---
id: jarowinkler
version: "2.0.1"
license: MIT
license_treatment: permissive
maintenance: dormant
---

# jarowinkler — library for fast approximate string matching using Jaro and Jaro-Winkler similarity

License: permissive · Maintenance: dormant · Downloads: 261.4K/mo

## What it is and what it does

JaroWinkler is a specialized string similarity library that computes Jaro and Jaro-Winkler similarity scores between strings or sequences of hashable objects. It wraps a C++14 implementation using bitparallelism to achieve high performance, and is designed to integrate directly with rapidfuzz for efficient batch operations. The library accepts any sequences of hashable objects, not just strings, and supports a score_cutoff parameter to filter weak matches and enable faster code paths internally.

The package is lightweight and installs as a pure Python wheel with a single runtime dependency on rapidfuzz. It targets developers building fuzzy matching, deduplication, or record-linkage systems where string similarity is a core operation. The MIT license and broad Python version support (3.8–3.12) make it suitable for most projects, though the dormant maintenance status means no active development or bug fixes are expected.

Use it for:

- Deduplicating or matching similar names or text entries in databases or data pipelines.
- Building a fuzzy search or autocomplete feature that tolerates typos and spelling variations.
- Record linkage or entity resolution tasks where you need to find likely matches across datasets.
- Batch similarity scoring via rapidfuzz's process.cdist for comparing large collections of strings.
- Custom sequence matching where objects implement __hash__ to define similarity by identity.

## Worth the install?

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

Calculates Jaro and Jaro-Winkler string similarity scores, optimized for performance and designed to integrate with rapidfuzz for batch operations on strings or sequences of hashable objects.

Yes, if you need fast Jaro-Winkler similarity scoring and are comfortable with dormant maintenance. The package is stable, has no known vulnerabilities, installs with low friction, and integrates well with rapidfuzz for batch operations. Not recommended if you require active maintenance or expect frequent updates to support new Python versions.

## Install

pip install jarowinkler
uv add jarowinkler
poetry add jarowinkler

## Installing jarowinkler

Before you install: Low friction: pure Python wheel distribution with no compiled dependencies required for installation. Maintenance is dormant—last commit was 2024-01-08 and no release in over a year—but the repository remains active and the package is stable.

License in practice: MIT license is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.

Quickstart:

pip install jarowinkler

from jarowinkler import jaro_similarity, jarowinkler_similarity

jaro_similarity("Johnathan", "Jonathan")
# 0.8796296296296297

jarowinkler_similarity("Johnathan", "Jonathan")
# 0.9037037037037037

Requires Python 3.8 or later. Source builds require a C++14 compatible compiler.

Verify before relying:

- Whether the dormant maintenance status (last commit 2024-01-08) affects long-term compatibility with future Python versions.
- Performance benchmarks claimed in the description—exact speedup figures vs. jellyfish and python-Levenshtein are not quantified in the fact sheet.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: dormant
- Downloads: 261.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

jaro winkler similarity, string matching algorithm, approximate string comparison, edit distance calculation, fuzzy string matching, sequence similarity scoring, string-similarity, fuzzy-matching, record-linkage

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