There is a R file and there is a function getInfo() in it.
I want to run this function in that script file alone.
Is that possible ?
I know running the script command on the file and then running the function name will help.
But then it will also run the rest of stuffs from the script file which i dont want.
What is the best way out here
When you use source on a script file, all the code in that file will be loaded into the R session currently active. Any code that is not in a function, will be executed. I see two options:
Put the function in a seperate source file, or even a package if the number of functions grows.
Set a global R variable using option and retrieve its value in the file to be sourced using getOption, making the execution of the non-function code dependend on this option. This does require you to always set this option before sourcing the file, in any project you use it in.
I would go for option 1.
Related
I'm building a package that uses two main functions. One of the functions model.R requires a special type of simulation sim.R and a way to set up the results in a table table.R
In a sharable package, how do I call both the sim.R and table.R files from within model.R? I've tried source("sim.R") and source("R/sim.R") but that call doesn't work from within the package. Any ideas?
Should I just copy and paste the codes from sim.R and table.R into the model.R script instead?
Edit:
I have all the scripts in the R directory, the DESCRIPTION and NAMESPACE files are all set. I just have multiple scripts in the R directory. ~R/ has premodel.R model.R sim.R and table.R. I need the model.R script to use both sim.R and table.R functions... located in the same directory in the package (e.g. ~R/).
To elaborate on joran's point, when you build a package you don't need to source functions.
For example, imagine I want to make a package named TEST. I will begin by generating a directory (i.e. folder) named TEST. Within TEST I will create another folder name R, in that folder I will include all R script(s) containing the different functions in the package.
At a minimum you need to also include a DESCRIPTION and NAMESPACE file. A man (for help files) and tests (for unit tests) are also nice to include.
Making a package is pretty easy. Here is a blog with a straightforward introduction: http://hilaryparker.com/2014/04/29/writing-an-r-package-from-scratch/
As others have pointed out you don't have to source R files in a package. The package loading mechanism will take care of losing the namespace and making all exported functions available. So usually you don't have to worry about any of this.
There are exceptions however. If you have multiple files with R code situations can arise where the order in which these files are processed matters. Often it doesn't matter or the default order used by R happens to be fine. If you find that there are some dependencies within your package that aren't resolved properly you may be faced with a situation where a custom processing order for the R files is required. The DESCRIPTION file offers the optional Collate field for this purpose. Simply list all your R files in the order they should be processed to satisfy the dependencies.
If all your files are in R directory, any function will be in memory after you do a package build or Load_All.
You may have issues if you have code in files that is not in a function tho.
R loads files in alphabetical order.
Usually, this is not a problem, because functions are evaluated when they are called for execution, not at loading time (id. a function can refer another function not yet defined, even in the same file).
But, if you have code outside a function in model.R, this code will be executed immediately at time of file loading, and your package build will fail usually with a
ERROR: lazy loading failed for package 'yourPackageName'
If this is the case, wrap the sparse code of model.R into a function so you can call it later, when the package has fully loaded, external library too.
If this piece of code is there for initialize some value, consider to use_data() to have R take care of load data into the environment for you.
If this piece of code is just interactive code written to test and implement the package itself, you should consider to put it elsewhere or wrap it to a function anyway.
if you really need that code to be executed at loading time or really have dependency to solve, then you must add the collate line into DESCRIPTION file, as already stated by Peter Humburg, to force R to load files order.
Roxygen2 can help you, put before your code
#' #include sim.R table.R
call roxygenize(), and collate line will be generate for you into the DESCRIPTION file.
But even doing that, external library you may depend are not yet loaded by the package, leading to failure again at build time.
In conclusion, you'd better don't leave code outside functions in a .R file if it's located inside a package.
Since you're building a package, the reason why you're having trouble accessing the other functions in your /R directory is because you need to first:
library(devtools)
document()
from within the working directory of your package. Now each function in your package should be accessible to any other function. Then, to finish up, do:
build()
install()
although it should be noted that a simple document() call will already be sufficient to solve your problem.
Make your functions global by defining them with <<- instead of <- and they will become available to any other script running in that environment.
I need to understand an R script. Since I did not use R until now, I try to understand the script step by step. At the beginning of the script command line arguments (input files) are passed with commandArgs(). I know that one can access additional arguments for an R script with commandArgs().
But I just cannot figure out how to run a script with arguments in the interactive mode, so that I can print all variables used in the script later on. For example source("script.R") does not seem to take arguments.
My apologies if I am just not capable of using the right search query...
