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Web scraping is the process of extracting data from web resources like websites, RSS feeds or clean web APIs. Also, it can be done manually by users using web browsers and some of their scraping extensions. But it could be time consuming and boring task. Still, if we decide to scrape all the required data manually, it may not be relevant or make sense by that time. So mostly these activities are automated by implementing processes such as web scraping bots or web crawlers.
Before exploring the above techniques, the first question might come to your mind that why do we need it. To answer that question, first, you might have heard recently about buzzwords like Data Analytics, Machine learning or Artificial Intelligence, etc. So to do these analytics first we need to gather data. If there are no good amount of different data sets available then there is not much use of this analysis. Let say you want to provide recommendations, reports, deeper insight into application data by showing some relationship between different data points to make business decisions easier and more correct. To build such a system big, proper and diverse data set is key to it.
Web scraping bots help to extract specific data from web resources whereas web crawlers extract the relevant data as well. To set up and create such bots you would need basic programming knowledge. There are few browser extensions also easily available which requires no / less programming knowledge but it has its own constraints. Mainly it works well with tabular type data extraction only. Also, some websites don’t provide clean APIs to access application data. Either case programmatically developed scraping bots work better.
In this blog, you would get to know about web scraping libraries and you might start developing one for your need using them in the near future. Keep in mind one thing, before extracting data from any web resources first to check their usage policies. Some websites don’t want to be scraped and used their data by any third party user freely without their consent. So go through their policies carefully and respect it by avoiding scraping such websites.
You can start building such web scraping bots in your choice of programming languages. There are many good libraries available that provide a standard set of features to ease our efforts.
For example, If you are familiar with Python then have look at the Beautiful soap library. If you want to build bots in Java then checkout Jsoup, Selenium web driver, etc.
Jsoup and all other libraries are nothing but Html DOM parsers and provide convenient API for extracting and manipulating data. It has many capabilities like a scrape and parses HTML webpages from web URL, saved web page file or HTML code text. It provides a handy range of selector functions (like CSS selectors) to find and extract required data by traversing DOM. Also, you can easily manipulate HTML elements, their attributes and text values.
In the next blog, we will try to scrape data from a simple webpage with the Jsoup library to understand how it works and its use cases. I have used it to build web scraping bots and liked it more.
One more thing to mention, though it takes efforts to develop bots once, it makes data freely available to you. By scheduling it you can extract data as and when you want. Automatically gathers incremental data to improve your business model and decisions.
I hope, this helps you to get familiar with Web scraping bots.
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