I am trying to write a R package that depends on latexmk.
However, I am unable to find how to tell in the DESCRIPTION of the package that it requires latexmk to be installed. I was hoping someone would have dealt with this before and could give me some help.
If that is not possible, is there any way to provide a custom warning message when installing a package if a command is not found on the PATH?
You want SystemRequirements: latexmk.
See Section 1.1.1 "The DESCRIPTION File" of Writing R Extensions:
Dependencies external to the R system should be listed in the ‘SystemRequirements’ field, possibly amplified in a separate README file.
There are few more reference to the field in later sections of the manual.
Related
When I use a package in R I install it and use it with loading it. Now what if I add a package which uses another package? Is this package automatically downloaded and loaded too? Or is it in general forbidden for a R package to use another package? I don't think that.
Suppose I want to publish a R package. Within my code, can I use functions from other packages and install and load these packages? Or how does this work when I need functions from other packages? Do I have to implement a message that this and that package is needed and that the user has to install and load it prior to it and I need to implement error catching functions in case the package cannot be found on the pc system?
When I want to publish a R package, can I use/call Java code within my package/code?
For a package which was already published - so let's take just as an example the fGarch package - I would like to see the complete code. How can I see this? I know that R is open source and I think it is more or less possible to just enter a function empty and get the code displayed, but sometimes this does not work and especially my question is: Is there a way I can look into the whole code of the package?
For a package which was already published, is it possible to see and look into all files which were submitted? So like a repository as git where all files are submitted - the code itself and further files which are needed like description files or whatever - and I can see these files and look into them?
Furthermore regarding this post here and hiding functions: Is there code in a R package which I cannot see as an end user? This refers also to my previous question, how can I or which way can I see the whole code in a R package?
I guess you have a few different questions here. Let's take them in the order you asked them:
What if I add a package which uses another package? Is this package automatically downloaded and loaded too? Or is it in general forbidden for a R package to use another package?
It is certainly not forbidden for an R package to use another R package. In fact, the majority of R packages rely on other packages.
The source code for each R package must include a text-based DESCRIPTION file in the root directory. In this file you will find (among other things) a "Depends" field, and an "Imports" field. Together, these two fields list all the other packages required to use this package. If a user doesn't already have these other packages installed in their local library, R will install them automatically when it installs the requested package.
If your package lists a dependency in "Depends", then the dependency package is attached whenever your package is attached. Thus if you looked at the source code for a package called "foo" and you see that its DESCRIPTION file contains the line
Depends: bar,
you know that when you call library(foo) in your R console, you have effectively done library(bar); library(foo)
This isn't always ideal. The package foo might only need a couple of functions from package bar, and bar might contain some other functions whose names could clash with other commonly used functions. Therefore, in general, if you are writing a package and you only want to use a few functions from another package, it would be better to use "Imports" rather than "Depends" to limit the number of unnecessary symbols being added to your user's search path.
Suppose I want to publish a R package. Within my code, can I use functions from other packages and install and load these packages
Yes, you can use functions from other packages. The simplest way to do this is to include the name of the package in the Depends field of your DESCRIPTION file.
However, when using just a few functions from another package inside your own package, best practice is to use the "Imports" field in the DESCRIPTION file, and use a namespace qualifier for the imported function in your actual R code. For example, if you wanted to use ggplot from the ggplot2 package, then inside your function you would call it ggplot2::ggplot rather than just ggplot.
If you publish your package for others to use, the dependencies will be installed automatically along with your package if the user calls install.packages with the default settings. For example, when I did:
install.packages("fGarch")
I got the associated message:
#> also installing the dependencies ‘timeSeries’, ‘fBasics’, ‘fastICA’
Do I have to implement a message that this and that package is needed and that the user has to install and load it prior to it and I need to implement error catching functions in case the package cannot be found on the pc system?
No, not in general. R will take care of this as long as you have listed the correct packages in your DESCRIPTION file.
When I want to publish a R package, can I use/call Java code within my package/code?