I think you're misunderstanding the use of commandArgs - it's for getting the arguments supplied when run through the command line... not the interpreter. If you just want to "supply arguments" when sourcing a file then just put those into the global namespace (just create the variables you want to use). Using source is almost just like copying the script and pasting it into the interpreter.
I am new to R and have been trying to use JRI. Through JRI, I have used the "eval()" function to get certain results. If I want to execute an R script, I have used "source()". However I am now in a situation where I need to execute a script on continuously incoming data. While I can still use "source()", I don't think that would be an optimal way from a performance perspectve.
What I did was to read the entire R script into memory and then try and use "eval()" passing the script - but this does not seem to work. I have ensured that the script has been correctly loaded into memory - that is because if I write this script (loaded into the memory) into a file and source this newly created file, it does produce the expected results.
Is there a way for me to not keep sourcing the same file over and over again and execute it from memory? Each of my data units are independent and have to be processed independently and as soon as they become available. I cannot wait to collect a bunch of data units and then pass them on to the R script.
I have searched a lot and not found anything related to this. Any pointers which could help me in this direction would be really helpful.
The way I handled this is as below -
I enclosed the entire script into a function.
I sourced the script file (which now contains the function) at the start of the execution of my program.
The place where I was sourcing the file, I am now just calling the function which contains the script itself i.e. -
REXP result = rengine.eval("retVal<-" + getFunctionName() + "()");
Here, getFunctionName() gives me the name of the name of the function which contains the script.
Since this is loaded into the memory and available, I do not have to source the script file every time I want to execute the script. Any arguments being passed to the script are done as env. variables.
This seems to be a workaround, but solves my problem. Any better options are welcome.
I have seen many related answers here,but i didn't get a proper way to solve my problem under windows system...
I know the link the similar question
I got that setwd() can locate the directory what i want,however,my R script may move to another directory without any modification,so I want to know the current file directory,becase there are expression like source(...),this called source file and the execution file under the same parent directory in a R project,how I can do?
any help appreciated.
You can get your current directory using the getwd() function and give it a name, say:
cpath = getwd()
Another useful function is the file.path, which can help you specify new directories with simple syntax. For example, you want to get the directory that is one level "above" the current directory, you can use:
upp.dir = file.path("..", "cpath")
This gives upp.dir as "../Your_Current_Dir". How about changing to another folder (called Folder_A) in current directory? Use:
folderA = file.path("cpath", "Folder_A")
These may help easy navigate the file system.
Basically, if you write scripts and those scripts depend on where they are, then you are Doing It Wrong.
Write code in packages. Parameterise functions to make them generally applicable. If you have folders with data in, then make one of those parameters a folder.
A script called with source() cannot reliably locate itself, but that shouldn't be a problem, because WHATEVER CALLED THE SCRIPT knows where the script is (it has to, or how else can it call it?) so it could pass that as a parameter. Something like:
> youarehere = "C:\foo\"
> source("C:\foo\bar.R")
and now bar.R can do setwd(youarehere) and it will work, even if it is badly written such that it relies on sourcing other code in its containing folder.
Or you can do:
> setwd(youarehere)
> source("bar.R")
in your calling function.
But really, its a fail, its a sign of badly written code. Use functions, write packages, use devtools, its really not that hard, then your code will work anywhere and you wont be writing stupid scripts that are a twisty turny maze of source() calls.
Stay classy.
I am creating an R package, and found it useful to break parts of the logic in one file into internal helper functions, which I define in the same file. I have sort of a special case where my function decides which helper function to use via match.fun(). Since they won't be useful to other functions or people, I don't want to put these in separate files, and I don't want to export them.
All my testthat cases pass using test_dir(). When I don't export these functions, my testthat cases fail during R CMD check.
"object 'helperfunction1' of mode 'function' was not found", quote(get(as.character(FUN),
mode = "function", envir = envir)))
After looking at this post, I am able to get things to work if I explicitly export or add export entries to NAMESPACE, but again I don't want to export these.
Is there a better way to do this and doesn't require me to export? (I'll admit that the source of the issue may be match.fun() and am open to other ways of calling functions at runtime.)
From memory it wasn't clear in the documentation last time I read it (it may have changed), but it will work correctly (without having to export) so long as everything is in the right directories:
You should have a file:
tests/run-all.R
That looks like:
library(testthat)
library(myPackage)
test_package("myPackage")
Then your individual test files should be in the directory inst/tests
These will be run when you do R CMD check, otherwise you can call test_package("myPackage") in R manually.