How to scrape huge amounts of data without getting banned
Jan 6, 20206 mins read
Web scraping is the process of automatically extracting a large amount of data from the internet using “scrapers”. These scrapers also called spiders will replace the manual human click and will get the needed data automatically.
The scraper, which is a written code, sends a GET query to the website and then it parses an HTML based on the feedback, then it gets the data needed with that document and saves it in the desired format.
Properly used data is a crucial factor for business growth. The more data a company is utilizing in its market analysis, the wider the perspective it will have for the market, thus improving its market understanding and decision making, giving a company lead over competitors, which all sums up to: More Profit.
Let’s say you sell your brand of products and you want to know how other competitors are doing their pricing, in which geographic regions this product is best-selling, and which time of the year is the peak season for demand.
Platforms such as LinkedIn, Amazon, AliExpress, Facebook, eBay and Instagram contain the largest amount of data and information. Your first choice is to open each page manually and to start saving information by copy-pasting them to your database. But considering the huge amount of data you are dealing with, you will have to go through thousands and millions of pages. Doing this manually is not efficient since it takes a lot of time and effort, and this is when our heroes of the day “Web Scrapers” come into play.
Your scraper will start going through these web pages, collecting and organizing the information and automatically saving them to your database, you will use this data wisely and efficiently, analyzing it, improving your brand, and in no time you’re a millionaire, CONGRATULATIONS. But wait, there is a twist. Even though part of the data you’re going through is public, websites welcome users that visit them to buy products. Also, they welcome crawlers from search engines like google so that they can appear on its first search result page, but since you are not here to buy and you’re not Google, “unconventional” users aiming to extract large amounts of data will not be welcomed and websites will utilize a lot of tools and obstacles to detect and block such users. This is why it is essential to use a reliable scraping tool that will get the work done.
Websites have their own “dos and don’ts” list and it is present in the form of “robot.txt” file. It defines the rules that you must follow while visiting, such as what data to scrape, how much and how often you can scrape. For these websites, one human user is one single client with one IP address with a specific access speed, any unusual behavior involving downloading large amounts of data and performing repetitive tasks and requests in a specific pattern within a specific time that exceeds the usual time from one single user will get you detected and blocked.
Websites set rules like traffic limits and access time limit for each single user, and set robot detection tools like setting password access to data and CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) in addition to traps called honeypot traps in the form of links in the HTML code that are invisible to human users but visible for robot scrapers, in which when the scraper find these links and browses them, the website will realize that the user is not a human and all its requests will be blocked.
This set of obstacles mentioned above is also accompanied by another set of challenges related to the scraper’s algorithm and intelligence, meaning its ability to deal with dynamic websites and websites with changing layout, its accuracy and ability of filtering and getting the required data with speed and efficient time.
A reliable scraper must deal with such obstacles and challenges mentioned above, but how? The scraper’s activity on a website needs to go undetected and masked; this can be done using a rotating proxy. A “Proxy” is a middle gateway between your device and the website, meaning that your activity will be masked and hidden behind the proxy’s IP since your requests are being routed through the other server, that of the proxy. Then, the proxy will keep changing, thus not drawing attention to one single IP.
Many web scraping services rely on proxy management when doing their work, but our Smart backconnect proxy has excelled in this domain, where the proxies we provide are reliable and come not only from data centers but also residential and mobile sources. Also, the bandwidths for these proxies are unlimited, which means that you don’t have to worry about scraping massive pages and downloading as much information as you want.
Moreover, ProxyCrawl has a Crawling API to avoid dealing with proxies and blocks and get raw HTML web data and a Scraper API to auto parse web data. Scraper API of ProxyCrawl uses very smart and efficient machine learning algorithms which enable us to bypass robot detection techniques such as CAPTCHA and other tools websites use, not to mention our easy to use application programming interface (API) which enables you to start working in less than 5 minutes.
You can work on developing you own web scraper, but keep in mind that it can be challenging and you might face a lot of downs and falls during this process. Going after big data will be easier using an already proven reliable service like ProxyCrawl.