Deep dives into web data infrastructure, extraction techniques, and the future of structured data at scale.
TL;DR: A web scraping project fails on planning long before it fails on code. These ten scraping questions walk you through legality, API alternatives, anti-bot defenses, cost, refresh cadence, data quality, and governance, so you scope the work, pick the right stack, and avoid the failure modes that quietly kill scrapers in production.
Learn how to use Node.js and our API to scrape nearby sellers from Google Shopping. Extract valuable data quickly and easily with our professional web scraper.
TL;DR: Use page.locator(selector).fill(value) for fast, deterministic Puppeteer submit form scripts and page.type() when the page watches for real keystrokes (autocomplete, anti-bot, live validation). Submit by clicking the button, pressing Enter, or calling form.requestSubmit(), and always wait for a concrete success signal instead of a fixed timeout.
TL;DR: Pyppeteer is the unofficial Python port of Puppeteer and still works for driving a real Chromium from asyncio. In this guide you will install it, write a modern web scraper with Pyppeteer using asyncio.run and try/finally, handle waits, forms, screenshots, infinite scroll, cookies, and proxies, and learn when to migrate to Playwright, Selenium, or a hosted scraping API.
TL;DR: This guide walks through how to web scrape Walmart product data end-to-end in Python, from parsing the hidden __NEXT_DATA__ JSON to scaling with proxies, retries, and async fetches. It also draws an honest line for when a managed scraper API beats DIY.
Discover the step-by-step guide to web scraping Google Shopping product specs using Node.js. Improve your web scraping skills with this tutorial.
