Collecting job listing data from Doda, one of Japan's largest job platforms, by hand is slow and breaks down quickly once you need more than a handful of records. Each company card on Doda surfaces multiple job references, salary structures, and linked detail pages, and copying that manually across hundreds of pages is not a realistic workflow. This guide walks through exactly how to extract that data using the Minexa.ai Chrome extension, no code required, starting from the c

The OSPI Online Learning Course Catalog lists every state-approved online course available to Washington K-12 students, including provider names, grade eligibility, course levels, and direct links to provider PDFs. Pulling that data manually means clicking through paginated tables and copying rows one by one. The Minexa API removes that entirely. Watch the full extraction walkthrough before diving into the steps below. What the extracted data looks like Here is a sample of wh

Drug label data sitting behind a browser is useless to a pipeline. This guide shows how to pull structured pharmaceutical listings from PDR at scale using the Minexa API, covering every field worth knowing and the exact request body to get started. What PDR exposes at the browse-by-drug-name endpoint PDR (pdr.net) is a clinical reference platform used across healthcare and biotech. Its drug browse page at pdr.net/browse-by-drug-name lists thousands of drug entries alphabetica

Air quality data is publicly available on AQICN, but getting it into a structured format that a pipeline can actually use is a different problem. The page renders pollutant readings dynamically, attribution strings span multiple lines, and each row carries embedded chart images encoded as Base64. None of that is accessible through a simple HTTP request. This guide walks through how to extract that data programmatically using the Minexa API, covering the full workflow from scr

Federal job listings contain more structured data than most people realize. USAJobs surfaces job titles, hiring organizations, salary ranges, employment types, application deadlines, and eligibility paths all on a single search results page. The challenge is getting that data out in a usable format without copying rows manually. This guide walks through how to extract that data using the Minexa.ai Chrome extension, a no-code tool that turns any structured web page into a down

Clinical trials data is one of the most structurally rich and time-sensitive categories of public research information available on the web. Fred Hutch Cancer Center publishes a continuously updated directory of active trials at fredhutch.org, covering oncology, hematology, behavioral interventions, and surgical comparisons across phase I through phase III studies. Extracting that data programmatically opens up a range of research intelligence workflows that are difficult to

Ryanair publishes a public flight listing page that shows available routes, departure dates, origin and destination cities, IATA airport codes, one-way fares, and direct booking links. All of it is visible in the browser. None of it is easy to collect at scale without a tool built for the job. This guide covers how to extract that data using Minexa.ai, a Chrome extension that detects page structure automatically and exports results to Excel, Google Sheets, or JSON without any

Metacritic's game browse page is one of the most complete public sources of critic-scored game data on the web. Every listing carries a Metascore, an ESRB rating, a release date, a full description, and a direct link to the game's detail page. If you are building a game analytics pipeline, a content recommendation engine, or a media intelligence feed, this is a dataset worth having in structured form. This guide walks through how to extract that data at scale using the Minexa

Kavak is one of Latin America's largest used car marketplaces, and its Brazilian listings page at kavak.com/br/seminovos contains hundreds of vehicle cards updated regularly with price, mileage, model year, location, and direct links to individual detail pages. Extracting that data at scale without writing custom scraper code is exactly what the Minexa API is built for. This walkthrough covers the full workflow: training a scraper once using the Minexa Chrome extension, then

Here is what the data looks like before you read a single instruction. [ { "course_title": "Level 2 Certificate in Awareness of Mental Health Problems", "provider_name": "Learning Curve Group", "enquiry_count": "8,704 enquiries", "course_description": "Complete online for FREE when it suits you, with study materials and tutor support.", "course_features": "Tutor support", "list_item_description": "Regulated qualification", "link_href": "/courses/level-2-certificate-in-awarene

Supply chain data is everywhere on the web, but getting it into a spreadsheet without copying it line by line is a different story. This walkthrough shows how to pull structured article data from SupplyChainBrain, one of the most referenced logistics and supply chain publications, using the Minexa.ai Chrome extension. The starting URL for this tutorial is the logistics service providers directory: https://www.supplychainbrain.com/directories/98-supplier-directory/topic/1254-l

The T-Bank invest portal lists dozens of ETFs and investment funds on a single paginated page. Each card carries a fund name, a logo, a performance chart rendered in SVG, and a link to the fund detail page. Visually, it reads cleanly. Programmatically, it is a different story: the chart data is embedded in SVG polyline attributes, gradient identifiers are scattered across path elements, and performance direction is encoded in CSS variable names rather than plain text values.

Michael Page publishes hundreds of active job listings across London every day. If you want that data in a spreadsheet, structured and ready to analyse, the Minexa.ai Chrome extension gets you there without writing a single line of code. This walkthrough covers the full extraction process from the michaelpage.co.uk/jobs/london page, showing exactly what you see at each step and what to do. Watch the full tutorial first The video below covers the complete workflow from install

Grant funding databases are only useful when you can actually work with the data inside them. The HRSA Find Funding page lists open federal health grant opportunities from bureaus including the Bureau of Health Workforce and the Federal Office of Rural Health Policy, but the data sits inside a paginated web listing with no export button. This guide walks through every step needed to extract that data using the Minexa.ai Chrome extension, no code required. Watch the full tutor

Alternative.to lists software alternatives organized by category, platform, and language. Every listing card contains a product name, description, external website link, feature count, social profiles, and platform metadata. Pulling that data manually across dozens of pages is slow. The Minexa API makes it programmable. The workflow has two phases: train a scraper once using the Minexa Chrome extension, then call the API to extract data at scale from any number of Alternative

GitHub Explore surfaces what the developer community is actually building right now. Trending repositories, active topics, star counts, programming languages, and full card-level metadata are all sitting on a single public page. The challenge is getting that data into a structured format you can query, filter, and feed into a pipeline. This guide walks through how to extract that data programmatically using the Minexa API. The workflow has two phases: train a scraper once usi

MUBI's all-films catalogue is one of the most consistently structured film listing pages on the web, which makes it a reliable source for building media datasets covering curated cinema from dozens of countries and decades. This guide walks through how to extract structured film data from mubi.com/en/films?all_films=true using the Minexa.ai Chrome extension, with no code required. Watch the tutorial first The video below covers the full extraction from start to export. Step 1

The data below was extracted from the Visit Fort Wayne restaurant directory in a single API call. Before explaining how the pipeline works, here is what the output looks like. What the extracted data looks like Each row in the response corresponds to one restaurant listing on the Visit Fort Wayne page. Here are three labelled records from the extraction: [ { "restaurant_name": "Wagyu Burger Shack", "listing_url": "/listing/wagyu-burger-shack/55389/", "external_link":...

Fleet procurement teams and logistics analysts working in Brazil regularly need structured vehicle specification data to compare configurations, validate supplier quotes, and build internal reference datasets. Mercado Livre publishes detailed catalogue pages for commercial vehicles, including full technical comparison tables per trim, but that data sits inside a web page rather than a spreadsheet. Getting it out manually, row by row, is slow and error-prone at any meaningful

Government funding portals publish structured competition data in plain HTML, yet collecting it at scale means clicking through pages manually or writing brittle scraping scripts that break whenever the layout shifts. The Apply for Innovation Funding service, part of the UK government's service.gov.uk platform, lists open and upcoming Innovate UK competitions with details that matter to grant consultants, R&D teams, and business intelligence analysts. This guide shows how to