fizzBuzz = function(range, x, y){
    for (i in seq(1, range, by=1)){
        if (i %% x == 0 & i %% y == 0){
            print('FizzBuzz')
        }
        else if (i %% y ==0){
            print('Buzz')
        }
        else if (i %% x == 0){
            print('Fizz')
        }
        else{
            print(i)
        }
    }
}
fizzBuzz(100, 3, 5)

# Run this once to install benchmark suite:
#install.packages(c("microbenchmark", "stringr"), dependencies = TRUE)
require(microbenchmark)
library(parallel)

# Setup parallelization particulars.
cores <- detectCores()
cluster <- makeCluster(cores)

gerardFizzBuzz <- function(i) {
    fizz <- i %% 3
    buzz <- i %% 5

    if (fizz == 0 & buzz == 0) {
      return('FizzBuzz')
    }
    else if (buzz == 0) {
      return('Buzz')
    }
    else if (fizz == 0) {
      return('Fizz')
    }

    return(i)
}

applyFizzBuzz <- function(range) {
    return(lapply(1:range, gerardFizzBuzz))
}

parallelFizzBuzz <- function(range) {
    return(parLapply(cluster, 1:range, gerardFizzBuzz))
}

vectorizedFizzBuzz <- function(range) {
    v <- Vectorize(gerardFizzBuzz)
    return(v(1:range))
}

papasmurfFizzBuzz <- function (range) {
    res <- seq(1, range)

    for (i in res){
      if (i %% 3 == 0 & i %% 5 == 0){
        res[i] <- 'FizzBuzz'
      }
      else if (i %% 5 ==0){
        res[i] <- 'Buzz'
      }
      else if (i %% 3 == 0){
        res[i] <- 'Fizz'
      }
      else{
        res[i] <- i
      }
    }

    return(res)
}

range <- 100000;

perf <- microbenchmark(applyFizzBuzz(range), vectorizedFizzBuzz(range), parallelFizzBuzz(range), papasmurfFizzBuzz(range), times=20)

# note the log scale.
boxplot(perf, names = c("lapply", "Vectorized", "parLapply", "forloop"))

stopCluster(cluster)