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Switching from ChatGPT to Claude no longer means starting from scratch. Anthropic’s memory import tool lets you transfer preferences, context, and instructions in under 5 minutes. This guide covers 3 migration paths – from a quick memory import to a full data transfer, plus feature comparisons, export steps, and power tips.

Requests, HTTPX, and AIOHTTP all make HTTP requests, but they differ in how they handle concurrency. Requests is synchronous and has been the default since 2011. HTTPX gives you both sync and async with HTTP/2 support. AIOHTTP is async-only and faster at high concurrency, but has a steeper learning curve. The right choice depends on your async model, whether you need WebSockets or HTTP/2, and how much code you're willing to rewrite. This article covers architecture, performance data, proxy setup, migration paths, and common mistakes in production scraping setups.

TL;DR: A web crawler is a program that systematically navigates the web by following links from page to page. Python is the go-to language for building crawlers thanks to libraries like Requests, Beautiful Soup, and Scrapy. This guide covers everything from your first 50-line crawler to a production-grade Scrapy setup with proxy integration, JavaScript rendering, and distributed architecture. If you've ever had to collect data from hundreds or thousands of pages and done it manually, this is for you.

Scrapy is a powerful web scraping framework available in Python. Its asynchronous architecture makes it faster than sequential scrapers built with Requests or Beautiful Soup, and it includes everything needed for production-ready scraping: spiders, items, pipelines, throttling, retries, data export, and middleware. In this guide, you'll learn how to set up Scrapy, build and customize spiders, handle pagination, structure and store data, extend Scrapy with middlewares and proxies, and apply best practices for scraping at scale.

AI-powered automation has moved from niche tooling to a 2026 priority. Tools such as OpenClaw turn large language models into proactive messaging assistants, while n8n offers a visual workflow builder for connecting apps and orchestrating processes. This guide compares their architecture, AI capabilities, pricing, and best-fit use cases so you can quickly decide which tool matches your needs.

Every time you check the weather, order food, or scroll through social media, APIs are working behind the scenes to make it happen. An API (Application Programming Interface) is essentially a set of rules that lets different software applications talk to each other and share data without you ever noticing. In this guide, you'll learn more about what they are, how they work, and even get the chance to create your own.

Manual eCommerce data collection breaks because the data doesn’t stay stable. Prices change daily, products disappear and reappear under the same URL, and even mid-sized stores list tens of thousands of SKUs. On top of that, much of the content is rendered with JavaScript, layouts shift due to constant A/B testing, and anti-bot systems detect repeated automated access. This guide shows you how to analyze a target site and choose the right extraction approach.

Not all proxies actually protect your identity. Some proxies openly tell websites, "This request came through a proxy," while some can even leak your real IP if they're configured poorly. There are three proxy anonymity levels: transparent, anonymous, and elite. This article will walk you through each one, explain how they work, and help you choose the most suitable option for you.

Dynamic pricing is everywhere – from the flight you booked last week to the headphones in your cart right now. But as AI-powered algorithms grow more sophisticated, adjusting prices millions of times a day based on demand, competition, and increasingly personal data, a critical question is emerging – is this still fair? We analyzed over 1.5M eCommerce price changes and introduced our second-annual Dynamic Pricing Index to find out what’s really happening beneath the surface.

Dynamic pricing, the practice of adjusting product prices in real time based on demand, competition, inventory, and other market signals, has become one of the defining features of modern eCommerce. Once limited to airline tickets and hotel rooms, algorithmic pricing now touches nearly every product category, from groceries and fashion to electronics and home improvement supplies. Our second-annual Dynamic Pricing Index, compiled from over 1.5M data points tracked at four-hour intervals across more than 120 eCommerce platforms in 40+ countries, reveals the scale and sophistication of this practice.

The US and Asia dominate global eCommerce, but their dynamic pricing strategies reveal distinct philosophies. Using 1.5M data points from 120+ platforms, our second-annual Dynamic Pricing Index compares how each region approaches price changes. We analyzed discount depth, pricing volatility, and stability to uncover what these patterns reveal about consumer behavior and competitive strategy.

There's a reason that a flat-screen TV costs $999 instead of $1,000. That grocery item rings up at $4.99, not $5.00. Your new sneakers are priced at $79.95, conveniently avoiding the psychological cliff of $80. It's called psychological pricing, and according to our Dynamic Pricing Index report of over 1M price observations on 120 eCommerce platforms, it's not just alive and well in eCommerce. It's absolutely everywhere.

Real-time pricing has moved from a competitive advantage to a competitive necessity. Retailers without algorithmic pricing capabilities now face a structural disadvantage against competitors who can respond to market conditions in minutes rather than days. This report provides the benchmarking data your pricing, merchandising, and technology teams need to assess your competitive position and inform investment decisions.

Our Dynamic Pricing Index report tracked over 1.5M data points across 120 North American, European, and Asian eCommerce platforms. The findings reveal which companies are most aggressively leveraging real-time pricing, and what this means for consumers, journalists, and policymakers.

If you’ve ever added a product to your cart only to find the price has shifted by the time you check out, you’ve experienced dynamic pricing in action. What once seemed like sporadic discounting is now a sophisticated, algorithmically driven discipline that reshapes prices across millions of products every hour of every day.