Build your own scrapers, with these FREE developer libraries in various languages.
Java library for HTML/XML parsing, data extraction, and element manipulation.
.NET library for parsing and manipulating malformed HTML, supports XPath and LINQ queries.
Python library for easy web scraping and data extraction from HTML/XML documents.
Efficient XML/HTML processing with Python's lxml library.
Python library for efficient XML/HTML processing with XPath, XSLT, and schema validation.
JavaScript library for efficient HTML/XML parsing with jQuery-like syntax.
Convert XML/HTML strings into DOM documents for easy manipulation via JavaScript.
Python library for HTML parsing and web scraping with jQuery-like syntax.
A command-line web scraper supporting HTML parsing, JSON parsing, and client-side JavaScript evaluation
Web text extraction tool for efficient crawling and content extraction.
High-performance HTML parser for Node.js following the WHATWG standard.
Heuristic tool for extracting meaningful text from HTML pages.
Python library for accurate HTML parsing, supports error recovery and multiple tree formats.
Scrapling is a fast, adaptive Python web scraper that bypasses anti-bot measures and outperforms libraries like BeautifulSoup.
Efficient Node.js HTML/XML parser for high-performance web scraping and data extraction.
Ruby gem for parsing and manipulating XML/HTML with CSS3 selectors and XPath expressions.
Efficiently extracts and parses online news articles using Python.
Streamlines web scraping with CSS, XPath, and regex for HTML/XML data extraction.
No tools in Web Scraping Libraries match your search
Try a different keyword or reset the active search filter.
Building a robust scraper isn't about finding one magic library; it's about combining several tools to handle the different stages of the process. A typical scraping workflow involves three key steps.
The first step is always to download the raw content from a URL. This is handled by an HTTP client library. For a simple GET request to a static website, a library like Python's requests or Node.js's axios is all you need. These tools are fast and straightforward, but remember: they don't render JavaScript. What you get is the initial HTML, just as the server sent it.
Once you have the raw HTML, you need to parse it into a navigable structure. This is where HTML parsing libraries are essential. Tools like BeautifulSoup (Python), Cheerio (Node.js), and Nokogiri (Ruby) excel at this. They transform messy HTML into a clean tree of objects that you can search and traverse using CSS selectors or XPath, making it easy to pinpoint and extract the exact data you need.
What if the content you need is loaded by JavaScript after the page loads? This is where browser automation libraries come in. Tools like Selenium, Puppeteer, and Playwright programmatically control a real headless browser (like Chrome or Firefox). They can wait for elements to load, click buttons, and scroll down the page, ensuring you can scrape the final, fully-rendered content from even the most complex, dynamic websites.
Building your own scraper with libraries offers ultimate control, but it also comes with responsibility. Hereβs how to decide which approach is right for you.