A simple Input Method Engine, inspired by Rime.
Project description
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.
The current codebase is 800+ lines, with efforts underway to reduce it to under 500 lines.
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 -
User learning — records your word choices and promotes them in future lookups
-
Custom phrases — add your own words via
~/.config/pinyinIME/custom_phrase.txt -
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
-
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)
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 import PinyinEngine
engine = PinyinEngine.default()
# Get candidate words
engine.candidates("nihao") # ['你好', ...]
engine.candidates("nh") # ['你好', '那好', ...]
engine.candidates("n") # ['你', '呢', '哪', ...]
# 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 (triggers learning)
engine.commit("你好", ["ni", "hao"])
# Select the i-th candidate on page p (also triggers learning)
engine.select("nh", index=0, page=0, page_size=5)
# Stateful paginated session
session = engine.new_session(page_size=5)
session.set_input("nihao")
print(session.current_page()) # ['你好', ...]
session.next_page()
session.select(0) # returns ('你好', '')
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
# Clear disk index cache
pinyinIME clear-cache
# 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
uv run --with rich pinyinIME interactive # then launch interactive UI
Configuration
User data is stored in ~/.config/pinyinIME/:
| File | Purpose |
|---|---|
custom_phrase.txt |
Custom words, one per line, loaded at startup |
pinyin.userdb |
User selection history (plain text log) |
config.json |
Engine config (see defaults below) |
Default config.json
{
"engine": {
"segment_delimiter": "'",
"top_n": 10,
"max_abbrev_fanout": 10,
"search_timeout": 0.5
},
"log": {
"level": "INFO"
}
}
Custom Phrases
Add your own words to ~/.config/pinyinIME/custom_phrase.txt, one word per line:
# 每行一个词条,格式:词[, 音节][, 权重](后两项可选)
一丹中心
阅读场
π, pi, 100
艾伦·凯, ai lun kai
动态媒介
Pinyin is auto-annotated from the built-in character dictionary.
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/
│ ├── dict_loader.py dictionary data
│ ├── essay_loader.py Word frequency data
│ ├── custom_phrase_loader.py User custom words
│ ├── builder.py IndexBuilder → (Prism, Table); PhraseAnnotator
│ ├── 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 (default) + DagAllPathsStrategy; SegmentationStrategy Protocol
│ ├── translator.py Querier: DFS over segments, Prism+Table lookup, timeout protection
│ ├── filter.py DeduplicateFilter; TraditionalFilter (simp→trad)
│ └── session.py InputSession: stateful pagination, NORMAL + CHAR_BY_CHAR modes
└── userdata/
├── user_paths.py Config dir & file path management
└── user_history.py UserHistory: plain-text frequency log (pinyin.userdb)
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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