Repo brief: ScrapeGraphAI/Scrapegraph-ai

Generated by RepoPilot · document generated 2026-09-16 · concise human review Evidence snapshot · analyzed 2026-09-16T18:44:03.960Z · commit 532dfffbf6ee

Verdict

Healthy — Healthy across all four use cases

• Last commit 1w ago
• 19 active contributors
• Distributed ownership (top contributor 49% of recent commits)
• MIT licensed
• 2 more receipts on the live page

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

What it is

ScrapeGraphAI is a Python web scraping library that uses LLM (Large Language Models) and graph-based logic to automatically generate scraping pipelines for websites and local documents (HTML, XML, JSON, Markdown, etc.). Instead of writing page-specific parsers, developers describe what data they want extracted and the library uses AI to determine how to get it. Monorepo structure: scrapegraphai/ package contains core logic organized into builders/ (graph construction), graphs/ (25+ specialized scraping graph types like SmartScraperGraph, OmniScraperGraph, SearchGraph), and docloaders/ (browser backends: Chromium, BrowserBase, Plasmate, ScrapeDo). Configuration-driven design where…

Start here

Read these in order:

• scrapegraphai/utils/logging.py — Foundation: doesn't import anything internally and is imported by 12 other files. Read first to learn the vocabulary.
• scrapegraphai/utils/copy.py — Foundation: imported by 12, no internal dependencies of its own.
• scrapegraphai/prompts/__init__.py — Built on the foundation; imported by 18 downstream files.
• scrapegraphai/helpers/__init__.py — Built on the foundation; imported by 5 downstream files.
• scrapegraphai/graphs/abstract_graph.py — Layer 2 — composes lower-level code into reusable abstractions (imported 26×).

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

git clone https://github.com/ScrapeGraphAI/Scrapegraph-ai.git
cd Scrapegraph-ai
# Verify pyproject.toml for dependencies before installing
pip install -e .
# Or use: pip install scrapegraphai (PyPI package available)

Note: pyproject.toml should specify all dependencies and Python version requirements—review it before proceeding.

Daily commands:

Inferred from Makefile presence and pytest.ini:

make test          # Run test suite (from Makefile)
pytest             # Direct pytest run
# For local development with Docker:
docker-compose up
# For container deployment:
docker build -t scrapegraphai .

Exact run commands require inspecting Makefile and pyproject.toml (not fully provided).

Key cautions & unknowns

• Scorecard: default branch unprotected (0/10)
• Critical unknown: Dependencies and version constraints are not shown in provided evidence—must inspect pyproject.toml for LLM provider SDK requirements, async/sync patterns, and Python version support. **LLM…
• Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

• Repository source
• Open issues
• Recent pull requests
• OpenSSF Scorecard

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.

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