Web scraping a web page involves fetching it and extracting from it. Fetching is the downloading of a page (which a browser does when a user views a page). Therefore, web crawling is a main component of web scraping, to fetch pages for later processing. Once fetched, then extraction can take place. Since we have defined our purpose of scraping, let us delve into the nitty-gritty of how to actually do all the fun stuff! Before that below are some of the housekeeping instructions regarding installations of packages. Python version: We will be using Python 3.0, however feel free to use Python 2.0 by making slight adjustments. Web Scraping with Python: Collecting More Data from the Modern Web — Book on Amazon. Jose Portilla's Data Science and ML Bootcamp — Course on Udemy. Easiest way to get started with Data Science. Covers Pandas, Matplotlib, Seaborn, Scikit-learn, and a lot of other useful topics. In this tutorial, you'll walk through the main steps of the web scraping process. You'll learn how to write a script that uses Python's requests library to scrape data from a website. You'll also use Beautiful Soup to extract the specific pieces of information that you're interested in. Python web scraping tutorial (with examples) Mokhtar Ebrahim Published: December 5, 2017 Last updated: June 3, 2020 In this tutorial, we will talk about Python web scraping and how to scrape web pages using multiple libraries such as Beautiful Soup, Selenium, and some other magic tools like PhantomJS.

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:

Prinde berea si dezbrac fata 2 hacked. 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. Astropad project blue. 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’.

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

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 Json

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.