In the global digitized marketplace, companies and products have potential rivals in every region of the world. As such, they may require competitor analysis, competitor data, and similar data from many regions.
Thankfully, online shops, marketplaces, and aggregated evaluation sites allow companies to access needed data online. Web scraping helps businesses collect this data from web pages automatically instead of manually copying them. However, the more data a company scales its web scraping to deal with, the more complex the process gets.
Thus, learning techniques to make scaling more efficient is as necessary as the scraping itself. In this article, we explore how web scraping works, the challenges it faces, and best practices and techniques to aid its scaling.
How Does Web Scraping Work?
With the importance of data and web scraping aside, how does web scraping work? Businesses that don’t have in-house experts handling the data collection might struggle when they come upon difficulties. However, having a better grasp of the process could point to where things might be breaking down. And this aids the search for a solution. Here is a simple breakdown of the process through which a scraper extracts data from a webpage:
- Sending of Request. The web scraper sends an HTTP request to the target website for access to a specific page, as represented in the URL.
- HTML Content Response. Upon receiving the request, the website’s server responds to the scraper with the HTML code of the webpage in question. The code contains the structure and content of the page.
- Parsing of the HTML Content. Every web scraper has a configuration or setting that guides identification, extraction, and data download. Based on this configuration, the web scraper parses the HTML code and locates the relevant data.
- Extraction of Identified Data. After identifying the data, the scraper extracts it from the HTML file in the chosen format.
- Storing and Processing of Data. The final step involves saving the extracted data onto a local file or database for further analysis.
Challenges to Scaling Web Scraping Operations
Scaling web scraping operations involves increasing the volume of data you want to extract, the number of websites you are extracting from, or the complexity of the data you need. Therefore, companies scaling up might encounter new problems that need solving in their scraping operation. Some of these problems include:
- Increased strain on server speed and resources due to higher data volume.
- Websites limit the rate of requests from specific IP addresses because they are too frequent. Websites that identify frequent requests originating from a certain location might reduce the rate for requests from the address. Such a measure serves to limit the usage of the website’s server by a single user or bot.
- Blocking of IP addresses. Websites that notice suspicious requests may also decide to block requests from that address temporarily or permanently. Businesses looking to scale their scraping operation predict this and employ web unblocking tools, such as Oxylabs’ Web Unblocker, or rotating proxies as needed.
- Changes to the structure of content. Any update to the structure of a website could affect the ability of the scraper to identify and extract relevant data. Such issues would require the human mind behind the scraping operation to reconfigure the tool.
- Decreases in data quality. Any update to website design and structure may add new elements to the preexisting data. A consequence of that is it could put off the configuration of the scraper, lead to parsing errors, and finally, decrease in data quality.
- Captcha challenges and other anti-scraping defense mechanisms. As the scale of a scraping operation increases, so does the likelihood of a scraper coming across an anti-scraping measure. Along with captcha challenges, other challenging measures include honeypots, JavaScript rendering, the addition of randomized data elements, etc.
Techniques And Ultimate Practices For Scaling Web Scraping Operations
The following are tips on how to make your web scraping operation more effective and efficient:
- Choosing the right tools. Beyond just picking a reliable web scraper, the additional tools you employ should consider the challenges the scraper may face. For instance, a business should use a headless browser when scraping JavaScript-rendered content, proxies to reduce IP blocking and escape geo-restrictions, or a streamlined two-in-one solution like Web Unblocker.
- Monitor and debug the process regularly. Businesses thrive on insights obtained from analyzing data. Such analysis should be treated as a continuous exercise if businesses are to benefit optimally. Monitoring the process for errors should be a part of the long-term scraping strategy.
- Respecting the website’s policies. Websites tend to have policies to regulate user activity. For instance, websites might have robot.txt files to indicate permitted paths for scraping. Following such rules, reducing the frequency and concurrency of scraping, etc, helps improve website performance and reduce the likelihood of IP bans on scrapers.
Conclusion
Reliable web scrapers, combined with the technical know-how to overcome obstacles, are the winning combo for any scraping operation. However, Web Unblocker can help businesses gain access to an otherwise inaccessible website without having to put manual effort into building an undetectable web scraping infrastructure. That is what makes them essential for scaling any web scraping operation.
