Levenshtein String Distance

0.27.3 · active · verified Sun Mar 29

The `levenshtein` Python C extension module provides highly optimized functions for fast computation of Levenshtein (edit) distance, string similarity, and other related metrics. It is currently at version 0.27.3 and maintains an active release cadence with regular updates to support newer Python versions.

Warnings

breaking The official package name on PyPI was changed from `python-Levenshtein` to `levenshtein`. While `python-Levenshtein` still exists and depends on the `levenshtein` package, using the new name directly is recommended for clarity and to ensure future compatibility.
Fix: Update your `requirements.txt` and `pip install` commands to use `levenshtein`. If you were importing as `from Levenshtein import ...`, this import path remains correct for both package names.
breaking Support for older Python versions is periodically dropped. For instance, Python 3.8 support was removed in version 0.26.0, and Python 3.9 support was removed in version 0.27.2.
Fix: Ensure your Python environment meets the minimum requirement, which is currently Python 3.10 or later for version 0.27.3.
gotcha The `Levenshtein.ratio()` function calculates a normalized 'Indel similarity' where substitutions are implicitly treated as a deletion followed by an insertion (costing 2 edit operations), rather than a single substitution (costing 1). This can lead to unexpected ratio values if users anticipate a different weighting scheme for substitutions.
Fix: Be aware of the underlying calculation for `ratio()`. If a different similarity metric or weighting is required, consider using `Levenshtein.distance()` with custom `weights` parameters (e.g., `weights=(1,1,1)` for equal costs) and calculating your own normalized ratio, or explore other libraries like `rapidfuzz` that offer various ratio algorithms.

Install

pip install levenshtein Recommended installation
pip install python-Levenshtein Legacy package name (installs 'levenshtein' as dependency)

Imports

Levenshtein
```
import Levenshtein
```
The primary functions like `distance`, `ratio`, `editops` are direct attributes of the imported `Levenshtein` module.

Quickstart

This quickstart demonstrates how to calculate the Levenshtein distance, the normalized similarity ratio, and retrieve the sequence of edit operations between two strings using the `levenshtein` library.

import Levenshtein

string1 = "kitten"
string2 = "sitting"

# Calculate Levenshtein distance
distance = Levenshtein.distance(string1, string2)
print(f"Levenshtein distance between '{string1}' and '{string2}': {distance}")

# Calculate Levenshtein ratio (normalized similarity)
ratio = Levenshtein.ratio(string1, string2)
print(f"Levenshtein ratio between '{string1}' and '{string2}': {ratio:.2f}")

# Get edit operations
edit_ops = Levenshtein.editops(string1, string2)
print(f"Edit operations: {edit_ops}")

view raw JSON →