Data Collection
The process of data collection is vital in all kinds of industries. It helps businesses learn about the market, know their customers better and adapt to their needs. Data collection can be automated by scraping a set target. It’s extra useful for analyzing business competition, records, trends, and other data.
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What is a Headless Browser: A Comprehensive Guide 2026
Do you want to unlock the power of invisible browsing? A headless browser works like a regular browser but without the visual interface. It runs invisibly, automatically visiting websites to test pages or collect data. Faster and lighter than regular browsers, it's perfect for developers. In this guide, we’ll explain how headless browsers work, their uses, pros/cons, and top tools to choose from.
Lukas Mikelionis
Last updated: Jan 06, 2026
5 min read

How to Train an LLM on Your Own Data: 2026 Step-by-Step Guide
Large language models (LLMs) are universal tools that improve text understanding and generation across different tasks. However, they often lack specific industry knowledge. Training a model on your own data is important for adjusting, accurate, and efficient responses. This article will guide you through the training process, best practices, and challenges to help you get started with confidence.
Mykolas Juodis
Last updated: Jan 05, 2026
8 min read

Navigating Anti-Bot Systems: Pro Tips For 2026
With the rapid improvements in artificial intelligence technologies, it seems that 2026 will present some new challenges for web scraping enthusiasts and professionals. Over the years, anti-bot systems have become increasingly sophisticated, which makes extracting valuable data from websites a true challenge. As businesses intensify their efforts to protect against automated bots, traditional web scraping methods are being put to the test. The surge in anti-bot measures is not only due to heightened cybersecurity awareness but also signifies a shift in the digital ecosystem and growing competition. As a result, those who want to leverage publicly available data need to recalibrate their strategies to navigate and circumvent anti-bot systems.
If CAPTCHAs and IP bans were not on your bingo card for 2026, our comprehensive guide is a must-read. We’ve sat down with our scraping gurus and discussed the best practices, gathered all the pro tips, and summarized what’s coming next for anti-bot systems and scrapers. As 2026 approaches, it demands a proactive approach to understanding, outsmarting, and ultimately thriving in the face of escalating anti-bot measures, so grab a cup of coffee and dive into our guide.
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Vilius Sakutis
Last updated: Jan 05, 2026
11 min read

AI Web Scraping With Python: A Comprehensive Guide
AI web scraping with Python lets you extract data from websites without relying on fragile parsing rules. AI helps handling page inconsistencies and dynamic content, while Python continues to manage fetching. In this guide, you'll see how models extract data from unstructured pages, reduce manual parsing rules, support automation, and scale into reliable pipelines.
Mykolas Juodis
Last updated: Dec 23, 2025
6 min read

How to Scrape Wikipedia: Complete Beginner's Tutorial
Wikipedia has over 60 million articles, making it a valuable resource for machine learning training data, research datasets, and competitive intelligence. This tutorial guides you through extracting your first article to building crawlers that navigate Wikipedia's knowledge graph. You'll learn to extract titles, infoboxes, tables, and image references, then scale up to crawling entire topic clusters.
Justinas Tamasevicius
Last updated: Dec 16, 2025
23 min read

How To Scrape Websites With Dynamic Content Using Python
You've mastered static HTML scraping, but now you're staring at a site where Requests + Beautiful Soup returns nothing but an empty <div> and <script> tags. Welcome to JavaScript-rendered content, where you get the material after the initial request. In this guide, we'll tackle dynamic sites using Python and Selenium (plus a Beautiful Soup alternative).
Justinas Tamasevicius
Last updated: Dec 16, 2025
12 min read

What Is AI Scraping? A Complete Guide
AI web scraping is the process of extracting data from web pages with the help of machine learning and large language models. It uses them to read a web page the same way humans do, by understanding its meaning. The problem with traditional scrapers is that they tend to stop working when the HTML structure is inconsistent or incomplete. In these cases, AI helps scrapers to quickly adapt and find the right information. Sometimes, even a single misplaced tag can ruin your whole web scraping run. AI solves that by shifting focus to the meaning of the content rather than relying on rigid rules to define what data to scrape. That's why AI web scraping is becoming a practical choice for many projects.
Vytautas Savickas
Last updated: Dec 15, 2025
10 min read

How to Scrape SoundCloud for AI Training: Step-By-Step Tutorial
SoundCloud is a mother lode for AI training data, with millions of audio tracks spanning every genre and style imaginable. In this guide, we’ll show you how to tap into that library using Node.js, with the help of proxies. You’ll get hands-on code examples and learn how to collect audio data for three key AI use cases: music generation, audio enhancement, and voice training.
Dominykas Niaura
Last updated: Dec 15, 2025
10 min read

Web Scraping with Ruby: A Simple Step-by-Step Guide
Web scraping with Ruby might not be the first language that comes to mind for data extraction – Python usually steals the spotlight here. However, Ruby's elegant syntax and powerful gems make it surprisingly effective. This guide walks you through building Ruby scrapers from your first HTTP request to production-ready systems that handle JavaScript rendering, proxy rotation, and anti-bot measures. We'll cover essential tools like HTTParty and Nokogiri, show practical code examples, and teach you how to avoid blocks and scale safely.
Zilvinas Tamulis
Last updated: Dec 12, 2025
15 min read

Real Estate Data Scraping: Ultimate Guide
Real estate web scraping has become an essential way to collect up-to-date property data from platforms like Zillow, Realtor.com, Redfin, Rightmove, and Idealista without manual effort. Automated extraction helps individuals and businesses track prices, compare neighborhoods, and monitor supply trends with higher accuracy. In this guide, you'll get a practical overview of the tools, methods, and considerations involved in working with real estate listings as structured data for analysis, research, and everyday business use.
Dominykas Niaura
Last updated: Dec 10, 2025
8 min read

How to Do Web Scraping with curl: Full Tutorial
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.
Zilvinas Tamulis
Last updated: Dec 02, 2025
16 min read

Web Scraping With Java: The Complete Guide
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.
Justinas Tamasevicius
Last updated: Nov 26, 2025
10 min read

How to Scrape Nasdaq Data: A Complete Guide Using Python and Alternatives
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.
Zilvinas Tamulis
Last updated: Nov 21, 2025
14 min read

How to Scrape Images From Any Website With Python
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.
Dominykas Niaura
Last updated: Nov 20, 2025
10 min read

Guide to Web Scraping Airbnb: Methods, Challenges, and Best Practices
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.
Dominykas Niaura
Last updated: Nov 17, 2025
10 min read

How to Scrape Hotel Listings: Unlocking the Secrets
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.
Vilius Sakutis
Last updated: Nov 13, 2025
5 min read

How to Web Scrape a Table with Python: a Complete Guide
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.
Justinas Tamasevicius
Last updated: Nov 10, 2025
9 min read

Mastering Web Scraping Pagination: Techniques, Challenges, and Python Solutions
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.
Dominykas Niaura
Last updated: Oct 28, 2025
10 min read
