Integrating PHP and R

August 18, 2010

(This article was first published on stotastic » R, and kindly contributed to R-bloggers)

“How can I integrate PHP and R?”

I know I’m not the only one who’s asked this question. After all, with great content management systems like Drupal, it would very cool to be able to drop an R module into some PHP code and instantly have a web app popping out some snazzy looking ggplot graphics. After spending some time Google searching for an easy implementation and finding very little in the PHP + R space, I was able to piece together a method for integrating the two. It uses no JavaScript… no AJAX… just plain old PHP.

The poor man’s R web app

Disclaimer: There are many reasons why you shouldn’t actually stick the following code on the web for all to see. It is a very stripped down example, which is great for experimenting on a localhost, but has some serious security flaws.

This implementation of PHP and R consists of only two files. One written in PHP, and the other an R script. The PHP returns a form which uses the GET method to send a variable N to the server. When the form is submitted, the PHP will then execute an R script from the shell using a combination of the PHP command exec() and the Rscript shell command. This command will pass the variable N to the R script. The R script will then execute and save a histogram plot of N normally distributed values to the filesystem. Finally, when the R script is complete, the PHP will return the HTML tag containing the saved images path. First, the PHP file…

// poorman.php
echo "
"; echo "Number values to generate: "; echo ""; echo ""
;   if(isset($_GET['N'])) { $N = $_GET['N'];   // execute R script from shell // this will save a plot at temp.png to the filesystem exec("Rscript my_rscript.R $N");   // return image tag $nocache = rand(); echo(""); } ?>

and the R script…

# my_rscript.R
args <- commandArgs(TRUE)
N <- args[1]
x <- rnorm(N,0,1)
png(filename="temp.png", width=500, height=500)
hist(x, col="lightblue")

Finally, to help you visualize the whole process a bit better, below is a screenshot of the results…

Some Issues

This is a very simple example that works fine on a localhost, but there are some BIG issues that need to be resolved before this code is opened up to the web.

  1. The user input isn’t sanitized
  2. Only one user can be using this web app at a time
  3. More care needs to be taken with read/write access
  4. More care needs to be taken with the relative file paths
  5. Speed?
  6. … and I’m sure I’m missing many more

The bottom line is that with less than 20 lines of code we are able to generate R graphics in a browser… everything else is just details.

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