R does not have a native Java API, but you can use your own Java code via the rJava package, which you can list as a dependency for your package. However, there are some users who have difficulty getting Java to run, for example business and academic users who may use R but do not have Java installed and do not have admin rights to install it, so this is something to bear in mind when writing a package.
For a package which was already published - so let's take just as an example the fGarch package - I would like to see the complete code. How can I see this?
Every package available for download from CRAN has its source code available. In the case of fGarch, its CRAN page contains a link to the gzipped tarball of the source code. You can download this and use untar in R to review all the source code. Alternatively, many packages will have an easily-found repository on Github or other source-control sites where you can examine the source code via a browser. For example, you can browse the fGarch source on Github here.
For a package which was already published, is it possible to see and look into all files which were submitted? So like a repository as git where all files are submitted - the code itself and further files which are needed like description files or whatever - and I can see these files and look into them?
Yes, you can look at all the sources files for all the packages uploaded to CRAN on Github at the unofficial Github CRAN mirror here
Is there code in a R package which I cannot see as an end user? This refers also to my previous question, how can I or which way can I see the whole code in a R package?
As above, you can get the source code for any package via CRAN or Github. As you said, you can look at the source code for exported functions just by typing the name of that function into R. For unexported functions, you can do the same with a triple colon. For example, ggplot2:::adjust_breaks allows you to see the function body of the unexported function adjust_breaks from ggplot2. There are some complexities when an object-oriented system like S4, ggproto or R6 is used, or when the source code includes compiled C or C++ code, but I haven't come across a situation yet in which I was not able to find the relevant source code after a minute or two with an R console and a good search engine.
I was trying to install the package RINDSEL but I am unable to install it and I keep getting the following error:
Error in install.packages : cannot open the connection
I downloaded the package from:
rindsel_1.0_2.zip | Integrated Breeding Platform
and loaded it from the directory. Other packages from the directory can be installed but just not this one.
Is the package corrupt or could there be any other error?
I would really be grateful for any help. Thanks in advance
Rename the zip file RinSel Software into Rindsel. That's the name specified in the discription file.
Then, you can install the package in R with the command
install.packages("C:/path/to/Rindsel.zip",repos=NULL,type="win.binary")
That works fine... at first (!!!).
Problem with the Rindsel package is. It is quite old. It was build with R 2.13.1. Therefore, if you want to load the library which would be the next step to use the package in R you will get the error:
Problems building package (Error: "package has been build before R-3.0.0")
My suggestion: Contact the authors of the package and ask them if they can either provide the source file that you can build the package by yourself or if they can bundle the Rindsel package with a newer R version.
(Or you could try to hunt down an old R version and see if you can get the thing running with an old R... However, I would not seriously suggest to do that. It would probably result in conflicting dependencies with the other required packages...)
EDIT 15-02-2018: OP asked if one can build an R package with sources that are presumeably the Rindsel source files.
Yes, basically, you could do that. You would have to make a your own description and namespace file and put the source file in the R folder than invoke the command in R to build it....
But it's not neccessary with the script files provided by the link the OP posted.
OP, just run the scripts in R! It's quite easy.
Download the zip-file and extract it on your machine.
Go to that directory. The R command would be
setwd('path/to/your/directory')
Than run the R script, e.g, the KNIndex.r. It's simple:
source('KNIndex.r')
Then the script will run and produce some output / prompts.
For future readers,
I was able to fix the error by running RStudio with administrative privileges to get the command to work.
If that does not fix it, you might wish to try
Installing "r tools" if that is not installed already. That can be downloaded from
https://cran.r-project.org/bin/windows/Rtools/
Download a relevant package that you are trying to install (e.g., tidyverse_1.3.0.zip) from https://cran.rstudio.com/
and install that from local path
It can also be installed directly from the web using install.packages("https://cran.rstudio.com/bin/windows/contrib/4.0/tidyverse_1.3.0.zip")
I had the same problem. R was not able to extract and compile the package files to the default installation directory for some system-specific reasons (not R related).
