If you’re thinking about taking your business to the next level, you’re probably considering web scraping. Data gathering can be highly beneficial for companies since it helps make data-driven decisions, learn more about your competitors, and track your company’s performance.
There are different web scraping techniques that you should know about. We’ll look into the most popular ones and review what web scraping automation tools are the best for different needs. We’ll also discuss what role proxies play when it comes to data collection.
But first of all, let’s revisit what web scraping means.
What is Web Scraping?
Web scraping is a process of automatically collecting web data. The data may include any information on a website, such as text, images, videos, etc.
The term web scraping has many synonyms, and some of them may be familiar to you: data collection, data extraction, data mining, etc. Web scraping is sometimes used interchangeably with data crawling, but these two terms are not the same.
To help you better understand the term, let’s look into how web scraping works. If manual scraping means selecting web elements, clicking on them, copying and pasting them into a spreadsheet, web scraping is the same process, just automated. It’s considerably faster than manual scraping because scrapers can quickly gather information from many websites simultaneously.
Web scraping is performed by computer programs. Those who need to gather large amounts of data can choose between different web scraping techniques, depending on their needs, knowledge, and resources.
Web Scraping Techniques
Before we dive into web scraping techniques, keep in mind that here we’re only covering automated web scraping software. The only technique for manual scraping is copy-pasting, and that’s pretty straightforward.
1. Web Scraping with Selenium
Selenium is a free and open-source testing framework. It’s powerful and has a number of features that can be used for web scraping, website testing, or automating tasks on a web browser. Selenium is also used to emulate AJax calls in web scraping.
The browser automation tool works by mimicking a regular user’s behavior on a website, and that’s why it’s a highly effective web scraping technique. It’s perfect for scraping text and images at large volumes and is relatively easy to use once you’ve got some practice.
2. Web Scraping with DOM Parsing
Document Object Model, or DOM, can be used in web scraping to provide a wholesome view of a website’s structure. HTML parsing essentially means parsing a page into a DOM tree. Scrapers can target selected DOM components and process or store the content in a particular DOM element of a website.
A DOM parser can be used to extract nodes with information, and then a tool such as XPath can scrape data from websites. Different web browsers, such as Internet Explorer or Firefox, can be embedded into a DOM parser to extract an entire web page.
3. Data Collection Using XPath
XPath, or XML Path, is a query language. It’s used to navigate XML documents because of their structure, which is tree-like. XPath allows selecting specific nodes to include or exclude on different parameters. Use XPath with a DOM parser if you wish to scrape data from an entire web page.
4. Extracting Data with CSS Selectors
CSS selectors have a similar function to XPath in regards to selecting HTML document parts. They’re patterns to select or match the elements that need to be extracted. Some developers prefer XPath, others choose CSS Selectors, but essentially it depends on your target web pages.
5. Extracting Data with CSS Selectors
If you don’t have the resources to build and maintain a scraper, you can always choose an already built tool that will do the work for you. Depending on the tool, it can only ask you to provide URLs of your targets, while others, open-source web scraping tools, may require slightly more input.
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Popular Automated Web Scraping Tools
We listed three ready-to-use web scraping technologies and three open-source choices.
Ready-to-Use Web Scraping Tools
With these tools, you don’t need strong coding skills. In most cases, you can simply provide a list of URLs and what data you need to extract data from them. The scraper will then do the job and return results for you.
- Octoparse helps easily extract data into spreadsheets. It doesn’t require any coding skills and conveniently returns scraped data in your preferred format. The tool can scrape data from dynamic pages, including drop-downs, infinite scrolls, and AJAX.
Open-Source Web Scrapers
Open-source web scraping tools are free and require coding knowledge. You can adjust scrapers based on your needs and development skills and use them with proxies of your choice.
- Scrapy is a web scraping and crawling framework written in Python. It’s used for large-scale web scraping operations. The tool can cover data extraction, its processing, and storage in a preferred structure and format.
- BS4 or BeautifulSoup4 is a Python library that helps extract data from HTML and XML documents. Since it’s a widely used web scraping library, it has loads of tutorials online. There’s a large community of BeautifulSoup users who can help you out if you run into any issues.
- ApacheNutch is a highly-scalable open-source web crawler software. It’s coded in Java, but data is written in formats that aren’t dependent on a programming language. The tool is highly customizable, allowing developers to add plugins for media-type parsing, querying, clustering, and retrieving data.
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Proxies and Web Scraping
Proxies are an essential component for any web scraping tool. Without proxies, scrapers would easily get blocked sometimes without even getting a chance to extract any data.
Depending on web scraping targets, the most popular proxy types for scrapers are datacenter and residential IPs:
- Datacenter proxies are faster and cheaper than other types of proxies. They’re also easier to be identified as proxies since they come from datacenters. But datacenter IPs are the best option for large web scraping projects due to their speed and price.
- Residential proxies are slow and expensive compared to datacenter IPs. However, they’re more difficult to be identified as proxies since they’re real IP addresses connected to residential locations. These proxies are mostly used for lower-scale web scraping projects.
If you’re launching a high-scale web scraping project, the best proxies for your case are datacenter ones.
In this guide, we covered the definition of web scraping, briefly mentioned what companies use scrapers for, and the difference between automated and manual scraping.
Web scraping has a number of different techniques. Which one to pick depends on your data extraction needs. You can choose between ready-to-use tools that take care of automatically extracting data and don’t require much upkeep. However, these are less customizable. Another option is building a scraper that you can customize to suit your needs. Keep in mind that an in-house scraper will need constant upkeep.
Whatever technique you pick, web scrapers will need proxies to be able to gather information without getting blocked. Depending on your targets, you can choose between residential and datacenter proxies. The latter are faster and cheaper than the former.
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