The internet has significantly disrupted human lives. No other technology innovation has touched so many people, impacted so many businesses as the internet has. Today, if we look around us, we will see people logging on to the internet for practically everything in their daily lives. Be it shopping, finding new places, booking cabs, or even dating, the internet has proved to be a boon to many. Thus, it is no surprise that the rate of adoption of this technology solution has been at an all- time high. With the introduction of smartphones, people now have the added convenience of accessing the internet through their mobile devices. This has further fueled the amount of people embracing the internet for making their lives simpler or better. In this blog, we will learn how to build a web scraper.
For businesses, this rapid proliferation of internet coupled with rapidly falling bandwidth rentals means better opportunities over the virtual space to capitalize on their business ventures. This is why many digital businesses have set up a huge scale of operations globally to cater to the burgeoning online user segment. They can set up their websites and give momentum to their digital marketing needs. What this also denotes is that a large amount of information is present on the entire ecosystem. Using smart methods, a company can harvest this information for various purposes – competitive intelligence, market segmentation, and customer behaviour analysis, to name a few.
Web scraping is one such smart method that seeks to bring together information from diverse sources into a single place in a pre-defined format. This activity helps to strengthen the online intelligence gathering mechanism of an enterprise and gives valuable insights on various success drivers of a product or service. The three key elements tracked by a web scraping service are –
- The published content–The information from web pages are extracted and retrieved
- Usage parameters–The information from browser type, activity, or server logs are collected
- Structure data–The information from interlinks between people, connections, and pages data.
Benefits of Web Scraping
Web scraping provides innumerable benefits to a company using it in a structured and meaningful manner. Multiple use cases highlight how web scraping can add value to people’s lives. A solution like Instapaper is a great way for saving content as and when you access it. It employs screen scraping to save a copy of the website on your phone. This facilitates consumption of content for reading on the go. Another interesting example is Mint.com that accesses your bank details after your approval and then visualises data around your financial summary in interesting ways. This helps users gain insights on trends and patterns in consumption, savings, investment, and spending.
Other than this, there are other crucial benefits of web scraping as under:
1. Your company can easily share notifications on the latest trends to their customers. Parameters like price changes, lowest prices, on-going deals, and new product launches are what drives customers to get a win-win deal and thus help them stay loyal to your brand. In the case of accurate web scraping, your brand stands a better chance of gaining repeat and referral business.
2. Your company can carry out smart pricing intelligence. With web scraping, you can compare prices of a product with that of the competitors. This lets you post the best prices with the aim to enable conversions better.
3. Multiple pointers on users’ preferences, behaviours, the trends they follow, and their pain points, can come out clearly through web scraping. This lets marketers devise personalised marketing messages and advertisements. As an outcome, your brand can witness faster conversions aided by a higher degree of customer engagement.
4. E-retail and virtual banking can provide better servicing to the clients. By employing web scraping, they can get the latest rate of exchange, stock exchange quotes, and interest rates.
5. With web scraping, you can extract data from both static and dynamic websites
1. Some nefarious organizations can go into unethical territory with web scraping. The automated bots may read the websites quicker than normal human comprehension speed. In turn, this causes severe strain on the destination site’s servers. In order to protect from service issues, these target websites may simply disallow a bot to crawl through their sites, thus rendering the web scraping process ineffective.
2. These non-professional entities may also breach into violations of copyright, intellectual property, and trademarks. This happens when they crawl the website and post the extracted content on their own website, which is in effect, stealing.
Professional solutions providers will always take care to see that they crawl websites at regular intervals rather than doing all the – scraping at one go. They will also comply with the terms and conditions listed on the destination website.
How to build a web crawling tool?
The below is the minimum configuration or setup needed to design a web scraper
1. HTTP Fetcher: This will extract the webpages from the target site servers
2. Dedup: This makes sure that the same content is not extracted more than once
3. Extractor: URL retrieval system from external links
4. URL Queue Manager: This lines up and prioritizes the URLs to be fetched and parsed.
5. Database: The place where the data extracted by web scraping will be stored for further processing or analysis.
We are looking specifically at crawling multiple websites. In this case, you would need to look at maintaining the integrity of the scraper program while keeping its efficiency and productivity high. By crawling huge scale websites, you need to factor in various aspects –
1. I/O mechanism
2. Multi-threading architecture
3. Crawl depth setting
4. DNS resolving
5. Robots.txt management
6. Request rate management
7. Support for non-HTML media
9. Canonicalization of URL for unique parsing
10. Distributed crawling mechanism
11. Server communication
In addition, we need to ensure that the choice of programming language is correct so that we can extract maximum utility from the web scraper. Many prefer Python and Perl to do most of the heavy lifting in the scraping exercise. Here, you will learn how to build a web scraper.
Building a Simple Crawler
Before we commence, it is important to note that this will be a simple crawler covering one machine in a single thread. The HTTP Get Request is the key to extracting information from a particular URL. The key steps that are carried out by a crawler will include. Now you will learn how to build a web scraper.
1. Begin with a list of websites we need the crawler to crawl
2. For each of the URL in the list, the crawler will issue a ‘HTTP Get Request’ and retrieve the web page content
3. Parse the HTML content of a page and retrieve the probable URLs the crawler needs to crawl
4. Update the list of websites with new URLs and continue crawling with the program
It is interesting to note that depending on the type of objectives you need to accomplish, the crawler needs to be integrated with a third-party application to help automate the generation of new URLs to the list. For instance, a third- party application continuously tracks RSS feeds based on a topic of interest. When it encounters a URL that has content around this topic, it can add the URL to the list. Now you have learned how to build a web scraper.
For a crawler to work successfully, it needs to respect the server load it will place on the URL it requests. You need to decide the crawling frequency of your program so that you can build a web scraper that is effective. Crawling one to two times a day can be called a reasonable frequency that ensures that the target site functions properly without facing crash due to server overload from repeated requests.
It is evident that a good web scraping program is a boon to modern day businesses of today. It can help companies collect real-time and relevant information to aid in client servicing and actionable insight generation. We looked at how a web scraper program can be built from scratch. We also explored the crucial parameters that need to be followed so that the scraper program extracts information without putting load constraints on the destination site’s servers. Now, you have learned how to build a web scraper.
An effective web scraper needs to counter the many issues related to multi-site crawling, including duplication checking, DNS resolving, multi-threading, and task scheduling to name a few. Once it has factored in the potential problems, it needs to check for issues of copyright, Robots.txt, and intellectual property. These pointers will ensure that you build, operate, and manage an effective web scraping tool with maximum success.