Before committing an external API to a production pipeline, developers ask specific questions. Not vague ones about "ease of use" or "scalability" but concrete ones about how the system actually behaves under real conditions. This article answers ten of those questions for the Minexa API, the programmatic interface to Minexa's deterministic DOM-based extraction engine. 1. Do I have to write CSS selectors or XPath to define what to extract? No. The Minexa API does not require

SimplyHired surfaces contract jobs, salary ranges, employer ratings, and benefit details all on a single search results page. Getting that data into a spreadsheet manually takes far longer than it should. This guide shows how to pull it all out using the Minexa.ai Chrome extension, no code required. What data you can extract from SimplyHired The SimplyHired contract jobs search page for Miami, FL returns a rich set of fields per listing. Here is what Minexa pulls out automati

Stock listing pages are full of structured data. Ticker symbols, last prices, percentage changes, volume, market cap, 52-week ranges. Every number is right there on the page. The problem is that it lives inside a browser, not inside your pipeline. If you trade actively and rely on data to make decisions, copying that data manually is not a real option at scale. And building a custom scraper from scratch means maintaining selectors every time a page updates. There is a better

Eater publishes some of the most curated restaurant guides on the web. The Seattle edition alone maps dozens of top picks across neighborhoods, with names, descriptions, and links to full reviews. Getting that data into a spreadsheet manually takes time. This tutorial shows how to pull it into structured JSON in one session using the Minexa.ai Chrome extension. What data is available on Eater The starting page for this tutorial is the Eater Seattle best restaurants map at...

Wise is best known as a money transfer platform, but it also hosts a publicly accessible stock directory covering thousands of listed companies across global exchanges. Each category page on wise.com lists company names, ticker symbols, and links to individual stock detail pages. If you need that data in a structured format for research, financial analysis, or portfolio tooling, copying it manually is not realistic at any meaningful scale. This guide shows how to extract that

Clinical research data published on institutional websites is some of the most structured, high-value information available publicly. Extracting it at scale, however, has traditionally required either manual copy-paste or fragile custom scrapers that break the moment a page layout changes. This guide shows how to extract clinical trial listings from UCSD Clinical Trials (the official trial browser at clinicaltrials.ucsd.edu/browse/) using the Minexa API — a data extraction pl

VesselFinder tracks hundreds of thousands of ships worldwide. The vessel list at vesselfinder.com/vessels is one of the most complete public directories of maritime assets available, covering cargo ships, tankers, cruise liners, and more. Getting that data into a spreadsheet for analysis, research, or fleet monitoring normally means a lot of manual copying. This tutorial shows how to do it automatically using the Minexa Chrome extension. What data you can extract from VesselF

Collecting job market data from Jora manually is slow, inconsistent, and breaks the moment you need more than a handful of listings. The Minexa API gives developers a repeatable, structured extraction pipeline that works across thousands of pages without writing a single selector. This guide covers the full workflow: training a scraper on Jora, retrieving your scraper_id, and calling the API to extract job listings at scale. What data Jora exposes Each listing on a Jora searc