| Name | joyokanji JSON |
| Version |
1.1.0
JSON |
| download |
| home_page | None |
| Summary | The joyokanji converts old-form kanji characters into new-form kanji characters. |
| upload_time | 2025-08-13 13:48:30 |
| maintainer | None |
| docs_url | None |
| author | new-village |
| requires_python | >=3.11 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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|
| keywords |
kanji
japanese
normalization
text
|
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 |
| bugtrack_url |
|
| requirements |
pdfminer.six
pypdfium2
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| coveralls test coverage |
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|
# joyo-kanji
[](https://github.com/new-village/joyo-kanji/actions/workflows/tests.yml) 
[日本語](./README_Ja.md) / [English](./README.md)
`joyokanji` is a tiny, fast Python library that converts old-form kanji (Japanese: *kyūjitai*, 舊字/旧字) to new-form kanji (*shinjitai*, 新字) using a mapping grounded in the Agency for Cultural Affairs’ **Jōyō Kanji list** (常用漢字表). See the source list (Japanese) published by the Government of Japan: [https://www.bunka.go.jp/kokugo\_nihongo/sisaku/joho/joho/kijun/naikaku/kanji/](https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/kanji/).
Optionally, you can also normalize common variant glyphs used in personal names (e.g., 髙/𠮷/﨑/隆) by enabling `variants=True`.
> **What’s kyūjitai vs. shinjitai?**
> After WWII, Japan simplified the shapes of many commonly used kanji. The older shapes are *kyūjitai* (e.g., **鹽 → 塩**, **國 → 国**, **體 → 体**), and the simplified shapes are *shinjitai*. This library helps normalize text by replacing old forms with their modern counterparts.
---
## Table of Contents
* [Features](#features)
* [Installation](#installation)
* [Quick Start](#quick-start)
* [Variants (optional)](#variants-optional)
* [How It Works](#how-it-works)
* [Examples](#examples)
* [Scope & Limitations](#scope--limitations)
* [Data Source & Attribution](#data-source--attribution)
* [Performance Notes](#performance-notes)
* [When to Use / Not to Use](#when-to-use--not-to-use)
* [Contributing](#contributing)
* [License](#license)
---
## Features
* converts old-form (kyūjitai) kanji to modern (shinjitai) forms.
* Mapping-based, deterministic behavior — no surprises.
* Fast single-pass conversion using `str.translate` (linear time O(n)).
* Loads mapping once from `joyokanji/config/kanji.json` and caches it.
* Optional: normalize common variant glyphs (e.g., 髙, 𠮷, 﨑, 隆, 羽, 練, …) by passing `variants=True` (uses `joyokanji/config/variants.json`).
* Pure-Python, minimal footprint, easy to embed in pipelines.
## Installation
```bash
pip install joyokanji
```
> If your package name differs on PyPI, update the command above accordingly.
## Quick Start
```python
import joyokanji
text = "鹽と黃と黑と點と發"
print(joyokanji.convert(text)) # => 塩と黄と黒と点と発
# Optional: include common variant glyphs
text2 = "髙﨑𠮷野屋"
print(joyokanji.convert(text2, variants=True)) # => 高崎吉野屋
```
API:
```
joyokanji.convert(text: str, variants: bool = False) -> str
```
## How It Works
* On first use, the library loads a JSON dictionary (`joyokanji/config/kanji.json`) of old→new pairs (e.g., `{"鹽": "塩"}`) and builds a translation table with `str.maketrans`.
* Conversion is then a single pass over your string using `str.translate`, which is both simple and efficient.
* The table is cached in memory for subsequent calls.
* When `variants=True`, an additional map from `joyokanji/config/variants.json` is merged in (variant entries take precedence on conflicts). A separate cached table is maintained for this mode.
## Examples
Input → Output:
| Kyūjitai | Shinjitai |
| -------- | --------- |
| 鹽 | 塩 |
| 黃 | 黄 |
| 黑 | 黒 |
| 點 | 点 |
| 發 | 発 |
*Only characters listed in the mapping are transformed; all others remain unchanged.*
### Variants (optional)
When `variants=True`, common variant glyphs (often seen in proper names) are also normalized. Examples:
| Variant | Normalized |
| ------- | ---------- |
| 髙 | 高 |
| 𠮷 | 吉 |
| 﨑 | 崎 |
| 隆 | 隆 |
| 羽 | 羽 |
| 練 | 練 |
## Scope & Limitations
* **Coverage**: The mapping focuses on characters relevant to modern Japanese usage and the Jōyō Kanji context. It is **not** a general Traditional ↔ Simplified Chinese converter and is **not** intended for zh-Hant texts (Taiwan/Hong Kong).
