Suppose I'm currently developing a package called mypackage. As time goes by, many different functions have landed in there, and I want to reorganize it. So I'd like to create a new package called newpackage in which I would move some of the functions of mypackage (and include new ones later).
The problem is that I don't want original users of mypackage to get object not found errors when they want to use one of the moved functions.
So, I thought about doing the following :
create newpackage and move the functions
add into mypackage DESCRIPTION file : Depends: newpackage
As such, when people would install, upgrade or load mypackage, newpackage would be installed or loaded too, and all the functions would be available.
Do you think it would work, or would there be some problems I don't think about ?
Thanks !
Isn't it so that it is not recommended to remove functions from a package without labeling them first to be depreciated?! So, maybe you proceed as you planned but before removing them from the mypackage, you could first mark them there as depreciated and then remove them from it finally in the next version of the package. And during the migrating phase you could use the namespace of the packages to refer already to the function in newpackage as you planned.
Related
I have already made a simple R package (pure R) to solve a problem with brute force then I tried to faster the code by writing the Rcpp script. I wrote a script to compare the running time with the "bench" library. now, how can I add this script to my package? I tried to add
#'#importFrom Rcpp cppFunction
on top of my R script and inserting the Rcpp file in the scr folder but didn't work. Is there a way to add it to my r package without creating the package from scratch? sorry if it has already been asked but I am new to all this and completely lost.
That conversion is actually (still) surprisingly difficult (in the sense of requiring more than just one file). It is easy to overlook details. Let me walk you through why.
Let us assume for a second that you started a working package using the R package package.skeleton(). That is the simplest and most general case. The package will work (yet have warning, see my pkgKitten package for a wrapper than cleans up, and a dozen other package helping functions and packages on CRAN). Note in particular that I have said nothing about roxygen2 which at this point is a just an added complication so let's focus on just .Rd files.
You can now contrast your simplest package with one built by and for Rcpp, namely by using Rcpp.package.skeleton(). You will see at least these differences in
DESCRIPTION for LinkingTo: and Imports
NAMESPACE for importFrom as well as the useDynLib line
a new src directory and a possible need for src/Makevars
All of which make it easier to (basically) start a new package via Rcpp.package.skeleton() and copy your existing package code into that package. We simply do not have a conversion helper. I still do the "manual conversion" you tried every now and then, and even I need a try or two and I have seen all the error messages a few times over...
So even if you don't want to "copy everything over" I think the simplest way is to
create two packages with and without Rcpp
do a recursive diff
ensure the difference is applied in your original package.
PS And remember that when you use roxygen2 and have documentation in the src/ directory to always first run Rcpp::compileAttributes() before running roxygen2::roxygenize(). RStudio and other helpers do that for you but it is still easy to forget...
I’ve written some R functions and dropped them into a script file using RStudio. These are bits of code that I use over and over, so I’m wondering how I might most easily create an R package out of them (for my own private use).
I’ve read various “how to” guides online but they’re quite complicated. Can anyone suggest an “idiot’s guide” to doing this please?
I've been involved in creating R packages recently, so I can help you with that. Before proceeding to the steps to be followed, there are some pre-requisites, which include:
RStudio
devtools package (for most of the functions involved in creation of a package)
roxygen2 package (for roxygen documentation)
In case you don't have the aforementioned packages, you can install them with these commands respectively:
install.packages("devtools")
install.packages("roxygen2")
Steps:
(1) Import devtools in RStudio by using library(devtools).
(devtools is a core package that makes creating R packages easier with its tools)
(2) Create your package by using:
create_package("~/directory/package_name") for a custom directory.
or
create_package("package_name") if you want your package to be created in current workspace directory.
(3) Soon after you execute this function, it will open a new RStudio session. You will observe that in the old session some lines will be auto-generated which basically tells R to create a new package with required components in the specified directory.
After this, we are done with this old instance of RStudio. We will continue our work on the new RStudio session window.
By far the package creation part is already over (yes, that simple) however, a package isn't directly functionable just by its creation plus the fact that you need to include a function in it requires some additional aspects of a package such as its documentation (where the function's title, parameters, return types, examples etc as mentioned using #param, #return etc - you would be familiar if you see roxygen documentation like in some github repositories) and R CMD checks to get it working.
I'll get to that in the subsequent steps, but just in case you want to verify that your package is created, you can look at:
The top right corner of the new RStudio session, where you can see the package name that you created.
The console, where you will see that R created a new directory/folder in the path that we specified in create_package() function.
The files panel of RStudio session, where you'll notice a bunch of new files and directories within your directory.
(4) As you mentioned in your words, you drop your functions in a script file - hence you will need to create the script first, which can be done using:
use_r("function_name")
A new R script will pop up in your working session, ready to be used.
Now go ahead and write your function(s) in it.
(5) After your done, you need to load the function(s) you have written for your package. This is accomplished by using the devtools::load_all() function.
When you execute load_all() in the console, you'll get to know that the functions have been loaded into your package when you'll see Loading package_name displayed in console.
You can try calling your functions after that in the console to verify that they work as a part of the package.
(6) Now that your function has been written and loaded into your package, it is time to move onto checks. It is a good practice to check the whole package as we make changes to our package. The function devtools::check() offers an easy way to do this.
Try executing check() in the console, it will go through a number of procedures checking your package for warnings/errors and give details for the same as messages on the screen (pertaining to what are the errors/warnings/notes). The R CMD check results at the end will contain the vital logs for you to see what are the errors and warnings you got along with their frequency.
