---
id: cutlet
version: "0.5.2"
license: unclear
license_treatment: permissive
maintenance: active
---

# cutlet — Romaji converter

License: permissive · Maintenance: active · Downloads: 110.4K/mo

## What it is and what it does

Cutlet is a Python library that converts Japanese text into Latin-character romanization. It supports three major romanization systems (Modified Hepburn, Kunrei-shiki, and Nihon-shiki) and includes features like proper noun capitalization, foreign spelling detection via UniDic, and URL-safe slug generation. The library uses fugashi for morphological analysis, meaning it shares the same tokenization and dictionary infrastructure as other Japanese NLP tools.

The package is useful when you need to make Japanese text readable to audiences unfamiliar with Japanese characters, generate URL-safe versions of Japanese names or phrases, or integrate romanization into broader Japanese language processing pipelines. It handles common exceptions (Tokyo, Osaka) and allows custom overrides for individual words or character mappings.

Use it for:

- Generate URL slugs from Japanese product or article titles for web applications
- Convert Japanese names and addresses to romanized form for international databases or forms
- Build search or filtering systems that accept both Japanese and romanized input
- Create phonetic transcriptions of Japanese text for accessibility or educational purposes
- Integrate romanization into NLP pipelines that process mixed-language content

## Worth the install?

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

Cutlet converts Japanese text to romaji (Latin characters) using multiple romanization systems including Modified Hepburn, Kunrei-shiki, and Nihon-shiki, with support for proper noun capitalization and URL slug generation.

Yes. Cutlet is actively maintained, has no known vulnerabilities, installs with low friction, and solves a specific problem well. Use it if you need to romanize Japanese text; the permissive MIT license and moderate popularity (top 15000 packages) suggest it is stable and reliable for production use. Verify that your environment can satisfy the MeCab dictionary requirement before deploying.

## Install

pip install cutlet
uv add cutlet
poetry add cutlet

## Installing cutlet

Before you install: Low install friction with a pure Python wheel. Actively maintained as of 2026-07-01 with 382 repository stars. Requires three runtime dependencies (jaconv, fugashi, mojimoji) and optionally a MeCab dictionary like unidic-lite for full functionality.

License in practice: Licensed under MIT (permissive), allowing free use, modification, and distribution with minimal restrictions.

Quickstart:

pip install cutlet

import cutlet
katsu = cutlet.Cutlet()
katsu.romaji("カツカレーは美味しい")
# => 'Cutlet curry wa oishii'

Requires Python 3.8 or later. For full functionality, install a MeCab dictionary such as unidic-lite.

Verify before relying:

- Whether fugashi's MeCab dependency is automatically satisfied or requires separate system installation
- Performance characteristics on large volumes of Japanese text
- Accuracy of romanization across different Japanese dialects or specialized terminology

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 110.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

japanese to romaji converter, japanese romanization, hepburn romanization python, japanese text to latin characters, kunrei nihon-shiki romanization, japanese slug generation, japanese phonetic conversion, japanese-nlp, text-conversion, romanization

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