---
id: wordninja
version: "2.0.0"
license: unclear
license_treatment: unclear
maintenance: abandoned
---

# wordninja — Probabilistically split concatenated words using NLP based on English Wikipedia uni-gram frequencies.

License: unclear · Maintenance: abandoned · Downloads: 1.2M/mo

## What it is and what it does

Word Ninja is a lightweight word segmentation library that splits concatenated English text into individual words using probabilistic modeling based on English Wikipedia uni-gram frequencies. It takes strings like 'imateapot' and returns ['im', 'a', 'teapot'], making it useful for humanizing database table names, reversing camelCase concatenations, or processing text where word boundaries have been lost. The library has no runtime dependencies and performs the segmentation quickly, handling both short strings and long passages. It also supports custom language models if you need non-English segmentation or want to override the default English model.

However, the package has been abandoned since 2019-08-10 with no updates since. Python version support is unspecified, and the license treatment is unclear, creating uncertainty about compatibility with modern Python releases and legal usage terms.

Use it for:

- Humanize database table or column names by splitting concatenated identifiers into readable words for display.
- Reverse camelCase or PascalCase strings back into space-separated words for logging or user-facing output.
- Process text where word boundaries have been removed or munged together, such as in legacy data formats.
- Build custom language models for word segmentation in non-English languages or specialized domains.

## Worth the install?

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

Splits concatenated words into their constituent parts using probabilistic English language modeling—for example, turning 'imateapot' into ['im', 'a', 'teapot'].

No. The package is abandoned (latest release 2019-08-10), Python version support is unspecified, the license is undeclared, and compatibility with modern Python is uncertain. For a simple, maintained alternative, consider other word segmentation libraries. If you have a specific legacy dependency on wordninja, verify the license terms from the repository and test thoroughly on your target Python version before deploying.

## Install

pip install wordninja
uv add wordninja
poetry add wordninja

## Installing wordninja

Before you install: High install friction: the package has been abandoned since its latest release on 2019-08-10 with no updates since. No runtime dependencies, but the stalled maintenance and lack of Python version specification create uncertainty about compatibility with current Python releases.

License in practice: License treatment is unclear—no SPDX identifier or raw license text is declared. Before using in production or distribution, verify the actual license terms from the GitHub repository to ensure compliance with your project's requirements.

Quickstart:

pip install wordninja

import wordninja
wordninja.split('derekanderson')
# Returns: ['derek', 'anderson']

Python version support is unspecified; compatibility with modern Python versions is uncertain given the package's abandonment since 2019-08-10.

Verify before relying:

- Whether the package works reliably on current Python versions, given no updates since 2019-08-10.
- Whether the bundled English language model remains accurate for modern English usage.
- Actual license terms and permissions (SPDX and raw license text are both absent from metadata).

## Package facts

- License: not declared (unclear)
- Python support: unspecified
- Install friction: high
- Maintenance: abandoned
- Downloads: 1.2M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

split concatenated words, word segmentation, camelcase to words, humanize database names, nlp word splitting, reverse word munging, english word boundary detection, nlp, word-segmentation, abandoned

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