In today's competitive environment, everyone seeks new methods to innovate and utilize new technology to get more advantages. 

A solution for individuals who wish to access structured online data is automatically provided by data scraping, also known as data extraction or web extraction. You can utilize data scraping to collect data from public websites that do not have APIs or allow restricted access.

This article will discuss data scraping, its challenges, and the best practices.

What Is Data Scraping?

Data scraping is a technique for automatically extracting data from websites, databases, business applications, and legacy systems. You can get much useful information for your business by scraping data from the web, including customer evaluations, company contact information, social media updates, and page content. 

Using custom software, you can import and export data from the web into a program that is fully integrated with the resources and processes of your company.

Professionals use numerous tools and techniques to scrape data. They also use it to collect, analyze, or integrate data into a company's systems. When an API is not accessible, scraping is a viable alternative to tedious, inefficient programs or human data input. 

While there are several online scraping applications available, custom scraper development offers a variety of benefits. For example, applications that integrate seamlessly with a company's databases can be built using APIs, a set of programming tools for software developers. 

Is It Legal?

Data scraping is legal if the gathered data is not utilized for immoral reasons. It is common for courts to decide in favor of companies who use web scrapers to access the information of their competitors, even while the data owners have expressed their displeasure with this practice.

However, online scraping would be unlawful if the scraped data caused direct or indirect copyright infringement. For the most part, data scraping and the software that facilitates it are not illegal.

Challenges of Data Scraping

Web scrapers encounter various technical difficulties because of the barriers implemented by data owners to prevent non-humans from accessing their information. The following are some of the difficulties.

Robots.txt

To start scraping a website, users need to check the website's robots.txt, which provides or denies access to URLs and specific content on a website. Robots.txt files state whether the content can be scrapped, and identify a scraping limit to avoid network congestions. 

A scraper will not be able to reach URLs or contents which are blocked by the robots.txt file. However, a user can contact the data owner, provide legitimate reasons for needing the data, and ask for permission to scrape their website.

CAPTCHAs

CAPTCHA is a website security mechanism designed to detect and prevent bots from accessing websites. To keep ticket prices from soaring, CAPTCHAs are mostly employed to restrict service registrations to people. 

However, good bots, such as Googlebot, scan the web to build a searchable index for Google, in case google faces a challenge, adversely affecting SEO tactics. Data scrapers can use a CAPTCHA solution to overcome the test and enable the bot to work on this issue.

IP Blockers

An IP address can be blocked and restrict data access for scraping bots if the site detects a pattern of frequent scraping from that address. To overcome this issue, bot owners can utilize a private proxy to transmit access requests from a new IP address each time they log in.

Dynamic Content

Dynamic content is a kind of web element that adapts to the user's data and activity. Most brands utilize past data and search queries to provide personalized information to their customers. Netflix and Amazon Prime Video, for example, monitor a user's preferences and screen time to provide customized suggestions. 

Web scraping bots designed to scrape static HTML components have a hurdle when dealing with dynamic material. However, it is possible to program a scraping bot to scroll down the website to discover the desired data and extract it.

Website Structure Alterations 

Web scrapers are built to explore a website based on its JavaScript and HTML components, which the website designer can modify to improve the website's appearance and appeal. The scrapers bot cannot gather correct data if the HTML code is altered in any way. Changes to the target website's code will need code modifications.

Honeypots

Honeypots are computing systems designed to lure hackers and prevent them from accessing websites. A honeypot trap is designed to look like a natural element of a website. However, it includes information that an attacker can use. For example, if a scraping bot harvests information from a honeypot trap, it will not get any further information from the website when it does that.

Best Practices

Scraping procedures can be defined as a set of principles and behaviors that you should follow while beginning your scraping process. The following are some recommended web scraping practices to keep in mind.

Maintain Frequency Intervals

Some websites specify a scraper's frequency interval. However, it is important to use it intelligently since not all websites have been tested to withstand huge loads. If you are constantly striking on the server, it can get overloaded and crash or fail to respond to other requests. 

As a result, you should either use a delay of 10 seconds or make the queries at the intervals provided in robots.txt. This ensures that you will not be banned from the target site.

Rotate User Agents 

A user agent is a piece of software that notifies the server of the kind of browser used. Websites will not read material if the user agent is not configured. A web browser's user-agent header is included in every request. Therefore, detection of a bot is more likely when the same user agent is used.

In Google's search box, type "what is my user agent?" and you will see your User-Agent. You can only get away with using a bogus User-Agent by making it look more legitimate than it is. Adding a User-Agent to most web scrapers is not automatic. It must be done manually.

Sending User-Agents would be sufficient to get past even the most rudimentary scripts and technologies used to identify bots. However, even if you put in a current User-Agent string, you should add extra request headers if your bots continue to be denied. The User-Agent is not the only header that most browsers transmit to web pages.

The header of every request contains a User-Agent string. This string identifies the browser, version, and platform you are using. Whenever a scraper requests data, the target website can easily verify that the request is from scrapers using the same User-Agent string. Try rotating the User and the Agent between queries to avoid this. The Internet is a great place to get real User-agent strings.

Randomize Scraping Pattern

Many websites have anti-scraping technology, and if you are scraping in the same manner, they will be able to identify it. Normally, people do not follow a pattern on a website. Therefore, your scraper will function more smoothly if you include mouse movements and visiting random links.

Use Canonical URLs

When we scrape, we often wind up scraping the same URLs repeatedly, which should not be done at all. It is possible to acquire numerous URLs with the same data on a single page. 

A canonical URL, which links to the parent or the original URL, will be established in this case. This ensures that we do not end up with a bunch of duplicate stuff. Scrapy and similar frameworks take care of URL duplication by default.

Use Off-Peak Hours

Off-peak hours are ideal for scrapers and bots since there is less traffic on the website. The geolocation from which the site's traffic comes can identify these hours. This also helps speed up the scraping process and reduce the strain on the server. As a result, scrapers should be scheduled to operate when traffic is low.

Use Headless Browsers

Web servers can tell whether a request is from a genuine browser based on the URL. They can use this to prevent your IPs from being blocked. Fortunately, Headless browsers include built-in browser capabilities to solve the issue. 

However, in certain circumstances, browser automation is required to extract data. JavaScript-related issues can be solved using built-in browser tools on headless browsers. Puppeteer, playwright, Selenium, CasperJS, PhantomJS, and many more browser automation libraries are readily available.

Inspect Modified Website Layouts

Scrapers can have difficulty accessing certain websites since they bring up different layouts.

For example, pages 1-20 can show a layout, but the remainder might show something different. Check whether your data is scraped using CSS selectors or XPaths to avoid this. If this is not the case, look at how the layout varies and modify your code to scrape those sites differently.

Use Captcha Solving Services

Anti-web scraping methods are common on many websites. Eventually, a website will ban you if you are scraping a lot of data from it. You will notice that you will encounter captcha pages instead of online sites. 2Captcha and AntiCaptcha are two services that allow you to bypass these limitations.

Using a captcha service is preferable to scraping Captcha websites. Large-scale scrapes benefit from the low cost of captcha services.

Conclusion

The absence of readily available data is one of the primary reasons for data scraping. The importance of data-driven research, insights, and strategies cannot be overstated when starting and growing a business. 

Businesses now rely on data and the quality of that data. That is why it is necessary to choose high-quality scrapers that can collect accurate data. While scraping online data is lawful, there are several difficulties. However, numerous options are available to assist in achieving the goal. But, it would be best if you scrape with care and not overload the site. Good Luck!