Installation
pip install cn-sort
Requires Python 3.6+. Dependencies (pypinyin, jieba) are installed automatically.
Quick start
from cn_sort import sort_text_list, Mode
# Sort by Pinyin (default)
sort_text_list(['唯依', '唯衣', '唯一', '啊'])
# → ['啊', '唯一', '唯衣', '唯依']
# Sort by stroke order
sort_text_list(['三', '二', '一', '一二'], mode=Mode.BIHUA)
# → ['一', '一二', '二', '三']
# Polyphonic characters handled by context
sort_text_list(['重要', '重庆'])
# → ['重庆', '重要'] (chóng < zhòng)
# Mixed Chinese / Latin
sort_text_list(['中国', 'abc', '啊'])
# → ['abc', '啊', '中国']
# Million-scale: multiprocess kicks in automatically
sort_text_list(big_list, threshold=100_000)
Features
- Two modes —
Mode.PINYIN(pinyin + stroke tiebreaker) orMode.BIHUA(stroke order only) - Polyphonic characters —
pypinyinuses surrounding context to pick the correct reading - Scales to 1M+ words — auto-switches to a multiprocess producer-consumer pipeline above
threshold - Mixed content — Latin / numeric / punctuation sorts before CJK by default
- Zero config — no extra data downloads; priority table ships inside the package
API
sort_text_list(text_list, *, freeze=False, threshold=100_000, mode=Mode.PINYIN) → list[str]
| Parameter | Type | Default | Description |
|---|---|---|---|
text_list |
list[str] |
required | Words to sort |
mode |
Mode |
Mode.PINYIN |
Sorting mode |
threshold |
int |
100_000 |
Switch to multiprocess above this count |
freeze |
bool |
False |
Set True when calling outside if __name__ == '__main__' on Windows |
Mode
| Value | Behaviour |
|---|---|
Mode.PINYIN |
Sort by Pinyin reading; stroke order breaks ties |
Mode.BIHUA |
Sort by stroke count only |
set_stdout_level(level: str) → bool
Set console log verbosity. level ∈ {"DEBUG", "INFO", "WARN", "ERROR", "CRITICAL"}.
How it works
cn_sort converts each word into a tuple of integer priorities, then applies LSD radix sort — sorting from the last character column to the first using Python's stable timsort.
Pinyin mode
- Priority table — 20 000+ characters pre-ranked by Pinyin + stroke order, stored in
all_word.jsonfor O(1) lookup. - Word → tuple — each character maps to a signature (e.g.
人_ren2) looked up in the table. - LSD radix sort —
operator.itemgettersorts each column in place; stable sort guarantees correct ordering. - Polyphonic chars —
pypinyinselects the right reading from word context automatically.
Stroke-order mode
Characters are ranked by stroke increment level instead of Pinyin signature.
Polyphonic character example
Priority table schema
Large-scale multiprocess pipeline
For lists larger than threshold, cn_sort spawns a producer-consumer process pool:
- N producer processes (CPU count − 1): segment with jieba, deduplicate, push to independent queues.
- 1 consumer process: collects tokens from all queues, builds a priority-tuple cache.
- Main process: reassembles segments, applies final radix sort.
Performance
| Scale | Time | Notes |
|---|---|---|
| 10 words | < 1 ms | first call loads the priority table (~40 ms); subsequent calls are instant |
| 10 000 words | ~20 ms | repeated words hit the pypinyin cache; near-instant on warm runs |
| 48 000 words | ~100 ms | single-process; cache makes repeated patterns essentially free |
| 1 000 000 words | ~20 s | multiprocess pipeline; bottleneck is jieba segmentation |
What makes it fast:
- The 20 000-character priority table loads once and stays in memory for the lifetime of the process.
pypinyinresults are cached per word — sorting a list where many words share characters (common in practice) skips redundant pinyin lookups entirely.- The multiprocess pipeline uses direct
multiprocessing.Queue— no Manager proxy server, so IPC overhead is minimal. operator.itemgetterreplaces per-call lambda objects in the radix sort inner loop.
The jieba segmentation step dominates million-scale runs. Replacing it with a faster segmenter is the highest-leverage future optimisation.
Contributing
git clone https://github.com/bmxbmx3/cn_sort.git
cd cn_sort
pip install pypinyin jieba
- Fork the repo and create a branch:
git checkout -b feat/your-feature - Make changes; add tests where applicable.
- Open a Pull Request.
Good first contributions: Traditional Chinese support, a pytest test suite, faster large-scale segmentation.
License
MIT © bmxbmx3
1 maintainer
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