Search Results for "xpath"

Scrapy is a fast, open source, high-level framework for crawling websites and extracting structured data from these websites. Portable and written in Python, it can run on Windows, Linux, macOS and BSD. Scrapy is powerful, fast and simple, and also easily extensible. Simply write the rules to extract the data, and add new functionality if you wish without having to touch the core. Scrapy does the rest, and can be used in a number of applications. It can be used for data mining, monitoring...

...Developers define crawlers using components such as spiders, parsers, and items, allowing them to organize crawling logic and data extraction rules clearly. Gain supports CSS selectors and XPath expressions for parsing page content and extracting specific elements. Gain also allows developers to configure headers, concurrency levels, and proxy settings to control how crawlers interact with target websites. Because it uses asynchronous programming, Gain can handle multiple requests efficiently while minimizing blocking operations.

Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations.

Dude is a very simple framework for writing web scrapers using Python decorators. The design, inspired by Flask, was to easily build a web scraper in just a few lines of code. Dude has an easy-to-learn syntax. Dude is currently in Pre-Alpha. Please expect breaking changes. You can run your scraper from terminal/shell/command-line by supplying URLs, the output filename of your choice and the paths to your python scripts to dude scrape command.

mlscraper is a Python library designed to automatically extract structured data from HTML pages without requiring developers to manually write CSS selectors or XPath rules. Instead of defining extraction logic by hand, users provide a few examples of the data they want to retrieve from a webpage. It analyzes those examples within the HTML document and determines patterns or rules that can be used to extract the same type of information from similar pages. Once trained, the generated scraper can process new pages and return the extracted data in structured formats such as dictionaries or lists. ...

...When using this library you automatically get full JavaScript support! (Using Chromium, thanks to puppeteer) CSS Selectors (a.k.a jQuery-style, thanks to PyQuery). XPath Selectors, for the faint of heart. Mocked user-agent (like a real web browser). Automatic following of redirects. Connection–pooling and cookie persistence. The Requests experience you know and love, with magical parsing abilities, and async support. The rest of the code operates the same way as the synchronous version except that results is a list containing multiple response objects however the same basic processes can be applied as above to extract the data you want.