R - Parallel Processing and ldply error - r

Question

I am trying to use the below code to make API calls in a parallel process to speed up the API calls. (I know this isn't the best way to speed up API calls but it works)
It only fails when I try to use parallel, otherwise it works. In the ldply function I am getting the below error:
Error in do.ply(i) :
task 1 failed - "object of type 'closure' is not subsettable"
In addition:
Warning messages:
1: : ... may be used in an incorrect context: ‘.fun(piece, ...)’
2: : ... may be used in an incorrect context: ‘.fun(piece, ...)’
any help would be appreciated!
One <- 26
cl<-makeCluster(4)
registerDoSNOW(cl)
func.time <- Sys.time()
## API CALL ONE FOR "kline"
url <- "https://api.binance.com"
path <- paste("/api/v1/klines?symbol=",pairs[1],"&interval=1m&limit=1", sep = "")
raw.results <- GET(url = url, path = path)
text_content <- content(raw.results, as = "text", encoding = "UTF-8")
kline <- data.frame(text_content %>% fromJSON())
kline$symbol <- pairs[1]
## API FUNCTION TO BE APPLIED FOR REST
loopfunction <- function(i){
url <- "https://api.binance.com"
path <- paste("/api/v1/klines?symbol=",pairs[i],"&interval=1m&limit=1", sep = "")
raw.results <- GET(url = url, path = path)
text_content <- content(raw.results, as = "text", encoding = "UTF-8")
kline_temp <- data.frame(text_content %>% fromJSON())
kline_temp$symbol <- pairs[i]
kline <- rbind(kline,kline_temp)
return(kline)
}
## DPLY PARALLEL FUNCTION
kline2 <- data.frame(ldply(2:(One - 1), .fun = loopfunction, .parallel = T, .paropts = c("httr", "jsonlite", "dplyr"))) ##"ONE" is a list varriable created earlier
stopCluster(cl)
func.end.time <- Sys.time()
func.tot.time <- func.end.time - func.time

Answer 1

Your question isn't fully reproducible, so the following is an educated guess.
Your loopfunction() references an object called pairs. It seems from your script that a variable called pairs is defined somewhere in your local environment. However, when loopfunction() is passed to ldply(), it no longer has access to that variable (ordinarily, it would, but parallelization requires fresh R environments to be created). Having failed to find an object called pairs in the environment, R continues searching, and finds a match in stats::pairs(). This is a plotting function, not a subsettable object like a vector or data frame. Hence the error message, "object of type 'closure' is not subsettable".
I'm not especially familiar with how ldply implements parallel processing, but you could probably modify your function definition like this:
loopfunction <- function(i, pairs) {
...[body of function]...
}
And pass pairs as an extra parameter in your ldply call:
kline2 <- data.frame(ldply(2:(One - 1), .fun = loopfunction, pairs = pairs, .parallel = T, .paropts = list(.packages = c("httr", "jsonlite", "dplyr"))))