---
id: habachen
version: "0.6.0"
license: MIT
license_treatment: permissive
maintenance: aging
---

# habachen — Yet Another Fast Japanese String Converter

License: permissive · Maintenance: aging · Downloads: 126.8K/mo

## What it is and what it does

Habachen is a Japanese text conversion library that handles transformations between full-width (zenkaku) and half-width (hankaku) characters, as well as conversions between hiragana and katakana scripts. It is written as a compiled extension and designed for speed and minimal memory overhead, making it suitable for processing large volumes of Japanese text.

The package provides straightforward functions like `han_to_zen()`, `zen_to_han()`, `to_katakana()`, and `to_hiragana()`, each with optional parameters to selectively convert only specific character types (ASCII, digits, or kana). It supports Python 3.8 through 3.14, including the No-GIL mode introduced in Python 3.14, and offers pre-built wheels for macOS, Linux, and Windows across multiple architectures.

Use it for:

- Normalize user input in Japanese web forms or search boxes by converting mixed-width characters to a standard form.
- Prepare Japanese text for natural language processing pipelines that require consistent character width or script representation.
- Convert hiragana-heavy user-generated content to katakana for consistency with technical or formal documentation standards.
- Batch-process large Japanese text corpora (e.g., historical documents, news archives) where performance and memory efficiency matter.
- Build Japanese text preprocessing steps in machine learning workflows where character normalization is a prerequisite.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Habachen converts between full-width and half-width characters, and between hiragana and katakana in Japanese text, with a focus on speed and low memory usage.

Yes, if you work with Japanese text and need fast, reliable character and script conversions. The library is stable (MIT-licensed, no known vulnerabilities), has no runtime dependencies, and offers measurably faster performance than comparable alternatives. The aging maintenance status (310 days since last release) is a minor concern but not a blocker—the repository is still active and the package is feature-complete for its narrow scope. Install if Japanese text normalization is a real requirement; skip if you only need occasional conversions or don't work with Japanese.

## Install

pip install habachen
uv add habachen
poetry add habachen

## Installing habachen

Before you install: Medium install friction due to compiled wheels for multiple platforms and Python versions (3.8–3.14). The package is aging—last release was 310 days ago—but the repository remains active with a recent commit on 2025-10-26, suggesting maintenance is ongoing rather than abandoned.

License in practice: MIT license is permissive; you can use, modify, and distribute habachen with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart:

pip install habachen

import habachen

# Convert half-width to full-width
result = habachen.han_to_zen('abc!?012ﾊﾝｶｸﾓｼﾞ')
print(result)  # 'ａｂｃ！？０１２ハンカクモジ'

# Convert hiragana to katakana
result = habachen.to_katakana('もじれつの変換')
print(result)  # 'モジレツノ変換'

Verify before relying:

- Whether the Free-threading (No-GIL) support in v0.6.0 is production-ready or still experimental.
- Current maintenance cadence and likelihood of future updates beyond bug fixes.
- Performance characteristics on very large documents or streaming use cases.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: aging
- Downloads: 126.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

japanese character width conversion, hiragana katakana converter, full-width half-width conversion, japanese string normalization, fast japanese text processing, japanese character transformation, zenkaku hankaku conversion, japanese-text, character-normalization, no-gil-ready

[View on SkillFed](https://skillfed.io/packages/habachen) · [View on PyPI](https://pypi.org/project/habachen/)