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A local figure-workflow tool for reproducible, publication-ready Matplotlib panels.

Project description

FigStudio

FigStudio is a local-first figure workflow for scientific Python users who want to turn data already present in a script or notebook into polished, reproducible Matplotlib panels.

It opens a browser editor from your Python process, lets you map live variables to plot layers or statistics recipes, previews through Matplotlib, exports publication files, and saves plain Matplotlib OO code back to a controlled script block or notebook cell.

Install

pip install figstudio

The wheel includes the React editor. End users do not need Node, npm, Vite, or the frontend source tree after installation.

Try It

figstudio demo

For a script, add FigStudio after data preparation and give generated plotting code one controlled block:

import figstudio

# Prepare data first.
session = figstudio.open(locals(), script_path=__file__, block_id="main")

# figstudio:start main
# figstudio:end main

In the editor, choose a live variable, add a plot layer or statistics recipe, polish the figure, export PNG/SVG/PDF, then click Save code.

Documentation

Language Start here
English docs/en/index.md
Chinese / 中文 docs/zh/index.md

Common entry points:

Reader English 中文
Figure users Get Started 快速开始
Scientific workflows Workflows 科研制图工作流
API consumers API Reference API 参考
Contributors Developer Guide 开发者指南

Development

uv run --extra dev pytest
cd frontend
npm install
npm run build
npm run dev

Build a publishable package:

uv build

The build hook bundles the frontend into the Python wheel. Runtime installs from a built wheel still use the packaged editor and do not require frontend tooling.

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