yfedoseev/pdf_oxide
The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.
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.
2 releases in the last 90 days, the latest 47 days ago, with 37 contributors on GitHub.
Peaked at #68 in the weekly ranking the week of Mar 8, its best in the past year.
Use Cases & Benefits
- Provides a fast, reliable PDF library for text extraction, image extraction, markdown conversion, creation, and editing across Rust, Python, WASM, CLI, and MCP server.
- Delivers 5× faster performance than leading libraries with 100% pass rate on 3,830 real-world PDFs and zero panics or timeouts.
- Use for building retrieval-augmented generation pipelines by converting PDFs to clean Markdown for LLM frameworks like LangChain or LlamaIndex.
- Use for integrating local PDF content extraction into AI assistants via the MCP server for privacy-preserving, high-speed document access.
- Ideal for large-scale document processing workflows requiring fast extraction of text, images, forms, and metadata from thousands of PDFs.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
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
The fastest PDF library for text extraction, image extraction, and markdown conversion. Rust core with Python bindings, WASM support, CLI tool, and MCP server for AI assistants. 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf. 100% pass rate on 3,830 real-world PDFs. MIT licensed.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
138+27
Open issues
410+339
Compared with peers in LLM
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| NVIDIA/auto-ontology | 7.5K | +5.6K | 37 | — |
| HKUDS/DeepTutor | 55.5K | +5.5K | 65 | 5 days ago |
| affaan-m/ECC | 297.9K | +5.2K | 63 | 35 days ago |
| DietrichGebert/ponytail | 185.3K | +5.1K | 60 | 7 days ago |
| yfedoseev/pdf_oxide | 1.1K | — | 55 | 47 days ago |
| Category median | 113.6K | +5.5K | 60 | — |
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