- Web Scraping Python Login Website
- Web Scraping Python Github
- Web Scraping Python Beautiful Soup
- Web Scraping Python Beautifulsoup
lxml and Requests¶
lxml is a pretty extensive library written for parsingXML and HTML documents very quickly, even handling messed up tags in theprocess. We will also be using theRequests module instead of thealready built-in urllib2 module due to improvements in speed and readability.You can easily install both using pipinstalllxml
andpipinstallrequests
.
Let’s start with the imports:
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Next we will use requests.get
to retrieve the web page with our data,parse it using the html
module, and save the results in tree
:
(We need to use page.content
rather than page.text
becausehtml.fromstring
implicitly expects bytes
as input.)
Web Scraping Python Login Website
tree
now contains the whole HTML file in a nice tree structure whichwe can go over two different ways: XPath and CSSSelect. In this example, wewill focus on the former.
XPath is a way of locating information in structured documents such asHTML or XML documents. A good introduction to XPath is onW3Schools .
There are also various tools for obtaining the XPath of elements such asFireBug for Firefox or the Chrome Inspector. If you’re using Chrome, youcan right click an element, choose ‘Inspect element’, highlight the code,right click again, and choose ‘Copy XPath’.
Web Scraping Python Github
After a quick analysis, we see that in our page the data is contained intwo elements – one is a div with title ‘buyer-name’ and the other is aspan with class ‘item-price’:
Knowing this we can create the correct XPath query and use the lxmlxpath
function like this:
Let’s see what we got exactly:
Web Scraping Python Beautiful Soup
Congratulations! We have successfully scraped all the data we wanted froma web page using lxml and Requests. We have it stored in memory as twolists. Now we can do all sorts of cool stuff with it: we can analyze itusing Python or we can save it to a file and share it with the world.
Web Scraping Python Beautifulsoup
Some more cool ideas to think about are modifying this script to iteratethrough the rest of the pages of this example dataset, or rewriting thisapplication to use threads for improved speed.