cihai 0.19.0

Library for CJK (chinese, japanese, korean) language data.

cihai ·

Python library for CJK (chinese, japanese, korean) data.

This project is under active development. Follow our progress and check back for updates!

Quickstart

API / Library (this repository)

$ pip install --user cihai

from cihai.core import Cihai

c = Cihai()

if not c.unihan.is_bootstrapped:  # download and install Unihan to db
    c.unihan.bootstrap()

query = c.unihan.lookup_char('好')
glyph = query.first()
print("lookup for 好: %s" % glyph.kDefinition)
# lookup for 好: good, excellent, fine; well

query = c.unihan.reverse_char('good')
print('matches for "good": %s ' % ', '.join([glph.char for glph in query]))
# matches for "good": 㑘, 㑤, 㓛, 㘬, 㙉, 㚃, 㚒, 㚥, 㛦, 㜴, 㜺, 㝖, 㤛, 㦝, ...

See API documentation and /examples.

CLI (cihai-cli)

$ pip install --user cihai-cli

Character lookup:

$ cihai info 好

char: 好
kCantonese: hou2 hou3
kDefinition: good, excellent, fine; well
kHangul: 호
kJapaneseOn: KOU
kKorean: HO
kMandarin: hǎo
kTang: "*xɑ̀u *xɑ̌u"
kTotalStrokes: "6"
kVietnamese: háo
ucn: U+597D

Reverse lookup:

$ cihai reverse library

char: 圕
kCangjie: WLGA
kCantonese: syu1
kCihaiT: '308.302'
kDefinition: library
kMandarin: tú
kTotalStrokes: '13'
ucn: U+5715
--------

UNIHAN data

All datasets that cihai uses have stand-alone tools to export their data. No library required.

• unihan-etl - UNIHAN data exports for csv, yaml and json.

Developing

$ git clone https://github.com/cihai/cihai.git`

$ cd cihai/

Bootstrap your environment and learn more about contributing. We use the same conventions / tools across all cihai projects: pytest, sphinx, flake8, mypy, black, isort, tmuxp, and file watcher helpers (e.g. entr(1)).

Quick links

• Quickstart
• Datasets a full list of current and future data sets
• Python API
• Roadmap
• Python support: >= 3.7, pypy
• Source: https://github.com/cihai/cihai
• Docs: https://cihai.git-pull.com
• Changelog: https://cihai.git-pull.com/history.html
• API: https://cihai.git-pull.com/api.html
• Issues: https://github.com/cihai/cihai/issues
• Test coverage: https://codecov.io/gh/cihai/cihai
• pypi: https://pypi.python.org/pypi/cihai
• OpenHub: https://www.openhub.net/p/cihai
• License: MIT