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Web scraping is a great way to automate the extraction of data from websites, and curl is one of the simplest tools to get started with. This command-line utility lets you fetch web pages, send requests, and handle responses without writing complex code. It's lightweight, pre-installed on most systems, and perfect for quick scraping tasks. Let's dive into everything you need to know.

Web scraping is the process of automating page requests, parsing the HTML, and extracting structured data from public websites. While Python often gets all the attention, Java is a serious contender for professional web scraping because it's reliable, fast, and built for scale. Its mature ecosystem with libraries like Jsoup, Selenium, Playwright, and HttpClient gives you the control and performance you need for large-scale web scraping projects.

Nasdaq offers a wealth of stock prices, news, and market reports. Manually collecting this data is a Sisyphean task, since new information appears constantly. Savvy investors, analysts, and traders turn to web scraping instead, automating data gathering to power more intelligent analysis and trading strategies. This guide walks you through building a Nasdaq scraper with Python, browser automation, APIs, and proxies to extract both real-time and historical market data.

If you need a bunch of images and the thought of saving them one by one already feels tedious, you're not alone. This can be especially draining when you're preparing a dataset for a machine learning project. The good news is that web scraping makes the whole process faster and far more manageable by letting you collect large quantities of images in just a few steps. In this blog post, we'll walk you through a straightforward way to grab images from a static website. We'll use Python, a few handy libraries, and proxies to keep things running smoothly.

The talk around whether the UK government could put a ban on ticket resale above face value is set to reshape the live events industry, from secondary ticketing platforms to artists and venues, with fan fairness at the center of the new rules. Decodo, a leading web data collection provider, has commented on the latest proposals to reform the ticket resale market, revealing the impact on key stakeholders.

Cloudflare is experiencing a global outage affecting hundreds of millions of users worldwide. Major platforms, including X and OpenAI, are impacted by it. This article breaks down the current Cloudflare status, what's causing widespread 500 errors, and actionable steps for users and website owners dealing with Cloudflare downtime.

Web scraping Airbnb (a global platform for short-term rentals and experiences) involves automatically extracting data from listings to reveal insights unavailable through the platform itself. It's useful for analyzing markets, tracking competitors, or even planning personal trips. Yet, Airbnb's anti-scraping defenses and dynamic design make it a technically demanding task. This guide will teach you how to scrape Airbnb listings successfully using Python.

As the biggest shopping festival of the year approaches, a dynamic shift occurs across thousands of online storefronts. Prices fluctuate by the hour, algorithms compete for consumer attention, and shoppers equip themselves with AI-powered price trackers and browser extensions. Black Friday has grown from a single-day shopping event into a months-long strategic tango between retailers and increasingly savvy consumers.

An exclusive analysis by web data company Decodo of 150K+ price observations across 37 major US eCommerce retailers, tracked throughout the year, reveals the complex strategies both sides deploy. The data paints a picture of a retail ecosystem in constant flux, where timing, category selection, and pricing algorithms can mean the difference between a genuine deal and clever marketing tricks.

Scraping hotel listings is a powerful tool for gathering comprehensive data on accommodations, prices, and availability from various online sources. Whether you're looking to compare rates, analyze market trends, or create a personalized travel plan, scraping allows you to efficiently compile the information you need. In this article, we'll explain how to scrape hotel listings, ensuring you can leverage this data to its fullest potential.

HTML tables are one of the most common ways websites organize data – financial reports, product listings, sports scores, population statistics. But this data is locked in the webpage's layout. To use it, you need to extract it. This guide will show you how to do it using Python, starting with simple static tables and working up to complex dynamic ones.

When we scale businesses, do research, or just scroll leisurely, it's always a good idea to be clued up on online security. Whatever your reasons for running your eyes over a web browser are, anonymity and privacy are two pretty important players here. The thing is that any browser, website, system, or network can see our IP address. Some of them might even log your IP address and track it. In this blog post, we’ll go over the dangers of using free software, fake IPs, and the illegal aspects of using IP information.

Managing proxies just got a lot easier. We’re launching IP replacement, a new feature that lets you replace any IP instantly from your dashboard without requesting help from our tech support or changing your plan. Whether you’re running eCommerce monitoring, multi-accounting, or large-scale scraping projects, you can now keep your IP pool clean, stable, and high-performing in real time.

Pagination is the system websites use to split large datasets across multiple pages for faster loading and better navigation. In web scraping, handling pagination is essential to capture complete datasets rather than just the first page of results. This guide explains what pagination is, the challenges it creates, and how to handle it efficiently with Python.

Craigslist is known as a valuable source of classified data across jobs, housing, and marketplace items for sale. However, scraping Craigslist presents challenges like CAPTCHAs, IP blocks, and anti-bot measures. This guide walks you through three Python scripts for extracting housing, job, and for sale item listings while handling these obstacles effectively with proxies or a scraper API.

While using Google Trends, you can discover the search interest rates for specific keywords during specific time frames in specific regions and analyze the popularity of Search keywords over time. This makes it possible to see how popular a topic is over time and across regions, without exposing sensitive search data. In this guide, we'll explain the kinds of data available from Google Trends, compare scraping techniques, and demonstrate two methods of gathering Google Trends data.

Production RAG fails when it relies on static knowledge that goes stale. This guide shows you how to build RAG systems that scrape live web data, integrate with LlamaIndex, and actually survive production. You'll learn to architect resilient scraping pipelines, optimize vector storage for millions of documents, and deploy systems that deliver real-time intelligence at scale.

In September 2025, Google officially discontinued the num=100 parameter. If you're an SEO professional, data analyst, or someone who prefers viewing all results at once, you've likely already felt the impact on your workflows. In this article, we'll explain what changed, why Google likely made this move, who it affects, and most importantly, how to adapt.

AI has evolved from programs that just follow rules to systems that can learn and make decisions. Businesses that understand this shift can leverage AI to tackle complex challenges, moving beyond simple task automation. In this guide, we'll walk you through how to connect modern AI tools with live web data to create an automated system that achieves a specific goal. This will give you a solid foundation for building even more sophisticated autonomous applications.