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python-levenshtein

library0.27.4pypypi✓ verified 27d ago

python-levenshtein is a Python C extension module providing highly optimized functions for computing string edit distances (like Levenshtein distance), similarity ratios, and related metrics. While the package itself has been renamed to `levenshtein` and is actively maintained under that name by the RapidFuzz team, the `python-levenshtein` PyPI package (version 0.27.3) continues to be updated as a compatibility wrapper. It maintains a positive release cadence.

data

pip install python-levenshtein

github ↗package ↗docs ↗changelog ↗

INSTALL

IMPORT

SIG · PYTHON-LEVENSHTEIN

python-levenshtein

datapythonv0.27.4

Install

2.7s avg

Import

35ms

Disk

32MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.27.4 · 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 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.036s · 38.2MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 2.7s · import 0.034s · 31MB

32MB installed

● package 32MB

Code

Verified usage

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

Levenshtein

✓ import Levenshtein

✗ from python_levenshtein import distance

The installed module is always named `Levenshtein` regardless of the PyPI package name (`python-levenshtein` or `levenshtein`).

Calculate the Levenshtein distance (minimum number of single-character edits) and a similarity ratio between two strings.

import Levenshtein str1 = "kitten" str2 = "sitting" # Calculate Levenshtein distance distance = Levenshtein.distance(str1, str2) print(f"Levenshtein distance between '{str1}' and '{str2}': {distance}") # Calculate similarity ratio ratio = Levenshtein.ratio(str1, str2) print(f"Similarity ratio between '{str1}' and '{str2}': {ratio:.2f}") # Example with different strings str3 = "hello" str4 = "hallo" distance2 = Levenshtein.distance(str3, str4) ratio2 = Levenshtein.ratio(str3, str4) print(f"\nLevenshtein distance between '{str3}' and '{str4}': {distance2}") print(f"Similarity ratio between '{str3}' and '{str4}': {ratio2:.2f}")

Debug

Known issues

breakingThe primary development for this library now occurs under the `levenshtein` PyPI package. `python-levenshtein` is maintained as a compatibility wrapper. It's recommended to install `levenshtein` directly for new projects and for accessing the latest features and fixes, though `pip install python-levenshtein` will still work by installing `levenshtein` as a dependency.

fix

Prefer `pip install levenshtein` for new projects. If using `python-levenshtein`, be aware it acts as a shim.

affects: All versions post-renaming (roughly 0.20.0 onwards for `levenshtein` and 0.25.0 onwards for `python-levenshtein`).

gotchaThe library is licensed under GPL-2.0. This copyleft license can be restrictive for projects with different licensing requirements, as it may necessitate that derivative works also be licensed under GPL.

fix

Review your project's licensing compatibility. For less restrictive alternatives, consider `rapidfuzz` (MIT license) or `pylev` (New BSD license).

affects: All versions

breakingRecent versions of the underlying `levenshtein` library (which `python-levenshtein` now wraps) have dropped support for older Python versions. For example, version 0.26.0 dropped support for Python 3.8, and 0.27.0 requires Python 3.10 or later.

fix

Ensure your project uses Python 3.10 or newer to maintain compatibility with the latest versions of the library.

affects: 0.26.0+

gotchaWhile `python-levenshtein` (and `levenshtein`) is highly optimized due to its C extension, for extensive fuzzy matching, especially with large datasets or when a wider array of string similarity algorithms (e.g., Jaro-Winkler, token-based matching) is needed, the `rapidfuzz` library is often a more modern and performant alternative. `rapidfuzz` also offers more flexible licensing (MIT).

fix

For new projects or performance-critical applications, evaluate `rapidfuzz` (`pip install rapidfuzz`) as a potential alternative. It offers a similar API for many functions.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'Levenshtein'

The old `python-Levenshtein` package (which used `import Levenshtein`) has been superseded; the current `python-levenshtein` PyPI package installs the `levenshtein` module, which should be imported with a lowercase 'l'.

fix

import levenshtein

error: Microsoft Visual C++ 14.0 or greater is required.

Installing Python packages with C extensions on Windows requires Microsoft Visual C++ Build Tools to compile the C source code if a pre-compiled wheel is not available or compatible.

fix

Install Microsoft C++ Build Tools, typically via the 'Desktop development with C++' workload in the Visual Studio Installer.

ImportError: cannot import name 'distance' from 'levenshtein'

The `levenshtein` module provides its functions directly at the top level, so specific functions are accessed as attributes of the main module rather than being imported individually.

fix

import levenshtein
# Then use functions like: levenshtein.distance('string1', 'string2')

ModuleNotFoundError: No module named 'python_levenshtein'

While the PyPI package is `python-levenshtein`, the actual Python module installed and intended for import is named `levenshtein`.

fix

import levenshtein

Upgrade

Version history

0.27.4latest on PyPI · released Aug 8, 2026

Audit

Dependencies

pythonrequiredRuntime environment

levenshteinrequiredThe underlying, actively developed package that `python-levenshtein` now wraps for compatibility.

Agent activity

21 hits · last 30 days

node

Resources

githubhttps://github.com/rapidfuzz/python-Levenshtein ↗

packagehttps://pypi.org/project/python-levenshtein/ ↗

docshttps://rapidfuzz.github.io/Levenshtein/ ↗

changeloghttps://github.com/rapidfuzz/python-Levenshtein/blob/main/CHANGELOG.rst ↗