nexaloid Python
Python bindings for the Nexaloid Chinese tokenizer.
The wheel bundles the native library and the default dictionary, so normal use does not need a separate dictionary file.
Install
pip install nexaloid
Usage
from nexaloid import Mode, Tokenizer
tokenizer = Tokenizer()
print([token.text for token in tokenizer.tokenize("南京市长江大桥")])
print([token.text for token in tokenizer.tokenize("中国科学院计算技术研究所", Mode.SEARCH)])
print([token.text for token in tokenizer.tokenize("中国科学院计算技术研究所", Mode.RECALL_SEARCH)])
for token in tokenizer.tokenize("昨日中概股集体跌超百分之五", Mode.SEARCH):
print(token.text, token.source, token.flags)
The default tokenizer uses the packaged data/dict/nexaloid.nxdict. Pass dict_path when you need a custom dictionary:
tokenizer = Tokenizer(dict_path="data/dict/nexaloid.tsv")
Domain dictionaries use a restricted identifier rather than a path. domain
must match [A-Za-z0-9_-]{1,64} and the resolved dictionary must remain below
NEXALOID_DOMAIN_DICT_DIR.
Whitespace tokens are filtered by default. Enable jieba-like whitespace retention when needed:
tokenizer = Tokenizer(preserve_whitespace=True)
print(tokenizer.lcut("中文 English\t混排\n第二行"))
Jieba-style API
import nexaloid.compat_jieba as jieba
print(jieba.lcut("我爱北京天安门"))
print(jieba.lcut("小明硕士毕业", HMM=True))
print(list(jieba.cut_for_search("中国科学院计算技术研究所")))
HMM=True loads the bundled BMES HMM plugin and artifact to recover unknown words such as short names and domain terms.
Token Contract
Mode.SEARCH preserves every non-whitespace token on the Accurate path, including single-character and repeated-position tokens, and adds in-boundary Han 2-gram / 3-gram expansions. Mode.RECALL_SEARCH also adds explicit lattice candidates. cut_for_search() keeps search-term behavior by filtering one-character terms and deduplicating text.
Each token exposes the stable source name in source and source-specific metadata in flags. For source == "rule", a nonzero flags value is the custom rule's 1-based JSON array index. Plugin tokens use flags for plugin-defined subtypes.
Threading and lifecycle
A Tokenizer serializes all native calls on that instance, including
tokenization, mutation, plugin loading, and close(). close() is idempotent,
waits for the current call to return, and later operations raise
NexaloidError. Use separate instances when application-level parallelism is
required.
Development
cd bindings/python
python -m build
cd ../..
$env:PYTHONPATH = "$PWD\bindings\python\src"
python tools\badcase_runner.py
python tools\regression_checks.py
1 maintainer
Metadata
1 maintainer
Release files for nexaloid 0.1.34
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 393.7 MB
Release files / nexaloid-0.1.34-cp313-cp313-win_amd64.whl
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| Tags | CPython 3.9 macOS 15.0+ x86-64 |
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| Size | 15.5 MB |
| Tags | CPython 3.9 macOS 15.0+ ARM64 |
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