Data Collection

Golang Colly is a fast, callback-driven scraping framework for the Go programming language. It wraps HTTP requests, HTML parsing, rate limiting, and concurrency in a clean API, so you can pull structured data from a website with very little code. This tutorial walks you through building a working Colly scraper from an empty project all the way to proxy rotation.

Vibe scraping is the practice of building scrapers by describing goals in natural language to an LLM rather than hand-writing selectors, a concept derived from Andrej Karpathy's 'vibe coding.' This allows developers to turn prompts into working extractors as LLMs now efficiently parse DOMs, infer schemas, and write code. While it enables rapid prototyping, it introduces new failure modes like hallucinated selectors; scaling these scripts for production still requires real proxies and rendering infrastructure.

Puppeteer makes browser automation feel easy until you need to save a file to disk. Triggering a download in headless mode isn't the same as clicking a button in a real browser, and the default behavior in headless Chrome won't help you. This guide covers the full Puppeteer download file workflow: configuring CDP correctly, picking the right method for your scenario, detecting when a file truly finished, and scaling to batch jobs without leaking memory or corrupting your queue.

Price data is important for monitoring competitors in eCommerce, enforcing MAP policies, and receiving deal alerts. Doing this manually isn't effective for scaling. A practical approach is price scraping, which helps automatically collect product pricing data from eCommerce websites. This guide will show you how to build a Python scraper using Playwright. It will help you gather real prices, deal with anti-bot measures, and create structured JSON data.

C++ web scraping is the process of sending HTTP requests from a C++ program, retrieving HTML or other structured responses, and parsing the data using libraries such as libcurl, CPR, libxml2, or pugixml. It's most useful in scraping workloads where CPU efficiency, memory control, predictable latency, or direct integration with an existing C++ system matter more than quick setup. That makes it a practical option for performance-critical pipelines, but a heavier one to build and maintain. The real question isn't whether C++ can scrape the web. It's whether that extra control is worth the extra engineering work.

Submitting forms with Puppeteer goes beyond just clicking a button on the browser or typing text into an input box. Puppeteer is a Node.js library that can control a headless or headful Chromium (browser) instance through the DevTools Protocol. That means you can use Puppeteer to automatically locate form fields, fill input boxes with necessary values, trigger the action of submitting a form, and confirm whether that form submission actually worked. If you’re into web scraping, or you’re testing your own product, or even automating anything in a browser with JavaScript, you’ll inevitably run into form fields and submit buttons that you will need to get passed programmatically with Puppeteer.

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.