Data Collection

Google search results are one of the essential ways to track rankings, ads, SERP features, and shifts in search intent at scale. The hard part is collecting that data reliably, because modern SERPs vary by query, location, device, and result type. In this guide, you'll learn 3 practical ways to scrape Google search results: lightweight extraction, a custom-built scraper, and a managed SERP API.

As websites become more dynamic and better at detecting automated traffic, choosing the right automation tool has become more challenging. At the same time, performance, reliability, and anti-detection capabilities matter more than ever. Two tools dominate the space: Selenium, a mature and widely adopted standard, and Playwright, a newer framework built for modern web apps. This guide compares them through practical use cases like web scraping and dynamic content extraction to help you decide which fits your needs best.

A proxy hostname is the domain you use to connect to a proxy service. Rather than entering a numeric IP address, the client connects through a readable host address that points to the provider’s proxy servers. Once configured in a browser, application, or script, this hostname ensures that outgoing requests pass through the proxy network before reaching the intended website.

Web scraping is one of the most effective ways to collect publicly available data at scale, but without the right infrastructure, it often leads to a familiar roadblock: the “Your IP Address Has Been Banned” error. This message means a website has blocked your IP address after detecting automated or unusually frequent requests. Fortunately, IP bans are both fixable and preventable. In this guide, we explain what causes IP bans during web scraping, how to recover when one happens, and the best practices for keeping your scraping operations running smoothly without interruption.

A Bing rank tracker is a tool or API that monitors where your website ranks in Bing search results for specific keywords. Since Microsoft retired all Bing Search APIs in August 2025, third-party solutions are the only way to track Bing rankings programmatically. This guide compares the best Bing rank trackers in 2026, covering SERP scraping APIs, all-in-one SEO platforms, pricing, and how to set up these tools.

Images, video, and audio are harder to collect and clean than text, and much less useful without context. Multimedia scraping helps you collect media, preserve the metadata that gives it meaning, and turn scattered files into training-ready datasets. The hard part is treating each media type differently from the start.

Yelp doesn't make scraping easy. The data you need is spread across multiple backend systems (no single endpoint gives you everything), and standard HTTP libraries get blocked before the first response. This guide covers every extraction method with Python, including the TLS impersonation and anti-bot techniques you need to avoid blocks at scale.

A bootstrapped data operation found that their web scrapers crawled to a halt as they tried to scale from 100 to 10,000 URLs. This is a common challenge with sequential processing and exactly why understanding concurrency vs parallelism is key to building efficient, scalable systems. This guide explains both concepts, their key differences, and limitations, so you can quickly decide the best mechanism for your project.

Most scraping APIs treat every request the same – maximum power, maximum cost. But real workloads are mixed: simple HTML pages, JavaScript-heavy targets, and protected sites that need premium proxies. If your pipeline covers all three, you’re paying worst-case prices on every request. We built a scraping API that matches cost to complexity, one request at a time.

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.

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.