Web Scraping, which is an essential part of Getting Data, used to be a very straightforward process just by locating the html content with xpath or css selector and extracting the data until Web developers started inserting Javascript-rendered content in the web page. Hence a css selector or an xpath pointing to a browser-generated / javascript-rendered front-end content does not contain html, instead a javascript snippet in the code source. This makes any conventional html scrapper incomplete in the stack since a javascript engine is required to run the extracted javascript code (actual scraped content from the web page) and output the desired result.

This above statement could be slightly confusing at first sight. Let me try to explain this with an example.

When you open this link: https://food.list.co.uk/place/22191-brewhemia-edinburgh/, You’d be presented with the details like Telephone, Email Id, Website of the listed place as in the below screenshot:

While it is easy to scrape some details like Telephone and Website from the above link, Email ID is the trickiest one – as the site’s developers have decided to make it js(javascript)-rendered content, possibly to fight spam or perhaps to discourage scraping.

Even the browser’s developer console does not reveal it is the trickiest, as it shows the rendered content (the actual Email ID) when we try to inspect that particular element (Refer the screenshot below):

But when we try scraping all we will be left with is a small snippet of javascript code, which is also revealed by the page source. (Refer the screenshot below)

This is when we realize, the go-to web scraping r-package rvest might not be able to help and a little bit of Google search would guide to use Selenium or Phantomjs (headless chrome). Behold, there might be something in R, precisely an R package, to help us. The package name is V8 which is an R interface to Google’s open source JavaScript engine. This package helps us execute javascript code in R without leaving the current R session. Coupling this package with rvest, It is now possible to programmatically extract the email ID in that page with the below R code.

#Loading both the required libraries library(rvest) library(V8) #URL with js-rendered content to be scraped link <- 'https://food.list.co.uk/place/22191-brewhemia-edinburgh/' #Read the html page content and extract all javascript codes that are inside a list emailjs <- read_html(link) %>% html_nodes('li') %>% html_nodes('script') %>% html_text() # Create a new v8 context ct <- v8() #parse the html content from the js output and print it as text read_html(ct$eval(gsub('document.write','',emailjs))) %>% html_text() [email protected]