I was able to fix this by specifying the installation directory of the package lib using:
install.packages("your package", lib = 'path/to your/required/installation/directory')
You can then load the package by specifying the lib.loc option while loading it:
library('your package', lib.loc='path/to your/required/installation/directory')
A better solution:
Create a new environment variable (if you are using windows) R_LIBS_USER with the following directory path/to your/required/installation/directory.
This will change the default installation directory of the packages and make it easier to load and install them without specifying the location everytime.
My R package vignette uses tikz/pgf graphics. The R CMD check command throws an error message on operating systems where the LaTeX package tikz/pgf is not installed. On a vanilla Ubuntu system, for example, the Ubuntu package 'pgf' must be installed for R CMD check to complete without an error message. The CRAN servers seem to have tikz/pgf installed, but I cannot make sure this is always and everywhere the case. Is there any way I can add a dependency on pgf to the DESCRIPTION file of my R package? Can I just add it to the 'Depends' field (even though it is not an R package)? I would not like to trash the diagram because the package vignette is an article that was published in the Journal of Statistical Software, and I would like to use it as a vignette without any modification.
From http://cran.r-project.org/doc/manuals/R-exts.html#The-DESCRIPTION-file :
Other dependencies (external to the R system) should be listed in the ‘SystemRequirements’ field, possibly amplified in a separate README file.
There won't be any automatic check or informative error message generated by the R installation process, but at least the information will be stored in a consistent place ...
I have a package that will not build on Mac as a binary but can still built if done with source. The intended audience for this package is likely not familiar with command line and I want to make it as easy on them as possible. I have a webpage explaining how to build from source but wanted it to be more prominent on CRAN as with the RCurl package which doesn't have a binary for Windows.
How can I do this link to a ReadMe or is this able to be done for RCurl because it's one of the R core members that's maintaining it?
Put a file called INSTALL in the same directory as the DESCRIPTION file and it will automatically be linked on CRAN. For example, see the CRAN page for the sqldf package -- its linked on the Materials: line.
EDIT:
Format of web page has changed and the INSTALL file is now listed on the Materials: line (was Installation: line previously).
From the Writing R Extensions Manual, I read that
As from R 2.14.0 the preferred location for the Sweave sources is the
subdirectory vignettes of the source packages, but for compatibility
with earlier versions of R, vignette sources will be looked for in
inst/doc if vignettes does not exist.
However, when I create a vignettes subdirectory of the package source, when I run devtools::check() or R CMD check I get a warning for Package vignette(s) without corresponding PDF. If I put the vignette (.Rnw and .pdf) in inst/doc the check completes without complaints. I tried looking in my library at installed packaged and did not see any directories named vignettes. Should I still use the deprecated location?
You put the .Rnw sources in vignettes/ as you did, but you missed out a critical step; don't check the source tree. The expected workflow is to build the source tarball and then check that tarball. Building the tarball will create the vignette PDF.
R CMD build ../foo/pkg
R CMD check ./pkg-0.4.tar.gz
for example will build a source package tarball from the sources in ../foo/pkg creating the .tar.gz package in the current directory with the package name and version appended. Then you run R CMD check on that source package.
If you want your vignette built for you put it in vignettes/ and build the source package. At some future date, R Core may remove the ability to build vignettes from inst/doc so go with the advised location now and avoid check the sources directly.
I had a hard time interpreting this too.
I believe the intention is that you should put the .Rnw file in vignettes/ and the PDF (suitably compacted) in inst/doc/, which technically agrees with the documentation if you read carefully enough. (That is, it says the sources should go in vignettes/. I don't see where it says in so many words that you ought to put the corresponding PDF in inst/doc/, but it doesn't not say it, and that interpretation seems to make R CMD check happy ...)
The resolution is in #GavinSimpson's answer (i.e. one is expected to build the tarball and then check it, rather than checking the source directory itself). (My two cents is that it might be best if R-core officially deprecated (and eventually removed) direct source checking rather than confusing all of us groundlings ...)