Web crawling - How to crawl Google without risk of blocking

Google Scraping

Currently, web scraping is becoming critically important for any business seeking to gain a competitive advantage. It provides rapid and efficient data collection from various sources, becoming a key element in developing advanced business and marketing strategies.

Approached seriously, web scraping rarely causes problems. However, without adhering to the best web scraping practices, the likelihood of blocking increases. Therefore, we are here to share with you effective ways of avoiding blocking while scraping Google.

What is scraping?

In simple terms, web scraping is the process of collecting publicly available data from websites. Of course, this can be done manually - all you need is to know how to copy and paste the necessary information and have a spreadsheet to track it. However, to save time and financial resources, both individuals and companies prefer automated web scraping, when publicly available information is extracted using specialized tools. We are talking about web scrapers, chosen by those who want to collect data quickly and with less expenditure.

Although there are many companies offering web scraping tools, they are often complex to use and sometimes limited for certain purposes. Even when you find a tool that seems perfect, it does not guarantee 100% success.

To make things easier for everyone, we have developed a set of powerful scraping tools.

Why is scraping important for your business?

It goes without saying that Google is the largest repository of information where you can find everything: from fresh market statistics and trends to customer reviews and product prices. Therefore, to use this data for business purposes, companies perform data scraping that allows extracting information.

Here are a few popular ways companies use Google scraping to stimulate business growth:

• Monitoring and analyzing competitors
• Sentiment analysis
• Business research and lead generation

Now let's move on to the purpose of your presence here - to learn about effective ways to avoid blocking when searching on Google.

8 Ways to Avoid Blocking While Scraping Google

Anyone who has ever tried web scraping knows that this can be quite tricky, especially if you lack knowledge of the best web scraping practices.

Therefore, here is a specially compiled list of tips to help ensure your future scraping activity is successful:

Rotate IP addresses

Refusing to use IP address rotation is a mistake that can help anti-scraping technologies to detect you. This is due to the fact that sending too many requests from the same IP address usually makes the target consider you a threat, or, in other words, a scrape bot.

In addition, rotating IP addresses makes you look like several unique users, which significantly reduces the likelihood of running into a CAPTCHA or, even worse, being banned. To avoid using the same IP for different requests, you can try using Google Search API with advanced proxy rotation. This will allow you to scan most targets without any problems and enjoy 100% success.

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Use real user agents

A user agent, a type of HTTP request header, contains information about the type of browser and operating system and is included in the HTTP request sent to the web server. Some websites can analyze, easily detect and block suspicious sets of HTTP(S) headers that do not resemble header sets sent by organic users.

Thus, one of the important steps to take before extracting Google data is to create a set of headers similar to organic ones. This will allow your web scanner to look like a legitimate visitor. To simplify your search, check out this list of the most common user agents.

It is also advisable to switch between several user agents so that there is no sudden increase in the number of requests from one user agent to a particular website. As with IP addresses, using the same user agent makes it easier to identify it as a bot and triggers a block.

Use a headless browser

Some of the most complex Google targets use extensions, web fonts, and other variables that can be tracked by running Javascript in the end user's browser to determine whether requests are legitimate and come from a real user.

To successfully extract data from these websites, you may need a headless browser. It will work just like any other browser; only the headless browser won't be configured with a graphical user interface (GUI). This means that such a browser will not display all the dynamic content necessary for the user to operate, which, in the end, will prevent you from being blocked when collecting data at high speed.

Use CAPTCHA solvers

CAPTCHA solvers are specific services capable of decoding tedious puzzles encountered when moving to a particular page or website. There are two types of these puzzles:

• Human method - here, people perform tasks and send you the results;
• Automated - here, powerful artificial intelligence and machine learning technology are used to identify and solve the puzzle without direct human intervention.

Since CAPTCHAs are widely used on websites looking to ensure that their visitors are real people, it's important to apply CAPTCHA solvers during the scraping process. They will help you quickly overcome these obstacles and, most importantly, will allow you to scrape without fear.

Slow down scraping and set intervals between requests

While manual data collection takes a lot of time, scraping bots are capable of doing this at high speed. However, super-fast requests are unnecessary - sites may get overloaded due to increased inbound traffic, and you may be blocked for reckless scraping.

For this reason, evenly distributing requests over time is another key rule for avoiding blocking. You can also add random delays between different requests to prevent the creation of a scraping pattern that can be easily detected by sites and lead to undesirable blocking.

Another useful concept to apply in your scraping activity is data collection scheduling. For example, you can pre-arrange a scrapping schedule, and then use it to send requests at a constant pace. This way, the process will be properly organized, and you are less likely to send requests too quickly or distribute them unevenly.

Detecting Changes on a Website

Data extraction is not the final step in data collection. One must not forget about parsing - the process in which raw data are analyzed to filter out the required information, which can be organized into different data formats. Like web scraping, data parsing also encounters problems. One such problem is the changing structure of web pages.

Websites cannot always be static. Their layouts are updated to add new features, improve user experience, renew the brand's appearance, and so forth. While these changes enhance user interactions with the sites, they can also cause parser failures. The main reason is that parsers are typically designed based on a specific web page design. If the web design changes, the parser won't be able to extract the data you expect without prior adjustments.

Hence, you need to be able to detect and track changes on a website. The most common way to do it is to monitor the parser performance: if its ability to parse certain fields drops, this probably indicates that the site's structure has changed.

Avoid Scraping Images

It's no secret that images are significant data-bearing objects. How can this impact the image extraction process?

Firstly, image scraping requires a lot of storage space and additional bandwidth. Moreover, images are usually loaded as Javascript fragments execute in the user's browser. This can complicate the data collection process and slow down the scraper's operation.

Extracting Data from Google's Cache

Lastly, extracting data from Google's cache is another possible way to avoid blockages during scraping. In this case, you have to make a request not to the website itself, but to its cached version.

Although this method seems reliable, as it doesn't require direct access to the website, keep in mind that it is only suitable for purposes that don't involve confidential information that may change over time.

Conclusion

Google scraping is an activity many companies undertake to get publicly available data necessary for improving their strategies and making informed decisions. However, remember that scraping requires a lot of effort if you want to do it consistently.