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Scrapling

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Scrapling is an adaptive Python scraping framework that learns from website changes, handling everything from single requests to full-scale crawls.

Screenshot of Scrapling website

Scrapling is an adaptive, intelligent web scraping framework that provides adaptive selectors for website changes and scales from simple requests to complex crawls.

Key Features:

  • Adaptive Selectors - Learns from website structure changes so scrapers stay resilient
  • Smart Fetching - Built-in support for both static and JavaScript-rendered pages
  • CLI Interface - Command-line tools for quick scraping tasks without writing code
  • Spider Framework - Full-featured spider system for large-scale crawling operations
  • Custom Types - Purpose-built data types for clean, structured extraction results
  • Integration Ready - Works with popular Python scraping tools and data pipelines

Whether you're maintaining long-running scrapers, prototyping extraction logic, or building production crawlers, Scrapling provides adaptive scraping that helps maintain extraction rules when sites change.

Features:
JavaScript RenderingStructured ExtractionOpen SourcePython SDKAdaptive SelectorsSpider Framework

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Source code

D4Vinci/Scrapling

  • Stars

    87.9K
  • Forks

    9K
  • Last commit

    2026-10-11
  • License

    BSD-3-Clause
  • Language

    Python

Metrics recorded 2026-10-16

Repository details

Last push: 2026-10-15

License source: Repository license file

View Repository

Frequently asked questions

What is Scrapling?

Scrapling is a Python web-scraping framework with parsing, fetchers and crawling components. You can choose static or browser-based fetching and extract page content through its documented selectors and APIs. Install the dependencies for the components you use.

Sources (checked ): Scrapling introduction and installation

How do I install Scrapling?

The base pip install scrapling package includes the parser and its dependencies. Fetchers and spiders require the fetchers extra, followed by the documented browser-dependency installation when applicable. Follow the current installation guide for your environment.

Sources (checked ): Scrapling introduction and installation

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Sources

github.com

Verified against the D4Vinci/Scrapling repository and the PyPI package.