The process of turning raw data into an organized well-structured representation is known as Data Parsers, an important part of web scraping. During programming, there are two parts in data parsing:
To parse the data, we need to understand two things:
When data is scraped, it is in HTML form as a whole, which includes complex expressions that only machines can understand and convert into a webpage. Extracting useful information from HTML can be next to impossible if done manually. This is where data parsing comes in, it reads the HTML code and filters unwanted expressions and information from the raw data, leaving only relevant details which were required by the user.
As the need to obtain information grew, many developers started working to develop standardized software-based data parsers that could be used commercially for those who want to obtain data. Through rigorous testing and widespread use, these data parsers have become an integral part of the web scraping world. Organizations invest in self-built data parsers so that their competitors are unaware of their extraction parameters.
Data parsers can both be self-built or bought from service providers easily, but it’s important to know about the benefits of each option.
If you are thinking of parsing a simple webpage, follow these steps:
In either way, the HTML source needs to be downloaded before the parser can extract the desired elements from the source. Information is then stored according to the user’s required format. In the case of multiple pages, the user needs to consider a good crawling logic for easy navigation.
If the user is working on a smaller scale, then data parsing is a simple straightforward task, but can easily spiral out of control if the parameters are not provided logically. Some challenges related to data parsing that need to be considered are:
Data parsing has become the most important element with regards to web scraping and many people are employing the use of web crawlers and data parsers to extract information for themselves or other people for increasing the competitive advantage or boost revenues. With parsing, users can experience easy navigation through an ocean of data, saving time and effort by picking the relevant information that proves beneficial to them in the long run.