* **Context-free**: Conversion is character-to-character. The library does **not** inspect context, readings, or word boundaries.
* **Proper nouns & personal names**: Historical documents, proper nouns, and person names may intentionally use old forms (e.g., in legal names). Automatic conversion can be undesirable in such use cases. Review outputs when accuracy matters.
- For this reason, variant glyph normalization is OFF by default. Enable `variants=True` only when desired.
* **Normalization**: The library does not perform Unicode normalization (e.g., NFKC) by itself. If you need it, run normalization **before or after** conversion according to your pipeline’s needs.
* **Ambiguous variants**: Some characters have multiple historical variants. The mapping chooses a widely accepted modern form; if you need domain-specific variants, consider customizing the mapping.
## Data Source & Attribution
* Primary reference: the **Jōyō Kanji list** (常用漢字表) as published by Japan’s Agency for Cultural Affairs: [https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/pdf/joyokanjihyo_20101130.pdf](https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/pdf/joyokanjihyo_20101130.pdf).
* The included mapping is derived from this reference and related historical simplifications. Any omissions or edge cases are welcomed as issues or PRs.
## Performance Notes
* Building the translation table happens once per process. Subsequent calls are memory-only and very fast.
* The complexity is O(n) with low constant overhead, making it suitable for batch text processing.
## When to Use / Not to Use
**Use when:** you need to normalize legacy texts into modern Japanese (OCR outputs, historical corpora, or mixed-form datasets).
**Avoid or review carefully when:** processing legal names, brand names, or scholarly editions where the original glyph choices carry meaning.
## Contributing
* Issues and PRs are welcome, especially for: (1) mapping improvements, (2) tests covering edge cases, (3) documentation in English/Japanese.
* If proposing new pairs, please include a source/rationale and examples.
## License
Apache License 2.0
Raw data
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"maintainer": null,
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"requires_python": ">=3.11",
"maintainer_email": null,
"keywords": "kanji, japanese, normalization, text",
"author": "new-village",
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/49/ae/d5fc7c7bd643921bb049f7f425c65ad68bbea4fb1e2ea4e50cabe0ef8c7a/joyokanji-1.1.0.tar.gz",
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"description": "# joyo-kanji \n[](https://github.com/new-village/joyo-kanji/actions/workflows/tests.yml) \n \n[\u65e5\u672c\u8a9e](./README_Ja.md) / [English](./README.md) \n \n`joyokanji` is a tiny, fast Python library that converts old-form kanji (Japanese: *ky\u016bjitai*, \u820a\u5b57/\u65e7\u5b57) to new-form kanji (*shinjitai*, \u65b0\u5b57) using a mapping grounded in the Agency for Cultural Affairs\u2019 **J\u014dy\u014d Kanji list** (\u5e38\u7528\u6f22\u5b57\u8868). See the source list (Japanese) published by the Government of Japan: [https://www.bunka.go.jp/kokugo\\_nihongo/sisaku/joho/joho/kijun/naikaku/kanji/](https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/kanji/).\n\nOptionally, you can also normalize common variant glyphs used in personal names (e.g., \u9ad9/\ud842\udfb7/\ufa11/\uf9dc) by enabling `variants=True`.\n\n> **What\u2019s ky\u016bjitai vs. shinjitai?**\n> After WWII, Japan simplified the shapes of many commonly used kanji. The older shapes are *ky\u016bjitai* (e.g., **\u9e7d \u2192 \u5869**, **\u570b \u2192 \u56fd**, **\u9ad4 \u2192 \u4f53**), and the simplified shapes are *shinjitai*. This library helps normalize text by replacing old forms with their modern counterparts.\n\n---\n\n## Table of Contents\n\n* [Features](#features)\n* [Installation](#installation)\n* [Quick Start](#quick-start)\n* [Variants (optional)](#variants-optional)\n* [How It Works](#how-it-works)\n* [Examples](#examples)\n* [Scope & Limitations](#scope--limitations)\n* [Data Source & Attribution](#data-source--attribution)\n* [Performance Notes](#performance-notes)\n* [When to Use / Not to Use](#when-to-use--not-to-use)\n* [Contributing](#contributing)\n* [License](#license)\n\n---\n\n## Features\n\n* converts old-form (ky\u016bjitai) kanji to modern (shinjitai) forms.