Web Scraping: Tool for Data Engineering

Mobarak Inuwa 27 Sep, 2022
4 min read

This article was published as a part of the Data Science Blogathon.

Introduction

Have you ever thought of a means to get new data? The usefulness of the topic is one that easily helps other disciplines. Web content could be required in a way that makes it less effective to visit and use a website regularly manually. This might occur in technical circumstances and specific requirements like those in robotics and data engineering. Experience with the web is an advantage in comprehending this article.

What is Web Scraping?

Web scraping allows you to collect content from a site from the back end rather than the usual front end or UI. Instead than reading texts, seeing photos, etc., from a website as they have been built, web scraping then extracts the content directly from the markup language of the webpage. This is done so that tasks needing repetition, iteration, etc. can be automated and completed more effectively. The advantage of is automation.

 

Web Scrapping
Source: Data illustrations by Storyset

Web scraping can be applied diversely. E.g., bots are designed to collect data from web pages, but they do so differently than humans typically do. This enhances their efficiency, quickness, and adaptability. Web scraping can be done for various other reasons, e.g., monitoring market trends, but in this article, we’ll focus on how it can be used to find datasets for data science projects.

Web Scraping for Data Scientists and Engineers

Finding data is important in data science. The more data there is, the more opportunities and possibilities there are to conduct data science projects. Content scraping offers the ability to acquire this information and extend possibilities. Let’s say you want to convert a table from a word document to a site on a website. The table contains toys and includes the names of the toys, sizes, colors, weight, material, and price. One must use table tags in HTML and adhere to the markup for laying out a table to represent this in a site.

Using this information about toys, let’s imagine that this information will be accumulated after business on this site. Since this is a site, web scraping becomes handy.

It could be difficult and time-consuming to extract this information by copying it directly from the front end. Web scraping then becomes the solution. The toys may have images. Imagine continuously downloading thousands of pictures from the internet. While this takes a lot of time and work, a data engineer can retrieve all the images easily.

This is why site scraping is so valuable, rather than attempting to copy and paste the website’s text and downloading the images one at a time.

It offers tools for finding and filtering the contents of websites so you can specify what you want from them. This is because the data engineer may not wish to extract all of the page content fully. In the toy scenario, he might only want to take toys that fall within a certain price range.

Web scraping is also used for social media content, where comments and posts may be taken for profitable commercial endeavors like running advertisements. It applies to email inboxes and folders like spam folders.

How Legal is Web Scraping?

When I started hearing about this subject, this was the first thought that came to mind. It is fairly common to suspect if scraping activity is legal or not. Neither yes nor no applies to this response. This is because certain countries consider it criminal and refer to it as trespassing, despite what some may say. Web scraping should, however, at the very least, continue to be subject to copywriting laws that generally apply to web content. Therefore, before performing online scraping, study the applicable copyright and privacy rules.

Some Challenges of Web Scraping

Despite the efficiency and promise of web scraping, several difficulties could arise. As was already indicated, legal concerns could limit how much web content can be used. Additionally, online scraping may need advanced programming skills. Therefore, data science engineers should have a foundational understanding of web development.

Other issues could arise from safeguards by web developers to protect the privacy or security of web content. This can be achieved by employing strategies like restricting IP addresses based on predetermined standards or turning off particular APIs that might assist the exposure of web content for scraping. Because online scraping may be more effective than manual processes, this may raise a red flag, rendering the activity suspect and allowing it to be banned. The frequent CAPTCHA interruptions could be another typical barrier.

The abovementioned issues might not impact web scraping as a data collection method. This is because web scraping used for data engineering would typically focus on a single page or a small number of pages. However, since we must still rely on the HTML elements and attributes to be laid out in this scenario, some developers may add obtrusive scripts to prevent the free flow of scraping even a single page, necessitating the continued involvement of humans. This will simply remove the benefit of web scraping.

Web Scraping Tools

Data engineers don’t always need to know how to code to perform web scraping. Some tools have been created without coding expertise to make the process easier. They include: Scrape.do, AvesAPI, ParseHub, Import.io, Octoparse, Scrapingdog, Diffbot, ScrapingBee, Grepsr, Scraper API, Scrapy.

In addition to the tools, libraries have been created to support the process via code. Some Python libraries for web scraping include Requests, BeautifulSoup, Scrapy, Selenium, Urllib3, MechanicalSoup, lxml.

Conclusion

Web scraping is the practice of applying automation to change the typical procedure of utilizing web content. Common uses include time savings, data extraction, traffic generation, robot operations, etc. To read websites it engages with HTML. It is lawful in some regions of the world but forbidden in others. Certain circumstances may need retraining of this technique or lessen the advantages.

Key takeaways:

  • Web scraping involves extracting data from the web indirectly using HTML tags instead of the usual front-end interaction.
  • Web scraping assists data in getting goals.
  • Web scraping is legal for most countries because visiting a web directly is legal. Be sure to check your privacy terms before going on.
  • Most websites try to set blockages for web scraping activities.

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Mobarak Inuwa 27 Sep, 2022

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