In R, How to Suppress "Note: No Visible Binding for Global Variable"

In R, is it possible to suppress Note: no visible binding for global variable?

All credit to @Tyler Rinker for this answer.

To eliminate these notes, prefix the source code above with this:

# Intent:
#   This function suppresses the following notes generated by "R CMD check":
#   - "Note: no visible binding for global variable '.->ConfigString'"
#   - "Note: no visible binding for '<<-' assignment to 'ConfigString'"
# Usage:
#   Add the following right in the beginning of the .r file (before the Reference
#   class is defined in the sourced .r file):
#   suppressBindingNotes(c(".->ConfigString","ConfigString"))
suppressBindingNotes <- function(variablesMentionedInNotes) {
    for(variable in variablesMentionedInNotes) {
        assign(variable,NULL, envir = .GlobalEnv)       
    }
}

suppressBindingNotes(c(".->ConfigString","ConfigString"))

In addition, sometimes Revolution R might need to be restarted if it has been running for a long time.

No visible global function definition/no visible binding for global variable in a project?

You could disable the object usage linter in your project. Example: https://github.com/ropensci/targets/blob/8c42336a228874889c9ee99dd154c567b4eee91a/.lintr#L4. More on linters: https://github.com/r-lib/lintr#available-linters

R no visible binding for global variable note when creating variables in sub-routines and returning to environment

SOLUTION USING ENVIRONMENTS

So I figured out how to do this. Yes, you can use the list approach, but it is somewhat artificial. Here is the proper way: define a named empty environment inside the wrapper function outside_function, to which all objects that you want to store (and return at the end) are written. This environment is then passed as a single argument (like a list) to the inside functions. Within inside_function, you can edit stored environment objects in real time, without having to explicitly return the objects in a list back to a list object. It is cleaner.

outside_function <- function() {
  
  myenv <- new.env(parent = emptyenv())
  #object k exists in local environment, but not myenv
  k <- LETTERS[17:23]
  #assign list of objects to 
  print(ls()) #two objects, k and myenv
  print(ls(myenv))

  print("first run")
  inside_function(env=myenv) 
  print("LS")
  print(as.list(myenv))
  print("second run")
  inside_function(env=myenv)
  print("LS")
  print(as.list(myenv))

  #inside here, have to refer to objects as list elements
  #the command print(m) searches through environments to find an object
  #if nothing exists locally, m will find myenv$m, but is misleading
  #try(print(m))  
  #now create a local object m that is different
  m <- "blah"
  print(m) #gives 'blah'
  print(myenv$m)
  
  #return at end as a list
  invisible(as.list(myenv))
 
}  
inside_function <- function(env) {
  #create/overwrite objects in env
  
  env$m <- matrix(stats::runif(4), ncol=2)
  #these are created in real time within inside_function without having
  #to return env (notice NULL is a returned value)
  print(env$m)
  #overwite
  env$m <- matrix(stats::runif(4), ncol=2)
  print(env$m)
  env$d <- 5
  print(env$d)
  env$d <- env$d + runif(1)
  env$z <- letters[sample(1:20, size=6)]
  invisible(NULL)
}

tmp <- outside_function()
print(tmp) #contains all the objects as a list

No visible binding for global variable Note in R CMD check

To get it past R CMD check you can either :

• Use get("b") (but that is onerous)
• Place a=b=NULL somewhere higher up in your function (that's what I do)

There was a thread on r-devel a while ago where somebody from r-core basically said (from memory) "NOTES are ok, you know. The assumption is that the author checked it and is ok with the NOTE.". But, I agree with you. I do prefer to have CRAN checks return a clean "OK" on all platforms. That way the user is left in no doubt that it passes checks ok.

EDIT :

Here is the r-devel thread I was remembering (from April 2010). So that appears to suggest that there are some situations where there is no known way to avoid the NOTE, but that's ok.

How can I handle R CMD check no visible binding for global variable notes when my ggplot2 syntax is sensible?

Have you tried with aes_string instead of aes? This should work, although I haven't tried it:

aes_string(x = 'x.values', y = 'y.values')

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