\n* Mapping-based, deterministic behavior \u2014 no surprises.\n* Fast single-pass conversion using `str.translate` (linear time O(n)).\n* Loads mapping once from `joyokanji/config/kanji.json` and caches it.\n* Optional: normalize common variant glyphs (e.g., \u9ad9, \ud842\udfb7, \ufa11, \uf9dc, \ufa1e, \ufa57, \u2026) by passing `variants=True` (uses `joyokanji/config/variants.json`).\n* Pure-Python, minimal footprint, easy to embed in pipelines.\n\n## Installation\n\n```bash\npip install joyokanji\n```\n\n> If your package name differs on PyPI, update the command above accordingly.\n\n## Quick Start\n\n```python\nimport joyokanji\n\ntext = \"\u9e7d\u3068\u9ec3\u3068\u9ed1\u3068\u9ede\u3068\u767c\"\nprint(joyokanji.convert(text)) # => \u5869\u3068\u9ec4\u3068\u9ed2\u3068\u70b9\u3068\u767a\n\n# Optional: include common variant glyphs\ntext2 = \"\u9ad9\ufa11\ud842\udfb7\u91ce\u5c4b\"\nprint(joyokanji.convert(text2, variants=True)) # => \u9ad8\u5d0e\u5409\u91ce\u5c4b\n```\n\nAPI:\n\n```\njoyokanji.convert(text: str, variants: bool = False) -> str\n```\n\n## How It Works\n\n* On first use, the library loads a JSON dictionary (`joyokanji/config/kanji.json`) of old\u2192new pairs (e.g., `{\"\u9e7d\": \"\u5869\"}`) and builds a translation table with `str.maketrans`.\n* Conversion is then a single pass over your string using `str.translate`, which is both simple and efficient.\n* The table is cached in memory for subsequent calls.\n* When `variants=True`, an additional map from `joyokanji/config/variants.json` is merged in (variant entries take precedence on conflicts). A separate cached table is maintained for this mode.\n\n## Examples\n\nInput \u2192 Output:\n\n| Ky\u016bjitai | Shinjitai |\n| -------- | --------- |\n| \u9e7d | \u5869 |\n| \u9ec3 | \u9ec4 |\n| \u9ed1 | \u9ed2 |\n| \u9ede | \u70b9 |\n| \u767c | \u767a |\n\n\n*Only characters listed in the mapping are transformed; all others remain unchanged.*\n\n### Variants (optional)\n\nWhen `variants=True`, common variant glyphs (often seen in proper names) are also normalized. Examples:\n\n| Variant | Normalized |\n| ------- | ---------- |\n| \u9ad9 | \u9ad8 |\n| \ud842\udfb7 | \u5409 |\n| \ufa11 | \u5d0e |\n| \uf9dc | \u9686 |\n| \ufa1e | \u7fbd |\n| \ufa57 | \u7df4 |\n\n## Scope & Limitations\n\n* **Coverage**: The mapping focuses on characters relevant to modern Japanese usage and the J\u014dy\u014d Kanji context. It is **not** a general Traditional \u2194 Simplified Chinese converter and is **not** intended for zh-Hant texts (Taiwan/Hong Kong).\n* **Context-free**: Conversion is character-to-character. The library does **not** inspect context, readings, or word boundaries.\n* **Proper nouns & personal names**: Historical documents, proper nouns, and person names may intentionally use old forms (e.g., in legal names). Automatic conversion can be undesirable in such use cases. Review outputs when accuracy matters.\n\t- For this reason, variant glyph normalization is OFF by default. Enable `variants=True` only when desired.\n* **Normalization**: The library does not perform Unicode normalization (e.g., NFKC) by itself. If you need it, run normalization **before or after** conversion according to your pipeline\u2019s needs.\n* **Ambiguous variants**: Some characters have multiple historical variants. The mapping chooses a widely accepted modern form; if you need domain-specific variants, consider customizing the mapping.\n\n## Data Source & Attribution\n\n* Primary reference: the **J\u014dy\u014d Kanji list** (\u5e38\u7528\u6f22\u5b57\u8868) as published by Japan\u2019s Agency for Cultural Affairs: [https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/pdf/joyokanjihyo_20101130.pdf](https://www.bunka.go.jp/kokugo_nihongo/sisaku/joho/joho/kijun/naikaku/pdf/joyokanjihyo_20101130.pdf).\n* The included mapping is derived from this reference and related historical simplifications. Any omissions or edge cases are welcomed as issues or PRs.