If the functions in your package are written well, (with additional package dependencies taken care of) it will give you two warnings upon execution of check:
The first warning will be regarding the license that your package uses, which is not specified for a new pacakge.
The second should be the one for documentation, warning us that our code is not documented.
To resolve the first issue which is the license, use the use_mit_license("license_holder_name") command (or any other license which suits your package - but then for private use as you mentioned, it doesn't really matter what you specify if only your going to use it or not its to be distributed) with your name as in place of license_holder_name or anything which suits a license name.
This will add the license field in the .DESCRIPTION file (in your files panel) plus create additional files adding the license information.
Also you'll need to edit the .DESCRIPTION file, which have self-explanatory fields to fill-in or edit. Here is an example of how you can have it:
Package: Your_package_name
Title: Give a brief title
Version: 1.0.0.0
Authors#R:
person(given = "Your_first_name",
family = "Your_surname/family_name",
role = c("package_creator", "author"),
email = "youremailaddress#gmail.com",
comment = c(ORCID = "YOUR-ORCID-ID"))
Description: Give a brief description considering your package functionality.
License: will be updated with whatever license you provide, the above step will take care of this line.
Encoding: UTF-8
LazyData: true
To resolve the documentation warning, you'll need to document your function using roxygen documentation. An example:
#' #param a parameter one
#' #param b parameter two
#' #return sum of a and b
#' #export
#'
#' #examples
#' yourfunction(1,2)
yourfunction <- function(a,b)
{
sum <- a+b
return(sum)
}
Follow the roxygen syntax and add attributes as you desire, some may be optional such as #title for specifying title, while others such as #import are required (must) if your importing from other packages other than base R.
After your done documenting your function(s) using the Roxygen skeleton, we can tell our package that we have documented our functions by running devtools::document(). After you execute the document() command, perform check() again to see if you get any warnings. If you don't, then that means you're good to go. (you won't if you follow the steps)
Lastly, you'll need to install the package, for it to be accessible by R. Simply use the install() command (yes the same one you used at the beginning, except you don't need to specify the package here like install("package") since you are currently working in an instance where the package is loaded and is ready to be deployed/installed) and you'll see after a few lines of installation a statement like "Done (package_name)", which indicates the installation of our package is complete.
Now you can try your function by first importing your package using library("package_name") and then calling your desired function from the package. Thats it, congrats you did it!
I've tried to include the procedure in a lucid way (the way I create my R packages), but if you have any doubts feel free to ask.
I'm working on an R package here and got this doubt: I need an auxiliar function from another package, but I don't want to include the entire package as a dependency because I only need this one function. What is the correct procedure here? Is it OK if both codes are GPL-2 and I just copy/paste the function to my package? Should I contact the author? Or is it best to include the whole package as a dependency?
If it's just a small function, I don't see a problem with copying the code into your own package (since everything is GPLed). You should acknowledge the source in your package though.
This has the benefit of insulating your code from any changes in the other package; it's not unusual for updates to packages to break other packages downstream. It has the downside that if those updates were useful (bug fixes or added functionality) then you don't benefit from them either.
Title should be pretty clear I hope. I'm writing a package called forecasting, with imports for dplyr among other packages. With the imports written in to the DESCRIPTION file, I am able to force these other packages to be installed along with forecasting - is there an equivalent way to do this for the loading of the package? In other words, is there a way that when I load my package with library(forecasting), it automatically also loads dplyr and the other packages?
Thanks
Yes.
Re-read "Writing R Extensions". The Depends: forces both the initial installation as well as the loading of the depended-upon packages.
But these days you want Imports: along with importFrom() in the NAMESPACE file which is more fine-grained.
But first things first: get it working with Depends.
Edit:
Opps you're correct, the documentation I referenced is not a primary source. Perhaps this is better:
From the R documentation:
The ‘Depends’ field gives a comma-separated list of package names which this package depends on. Those packages will be attached before the current package when library or require is called.
and
The ‘Imports’ field lists packages whose namespaces are imported from (as specified in the NAMESPACE file) but which do not need to be attached. Namespaces accessed by the ‘::’ and ‘:::’ operators must be listed here, or in ‘Suggests’ or ‘Enhances’
Original:
From the R packages documentation:
Adding a package dependency here [the DESCRIPTION file] ensures that it’ll be installed. However, it does not mean that it will be attached along with your package (i.e., library(x)). The best practice is to explicitly refer to external functions using the syntax package::function(). This makes it very easy to identify which functions live outside of your package. This is especially useful when you read your code in the future.
I've hit an issue trying to import a package (namely, 'robfilter') inside one of my own packages. One of its methods that I am trying to use, adore.filter, is failing at this line:
data(critvals)
With error 'data set 'critvals' not found'.
The function works fine if I load the library via require(robfilter). However, this means that in order to use my custom package which calls adore.filter, I will have to load my own package, and then load robfilter. Not a huge problem but slightly annoying.
I'm not sure if the problem is that there is an extra step I need to do in order to make critvals visible within my package, or if perhaps there is something the package author needed to do (and hasn't done) to add critvals to its package namespace; there is no sign of 'critvals' in the robfilter NAMESPACE file. I haven't encountered this issue before and don't really understand how the use of data() inside a package is supposed to work.
There are two solutions as far as I know:
Either ask the robfilter Maintainer to put the data needed by robfiler in the internal data file of robfilter. (R/sysdata.rda)
Or make your package Depends on robfilter
So it works if you put robfilter in the depends section of your description file. But in my case (both are my packages), I was trying to avoid the Depends solution as it loads the imported package and also any other package will need to depend ont its imported package... See my question is quite a duplicate of yours but not in the same context.