Package to calculate the Levenstein distance

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  • License: MIT License (MIT)
  • Author: Dmitry Erlikh
  • Tags levenstein , edit distance
  • Requires: Python >=3.9
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Project description

levdist

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A Python package to calculate the Levenstein distance algorithm implementation with non-GPL license, typing and speedups. The implementation is based on code samples from Levenstein Wiki.

Installation

pip install levdist

Usage

from levdist import levenshtein

distance = levenshtein("dog", "cat")

Development

Setup

  1. Install PDM using this documentation
  2. Install development dependencies pdm install
  3. Install pre-commit hooks pre-commit install

Testing

This project is using pytest for unit testing. To run the test you need to run pdm test In addition to that you can lint your code using pdm lint and check the typing by pdm mypy.

Type checks

mypy is configured to run in strict mode for files in src folder. Typing is not checked in tests folder.

CI

PR checks

Each PR run GitHub actions for all actual Python versions to check if native extension is built and tests pass. Also formatting and typing will be checked.

The coverage is published to CodeCov.

Dependency updates

To update dependencies and pre-commit hooks there is a GHA job that is scheduled to run weekly.

Release

To create a release, create a tag v<MAJOR>.<MINOR>.<PATCH>. The release will be created with the source code and wheels.

Benchmark

The benchmark of this package can be run using pdm benchmark console command. It compare its speed with other Python implementations. Check the BENCHMARK.md for the latest measurements.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for derlih from gravatar.com derlih

Unverified details

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Project links
Meta
  • License: MIT License (MIT)
  • Author: Dmitry Erlikh
  • Tags levenstein , edit distance
  • Requires: Python >=3.9
Classifiers

Release history Release notifications | RSS feed

This version

1.0.3

1.0.2

1.0.1

1.0.0

0.1.10

0.1.9

0.1.8

0.1.7

0.1.6

0.1.5

0.1.2

0.1.1

0.1.0

0.0.2

0.0.1

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