Data Collection

When you need to scrape 50 pages of search results behind a login wall, raw Requests + Beautiful Soup force you to track cookies and assemble form payloads by hand, while Selenium launches a full browser for pages that don't even use JavaScript. MechanicalSoup sits between those extremes. It wraps Requests and Beautiful Soup into a stateful browser that handles web scraping sessions, forms, and navigation automatically. This guide covers everything from installation to proxy-powered production scrapers.

Cloudflare is a massive global cloud network that sits firmly between your scraper and the data you need, blocking all requests that fail its multi-layered detection system. It powers nearly 21% of all websites globally, meaning that 1-in-5 sites rely on this network. Therefore, knowing how to bypass it is essential for serious scrapers. This practical walkthrough covers detection methods, tools like Puppeteer and Playwright, and both DIY approaches and managed solutions, including proxy strategies and web scraping APIs.

If you try to run curl on an infinite scroll page and then search (grep) for the content, the result will show zero matches. The required items aren't available in the initial HTML. The content is loaded using fetch requests that the page sends when a scroll event is triggered. This guide will cover: diagnosing the target, three scroll strategies, verification, speed, anti-detection methods, and a real-world walkthrough.

On a recent run, wired.com ranked no. 1 on US desktop and no. 2 on UK desktop computers for "best laptop 2026". Same query, same hour, different country. That gap is what a single-number rank tracker misses, especially now that modern SERPs add AI Overview citations, featured snippets, and "People also ask" blocks that most older tracking tools ignore. This post walks through building a tracker that captures all of it, starting with a manual baseline for ground truth, then moving to a Python implementation against a SERP API, and finally setting up a scaling path for more keywords and locations.

Web data extraction typically follows two main paths: requesting through an API or directly scraping target pages. If you're building distributed data pipelines, your choice can impact scalability, reliability, and overall cost. In this guide, we'll explore what each path entails, provide a detailed comparison between them, and explain when to use APIs, web scraping, or both.

Dify is an open-source platform for building LLM apps and AI workflows visually. It gives teams a drag-and-drop canvas for chaining LLMs, tools, and APIs into complete AI workflows. Modern AI apps need fresh, structured web data, but most teams don't want to write and maintain Python scrapers. In this article, you'll learn how to build a no‑code Dify workflow and switch to a managed Web Scraping API when basic plugins aren't enough.

To scrape IMDb data with Python at scale, you work with the 6 data layers IMDb sends to the browser instead of parsing the rendered HTML. IMDb is a Next.js application sitting behind AWS Web Application Firewall (AWS WAF) Bot Control, and the data lives in JSON-LD blocks, hydration payloads, and an internal GraphQL endpoint. To reach any of them past IMDb's WAF, you need more than plain requests and a real User-Agent, and the rest of this guide builds the setup that holds up.

Cursor AI is a code-aware IDE that generates, debugs, and refines scraper code through natural language, advancing AI-assisted scraping from concept to production. Building scrapers by hand means dealing with selector breakage, anti-bot walls, and proxy rotation logic that compounds every time a target site changes. This article covers setup, Cursor rules, scraper types, Decodo MCP integration, and project maintenance.

Class names are often the quickest way to target elements when you scrape a page. But in XPath, they are not as simple as they look. Because HTML stores multiple classes inside a single space-separated attribute value, a selector that seems correct can still match the wrong element or miss the right one entirely. In this blog post, you’ll learn how to select elements by class in XPath, when to use exact or partial matching, and how to avoid common class matching pitfalls.

Choosing between urllib3 and Requests is like choosing between a manual and an automatic transmission, except one (Requests) is built into the other (urllib3). The automatic gets you moving in seconds, but the manual gives you control over every shift. Both libraries power web scraping, API calls, and automation, and this article will tell you which belongs in your project.

Charles Proxy (or simply Charles) is an HTTP debugging proxy that acts as a man-in-the-middle between the computer and the internet, which developers and QA teams use to monitor, inspect, and modify data flow. In web scraping, it allows users to intercept, decrypt, and manipulate network traffic to extract data. This guide covers setup, core features, SSL handling, practical use cases, scraping workflows, troubleshooting, and notable alternatives of Charles Proxy.

If you work with APIs, webhooks, automation scripts, or web scraping, chances are you've needed to send JSON with cURL. cURL is one of the most widely used command line tools for making HTTP requests, and modern APIs almost always rely on JSON payloads. In this guide, you’ll learn how to send JSON with cURL, work with files and authentication, debug requests, and route traffic through proxies when needed.

Elixir web scraping solves one of the hardest problems in high-volume data collection: concurrency without thread overhead. The BEAM virtual machine (Erlang's runtime) runs each HTTP request as a lightweight process, not an OS thread, so you can fetch thousands of pages concurrently. If a process crashes, the supervisor restarts it automatically. This guide builds a complete Elixir scraper from scratch, covering static pages, paginated targets, JavaScript-heavy sites, and anti-bot countermeasures.

A scraper that fetches pages one at a time spends most of its time waiting on the network. Asynchronous web scraping in Python (built on asyncio and aiohttp) fixes that by handling many requests at once on a single event loop. This guide walks through building a working async scraper, then covers the proxy, retry, and anti-bot escalation patterns you'll need at scale.

​​HTML structure shifts constantly, but the visible text on a page tends to remain more stable. That stability is what makes text-based selectors useful in web scraping. This guide covers the core functions you need to work with text in XPath: text(), contains(), starts-with(), normalize-space(), and translate(), including where each one breaks and how to combine them to build selectors that survive page updates.

If you're building a Playwright scraper and not using Xpath, you're probably leaving your most precise location strategy on the table. Think of the DOM as a tree of nodes, and an XPath expression as the specific zip code to reach any node. In this article, we'll explain XPath fundamentals, how to construct XPath expressions, and how to interact with elements, including real-world examples.

Every JSON payload a JavaScript app receives passes through JSON.parse(). The method has to handle malformed payloads, lossy type round-trips, files that exceed Node's default heap, and APIs that change shape without warning. Each of those failures surfaces at parse time. This guide covers them all, including practical patterns for web scraping.

Puppeteer and Selenium are the 2 most-used browser automation tools for scraping JavaScript-heavy pages. Comparing puppeteer vs selenium for web scraping isn't just about speed. Browser support, language support, and anti-bot handling all play a role. This guide covers what each tool does well, what it doesn't, and how to pick the right one.