editdistpy

library0.4.0pypypi✓ verified 23d ago

editdistpy (version 0.2.0) provides fast implementations of the Levenshtein and Damerau Optimal String Alignment (OSA) edit distance algorithms. Written in Cython/C++, it offers significant speed improvements for string comparison tasks. The library is actively maintained, with releases made periodically, the latest major version (0.2.0) released in February 2026.

data ai-ml

pip install editdistpy

github ↗package ↗changelog ↗

INSTALL

IMPORT

SIG · EDITDISTPY

editdistpy

datapythonv0.4.0

Install

1.6s avg

Import

—

Disk

17MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.4.0 · 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 0.000s · 18.9MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 1.6s · import 0.000s · 19MB

17MB installed

● package 17MB

Code

Verified usage

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

levenshtein

✓ from editdistpy import levenshtein

damerau_osa

✓ from editdistpy import damerau_osa

This quickstart demonstrates how to calculate both Levenshtein and Damerau Optimal String Alignment (OSA) distances using `editdistpy`. It also highlights the use of `max_distance` for performance optimization, which returns -1 if the actual distance exceeds the specified maximum.

import sys from editdistpy import levenshtein, damerau_osa string_1 = "flintstone" string_2 = "hanson" # Levenshtein distance max_dist_lev = 2 lev_dist_bounded = levenshtein.distance(string_1, string_2, max_dist_lev) print(f"Levenshtein (max_distance={max_dist_lev}): {lev_dist_bounded}") # Expected: -1 lev_dist_full = levenshtein.distance(string_1, string_2, sys.maxsize) print(f"Levenshtein (full): {lev_dist_full}") # Expected: 6 # Damerau Optimal String Alignment (OSA) distance max_dist_osa = 2 osa_dist_bounded = damerau_osa.distance(string_1, string_2, max_dist_osa) print(f"Damerau OSA (max_distance={max_dist_osa}): {osa_dist_bounded}") # Expected: -1 osa_dist_full = damerau_osa.distance(string_1, string_2, sys.maxsize) print(f"Damerau OSA (full): {osa_dist_full}") # Expected: 6

Debug

Known issues

breakingSupport for Python 3.8 was officially dropped in version 0.1.6. Users on Python 3.8 or older must upgrade their Python environment to Python 3.9 or newer to use versions >= 0.1.6.

fix

Upgrade Python to version 3.9 or higher.

affects: >=0.1.6

gotchaWhen `max_distance` is provided to the `distance` method, it will return `-1` if the calculated edit distance exceeds this maximum. This is an intentional performance feature, not an error. To always get the full distance, pass `sys.maxsize` as `max_distance`.

fix

Handle the `-1` return value appropriately, or explicitly pass `sys.maxsize` for an unbounded calculation.

affects: All versions

gotchaThe `damerau_osa` module implements the Damerau Optimal String Alignment (OSA) distance, which is a restricted form of the Damerau-Levenshtein distance. OSA imposes a constraint that no substring may be edited more than once, meaning it does not always satisfy the triangle inequality and might return a different distance in certain cases compared to a full Damerau-Levenshtein implementation.

fix

Be aware of the distinction between Damerau OSA and the unrestricted Damerau-Levenshtein distance, and ensure it aligns with your specific use case. For typical typo correction, OSA is usually sufficient.

affects: All versions

deprecatedIn versions prior to 0.1.3, the library might not correctly handle distance calculations when one of the input strings is `None` or when `max_distance` is set to `0`. These issues were fixed in version 0.1.3.

fix

Upgrade to version 0.1.3 or later to ensure robust handling of `None` inputs and `max_distance=0`.

affects: <0.1.3

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'editdistpy'

The 'editdistpy' package is not installed in the Python environment being used, or the environment is not correctly activated.

fix

Install the package using pip: `pip install editdistpy` or `pip install -U editdistpy` to upgrade to the latest version. Ensure you are installing it in the correct Python environment (e.g., a virtual environment).

ERROR: Failed building wheel for editdistpy

This error typically occurs on Windows or other systems when the necessary C++ build tools (like Microsoft Visual C++ Build Tools) are not installed, as `editdistpy` is a Cython/C++ extension and requires compilation during installation if a pre-built wheel is not available for your specific Python version and operating system.

fix

On Windows, install 'Microsoft Visual C++ Build Tools'. For other operating systems, ensure you have a C/C++ compiler installed (e.g., `build-essential` on Debian/Ubuntu, or Xcode Command Line Tools on macOS).

AttributeError: module 'editdistpy' has no attribute 'levenshtein'

Users attempting to access `levenshtein.distance` or `damerau_osa.distance` directly from the top-level `editdistpy` module without explicitly importing the `levenshtein` or `damerau_osa` submodules.

fix

Import the specific edit distance algorithm (e.g., `levenshtein` or `damerau_osa`) from the `editdistpy` package: `from editdistpy import levenshtein` then use `levenshtein.distance(str1, str2)`.

Python version compatibility issues during installation or import.

Versions of `editdistpy` (e.g., 0.1.6 and later, including 0.2.0) dropped support for older Python versions like 3.8. Attempting to install or use the library with an incompatible Python interpreter will lead to installation failures or import errors.

fix

Upgrade your Python environment to version 3.9 or newer to be compatible with `editdistpy` version 0.2.0.

Upgrade

Version history

0.4.0latest on PyPI · released Jul 12, 2026

Audit

Dependencies

packagingrequiredAdded as a requirement in v0.2.0 for improved build and packaging robustness, particularly for wheel generation.

Agent activity

16 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/mammothb/editdistpy ↗

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

changeloghttps://github.com/mammothb/editdistpy/blob/master/CHANGELOG.md ↗