgets)
library(devtools)
# need to be something in the package
placeholder <- function(x, y) x+y
# generate package
package.skeleton(name = "mywidget", list = c("placeholder"),
environment = .GlobalEnv,
path = ".", force = FALSE,
code_files = character())
# package dir
path <- "C:/Users/kaspe/Desktop/R/practise/htmlWidgets/mywidget"
#devtools::create("mywidget") # create package using devtools
setwd(path) # navigate to package dir
htmlwidgets::scaffoldWidget("mywidget") # create widget scaffolding
devtools::install()
When I am running the command:
> htmlwidgets::scaffoldWidget("mywidget") # create widget scaffolding
It produces the following error:
Created boilerplate for widget constructor R/mywidget.R
Error in editor(file = file, title = title) :
argument "name" is missing, with no default
Same base R and R-studio on both machines.
Does anyone have a clue about what might be wrong here?
Best
Kasper
What about htmlwidgets::scaffoldWidget("mywidget", edit = FALSE)? I don't know anything about windows, but perhaps some analogue of the $EDITOR system variable hasn't been properly set.
Related
I am running several scripts in RStudio and checking syntax errors. I am using source() in a loop to perform those tasks. In some scripts, install.packages("packagename") occurs. My problem is that when i have the required packages already installed in my computer, a message pops up asking me to update the library. In these cases, I would like to be able to "ignore" install.packages("packagename") call and running code to continue without showing any message.
So, how can i check if package installation is required or not while running code via source()?
Bit of a hack, but given the location file, this will list all the packages inside the script:
require(readr)
require(stringr)
listPackages <- function(file)
{
r <- readr::read_file(file)
r = str_replace_all(r, '\\"', "") # remove all quote marks
packages <- str_extract_all(r, regex("(install.packages|library|require|p_load)\\([:alnum:]*\\)*", multiline = TRUE))[[1]]
return(unique(gsub("\\(", "", str_extract(packages, regex("\\([:alnum:]*", multiline = F)))))
}
Example
test.R:
library("ggplot2")
library(stats)
require("cowplot")
require(MASS)
add <- function(x,y) {x+y}
install.packages("cowplot")
p_load(dplyr)
p_load("dplyr")
listPackages("test.R")
# [1] "ggplot2" "stats" "cowplot" "MASS" "cowplot" "dplyr"
I have a bunch of sf objects I'd like to export to GDB from R. I'm running R 4.0.2 on Windows 10. In this case the sf objects are all vector point data. The main reasons to export to GDB are to keep longer field names (the shapefile truncation is very annoying), and because GDBs are more desirable storage locations for our workflows.
Yes, I know about the ArcGisBinding package. I've got it to work in a test script but it's pretty unstable - often crashing and requiring a restart of R. This is a problem, because the sf objects I'd like to export come after an already long Rmd that reads in, formats and cleans the data. So it's not a simple manner of re-running the script until arc.write doesn't break. I could break up the script, but then I'd still have to read in a bunch of shapefiles. One option I haven't yet explored is using reticulate to call a python script instead of trying to do everything in R, but we're trying to do our analysis all in one place, if possible.
I'm pretty sure I've managed to set up RPyGeo appropriately, first setting my python path using the reticulate package. I'm doing it this way because IT restrictions means I can't edit PATH variables on my machine.
#package calls
library(sf)
library(spData)
library(reticulate)
#set python version in reticulate
py_path <- "C:/Program Files/ArcGIS/Pro/bin/Python/envs/arcgispro-py3/python.exe"
reticulate::use_python(python = py_path, required = TRUE)
#call RPyGeo
library(RPyGeo) # for potential point export
#output gdb
out.gdb <- "C:/LOCAL_PROJECTS/Output/Output.gdb"