\n\n## Performance Notes\n\n* Building the translation table happens once per process. Subsequent calls are memory-only and very fast.\n* The complexity is O(n) with low constant overhead, making it suitable for batch text processing.\n\n## When to Use / Not to Use\n\n**Use when:** you need to normalize legacy texts into modern Japanese (OCR outputs, historical corpora, or mixed-form datasets).\n\n**Avoid or review carefully when:** processing legal names, brand names, or scholarly editions where the original glyph choices carry meaning.\n\n## Contributing\n\n* Issues and PRs are welcome, especially for: (1) mapping improvements, (2) tests covering edge cases, (3) documentation in English/Japanese.\n* If proposing new pairs, please include a source/rationale and examples.\n\n## License\n\nApache License 2.0\n",
"bugtrack_url": null,
"license": "Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n \n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n \n 1. Definitions.\n \n \"License\" shall mean the terms and conditions for use, reproduction,\n and distribution as defined by Sections 1 through 9 of this document.\n \n \"Licensor\" shall mean the copyright owner or entity authorized by\n the copyright owner that is granting the License.\n \n \"Legal Entity\" shall mean the union of the acting entity and all\n other entities that control, are controlled by, or are under common\n control with that entity. For the purposes of this definition,\n \"control\" means (i) the power, direct or indirect, to cause the\n direction or management of such entity, whether by contract or\n otherwise, or (ii) ownership of fifty percent (50%) or more of the\n outstanding shares, or (iii) beneficial ownership of such entity.\n \n \"You\" (or \"Your\") shall mean an individual or Legal Entity\n exercising permissions granted by this License.\n \n \"Source\" form shall mean the preferred form for making modifications,\n including but not limited to software source code, documentation\n source, and configuration files.\n \n \"Object\" form shall mean any form resulting from mechanical\n transformation or translation of a Source form, including but\n not limited to compiled object code, generated documentation,\n and conversions to other media types.\n \n \"Work\" shall mean the work of authorship, whether in Source or\n Object form, made available under the License, as indicated by a\n copyright notice that is included in or attached to the work\n (an example is provided in the Appendix below).\n \n \"Derivative Works\" shall mean any work, whether in Source or Object\n form, that is based on (or derived from) the Work and for which the\n editorial revisions, annotations, elaborations, or other modifications\n represent, as a whole, an original work of authorship. For the purposes\n of this License, Derivative Works shall not include works that remain\n separable from, or merely link (or bind by name) to the interfaces of,\n the Work and Derivative Works thereof.\n \n \"Contribution\" shall mean any work of authorship, including\n the original version of the Work and any modifications or additions\n to that Work or Derivative Works thereof, that is intentionally\n submitted to Licensor for inclusion in the Work by the copyright owner\n or by an individual or Legal Entity authorized to submit on behalf of\n the copyright owner. For the purposes of this definition, \"submitted\"\n means any form of electronic, verbal, or written communication sent\n to the Licensor or its representatives, including but not limited to\n communication on electronic mailing lists, source code control systems,\n and issue tracking systems that are managed by, or on behalf of, the\n Licensor for the purpose of discussing and improving the Work, but\n excluding communication that is conspicuously marked or otherwise\n designated in writing by the copyright owner as \"Not a Contribution.\"\n \n \"Contributor\" shall mean Licensor and any individual or Legal Entity\n on behalf of whom a Contribution has been received by Licensor and\n subsequently incorporated within the Work.\n \n 2. Grant of Copyright License. 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