pinyinIME 0.2.0

A simple Input Method Engine, inspired by Rime.

pinyinIME

Know how to solve every problem that has been solved. -- Feynman

A simple Pinyin Input Method Engine, inspired by Rime.

Pure Python implementation, with no dependencies on any third-party libraries.

Under 500 lines of code!

It is the Chinese input method I currently use in my daily life.

• Author: Wenjie Wu
• PyPI: https://pypi.org/project/pinyinIME/
• Free software: MIT License

Features

• Full pinyin & abbreviation — nihao → 你好；nh → 你好（声母缩写）
• Manual syllable separation(configurable) — xi'an → 西安; ke'neng → 可能
• Emoji input — type Chinese keywords to get emoji candidates
• Traditional Chinese — optional simplified → traditional conversion
• Python API — embed the engine directly in your own Python app
• Custom phrases
• HTTP server — local HTTP daemon for integration with native input method frameworks (e.g. macOS IMKit / Swift)
• Interactive terminal UI — optional TUI for trying the IME in your terminal (connects to the HTTP server)
  • User learning — records your word choices and promotes them in future lookups

Installation

pip install pinyinIME

Or with uv:

uv tool install pinyinIME

To enable traditional Chinese output, install with the optional dependency:

pip install "pinyinIME[traditional]"

Python API

from pinyinIME.engine import PinyinEngine

engine = PinyinEngine()

# Get candidate words (page=0, page_size=9)
engine.query("nihao", 0, 9)
# {
#   "syllables": ["ni", "hao"],
#   "candidates": [{"word": "你好", "syllables": ["ni", "hao"]}, ...],
#   "max_page": 20
# }

# Get candidates with full pinyin and frequency score
engine.lookup("nh")
# [('你好', 'ni hao', 135314), ('那好', 'na hao', 812), ...]

# FMM syllable segmentation
engine.segment("nihao")      # ['ni', 'hao']

# Record a user selection
engine.commit("你好", ["ni", "hao"])

CLI Usage

# Look up candidates for a pinyin string
pinyinIME lookup nihao
pinyinIME lookup nh           # abbreviation: 声母缩写
pinyinIME lookup "xi'an"      # manual syllable split → 西安

# Open debug playground in browser (requires server running)
uv run --with bottle pinyinIME serve   # start HTTP server first
pinyinIME playground                   # then open playground in browser

# Enable debug logging
pinyinIME --verbose lookup nihao

# Interactive terminal UI (requires bottle + rich; start server first)
uv run --with bottle pinyinIME serve                              # start HTTP server (default 127.0.0.1:12358)

uv run  pinyinIME playground     # open browser playground (recommended) ✨
uv run --with rich pinyinIME interactive     # or use terminal interactive UI

Development

git clone https://github.com/wwj718/pinyinIME.git
cd pinyinIME

# Install in editable mode (changes take effect immediately)
uv tool install --editable .

# Run tests
uv run pytest

# Full QA (format, lint, type check, test)
just qa

Architecture Overview

PinyinEngine
├── index/
│   ├── builder.py   IndexBuilder → (Prism, Table)
│   ├── prism.py     Spelling → [(syllable_id, SpellingType)]
│   └── table.py     Trie: syllable_id[] → DictEntry[] (sorted by score)
├── pipeline/
│   ├── types.py        SpellingType enum, SPELLING_PENALTY constants
│   ├── segmentor.py    FmmStrategy (forward maximum matching, O(n×6))
│   ├── translator.py   Querier: DFS over segments, Prism+Table lookup, timeout protection
│   └── filter.py       Filter Protocol; TraditionalFilter (simp→trad)
├── tools/
│   ├── cli.py          Typer CLI: lookup / interactive / clear-cache commands
│   ├── server.py       HTTP daemon (bottle); exposes query/commit/segment API
│   ├── interactive.py  Interactive terminal UI (HTTP client mode)
│   └── user_history.py UserHistory management CLI
└── engine.py           PinyinEngine: init, lookup(), candidates(), select(), commit()

Scoring

Candidates are ranked by an adjusted score:

adjusted_score = round((log(max(raw_score, 1)) + spelling_penalty) × 1_000_000)

Weight multipliers before the log:

Source	Multiplier
User history	10,000,000
Custom phrases	1,000,0 * (1-100)
Emoji	1,000
Essay (Rime) base	1

Spelling penalties: NORMAL → 0.0, ABBREVIATION → log(0.1) ≈ −2.303

Author

pinyinIME was created in 2026 by Wenjie Wu.

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