Embed Directive in R Programming Language

Here’s the translation of the Go code to R, formatted in Markdown suitable for Hugo:

Our first example demonstrates how to embed files and folders into an R script. While R doesn’t have a built-in embed directive like some other languages, we can achieve similar functionality using base R functions.

# Import necessary libraries
library(base64enc)

# Read the contents of a single file into a string
fileString <- readChar("folder/single_file.txt", file.info("folder/single_file.txt")$size)

# Read the contents of a single file into a raw vector
fileByte <- readBin("folder/single_file.txt", "raw", n=file.info("folder/single_file.txt")$size)

# Create a list to store multiple files
folder <- list()

# Read multiple files from a folder
folder$single_file <- readChar("folder/single_file.txt", file.info("folder/single_file.txt")$size)
folder$file1 <- readChar("folder/file1.hash", file.info("folder/file1.hash")$size)
folder$file2 <- readChar("folder/file2.hash", file.info("folder/file2.hash")$size)

# Main function
main <- function() {
  # Print out the contents of 'single_file.txt'
  cat(fileString)
  cat(rawToChar(fileByte))
  
  # Retrieve some files from the embedded folder
  cat(folder$file1)
  cat(folder$file2)
}

# Run the main function
main()

To set up the necessary files for this example, you can use the following commands in your terminal:

$ mkdir -p folder
$ echo "hello r" > folder/single_file.txt
$ echo "123" > folder/file1.hash
$ echo "456" > folder/file2.hash

Then, you can run the R script:

$ Rscript embed_files.R
hello r
hello r
123
456

In this R implementation, we use readChar() and readBin() functions to read file contents into strings and raw vectors, respectively. We create a list called folder to simulate the embedded file system. The main() function demonstrates how to access and print the contents of these “embedded” files.

Note that this approach doesn’t actually embed the files into the R script at compile-time like the original example. Instead, it reads the files at runtime. For a more secure or portable solution, you might consider base64 encoding the file contents and including them directly in the script, or using a package designed for resource bundling in R.