How data parsing works
A parser reads raw input and gives it structure in a few steps. First it tokenizes the text - splits it into meaningful chunks like tags, words, and symbols. Then it builds a model of the document; for HTML that model is a DOM tree (a nested map of every element on the page). From there you point at the pieces you want - usually with CSS selectors or XPath, two query languages for picking elements out of that tree - and convert them into typed values like numbers or dates. The output is a predictable shape, such as one JSON object per product, instead of a wall of markup.
Data parsing in web scraping
After you fetch a page, parsing is where the value gets created. You select the elements that hold each field, pull out their text or attributes, and normalize them - that means cleaning them up so every record looks the same: stripping currency symbols off prices, putting dates in one format, filling in or flagging missing fields. Done well, a single parser can turn thousands of slightly different pages into one clean, uniform dataset.
Getting clean structured output reliably
Parsers are fragile. When a site changes its markup, your selectors stop matching and data quietly disappears - no error, just empty fields. So resilient selectors (ones that don't depend on tiny layout details), validation, and monitoring all matter. To avoid the constant parser-maintenance treadmill, some scraping APIs return already-structured data for common targets, or hand you fully rendered HTML through a web scraping API that's clean enough to parse with a tool like jsoup or Beautiful Soup.