Technistas

It’s hard to read a website, blog post or even mainstream business press article without coming across the term ‘big data’. Big Data is one of those terms that means nothing and everything all at once, and for that reason alone, you should pay attention to it. When it comes to the how of big data, it’s equally hard to avoid bumping into R, the open source statistics and computational environment. If you’re going to describe and model the behavior of your customers in a big data initiative, R is one tool that you need in your software toolbox.

Data is everywhere, and increasing, data of all kinds on customer engagement is available through REST APIs. I started a little project in my spare time to bring data available via REST interfaces into R, to set the stage for doing what I expect to be some fairly sophisticated model building. The rest of this post is a quick introduction to how to work with REST APIs in R.

At its most basic, calling a REST API to obtain data involves making an HTTP GET request to a server. If the call succeeds, you’ll have a document that contains the requested data. In R, the best way to make these requests is by using RCurl. The RCurl package is – you guessed it – an R interface to curl. Once you’ve installed it into your R environment, getting data from REST APIs is pretty straightforward.

For my project, I started with the Constant Contact API, partly because I work for Constant Contact on the Web Services team, and party because the API makes available exactly the kind of data that you typically want to analyse in a marketing big data project – specifically, sends, clicks, opens and the like for marketing campaigns. The current v1 API returns XML, so I also installed the XML package into my R environment (though I haven’t done much with it yet). To install the packages use the following command in R:

> install.packages(‘RCurl’, ‘XML’)

To load these packages, use:

> library(‘RCurl’)

> library(‘XML’)

Once these preliminary tasks are taken care of, there are just 2 steps required to get campaign data from the API and into R:

1. Obtain an access token. Constant Contact uses OAuth 2.0 for authentication, as do many other public REST APIs. There’s no good way to get a token from inside R, so I used the client flow with a little bit of javascript to get the token in my browser, and then just saved it for use in R. See here for details on how to get access tokens. If you’re building an app that analyses data from multiple Constant Contact accounts, you’ll need the owners of those accounts grant access to your app in order for you to obtain access tokens. But for now, sign up for a trial and use your own account.

2. Call an HTTP endpoint using RCurl. This is very easy. For my initial test, I wanted to get the list of available email campaigns, so that I could later iterate over the list and get the campaign statistics for analysis. The call is:

campaignsXML = getURL(“https://api.constantcontact.com/ws/customers/{username}/campaigns?access_token={token}”)

{username} : replace with the name of the account for which you have the access token

{token} : replace with the actual access token granted to you by the account owner

This issues the HTTP GET request, and puts the resulting XML response into the R vector ‘campaignsXML’, ready to be processed further. That’s all there is to it.

In my next post on this topic, I’ll show you how to parse the XML to get it into a more usable form using the R XML package.

Happy Model Building!

– Matt