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.

Python Web Scraping Tutorial. PDF Version Quick Guide Resources Job Search Discussion. Web scraping, also called web data mining or web harvesting, is the process of constructing an agent which can extract, parse, download and organize useful information from the web automatically. Oct 03, 2018 Scrapper To Scrape All Comments from a Web Page Lastly, if you check our url has page numbers, starting from 702. So, we can recursively go to previous pages by simply changing the page numbers in the url to extract more comments until we get the desired number of comments. Jul 25, 2014 Python and Data Science Python is an excellent choice for Data Scientist to do his day-to-day activities as it provides libraries to do all these things. Python has a diverse range of open source libraries for just about everything that a Data Scientist does in his day-to-day work. Python and most of its libraries are both open source and free. Step 1:Install Python 2. Since we will be using Python scripts to extract data from the Facebook page then we need to install Python interpreter to execute them.Installation instructions will vary depending on whether you are using Mac OS X,Linux/UNIX or Windows.I will cover the installation in brief.But it is very easy and there is a lot of detailed instructions online incase you can’t.

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.)

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’.

Fuzion tank t20. 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’: Srimad bhagavata purana in kannada pdf.

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Knowing this we can create the correct XPath query and use the lxmlxpath function like this:

Let’s see what we got exactly:

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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.

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.