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Web crawling has become a necessity for the travel and e-commerce sector to monitor prices across hundreds of websites and thousands of subcategories constantly. It ensures that the prices on their own website are attractive enough. The problem with these two sectors is that prices update frequently based on the demand-supply gap. Hence live crawling is the go-to solution for the sectors, to crawl multiple source websites and extract data ‘live’ for their business portals.
Had you been downloading and storing all the data in cloud storage or on-site, you would have needed either expensive storage hardware or a cloud-based service provider. This is averted since you will be scraping the web and displaying the data in real-time, and there’s no need to store data for millions of listings. At most, you could store data for recent searches, so as to make the process faster.
With real-time search based web scraping, there is no more need to run the data scraper engine after frequent intervals to update all pre-existing data. This will reduce your costs considerably since you only need to crawl whatever is searched.
If you web crawl and update your data after fixed intervals, there’s a chance that some updates in data might not happen on time and people might be seeing stale data. This would lead to an unfavourable experience, and they might not return to your website a second time. This is averted with real-time search based web scraping, called live scraping or live crawl.
Adding new items won’t take any extra work since as long as the sources (the websites where you are grabbing data from) are updated, your search based crawling algorithm should work fine for any new items. As for adding a new website to your arsenal, all you need to do is specify how the webcrawling mechanism would work for one product and the same will be replicated for any product that is searched.
Since you will be scraping websites in real-time, network lapses can prove fatal to your business model. Your network connectivity has to be at its best at all times.
Today’s customers are impatient and would not like to wait even for a few seconds for prices to load. Hence the scraping has to be fast enough, so that there is a little time gap between the search and the display of results. Even if there is a second or two-time gap, it has to be made up with some sort of transition or animation, so that the customer doesn’t think that the prices are loading or that he or she is waiting for the website to load some data.
If you want to do even better than what is suggested in the previous point, you should be doing the search based live scraping (real-time scraping) even while the customer is typing. This can be handled in several ways, such as time gap – if he stops while typing you send a crawl request, or space gap–when he presses his spacebar you send whatever is typed till then, to be crawled and scraped. This way, you will be loading the extracted data faster but incurring more processing costs.
In case the structure of a website changes, or if its server is down, you will have no access to its data since you have not been storing any data. Hence you will be coming up only with blanks for any product/ service for that particular website.
Every website has a specific structure of the HTML page in which its product is displayed (called the product page). Once you can ascertain the structure, you can write a program that will send a request with a browser as a header, get back the HTML page, and then go through the HTML page automatically so as to capture data fields.
Once you have this hard-coded algorithm in place, the rest is taken care of. No matter which item is searched for, the website will be requested to return the HTML page for that specific product, and the HTML page again will be scraped for data.
Price comparison happens best when the data is available in real-time, and that is what customers want most. This is done through real-time crawling and scraping, aka live crawlers. With faster scraping techniques in programming languages such as R and Python, live scraping is taking over other sectors as well, such as news aggregators and advertisements.
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