Kanjigen — Kanji Learning Roadmap Generator
A Jupyter Notebook tool that generates optimal learning roadmaps for a given kanji list, ordering characters by component dependencies.
Overview
Kanjigen generates a learning roadmap for a list of kanji characters. Instead of learning kanji in random order, it figures out which characters to learn first based on their component radicals — so you always learn the building blocks before the compound characters that use them.
Given a target kanji list (e.g., JLPT N3), it outputs a dependency-sorted sequence: learn 木 before 森, learn 日 before 明, and so on.
How It Works
- Parse each kanji into its component radicals/primitives
- Build a dependency graph: kanji A depends on kanji B if B is a component of A
- Topological sort the graph to produce a valid learning order
- Output the ordered list with annotations
Tech Stack
- Python — graph construction and topological sort
- Jupyter Notebook — interactive exploration and visualization
- Kanji decomposition data — component/radical mappings