Indonesia's logistics sector spans hundreds of verified freight forwarders, cargo agents, and supply chain operators, all listed publicly on Indonetwork (indonetwork.co.id). Getting that data into a spreadsheet manually is slow and error-prone. This guide shows how to extract it in minutes using the Minexa.ai Chrome extension, no code required. Stage 1: Open the directory and launch the extension Navigate to the Indonetwork cargo and logistics company directory at indonetwork

IMDb holds some of the most detailed publicly available entertainment data on the internet. Episode lists, air dates, ratings, cast details, and season breakdowns are all sitting right there on the page. The problem is that none of it is structured in a way you can actually work with. If you have ever tried to copy episode data from IMDb into a spreadsheet manually, you already know how quickly that falls apart. This post walks through how to extract that data cleanly using t

Commercial property data sitting inside a browser tab is not useful to a pipeline. Structured rows in a dataset are. This guide shows how to extract commercial real estate listings from OnTheMarket using the Minexa API, covering every step from scraper training to a working Python request. Watch the full walkthrough first The video below covers the complete extraction workflow on OnTheMarket's commercial listings page for Kent. Watch it before going through the screenshots so

Flight price data sitting behind a search interface is genuinely difficult to collect at scale. Kayak surfaces destination tiles with prices, stop counts, and editorial tags, but none of that is available via an official API. This walkthrough shows how to extract it using the Minexa API, a data extraction platform that combines a browser-based training step with a programmatic extraction endpoint. The workflow has two phases: train a scraper once using the Minexa Chrome exten

The London Metal Exchange publishes a steady stream of market reports, press releases, member notices, and metal price pages. If you are tracking copper warrant stocks, monitoring off-warrant reporting changes, or building a dataset of LME announcements over time, the search interface at lme.com/search?searchTerm=stocks surfaces exactly the kind of structured content you need. The problem is that it is all locked inside a web page, not a spreadsheet. This guide walks through

Financial product pages like Kotak Mahindra Bank's credit card listings are structured, publicly accessible, and updated regularly. That makes them a practical data source for fintech developers, competitive analysts, and financial researchers who need card features, eligibility criteria, and product metadata in a structured format. This guide covers how to extract that data programmatically using the Minexa API, a deterministic web extraction platform that handles JavaScript

Event data sitting behind a paginated listing page is useful only when it is structured, repeatable, and accessible without manual copying. Live Nation Asia publishes a full event directory at livenation.asia/event/allevents, and the Minexa API gives developers a direct path from that page to a clean JSON dataset they can query, store, or pipe into any downstream system. This guide walks through the complete workflow: training a scraper once using the Minexa Chrome extension,

Manually copying flight data from Cheapflights row by row is the kind of task that looks simple until you are three pages in and the prices have already changed. This guide shows how to connect the Minexa API to Cheapflights and pull structured flight data programmatically, starting from a single trained scraper. What the data looks like before and after Without automation, flight data from Cheapflights lives in a rendered page that updates dynamically. You can see the prices

Map-based real estate data is genuinely hard to collect at scale. The listings are rendered dynamically, the placemarks carry structured metadata embedded in CSS classes and href attributes, and the page requires JavaScript execution before any data is visible. Yandex Realty's apartment rental map for Moscow is a good example of this pattern, and it is exactly the kind of source where a deterministic, DOM-based extraction approach pays off. This guide walks through how to bui

If you track Indian startup funding rounds, monitor sector trends, or build datasets for VC research, Inc42 is one of the most consistently updated sources available. The challenge is that the data sits inside article cards spread across paginated listing pages, and there is no official API to pull it programmatically. This guide shows how to extract structured startup and investment data from Inc42 using the Minexa API. The workflow has two phases: train a scraper once using

Logistics data sits on public-facing pages in plain sight, but getting it into a structured format for analysis is rarely straightforward. Shiprocket, one of India's widely used shipping and logistics platforms, publishes a range of supply chain-relevant content across its site. Extracting that content consistently, at scale, and without writing custom scraper code is exactly the kind of problem the Minexa API is built to solve. This guide walks through the full workflow: tra

Bilingual food and grocery data sitting inside a translation database is not the most obvious scraping target. But if you work in food labelling, cross-border product research, or multilingual content, Linguee is one of the few places where real-world sentence pairs from verified sources are publicly available at scale. This guide walks through how to extract that data from Linguee (linguee.com.br) using the Minexa.ai Chrome extension, with no code required. Before getting in

BSE India publishes live derivatives market data on its streamer page, and that data updates constantly. If you want to capture it, analyze it, or track it over time, copying rows manually is not a realistic option. This guide shows exactly how to extract it using the Minexa.ai Chrome extension, step by step, with no code required. The target page is the BSE India equity streamer market watch at bseindia.com/eqstreamer/streamermarketwatch?flag=2. It lists the most active SENS

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

Cafeland is one of Vietnam's main real estate portals, and its urban development project listings for Hai Phong carry a useful mix of investor details, sale status, geo-coordinates, and direct links to transaction pages. Getting that data into a spreadsheet manually is slow. This walkthrough shows how to do it in a few minutes using the Minexa.ai Chrome extension. Watch the full tutorial first The video below covers the complete extraction from start to export. Watch it once

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

Public statistical data is often the most reliable source available for sector-level research, and CBS publishes some of the most detailed enterprise statistics in Europe. The challenge is not finding the data. It is getting it out of the browser and into a format you can actually work with. This guide walks through how to extract structured enterprise statistics from CBS, the Dutch national statistics bureau, using the Minexa.ai Chrome extension. No code required. The target

Every job listing on Freshersworld contains more structured data than it appears to hold at first glance. Behind each card sits a salary range, a relative posting timestamp, a numeric job ID embedded in a CSS class, and a full list of eligible qualifications packed into a single traversable array. Getting all of that out cleanly, at scale, without writing selectors or maintaining parsing logic, is exactly what the Minexa API is built for. This guide walks through the complete

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