Nowadays, it’s hard to imagine our life without search systems. “If you don’t know something, google it!” – is one of the most popular maxims in our life. But how many people use Google in an optimal way? A lot of developers use google commands to get needed answers as fast as it possible.
Even this is not enough today! Large and small companies need terabytes of data to make their business profitable. It’s necessary to automate the search process and make it reliable to satisfy the user with fresh news, updates or posts. In today’s article we will consider a very helpful tool – Real-Time Crawler (RTC) for the collection of fresh data. Let’s start!
The web scraping topic has been actively growing in popularity for dozens of years now. Freelance sites are overcrowded with orders connected with this contradictory data extracting process. Today we will combine two new and revolutionary directions in web development. So, let’s consider an elegant and modern way to scrape data from websites with Node.js! 
One of these tasks is scraping javascript sites, those that output data using JavaScript. Facing this task, classic scrapers (not all of them though) ignore JS-data and continue their own life-cycle. However, when this little defect becomes a big trouble, developers all over the world take measures. And they did it! Today we consider one of the most awesome tools which scrapes JS-generated data – Splash.
has recently launched a brand new version 7.0, which has turned out to be the most revolutionary upgrade in the past two years, with not only a more user-friendly UI, but also some of the advanced features make web scraping even easier. In this post, I will walk through some of the new features/changes made available in this new version, with respect to how a beginner, even one without any coding background, can approach this web scraping tool. 
Web scraping or crawling is the act of fetching data from a third party website by downloading and parsing the HTML code to extract the data you want. It can be done manually, but generally this term refers to the automated process of downloading the HTML content of a page, parsing/extracting the data, and saving it into a database for further analysis or use. 
