PyMuPDF (fitz)
Fast Python PDF/XPS/EPUB processing library that extracts text, images, annotations, and metadata from PDFs at 10-20x the speed of alternatives.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Process only trusted PDFs — malicious PDFs can exploit parser vulnerabilities; keep library updated
⚡ Reliability
Best When
High-throughput PDF text/image extraction where processing speed matters and AGPL license is acceptable.
Avoid When
You need a permissive license for commercial software — AGPL requires open-sourcing your code unless you purchase a commercial license.
Use Cases
- • Extract text from 1000-page PDF reports maintaining reading order and page coordinates
- • Convert PDF pages to high-resolution PNG images for vision model processing
- • Extract all embedded images from PDF documents for downstream image analysis
- • Search for specific text patterns across large PDF collections using page-by-page scan
- • Annotate PDFs programmatically — add highlights, redactions, watermarks, and bookmarks
Not For
- • Extracting tables with complex borders — use Camelot or Tabula for tabular data
- • Commercial applications without a commercial MuPDF license (AGPL license restriction)
- • Web browser environments — requires native MuPDF C library installation
Interface
Authentication
Local Python library, no network auth
Pricing
AGPL v3 — commercial use requires separate license from Artifex
Agent Metadata
Known Gotchas
- ⚠ AGPL license — embedding in proprietary software without commercial license is a legal violation; verify before deployment
- ⚠ Scanned PDFs return empty text — must combine with Tesseract/EasyOCR for image-based documents
- ⚠ fitz.open() does not raise on corrupted files — check doc.is_pdf and page count before processing
- ⚠ Text extraction order follows content streams, not visual reading order — complex multi-column layouts may require sort_coords=True
- ⚠ pip install pymupdf downloads pre-built wheels (300-500MB total); fails on platforms without wheel support and requires MuPDF build toolchain
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for PyMuPDF (fitz).
Scores are editorial opinions as of 2026-03-06.