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library(XML)
cleanGoogleTable <- function(dat, table=1, skip=0, ncols=NA, nrows=-1, header=TRUE, dropFirstCol=NA){
  if(!is.data.frame(dat)){
    dat <- dat[[table]]
  }
  if(is.na(dropFirstCol)) {
    firstCol <- na.omit(dat[[1]])
    if(all(firstCol == ".") || all(firstCol== as.character(seq_along(firstCol)))) {
      dat <- dat[, -1]
    }

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library(foreach)
library(doParallel)


# Estimate value of pi using simulation
mcPi <- function(n=1e6) 4 * sum( runif(n)^2 + runif(n)^2 < 1) / n


# Set up cluster
cl <- makeCluster(4)

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# Create RRT repo checkpoint

library(RRT)
checkpoint("2014-08-28")
rrt_browse()

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# Install package from CRAN

getOption("repos")
options(repos=c(CRAN="http://cran.at.r-project.org/"))
install.packages("miniCRAN", type="source")

library("miniCRAN")
sessionInfo()

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library(checkpoint)
checkpoint("2014-09-17")

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install.packages("checkpoint")
library("checkpoint")

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# Create temporary project and set working directory
 
example_project <- paste0("~/checkpoint_example_project_", Sys.Date())
 
dir.create(example_project, recursive = TRUE)
oldwd <- setwd(example_project)
 
 
# Write dummy code file to project
 

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# Run Simon Urbanek's benchmark v2.5

cat("R version\n")
cat("=========\n")
print(R.version)

if(exists("Revo.version")) {
  cat("Revo version")
  cat("============")
  print(Revo.version)

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# Set MKL threads if Revolution R Open or Revolution R Enterprise is available

if(require("RevoUtilsMath")){
  setMKLthreads(4)
}


# Initialization

set.seed (1)

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setSnapshot <- function(date){
  if(missing(date)) return(getOption("repos"))
  repoDate <- paste0("http://mran.revolutionanalytics.com/snapshot/", date)
  response <- tryCatch(
    suppressWarnings(readLines(repoDate)),
    error = function(e)e
    )
  if(inherits(response, "error")) stop(paste0("Invalid snapshot date."))
  options(repos = c(CRAN = repoDate))
}