You open a website. The data you need is right there, laid out in rows, clearly labeled, exactly what your project requires. Then you realize you have to get it out of the page and into a spreadsheet, and that is where things stop being simple. Copying row by row is not realistic if there are hundreds of results. Building a scraper requires knowing how the site is structured in code. Hiring someone to do it takes time and budget you may not have. And if the site updates its layout next month,...

Most developers who integrate the Minexa API use it the same way: train a scraper, pass some URLs, get structured JSON back. That covers the basics. But there is a wider set of capabilities built into the API that rarely gets used, either because it is not obvious from the docs or because the default setup already works well enough that no one goes looking further. This article covers ten of those capabilities, with enough detail to know when each one is worth reaching for. 1. The scraper ID...

Most scraping pipelines break. Not dramatically, not all at once, but steadily. A site updates its layout, a field shifts position, a column name changes, and suddenly the data your pipeline has been collecting quietly for three months is wrong. Nobody noticed until someone checked. The assumption baked into most scraping tooling is that maintenance is inevitable. You build, it breaks, you fix, repeat. That assumption shapes how teams budget engineering time, how they think about reliability,...