Scrapling is a high-performance, intelligent web scraping library for Python that adapts to website changes and outperforms popular alternatives.
It provides features like dynamic loading, automation, anti-bot protection bypass, smart element tracking, and flexible selection methods.
Scrapling offers lightning-fast HTTP requests, memory efficiency, and fast JSON serialization.
Developer-friendly features include a powerful navigation API, rich text processing, auto selectors generation, and familiar API.
Installation is simple using pip and browsers' dependencies can be installed by running a command.
The library allows fetching websites with interfaces like Fetcher, StealthyFetcher, and PlayWrightFetcher.
Scrapling's advanced parsing features include smart navigation, content-based selection, finding similar elements, and handling structural changes.
The article also compares Scrapling's performance with popular Python libraries like Scrapy and Lxml in text extraction and extraction by text speed tests.
The library addresses common questions in FAQs and emphasizes educational and research purposes only with a BSD-3 license.
Contributions are welcome, with known issues highlighted, acknowledgments given, and references to related projects.
Scrapling is designed and crafted by Karim Shoair, emphasizing its high functionality, ease of use, and performance benefits.