strsimpy

library0.2.1pypypi✓ verified 84d ago

Strsimpy is a Python library that provides implementations for various string similarity and distance measures, including popular algorithms like Levenshtein, Jaro-Winkler, N-Gram, Cosine Similarity, and Jaccard Index. It's designed to be straightforward to use for text analysis and data matching tasks. The current version is 0.2.1. Releases are infrequent, typically addressing bug fixes or adding new algorithms.

data

pip install strsimpy

github ↗package ↗

INSTALL

IMPORT

SIG · STRSIMPY

strsimpy

datapythonv0.2.1

Install

1.6s avg

Import

9ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.2.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.010s · 18.1MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 1.6s · import 0.007s · 19MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Levenshtein

✓ from strsimpy.levenshtein import Levenshtein

JaroWinkler

✓ from strsimpy.jaro_winkler import JaroWinkler

Ngram

✓ from strsimpy.ngram import Ngram

WeightedLevenshtein

✓ from strsimpy.weighted_levenshtein import WeightedLevenshtein

✗ from strsimpy.weighted_levenshtein import Levenshtein

This quickstart demonstrates calculating Levenshtein distance and Jaro-Winkler similarity between strings. Most algorithms follow a pattern of instantiating a class and then calling a `distance()` or `similarity()` method.

from strsimpy.levenshtein import Levenshtein s0 = "안녕하세요" s1 = "안녕하세유" levenshtein = Levenshtein() distance = levenshtein.distance(s0, s1) print(f"Levenshtein distance between '{s0}' and '{s1}': {distance}") s2 = "apple" s3 = "aple" distance2 = levenshtein.distance(s2, s3) print(f"Levenshtein distance between '{s2}' and '{s3}': {distance2}") from strsimpy.jaro_winkler import JaroWinkler jaro_winkler = JaroWinkler() similarity = jaro_winkler.similarity(s2, s3) print(f"Jaro-Winkler similarity between '{s2}' and '{s3}': {similarity}")

Debug

Known issues

breakingThe package name was changed from `similarity` to `strsimpy`. Old import paths will fail.

fix

Update all `import similarity...` statements to `import strsimpy...` and reinstall the package.

affects: <0.1.2

breakingThe `WeightedLevenshtein` algorithm's API changed significantly in v0.1.7. It now uses functions for weight calculation instead of expecting Class or Objects, simplifying its usage.

fix

Review the documentation for `WeightedLevenshtein` and update your weight calculation logic to use direct functions as arguments, rather than class instances.

affects: <0.1.7

gotchaThe `numpy` dependency was removed in v0.1.5 to lighten the package. If you were implicitly relying on `numpy` being installed alongside `strsimpy`, it might no longer be present.

fix

If your project requires `numpy`, ensure it is explicitly listed in your project's dependencies.

affects: <0.1.5

gotchaA `ZeroDivisionError` was fixed in ShingleBased algorithms (e.g., Jaccard, Cosine Similarity) for certain edge cases.

fix

Upgrade to version 0.1.2 or later to ensure correct calculations and avoid potential runtime errors with ShingleBased algorithms.

affects: <0.1.2

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'strsimpy.JaroWinkler'

String similarity algorithms like JaroWinkler are not directly exposed at the top level of the `strsimpy` module; they reside in their specific submodules within `strsimpy.similarity`.

fix

from strsimpy.similarity.jarowinkler import JaroWinkler

AttributeError: module 'strsimpy' has no attribute 'JaroWinkler'

The `JaroWinkler` class is not a direct attribute of the top-level `strsimpy` module. It must be imported from its specific submodule.

fix

from strsimpy.similarity.jarowinkler import JaroWinkler
jarowinkler_sim = JaroWinkler()

TypeError: object of type 'NoneType' has no len()

One or both of the input arguments passed to a similarity method (e.g., `similarity(s1, s2)`) are not strings, leading to string operations failing.

fix

s1 = str(s1) if s1 is not None else ''
s2 = str(s2) if s2 is not None else ''
similarity_score = your_similarity_object.similarity(s1, s2)

TypeError: __init__() missing 1 required positional argument: 'n'

When initializing an `NGram` similarity object, the required `n` parameter, which defines the size of the n-grams, was not provided.

fix

from strsimpy.similarity.ngram import NGram
ngram_sim = NGram(n=2) # Specify 'n' for bigrams, trigrams, etc.

Upgrade

Version history

0.2.1latest on PyPI · released Sep 10, 2021

Audit

Dependencies

No dependency data recorded yet.

Agent activity

11 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/luozhouyang/python-string-similarity ↗

packagehttps://pypi.org/project/strsimpy/ ↗