Best practice on naming inputs for functions

Hey guys,
I would love to hear your opinion on how to best name inputs for functions. As functions in R are able to also use objects from the global environment, I explicitely name my "local" variables inside the function to avoid accidentally use a global object.

Minimalistic example on how I currently do it:

# Packages and options ----------------------------------------------------

library(dplyr)

speed_filter <- 10

# Some Function -----------------------------------------------------------

some_function <- function(cars_input, speed_filter_input) {  # I often have more than one data frame that enters a function, so just naming the input "data" is not an option. ;-)
  
speed_filter_input <- speed_filter_input * 2 # Just an operation to show why I want to have an explicit distinction between the local entity of speed_filter(_input) and the global speed_filter variable.

  cars_input <- cars_input %>% 
    dplyr::filter(speed >= speed_filter_input)  

  return(cars_input)  
}

some_function(
  cars_input = cars
  , speed_filter_input = speed_filter
)

Is there any better convention than using the suffix "_input"?

I have seen some functions that use a . (dot) in front of every input. Is that done to have a distinction with objects in the global environment or is there any other reason?

Thanks for your input in advance.

I think you're worrying about something that doesn't require any worry.

The condition on which R will move out of the function environment to look for a variable is if the variable is not found in the list of arguments. If, however, there is a matching argument name, it will restrict itself to the function environment only.

The following is a trivial example, and shows that as long as y is an argument in the function, I can not inadvertently access the y in the global environment (at least not without undergoing shenanigans that probably ought to be avoided anyway)

y <- 7

add <- function(x, y){
  x + y
}

add_danger <- function(x){
  x + y
}

add(x = 3, y = y)
#> [1] 10
add(x = 3 ,y = 7)
#> [1] 10
add(x = 3) # without giving the `y` argument, I can't complete the function
#> Error in add(x = 3): argument "y" is missing, with no default
add_danger(x = 3) # since this has not `y` argument, R will look to the global environment to find it.
#> [1] 10

Created on 2018-08-01 by the reprex package (v0.2.0).

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Thank you very much for your explanation and the good example, @nutterb. In my most important R scripts I prefer to get an error, if I forget to define the function input properly. But that is of course depending on one's likelihood to worry. :wink:

Maybe someone else also share my worriness and also defines local variables differently?

Can you also explain, why some functions use a dot in front of their function input? I have seen this for example in purrr where map has dots in front of the function inputs: map(.x, .f, ...).

There is a discussion around "to dot or not to dot" here:

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