OpenCC
Conversion between Traditional and Simplified Chinese
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, uses a permissive license, and solves a specific, well-defined problem for Chinese text processing. Install friction is moderate but manageable via prebuilt wheels. Recommended for any project requiring Chinese character normalization or regional text adaptation.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Medium install friction due to compiled wheels; prebuilt binaries available for Python 3.10–3.13 on Windows, macOS (Intel and ARM), and Linux.
- Package is actively maintained with a recent release and no known vulnerabilities.
License · maintenance · safety
Apache License 2.0 (permissive) — Licensed under Apache License 2.0 (permissive); safe for commercial and proprietary use with standard attribution requirements.
last release 2026-07-12 (33 days) · last repo commit 2026-08-14 · 9,902 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 472,733 downloads/mo, #6,474 on PyPI
Alternatives
Verify before relying
pip install opencc
import opencc
converter = opencc.OpenCC('s2t.json')
result = converter.convert('汉字')
print(result) # 漢字- Whether the package includes pre-downloaded conversion dictionaries or requires separate resource installation
- Performance characteristics for large-scale text conversion (throughput, latency)
- Whether custom conversion chains or inline configurations are accessible from the Python API
What it is and what it does
OpenCC is a Python binding to an open-source Chinese character conversion engine that handles bidirectional conversion between Simplified and Traditional Chinese, plus Japanese Kanji (Shinjitai). It operates at both character and phrase level, preserving context-aware meaning and supporting regional vocabulary differences across Mainland China, Taiwan, and Hong Kong.
The package wraps a compiled C++ library and ships prebuilt wheels for modern Python versions on major platforms. It has no runtime dependencies and is designed for text processing pipelines where Chinese normalization or localization is needed. The conversion is deterministic and does not perform translation between languages or dialects.
Use it for
- Normalize Chinese text in a document processing pipeline to a single script (e.g., all Simplified for consistency)
- Localize Chinese content for specific regions by converting vocabulary (e.g., '鼠标' to '滑鼠' for Taiwan)
- Prepare training data for NLP models by standardizing character representation across mixed-script corpora
- Convert user-generated content in web applications to a canonical form before storage or search indexing
- Handle Japanese Kanji modernization (Shinjitai) in text that mixes modern and historical forms
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, uses a permissive license, and solves a specific, well-defined problem for Chinese text processing. Install friction is moderate but manageable via prebuilt wheels. Recommended for any project requiring Chinese character normalization or regional text adaptation.
Install
opencc on PyPI
Before you install
Medium install friction due to compiled wheels; prebuilt binaries available for Python 3.10–3.13 on Windows, macOS (Intel and ARM), and Linux. Package is actively maintained with a recent release and no known vulnerabilities.
License in practice
Licensed under Apache License 2.0 (permissive); safe for commercial and proprietary use with standard attribution requirements.
Quickstart
pip install opencc
import opencc
converter = opencc.OpenCC('s2t.json')
result = converter.convert('汉字')
print(result) # 漢字Verify before relying
- Whether the package includes pre-downloaded conversion dictionaries or requires separate resource installation
- Performance characteristics for large-scale text conversion (throughput, latency)
- Whether custom conversion chains or inline configurations are accessible from the Python API
Package facts
| License | Apache License 2.0 permissive |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 33 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 472,733 / month, #6,474 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseNatural Language :: Chinese (Simplified)Natural Language :: Chinese (Traditional)Programming Language :: PythonProgramming Language :: Python :: 3Topic :: Scientific/EngineeringTopic :: Software DevelopmentTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python ModulesTopic :: Software Development :: LocalizationTopic :: Text Processing :: LinguisticTyping :: Typed |
Evidence: opencc-1.4.1-cp310-cp310-macosx_10_9_x86_64.whl; opencc-1.4.1-cp310-cp310-macosx_11_0_arm64.whl; opencc-1.4.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; opencc-1.4.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; opencc-1.4.1-cp310-cp310-win_amd64.whl; opencc-1.4.1-cp311-cp311-macosx_10_9_x86_64.whl; opencc-1.4.1-cp311-cp311-macosx_11_0_arm64.whl; opencc-1.4.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; opencc-1.4.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; opencc-1.4.1-cp311-cp311-win_amd64.whl; opencc-1.4.1-cp312-cp312-macosx_10_13_x86_64.whl; opencc-1.4.1-cp312-cp312-macosx_11_0_arm64.whl; opencc-1.4.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; opencc-1.4.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; opencc-1.4.1-cp312-cp312-win_amd64.whl; opencc-1.4.1-cp313-cp313-macosx_10_13_x86_64.whl; opencc-1.4.1-cp313-cp313-macosx_11_0_arm64.whl; opencc-1.4.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl; opencc-1.4.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; opencc-1.4.1-cp313-cp313-win_amd64.whl
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See also opencc-python-reimplemented · zhconv · wetext · jieba · hanzidentifier · pypinyin · jieba3k · kanjize · pykakasi · spacy-pkuseg