Data Collection

Most AutoGPT tutorials stop at "get it running", but that's the easy part. The harder part that determines whether your agents are useful is connecting them to live data, and AutoGPT helps you fix that. This guide covers AutoGPT local setup, UI navigation, custom Python block development, and the integration patterns that turn AutoGPT into a production workflow tool.

Most Shopify stores have a built-in JSON endpoint for product data: prices, variants, inventory, images. Web scraping Shopify means requesting /products.json, paginating, and getting the catalog as JSON. But the endpoint is limited to 250 products per page, and some merchants disable it. This guide covers both: the JSON approach for stores that have it, and the fallback for stores that don't.

Axios POST headers are one of the most important items for JavaScript developers working with HTTP. Configure them incorrectly, and your requests fail, authentication breaks, or data gets rejected. The good news? Axios gives developers several ways to manage headers, including inline on individual requests, globally via defaults, through reusable instances, and dynamically with interceptors. This guide explores how to use Axios to set headers across all request types, covering POST, GET, PUT, and DELETE requests, plus common pitfalls and fixes.

Scraping emails from a website is essential for lead generation, partner research, and CRM enrichment. However, to reliably scrape emails from a website, you need to handle multiple formats, including mailto links, plain-text addresses, obfuscated strings, and JavaScript-rendered content. This guide shows how to safely build a Python email scraper and scale it into a multi-page crawling workflow.

Bulk text extraction has become an inseparable part of modern-day existence, with real-world cases including building datasets for LLM training, archiving, content analysis, and RAG systems. However, extracting all text is far more complex than scraping a single page, so we’ve prepared a step-by-step guide to discover pages, extract clean text, remove unnecessary elements, and export structured datasets into proper formats. The tools we use are Python, Beautiful Soup, Playwright, and Decodo proxies.

Python is usually the first choice for web scraping, but it can struggle in high-throughput scenarios where you’re fetching many pages concurrently or need stronger reliability. That’s where Rust comes in. In this tutorial, you’ll build a Hacker News scraper in Rust, covering setup, JSON output, and scaling, along with where Rust excels, where it adds friction, and when to offload to a managed scraping API.

Playwright MCP lets an AI agent drive a real browser: open pages, click through them, and read what renders, all from a plain-language instruction. It is the fastest route to structured data from a website when you do not want to write, debug, and maintain scraping code. Here's how to set it up.

You've likely encountered “REST API” in documentation, job descriptions, or technical discussions, but what is a characteristic of the REST API? While APIs power everything from mobile apps to enterprise integrations, most developers implement them, ignoring their architectural constraints. In this guide, we'll break down the six characteristics of REST APIs from Roy Fielding's 2000 dissertation and explain why they matter for building scalable, maintainable systems.

Every Glassdoor scraping tutorial that uses Selenium or Playwright fails for the same reason: Cloudflare anti-bot protection fingerprints the TLS connection and blocks non-browser traffic. Glassdoor has internal API endpoints that return the same structured JSON that the frontend uses, without rendering a page. Because these endpoints accept standard HTTP calls, you can bypass Cloudflare by calling them with Python and curl_cffi for browser-grade TLS fingerprinting, plus Decodo residential proxies for IP rotation. This guide covers 4 complete scrapers for reviews, jobs, interviews, and company profiles.

Scraping Google can quickly turn frustrating when you're repeatedly met with CAPTCHA challenges. Google's CAPTCHA system is notoriously advanced, but it’s not impossible to avoid. In this guide, we’ll explain how to bypass Google CAPTCHA verification reliably, why steering clear of Selenium is critical, and what tools and techniques actually work in 2026.

Google AI Mode was launched as a Search Labs experiment in March 2025. It's powered by Gemini 2.5, which synthesizes answers from multiple sources and allows you to ask follow-up questions. Google AI Mode isn't the same as Google search results; it's an entirely full-page conversational interface using different URL parameters, rendering pipelines, and scraping logic. This guide provides a walkthrough of two different approaches: a working Playwright script you can execute right away, and the Decodo Web Data API for production.

nodriver is a Python package for browser automation and web scraping built as the successor to undetected-chromedriver. It skips the usual WebDriver layer, talks to Chrome more directly than Selenium, and uses an async-first design. In this guide, you'll learn what nodriver is, how it works in Python, and where it fits for scraping JavaScript-heavy pages when basic browser automation starts showing its limits.

Web scraping becomes truly valuable when it is automated. It allows you to track competitor prices, monitor job listings, and continuously feed fresh data into AI pipelines. But while building a scraper that works can be exciting, real-world use cases require repeatedly and reliably collecting data at scale, which makes manual or one-off scraping ineffective. 

Scheduling enables this by ensuring consistent execution, reducing errors, and creating reliable data pipelines. In this guide, you will learn how to automate scraping using 3 approaches: in-script scheduling with Python libraries, system-level tools like cron or Task Scheduler, and cloud-based solutions such as GitHub Actions.

If you're scraping with Playwright or Selenium, you've hit this. Your script works on unprotected sites, but Cloudflare, PerimeterX (HUMAN Security), and DataDome detect the headless browser and block it within seconds. Stealth plugins help, but each browser update breaks the patches. Camoufox takes a different approach – it modifies Firefox at the binary level to spoof browser fingerprints, making automated sessions look like real user traffic. This guide covers Camoufox setup in Python, residential proxy integration, real-world test results against protected targets, and when browser-level tools aren't enough.

Since there are thousands of job postings scattered across different websites and platforms, it's nearly impossible to keep track of all the opportunities out there. Thankfully, with the power of web scraping and the versatility of Python, you can automate this tedious job search process and land your dream job faster than ever.

eBay is the second-largest online marketplace in the US, and unlike traditional eCommerce platforms, it's an open marketplace where people auction cars, sell rare collectibles, and seal personal deals directly with buyers. That makes it one of the richest targets for web scraping and data extraction – you get access to auction bids, final sale prices, seller ratings, and historical records of what buyers actually paid, not just listed prices. In this guide, you'll learn how to scrape eBay with Python, covering the tools, methods, and best practices to extract data cleanly and at scale without getting blocked.

Google Flights is a rich source of crucial flight information, such as prices, airlines, times, stops, durations, and emissions, but scraping this information has never been easy. The flight search engine hides valuable data behind JavaScript-heavy pages and anti-bot protections. This guide explains how to scrape Google Flights using Python by building a browser-based scraper powered by Playwright.

Google Sheets is a powerful data management tool, but few people know it can also pull data directly from the web without a single line of code. Using built-in import functions, you can scrape website content, parse tables, and pull live feeds straight into your spreadsheet. In this guide, you'll learn how to use IMPORTXML for XPath-based data extraction, IMPORTHTML for grabbing tables and lists, IMPORTFEED for RSS and Atom content, IMPORTDATA for CSV files, and IMPORTRANGE to link scraped data across spreadsheets. We'll also cover Google Apps Script for automation, common errors and how to fix them, and when to reach for a dedicated scraping tool instead.