pyjarowinkler
Finds the Jaro Winkler Distance indicating a distance or similarity score between two strings.
Decision gist · record as of 2026-08-14
Yes. This is a stable, actively maintained library with no dependencies, permissive licensing, and a focused, well-documented purpose. Install it if you need to compare short strings (names, addresses, codes) and want a non-edit-distance metric that handles transpositions and prefix similarity. The API is straightforward and the implementation is grounded in a published algorithm.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction: pure Python wheel with no runtime dependencies.
- Actively maintained with recent commits; last release 251 days ago and repository shows ongoing activity.
License · maintenance · safety
permissive license (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must retain license notices and document modifications.
last release 2025-12-06 (251 days) · last repo commit 2026-05-12 · 29 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 387,993 downloads/mo, #7,038 on PyPI
Alternatives
Verify before relying
from pyjarowinkler import distance
# Jaro similarity
distance.get_jaro_similarity("PENNSYLVANIA", "PENNCISYLVNIA", decimals=12)
# 0.830031080031
# Jaro-Winkler similarity
distance.get_jaro_winkler_similarity("hello", "haloa", decimals=2)
# 0.76- Whether the package is thread-safe or suitable for concurrent use in multi-threaded applications.
- Performance characteristics on very long strings or in batch processing scenarios beyond the benchmark provided.
What it is and what it does
pyjarowinkler implements the Jaro and Jaro-Winkler string similarity algorithms, which measure how alike two strings are on a scale between 0 and 1. Unlike edit-distance metrics, these algorithms weight errors at the end of strings more heavily and reward matching prefixes, making them useful for comparing short strings like names or addresses where transposition and suffix errors are common.
The package wraps the original C implementation of strcmp95 from the U.S. Census Bureau but adds Python conveniences: optional UTF-8 normalization, homoglyph detection (e.g., distinguishing Cyrillic from Latin characters), case-sensitivity control, and configurable decimal rounding. It has no runtime dependencies and supports Python 3.10 and later.
Use it for
- Deduplicating or matching person names in databases where spelling variations and transpositions are common.
- Comparing address strings to identify duplicate or near-duplicate records in data cleaning pipelines.
- Fuzzy-matching product names or SKUs in e-commerce systems to handle typos and abbreviations.
- Detecting potential duplicate entries in user registration or data import workflows.
- Scoring string pairs in record linkage or entity resolution tasks where exact matching fails.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a stable, actively maintained library with no dependencies, permissive licensing, and a focused, well-documented purpose. Install it if you need to compare short strings (names, addresses, codes) and want a non-edit-distance metric that handles transpositions and prefix similarity. The API is straightforward and the implementation is grounded in a published algorithm.
Install
pyjarowinkler on PyPI
Before you install
Low friction: pure Python wheel with no runtime dependencies. Actively maintained with recent commits; last release 251 days ago and repository shows ongoing activity.
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must retain license notices and document modifications.
Quickstart
from pyjarowinkler import distance
# Jaro similarity
distance.get_jaro_similarity("PENNSYLVANIA", "PENNCISYLVNIA", decimals=12)
# 0.830031080031
# Jaro-Winkler similarity
distance.get_jaro_winkler_similarity("hello", "haloa", decimals=2)
# 0.76Verify before relying
- Whether the package is thread-safe or suitable for concurrent use in multi-threaded applications.
- Performance characteristics on very long strings or in batch processing scenarios beyond the benchmark provided.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 251 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 387,993 / month, #7,038 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Text Processing |
Evidence: pyjarowinkler-3.0.0-py3-none-any.whl
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See also jaro-winkler · jarowinkler · textdistance · strsimpy · pylcs · pylev · python-Levenshtein · pyuca · pyphonetics · Levenshtein