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.
Related
I can run julia script with arguments from Powershell as > julia test.jl 'a' 'b'. I can run a script from REPL with include("test.jl") but include accepts just one argument - the path to the script.
From playing around with include it seems that it runs a script as a code block with all the variables referencing the current(?) scope so if I explicitly redefine ARGS variable in REPL it catches on and displays corresponding script results:
>ARGS="c","d"
>include("test.jl") # prints its arguments in a loop
c
d
This however gives a warning for redefining ARGS and doesn't seem the intended way of doing that. Is there another way to run a script from REPL (or from another script) while stating its arguments explicitly?
You probably don't want to run a self-contained script by includeing it. There are two options:
If the script isn't in your control and calling it from the command-line is the canonical interface, just call it in a separate Julia process. run(`$JULIA_HOME/julia path/to/script.jl arg1 arg2`). See running external commands for more details.
If you have control over the script, it'd probably make more sense to split it up into two parts: a library-like file that just defines Julia functions (but doesn't run any analyses) and a command-line file that parses the arguments and calls the functions defined by the library. Both command-line interface and the second script your writing now can include the library — or better yet make the library-like file a full-fledged package.
This solution is not clean or Julia style of doing things. But if you insist:
To avoid the warning when messing with ARGS use the original ARGS but mutate its contents. Like the following:
empty!(ARGS)
push!(ARGS,"argument1")
push!(ARGS,"argument2")
include("file.jl")
And this question is also a duplicate, or related to: juliapassing-argument-to-the-includefile-jl as #AlexanderMorley pointed to.
Not sure if it helps, but it took me a while to figure this:
On your path "C:\Users\\.julia\config\" there may be a .jl file called startup.jl
The trick is that not always Julia setup will create this. So, if neither the directory nor the .jl file exists, create them.
Julia will treat this .jl file as a command list to be executed every time you run REPL. It is very handy in order to set the directory of your projects (i.e. C:\MyJuliaProject\MyJuliaScript.jl using cd("")) and frequent used libs (like using Pkg, using LinearAlgebra, etc)
I wanted to share this as I didn't find anyone explicit saying this directory might not exist in your Julia device's installation. It took me more than it should to figure this thing out.
I have wrote a bunch of functions for my project for users to invoke interactively.
Now I'd like to have them safely included in the session.
I want to avoid a scenario where user types rm(list=ls()) and erases my functions from memory.
Initially I tried to save function to another environment and attach that environment to search path but along the way I changed something and R is not longer able to find my function.
My code is split among multiple files but snippet below ilustrates how are things organised, normally user will run app.R because it contains refernces to other files, configurations etc.:
./funs.R
id.mapping.env <- new.env(parent = emptyenv())
attach(id.mapping.env)
id.mapping.env$test_function<- function() {
print("It works")
}
./app.R
source("./funs.R")
test_function
If I run app.R I get error:
Error: could not find function "test_function"
Why won't R find my function? Do I have to resort to writing my own package to ensure all of my functions can be found?
I am not familiar with writing packages, if this is needed could you give me a tiny demo/tutorial(which I am googling right now).
Following your recommendations (or trying to do it, at least), I have tried some options, but the problem remains, so there must be something I am missing.
I have included a more complete code
setwd("C:/naapp")
#' #import utils
#' #import devtools
I have tried with and without using suppressForeignCheck
if(getRversion() >= "2.15.1"){
utils::globalVariables(c("eleven"))
utils::suppressForeignCheck(c("eleven"))
}
myFunctionSum <- function(X){print(X+eleven)}
myFunctionMul <- function(X){print(X*eleven)}
myFunction11 <- function(X){
assign("eleven",11,envir=environment(myFunctionMul))
}
maybe I should use a particular environment?
package.skeleton(name = "myPack11", list=ls(),
path = "C:/naapp", force = TRUE,
code_files = character())
I remove the "man" directory from the directory myPack11,
otherwise I would get an error because the help files are empty.
I add the imports utils, and devtools to the descrption
Then I run check
devtools::check("myPack11")
And I still get this note
#checking R code for possible problems ... NOTE
#myFunctionMul: no visible binding for global variable 'eleven'
#myFunctionSum: no visible binding for global variable 'eleven'
#Undefined global functions or variables:eleven
I have tried also to make an enviroment, combining Tomas Kalibera's suggetion and an example I found in the Internet.
myEnvir <- new.env()
myEnvir$eleven <- 11
etc
In this case, I get the same note, but with "myEnvir", instead of "eleven"
First version of the question
I trying to use "globalVariables" from the package utils. I am building an interface in R and I am planning to submit to CRAN. This is my first time, so, sorry if the question is very basic.I have read the help and I have tried to find examples, but I still don't know how to use it.
I have made a little silly example to ilustrate my question, which is:
Where do I have to place this line exactly?:
if(getRversion() >= "2.15.1"){utils::globalVariables("eleven")}
My example has three functions. myFunction11 creates the global variable "eleven" and the other two functions manipulate it. In my real code, I cannot use arguments in the functions that are called by means of a button. Consider that this is just a silly example to learn how to use globalVariables (to avoid binding notes).
myFunction11 <- function(){
assign("eleven",11,envir=environment(myFunctionSum))
}
myFunctionSum <- function(X){
print(X+eleven)
}
myFunctionMul <- function(X){
print(X*eleven)
}
Thank you in advance
I thought that the file globals.R would be automatically generated when using globalsVariables. The problem was that I needed to create the package skeleton, then create the file globals.R, add it to the R directory in the package and check the package.
So, I needed to place this in a different file:
#' #import utils
utils::globalVariables(c("eleven"))
and save it
The documentation clearly says:
## In the same source file (to remind you that you did it) add:
if(getRversion() >= "2.15.1") utils::globalVariables(c(".obj1", "obj2"))
so put it in the same source file as your functions. It can go in any of your R source files, but the comment above recommends you put it close to your code. Looking at a bunch of github packages reveals another common pattern is to have a globals.R function with it in, but this is probably a bad idea. If you later remove the global from your package but neglect to update globals.R you could mask a problem. Putting it right close to the functions that use it will hopefully remind you when you edit those functions.
Make sure you put it outside any function definitions in the file, or it won't get seen.
You cannot modify bindings in a package namespace once the package is loaded (and namespace sealed, and bindings locked). The check tool helps you to spot violations of this restriction, so you find out about the problem when checking the package rather than while running it. globalVariables is just a call to silence check when looking for these violations, which is undesirable in almost all cases. If you really need mutable state in a package, you can create a new environment (using new.env) and bind it to an (unexported) "global" variable in your namespace. This binding will be locked, but this is ok, because in R you can change an environment in place (add/remove elements, effectively modifying the elements).
The best situation is however when you can keep all mutable state in user objects (passed in as arguments into functions, and their modified versions returned as output values of functions).
I have a user defined function in R
blah=function(a,b){
something with a and b
}
is it possile to put this somewhere so that I do not need to remember to load in the workspace every time I start up R? Similar to a built in function like
summary(); t.test(); max(); sd()
You can put the function into your .rprofile file.
However, be very careful with what you put there, since it essentially makes your code non-reproducible — it now depends on your .rprofile:
Let’s say you have an R code file performing some analysis, and the code uses the function blah. Executing the code on any other system will fail due to the non-existence of the blah function.
As a consequence, this file should only contain system-specific setup. Don’t define helper functions in there — or if you do, make them defined only in interactive sessions, so that you have a clear environment when R is running a non-interactive script:
if (interactive()) {
# Helper functions go here.
}
And if you find yourself using the same helper functions over and over again, bundle them into packages (or modules) and reuse those.
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.