#RPyGeo Parameters
# Note that, in order to use RPyGeo you need a working ArcMap or ArcGIS Pro installation on your computer.
# python path - note that this will change depending on which version of Arc one is using
# py_path <- "C:/Program Files/ArcGIS/Pro/bin/Python/envs/arcgispro-py3/python.exe"
arcpy <- rpygeo_build_env(workspace = out.gdb,
overwrite = TRUE,
extensions = c("Spatial","DataInteroperability"),
path = py_path)
I've tried a bunch of different tools to export an sf object, here using dummy data also used in the RPyGeo vignette
data(nz, package = "spData")
arcpy$Copy_management(in_data = nz,out_data = "nz_test")
arcpy$Copy_management(in_data = nz,out_data = file.path(out.gdb,"nz"))
arcpy$FeatureClassToGeodatabase_conversion(Input_Features = nz,Output_Geodatabase = out.gdb)
arcpy$FeatureClassToFeatureClass_conversion(in_features = nz,out_path = out.gdb,out_name = "nz")
arcpy$QuickExport_interop(Input = nz,Output = file.path(out.gdb,"nz"))
arcpy$CopyFeatures_management(in_features = nz,out_feature_class = file.path(out.gdb,"nz"))
arcpy$CopyFeatures_management(in_features = nz,out_feature_class = "nz")
Each time I get an error, for example:
Error in py_call_impl(callable, dots$args, dots$keywords) :
RuntimeError: Object: Error in executing tool
Detailed traceback:
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\management.py", line 3232, in CopyFeatures
raise e
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\management.py", line 3229, in CopyFeatures
retval = convertArcObjectToPythonObject(gp.CopyFeatures_management(*gp_fixargs((in_features, out_feature_class, config_keyword, spatial_grid_1, spatial_grid_2, spatial_grid_3), True)))
File "C:\Program Files\ArcGIS\Pro\Resources\ArcPy\arcpy\geoprocessing\_base.py", line 511, in <lambda>
return lambda *args: val(*gp_fixargs(args, True))
I'm not an expert in ArcPy by any means. Nor am I an expert in tracing errors inside packages. Am I making a simple syntax mistake? Is there something else that I'm missing? Any help would be much appreciated!
When running install.packages("any_package") on windows I get the message :
trying URL
'somepath.zip'
I would like to get this path without downloading, is it possible ?
In other terms I'd like to get the CRAN link to the windows binary of the latest release (the best would actually be to be able to call a new function with the same parameters as install.packages and get the proper url(s) as an output).
I would need a way that works from the R console (no manual checking of the CRAN page etc).
I am not sure if this is what you are looking for. This build the URL from the repository information and building the file name of the list of available packages.
#get repository name
repos<- getOption("repos")
#Get url for the binary package
#contrib.url(repos, "both")
contriburl<-contrib.url(repos, "binary")
#"https://mirrors.nics.utk.edu/cran/bin/windows/contrib/3.5"
#make data.frame of avaialbe packages
df<-as.data.frame(available.packages())
#find package of interest
pkg <- "tidyr" #example
#ofinterest<-grep(pkg, df$Package)
ofinterest<-match(pkg, df$Package) #returns a single value
#assemble name, assumes it is always a zip file
name<-paste0(df[ofinterest,]$Package, "_", df[ofinterest,]$Version, ".zip")
#make final URL
finalurl<-paste0(contriburl, "/", name)
Here's a couple functions which respectively :
get the latest R version from RStudio's website
get the url of the last released windows binary
The first is a variation of code I found in the installr package. It seems there's no clean way of getting the last version, so we have to scrape a webpage.
The second is really just #Dave2e's code optimized and refactored into a function (with a fix for outdated R versions), so please direct upvotes to his answer.
get_package_url <- function(pkg){
version <- try(
available.packages()[pkg,"Version"],
silent = TRUE)
if(inherits(version,"try-error"))
stop("Package '",pkg,"' is not available")
contriburl <- contrib.url(getOption("repos"), "binary")
url <- file.path(
dirname(contriburl),
get_last_R_version(2),
paste0(pkg,"_",version,".zip"))
url
}
get_last_R_version <- function(n=3){
page <- readLines(
"https://cran.rstudio.com/bin/windows/base/",
warn = FALSE)
line <- grep("R-[0-9.]+.+-win\\.exe", page,value=TRUE)
long <- gsub("^.*?R-([0-9.]+.+)-win\\.exe.*$","\\1",line)
paste(strsplit(long,"\\.")[[1]][1:n], collapse=".")
}
get_package_url("data.table")
# on my system with R 3.3.1
# [1] "https://lib.ugent.be/CRAN/bin/windows/contrib/3.5/data.table_1.11.4.zip"
I am having trouble using R, 'tm' package, to read in .pdf files.
Specifically, I try to run the following code:
library(tm)
filename = "myfile.pdf"
tmp1 <- readPDF(PdftotextOptions="-layout")
doc <- tmp1(elem=list(uri=filename),language="en",id="id1")
doc[1:15]
...which gives me the error:
Error in readPDF(PdftotextOptions = "-layout") :
unused argument (PdftotextOptions = "-layout")
I assume this is due to the fact that the pdftotext program (part of xpdf, http://www.foolabs.com/xpdf/download.html) has not been installed correctly on my machine, so that R cannot access it.
What are the steps to install xpdf/pdftotext correctly such that the above R code can be executed? (I am aware of similar questions already posted, however they don't address the same issue)
PdftotextOptions is no parameter of readPDF. readPDF has a control parameter, which expects a list. So correct use would be:
if(all(file.exists(Sys.which(c("pdfinfo", "pdftotext"))))) {
tmp1 <- readPDF(control = list(text = "-layout"))
doc <- tmp1(elem=list(uri=filename),language="en",id="id1")
}
Set
setwd('C:/xpdf/bin64')
It works for me.
My server.R contains the following code for dynamically installing packages when needed:
package <- input$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.