Table of Contents
- What is website scraping?
- How does website scraping work?
- Who is website scraping for exactly?
- Why is website scraping important?
- What you can expect from website scraping?
- Use cases and examples of website scraping
- What are the benefits of website scraping?
- How to scrape websites with Python
There are many different sources of data on the Internet today including web pages, RSS feeds, and web services. Most websites and online sources of data provide access to their data to users via a web browser. This means that users could only view it on the screen or copy and paste it to another application. If a user wants to collect and use a large amount of data, this can be a tedious and painstaking process.
Knowing how to scrape websites for data is the solution to solve this problem. Web scraping, also known as harvesting or extraction, is a technique used by developers to extract data from these sources. Then applications process and make use of it in other ways.
What is website scraping?
Web scraping is a process performed by software that automatically loads, extracts, and processes large amounts of data from websites. Software can collect any and all data from any website that the user chooses.
Some websites put mechanisms in place in an attempt to prevent scraping. Examples of such methods include detecting and blocking bots from crawling their pages. There are counter methods that scrapers use to circumvent such mechanisms.
How does website scraping work?
Software calls the URL for the desired web page. The web server returns all of the HTML code to the application. The software then loads the code into memory and processes it according to the specific technique. It extracts the specified content and exports it into a format and location specified by the software. Common formats are Excel, CSV, databases, XML, or JSON files.
Developers that want to learn how to scrape websites for data should become familiar with several variations of the technique, including:
Text pattern matching: a simple approach to extracting data from web pages that uses methods like regular expressions with programming languages like Python or Perl.
HTTP programming: a technique that makes use of socket programming to post HTTP requests to remove web servers to retrieve web page content.
HTML parsing: a technique that extracts content from common templates and exports them into other formats.
DOM parsing: a technique that enables a full web browser into the application and makes use of the browser’s Document Object Model parsing capabilities to extract parts of the web pages.
There is also off-the-shelf software that users can download and install on their computer or web browser that does the scraping for them. This software is often generic and made for broad audiences and wide use cases and may not solve specific, niche needs.
Who is website scraping for exactly?
Scraping techniques are important for developers or businesses that need to utilize large amounts of data from the Internet. Many industries and careers require web scraping skills, both in technology industries and non-tech sectors. Typical positions include software engineers, data scientists, and machine learning research engineers. Web scraping is also important for sales and account management professionals, likely for use in generating leads and contact information.
Why is website scraping important?
Manually loading websites in browsers and copying and pasting is not an efficient or effective way to collect and store data. Scraping software enables an automated and repeatable process that runs as often as needed without human intervention.
What you can expect from website scraping?
Scraping is not magic, although it may seem like it to the uninitiated. Depending on the technique used, the user must configure scraping software properly to parse the specific source correctly to extract the specific data desired. You can’t just point the software at “the Internet” and expect to get back the data you want. Users must configure the criteria for each website they want to scrape and for each portion of the website.
Use cases and examples of website scraping
News aggregation: aggregators collect news and other data from around the web and present it in a unified experience. An example of a news aggregator is Google News.
Extracting product details: companies can use web scrapers to collect product information including availability, price, and more to perform market analysis and improve their own offerings.
Competition monitoring: businesses can keep an eye on the competition by using web scrapers on competitor websites to look for new product launches, press releases, or other important announcements.
Business contact details for marketing and lead gen: web scrapers can extract contact details including email addresses, names, phone numbers, website URLs, and more from sites like LinkedIn or yellowpages.com.
Extracting property details from real estate websites: real estate market participants can use web scrapers to collect important market data including recent sales, current prices, and more.
Research: web scrapers can collect and store data that researchers analyze, whether it be medical, marketing, academic, or scientific.
What are the benefits of website scraping?
Web scraping allows individuals and businesses to collect and process data from the web at a scale and volume that wouldn’t be achievable by humans. Extracted data can inform critical business processes to improve customer experiences, inform business and product strategy, or enable research that wouldn’t be possible otherwise.
How to scrape websites with Python
Python is one of the most popular programming languages right now. It’s used across industries for many different purposes and it’s one of the best languages to learn how to scrape websites.
Urllib2: a module used to fetch URLs
Beautiful Soup: a package used to extract parse data from web pages
Using Urllib2 is simple. Once you include the library, you can retrieve web pages with a single get command.
Once you have the HTML using Urllib2, Beautiful Soup makes it easy to navigate the data structure and retrieve certain elements. Here are some common features of the package:
- Find all links with a tags
- Find elements by class name
- Find elements by ID
With these two libraries, a developer can easily retrieve a web page and extract the data that they want. Learning how to scrape websites with Python is a breeze with these two libraries.
Website scraping is a common and popular technique that developers use to collect data from around the web. That data is then processed to extract the desired information and stored in a format for future use. Some common use cases include marketing, lead generation, and research. There are a variety of methods, tools, and programming languages used by developers.