Project Title
PyMuPDF — High Performance Python Library for PDF and Document Manipulation
Overview
PyMuPDF is a high-performance Python library designed for data extraction, analysis, conversion, and manipulation of PDF and other document types. It stands out for its efficiency and the ability to handle a wide range of document formats. PyMuPDF adds Python bindings and abstractions to MuPDF, a lightweight PDF, XPS, and eBook viewer, renderer, and toolkit.
Key Features
- High-performance document processing
 - Data extraction and analysis
 - Conversion and manipulation of PDF and other document formats
 - Python bindings for MuPDF
 
Use Cases
- Data scientists and analysts for extracting and analyzing data from PDFs
 - Developers needing to convert and manipulate PDFs within their applications
 - Businesses requiring document management solutions for various file types
 
Advantages
- Supports a wide range of document types
 - High performance and efficiency in processing
 - Python bindings for easy integration into Python applications
 
Limitations / Considerations
- Requires Python 3.9 or later
 - Some optional features require additional packages to be installed
 
Similar / Related Projects
- PDFMiner: A tool for extracting information from PDF documents, but without the high-performance capabilities of PyMuPDF.
 - PyPDF2: A pure-python library for working with PDFs, but with less functionality compared to PyMuPDF.
 - PDFPlumber: A Python library for extracting data from PDFs, focusing more on text extraction rather than the broader capabilities of PyMuPDF.
 
Basic Information
- GitHub: https://github.com/pymupdf/PyMuPDF
 - Stars: 8,181
 - License: AGPL-3.0
 - Last Commit: 2025-10-05
 
📊 Project Information
- Project Name: PyMuPDF
 - GitHub URL: https://github.com/pymupdf/PyMuPDF
 - Programming Language: Python
 - ⭐ Stars: 8,181
 - 🍴 Forks: 646
 - 📅 Created: 2012-10-06
 - 🔄 Last Updated: 2025-10-05
 
🏷️ Project Topics
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🔗 Related Resource Links
📚 Documentation
🌐 Related Websites
This article is automatically generated by AI based on GitHub project information and README content analysis