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1. #GO LANG WEBSCRAPER HOW TO#
2. #GO LANG WEBSCRAPER INSTALL#
3. #GO LANG WEBSCRAPER CODE#
4. #GO LANG WEBSCRAPER DOWNLOAD#

These HTML elements are the same for address in each town. Thus we see that the address for 285 Columbus Ave is in an HTML element called p (paragraph elements) with a class attribute equal to “store-address”. To open the developer’s tools and find the relevant HTML elements this time, we right click on an address and choose inspect as seen below (note: we could have used inspect above instead of F12): For example here are the first 9 of 27 locations in Boston: For example the link to Boston is open on the right hand pane.Īnd finally once when we click a town then we see all the CVS locations in the town. In this case the elements are a div (division elements) with a class attribute called “states” followed by list elements, li, which contain a (anchor) elements with href attributes that hold the desired web-links. As above we locate the HTML elements that we need to navigate to a town’s CVS address webpage. On the left, once again, is the list of Massachusetts towns and the number of pharmacies per town, while on the right is the HTML document of that same list of towns. If we again press F12 to open the developer tools to see the corresponding HTML, then the page is transformed into the following view: Here we have a list of all the towns in Massachusetts with a CVS pharmacy and the number of pharmacies in the town. As we will see below these HTML elements are what we need for the scraper.įollowing the link to the Massachusetts webpage we get the following: It has an HTML element a (“a” is for anchor) with an href attribute linking to the webpage of Massachusetts stores. For example in the right pane above, the link to the webpage for the Massachusetts pharmacies is in the second horizontal blue line.

#GO LANG WEBSCRAPER CODE#

It is this code on the right that our scraper needs to find the links to each of the CVS state specific webpages. On the right is the developer’s view, which contains the HTML and CSS code that generates the view on the left. On the left is the page as we see it when we navigate to it (minus the blue and green colors which are just highlighting the selected sections from the right pane). To see both the view above and the HTML document click F12 on your keyboard, which brings up the browser’s developer tools and looks something like the following: Our scraper sees the website differently, as a tree of HTML elements and attributes. However this is just the human readable format for the webpage. This page will be the starting point for our web scraper. The first webpage to look at is the page with links to the pharmacies for each state on the CVS website. We have to go step by step, just as our scraper will, and inspect the key HTML elements that we need to inform our scraper of what to look for on each webpage. When scraping the web it is important to explore the webpages that contain the data we want.

#GO LANG WEBSCRAPER INSTALL#

Once Go is installed create a project directory and a Go module to allow Go to install the packages needed to perform the web scraping with the following commands: The Tour of Go is an excellent tutorial to begin to get comfortable coding in Go.

#GO LANG WEBSCRAPER DOWNLOAD#

To download Go and install it on your computer follow these instructions. I am going to assume that you have some facility with programming and Go or a similar language. I will demonstrate proximity analysis with this CVS store data in the next post. With these coordinates we can then perform various GIS analyses such as a proximity analysis to locate the nearest CVS store given any location in the world. Once we have scraped the store addresses we can then use a geocoder to convert the addresses into longitude and latitude coordinates.

#GO LANG WEBSCRAPER HOW TO#

The example below is how to web scrape the store addresses of every CVS Pharmacy in the United States.

Colly adds numerous functions to Go that makes web scraping straightforward.

I have used Go to build the backends for several websites and I have found the experience very enjoyable. Go is a modern, no nonsense, easy to use programming language that is continuing to grow in popularity. Thus for this blog post I am going to demonstrate a web scraping example using the Go programming language and an excellent package written in Go, designed for web scraping, called Colly. However, while we can easily read the information displayed on a website, scrapping the very same information algorithmically for data analysis is not so simple. The web is a treasure trove of information.