The PDF engine behind over 50 million monthly downloads, powering AI pipelines worldwide.
PyMuPDF Lite is a cut-down version of PyMuPDF without the PyMuPDF Layout engine.
- Minimal
- Reduced disc space (e.g. 25MB pymupdf-lite vs 100's of MB for pymupdf and its required packages.
- Available for more OS's, cpus and python versions, for example:
- Pyodide
- Musllinux
- MacOS-x64
- All official python versions
- No mandatory dependencies —
pip install pymupdf-liteand you're done
pip install pymupdf-liteWheels are available for Windows, macOS, and Linux on Python 3.11–3.15. If no pre-built wheel exists for your platform, pip will compile from source (requires a C/C++ toolchain).
See: https://pypi.org/project/pymupdf-lite/#files for the definitive list of available wheels.
After installation, run the pymupdf-config command,
This will review what is installed and show information about what other packages
(Python and otherwise) may be available for your system and could improve accuracy and speed.
Use the API just as you would use PyMuPDF, e.g.
import pymupdf
doc = pymupdf.open("sample.pdf")
...| Category | Formats |
|---|---|
| PDF & derivatives | PDF, XPS, EPUB, CBZ, MOBI, FB2, SVG, TXT, MD |
| Images | PNG, JPEG, BMP, TIFF, GIF, and more |
| Format | Notes |
|---|---|
| Full fidelity conversion from Office formats | |
| SVG | Vector page rendering |
| Image (PNG, JPEG, …) | Page rasterisation at any DPI |
| Markdown | Structure-aware, LLM-ready |
| JSON | Bounding boxes, layout data, per-element detail |
| Plain text | Fast, lightweight extraction |
Python 3.11 – 3.15. Wheels ship for:
manylinuxx86_64 and aarch64musllinuxx86_64- macOS x86_64 and arm64
- Windows x86 and x86_64
Full installation guide, API reference, cookbook, and tutorial at pymupdf.readthedocs.io.
PyMuPDF and MuPDF are maintained by Artifex Software, Inc.
- Open source — GNU AGPL v3. Free for open-source projects.
- Commercial — separate commercial licences available from Artifex for proprietary applications.
Contributions are welcome. Please open an issue before submitting large pull requests.
If you find this useful, please consider giving it a star — it helps others discover it!