The NC.gov grant opportunities page lists every active state grant program in one place, organized by category. Getting that data into a spreadsheet manually means copying row by row across dozens of programs. With the Minexa.ai Chrome extension, the whole page becomes a structured dataset in a few minutes. Here is exactly what the process looks like, step by step. What data you get Each row on the NC.gov grant opportunities page contains four fields Minexa extracts cleanly:

LeCEGEP (lecegep.ca) is the central directory for continuing education and professional development courses offered across Quebec's CEGEP network. Hundreds of institutions list their programs there, covering everything from 3D design and database management to workplace safety and HR certification. The data is public and well-structured, but there is no export button and no official API. If you need this data in a usable format, whether to map the continuing education landsca

Most developers get a Minexa.ai API pipeline running quickly. The default request body works for a large share of sites, and the Chrome extension generates ready-to-use Python code in minutes. But a handful of parameters sit quietly in the request schema and go unused, even when they would directly solve a problem the developer is already fighting with. Here are ten parameters worth knowing before you hit your first wall. 1. bypass: anti-bot handling that only activates on se

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

Seek is one of the largest job boards in Australia, and its listings page for Perth alone can surface hundreds of roles across industries. If you need that data in a structured format for analysis, hiring intelligence, or market research, copying it manually is not a realistic option. This guide covers how to extract jobs data from Seek using the Minexa API developer workflow: train a scraper once using the Minexa Chrome extension, get a stable scraper_id, then call the API t

You set up a data collection workflow. It works. You move on. Then three weeks later, the numbers look off, a column is empty, or the whole output is blank. You spend an afternoon figuring out what broke and why. This is not an edge case. It is one of the most common experiences in any ongoing data extraction project. The setup is never the hard part. What happens over time is where things get complicated. This post walks through a realistic extraction workflow, stage by stag

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...

OLX is one of Eastern Europe's largest classifieds platforms. Its real estate section for Ukraine lists thousands of houses, apartments, and land plots updated daily. Getting that data into a structured format without writing a custom scraper from scratch is where the Minexa API workflow saves significant time. This guide walks through extracting house sale listings from OLX's Lviv region page using Minexa. Step 1: Train a scraper with the Chrome extension Before calling the

Most data extraction pipelines do not fail dramatically. They degrade quietly, one bad row at a time, until someone notices the numbers look wrong. These ten mistakes are responsible for the majority of that silent damage. 1. Selecting individual fields instead of the parent container When training a scraper, the instinct is to click the exact field you want, like a price or a title. The problem is that individual fields shift position constantly as layouts change. The correc

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

You can see the data. It is sitting right there on the page: prices, listings, contact details, job postings, product specs. But getting it out in a usable format means copying row by row, writing brittle selectors that break on the next deploy, or feeding pages into an LLM and hoping the output is consistent. None of these hold up past a few hundred pages. This is the actual problem with web data collection today. It is not that the data is hidden. It is that every path to e

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

Most data extraction pipelines start the same way: someone needs structured data from a website, and the first instinct is to write a scraper. Then comes the selector logic, the edge cases, the JavaScript rendering layer, the proxy setup, and eventually a fragile script that breaks when the site updates. The Minexa API was built to replace that entire process with a single trained scraper and a POST request. This guide walks through exactly how that works, from training your

VietnamWorks is one of Vietnam's largest job platforms, and its HR category page lists hundreds of active positions across recruitment, HRBP, generalist, and workforce management roles. Getting that data into a spreadsheet manually takes hours. With the Minexa.ai Chrome extension, the same job takes minutes. This guide walks through every step to scrape job listings from vietnamworks.com/nhan-su-kv and export structured data with no code required. What data you get Each listi