Merge remote-tracking branch 'origin/hotfix-v1.0.1'

Merge in latest from `hotfix-v1.0.1 branch.`

R/deployrExternal.R

@@ -1,12 +1,14 @@
 #' Access big data files in a portable way across environments.
 #'
-#' @description If you need to work with very large data files and want your R code to run consistently when accessing those files locally and on the DeployR Server, the use the \code{deployrExternal} function. 
+#' @description If you need to work with very large data files and want your R code to run consistently when accessing those files locally and on the DeployR Server, then use the \code{deployrExternal} function. 
 #' This function provides you with a consistent way of referencing these big data files for reading and writing; thereby, making your R code portable.
 #' 
 #' \strong{Important!} In order to get your big data files into the DeployR environment, you must first ask the DeployR administrator to place a copy of those files in the appropriate external directory on the server on your behalf. Once the files have been copied onto the server, your R code can reference these files by specifying the filename as an argument on the \code{deployrExternal} function.
 #' 
 #' When your code executes locally, the function looks for the data files in the current working directory of your R session. When your code executes remotely on the DeployR server, the function looks for the data files in the dedicated external directories configured and managed by the DeployR administrator.
 #' 
+#' For more information on configuring or using external directories, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
+#' 
 #' @param file Required. A character string specifying a valid filename with its extension. 
 #' @param isPublic Optional. If \code{isPublic = NULL} or \code{isPublic = FALSE} and code is running on DeployR, then the file is assumed to be in your private user external directory. If \code{isPublic = TRUE} and code is running on DeployR, then the file is assumed to be in the public external directory. Since the usage of the public external directory is ultimately a deployment decision, please coordinate with the application developer(s) before enabling this argument.
 #' 

R/deployrInput.R

@@ -7,7 +7,8 @@
 #'    \item{Test a script locally within your R IDE environment AND again remotely within the DeployR Repository Manager Test page. In both test cases, use the default values to verify consistent behavior across environments.}
 #'    \item{Provide client application developers with clear guidance as to which script inputs their application will be required to supply to produce meaningful output.}
 #' }
-#'
+#' 
+#' For more information on declaring your inputs, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
 #'    
 #' @param content  A valid JSON string configuration using the following 
 #'   structure:
@@ -119,7 +120,7 @@ deployrInput <- function(content) {
   }
 
   # 
-  # Assigne `factor` and `ordered-factor` with `levels|labels` if present
+  # Assign `factor` and `ordered-factor` with `levels|labels` if present
   # to the `default`. Skip if object already exsists and use that.
   #
   if (!exists(name) && render %in% c("factor", "ordered")) {

R/deployrPackage.R

@@ -4,6 +4,7 @@
 #'    
 #' This function safeguards your R code by making certain that the necessary packages are available to your R code at runtime.
 #' 
+#' For more information on ensuring package portability, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
 #'    
 #' @details Declare the set of package dependencies using this function at the top of your script.
 #'    

man/deployrExternal.Rd

@@ -12,12 +12,14 @@ deployrExternal(file, isPublic = FALSE)
 \item{isPublic}{Optional. If \code{isPublic = NULL} or \code{isPublic = FALSE} and code is running on DeployR, then the file is assumed to be in your private user external directory. If \code{isPublic = TRUE} and code is running on DeployR, then the file is assumed to be in the public external directory. Since the usage of the public external directory is ultimately a deployment decision, please coordinate with the application developer(s) before enabling this argument.}
 }
 \description{
-If you need to work with very large data files and want your R code to run consistently when accessing those files locally and on the DeployR Server, the use the \code{deployrExternal} function.
+If you need to work with very large data files and want your R code to run consistently when accessing those files locally and on the DeployR Server, then use the \code{deployrExternal} function.
 This function provides you with a consistent way of referencing these big data files for reading and writing; thereby, making your R code portable.
 
 \strong{Important!} In order to get your big data files into the DeployR environment, you must first ask the DeployR administrator to place a copy of those files in the appropriate external directory on the server on your behalf. Once the files have been copied onto the server, your R code can reference these files by specifying the filename as an argument on the \code{deployrExternal} function.
 
 When your code executes locally, the function looks for the data files in the current working directory of your R session. When your code executes remotely on the DeployR server, the function looks for the data files in the dedicated external directories configured and managed by the DeployR administrator.
+
+For more information on configuring or using external directories, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
 }
 \details{
 The \code{deployrExternal} function allows you access to file data portably by identifying the filename as an argument on the function call. The function then locates the file for you as follows:

man/deployrInput.Rd

@@ -29,6 +29,8 @@ The inputs can be used to:
    \item{Test a script locally within your R IDE environment AND again remotely within the DeployR Repository Manager Test page. In both test cases, use the default values to verify consistent behavior across environments.}
    \item{Provide client application developers with clear guidance as to which script inputs their application will be required to supply to produce meaningful output.}
 }
+
+For more information on declaring your inputs, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
 }
 \details{
 The  \code{name}, \code{render}, and \code{default} arguments are required. The entire input to the \code{deployrInput} function must be a valid JSON string. Within that string, JSON dictates that the argument names be double-quoted as should any strings.

man/deployrPackage.Rd

@@ -19,6 +19,8 @@ deployrPackage(pkgs, lib, repos = getOption("repos"), ...)
 The \code{deployrPackage} function guarantees package portability from your local environment to the DeployR server environment when you use it to declare all of the package dependencies in your R script.
 
 This function safeguards your R code by making certain that the necessary packages are available to your R code at runtime.
+
+For more information on ensuring package portability, see the \sQuote{Writing Portable R Code} document for your DeployR version on the official DeployR website (\url{http://deployr.revolutionanalytics.com/documents/dev/scientist-portable-code/}).
 }
 \details{
 Declare the set of package dependencies using this function at the top of your script.