botasaurusvsferret
Botasaurus is an all-in-one Python web scraping framework that combines browser automation, anti-detection, and scaling features into a single package. It aims to simplify the entire web scraping workflow from development to deployment.
Key features include:
- Anti-detect browser Ships with a stealth-patched browser that passes common bot detection tests. Automatically handles fingerprinting, user agent rotation, and other anti-detection measures.
- Decorator-based API Uses Python decorators (@browser, @request) to define scraping tasks, making code clean and easy to organize.
- Built-in parallelism Easy parallel execution of scraping tasks across multiple browser instances with configurable concurrency.
- Caching Built-in caching layer to avoid re-scraping pages during development and debugging.
- Profile persistence Can save and reuse browser profiles (cookies, localStorage) across scraping sessions for maintaining login state.
- Output handling Automatic output to JSON, CSV, or custom formats with built-in data filtering.
- Web dashboard Includes a web UI for monitoring scraping progress, viewing results, and managing tasks.
Botasaurus is designed for developers who want a batteries-included framework that handles anti-detection automatically, without needing to manually configure stealth settings or manage browser fingerprints.
Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast.
Features
- Declarative language
- Support of both static and dynamic web pages
- Embeddable
- Extensible
Ferret is always implemented in Python through pyfer