ScrapeGraphAI/Scrapegraph-ai
Python scraper based on AI
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 26 days ago, with 122 contributors on GitHub.
Peaked at #25 in the weekly ranking the week of Aug 30, its best in the past year.
Use Cases & Benefits
- Provides an AI-powered Python library to create intelligent web scraping pipelines using large language models and graph logic.
- Enables effortless extraction of structured data from websites and local documents with minimal code and multi-LLM support.
- Use for building single-page scrapers that extract targeted information from webpages using natural language prompts.
- Use for aggregating data from multiple search engine results or multiple webpages in parallel for comprehensive research.
- Use for generating Python scripts or audio files from scraped content to automate workflows or create multimedia outputs.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.).
Just say which information you want to extract and the library will do it for you!
ScrapeGraphAI offers seamless integration with popular frameworks and tools to enhance your scraping capabilities. Whether you're building with Python or Node.js, using LLM frameworks, or working with no-code platforms, we've got you covered with our comprehensive integration options..
You can find more informations at the following link
The reference page for Scrapegraph-ai is available on the official page of PyPI: pypi.
Note: it is recommended to install the library in a virtual environment to avoid conflicts with other libraries 🐱
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+3,007 stars over 82 days across 9 snapshot days; best day +35 on Sep 3.
Forks
3.3K+418
Open issues
28+13
Compared with peers in LLM
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| NVIDIA/auto-ontology | 11.4K | +8.5K | 75 | — |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| DietrichGebert/ponytail | 188.4K | +4.4K | 75 | 12 days ago |
| affaan-m/ECC | 300.8K | +4.3K | 75 | 40 days ago |
| Graphify-Labs/graphify | 145.7K | +3.8K | 75 | today |
| ScrapeGraphAI/Scrapegraph-ai | 32.4K | — | 64 | 26 days ago |
| Category median | 145.7K | +4.4K | 75 | — |
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