plotlet 0.6.0

Python library for reproducible, multi-panel scientific figures, with byte-identical output across machines and an extension API for custom plot types.

plotlet

plotlet is a Python library for reproducible, multi-panel scientific figures. Byte-identical output across machines, a standard plotting vocabulary, and a first-class extension story for custom plot types.

Documentation

Hands-on tour with executable examples:

• notebooks/00_introduction.ipynb — long-form data, aesthetic inheritance, layering, composition (more topic notebooks in notebooks/)

Reference docs in docs/:

• API reference — mark methods, frame options, scales, tick overrides
• Philosophy — what's in core, what's not, and why
• Subplots — multi-panel composition, shared scales
• Coordinates — Circular, custom non-Cartesian projections
• Extending — write your own plot type
• Themes — visual presets
• AI attributes — data-plotlet-* schema for automation

Reference plot types beyond the standard vocabulary ship in the separate plotlet-extensions package (single-file artists — sankey, alluvial, raincloud, upset_plot, …; pip install plotlet-extensions, then import plotlet.extensions.<name>) and in the plotlet-cookbook repo (multi-file, domain-specific projects). A few extensions the core tests depend on still ship in core under src/plotlet/extensions/.

For AI assistants

Compact, vendor-neutral onboarding docs live in skills/:

• skills/users.md — for AI tools generating plotlet code on a user's behalf.
• skills/developers.md — for AI (or human) contributors working on plotlet itself. Symlink as CLAUDE.md / .cursorrules / AGENTS.md as your tool expects.

Dependencies

plotlet supports Python 3.10+.

Required: fonttools, scipy (regression, qq, CI error bands, clustering/dendrogram), resvg_py (PNG rendering — prebuilt wheels, no system libraries). numpy / pandas / polars inputs work transparently.

Optional: cairosvg for PDF export (pip install plotlet[pdf]).

Installation

pip install plotlet

Testing

pip install -e ".[test]"
pytest tests/                  # check vs. committed baselines
pytest tests/ --update         # regenerate (review the diff!)

Development

Development takes place on GitHub. Please submit bugs to the issue tracker with a reproducible example.

License

MIT