Measure file similarity in a many-to-many fashion

Last update: Feb 02, 2022

Overview

Mesi

Mesi is a tool to measure the similarity in a many-to-many fashion of long-form documents like Python source code or technical writing. The output can be useful in determining which of a collection of files are the most similar to each other.

Installation

Python 3.9+ and pipx are recommended, although Python 3.6+ and/or pip will also work.

pipx install mesi

If you'd like to test out Mesi before installing it, use the remote execution feature of pipx, which will temporarily download Mesi and run it in an isolated virtual environment.

pipx run mesi --help

Usage

For a directory structure that looks like:

lab-one
├── StudentOne
│   ├── pyproject.toml
│   ├── deliverables
│   │   └── python_program.py
│   └── README.md
├── StudentTwo
│   ├── pyproject.toml
│   ├── deliverables
│   │   └── python_program.py
│   └── README.md
│

where similarity should be measured between each student's deliverables/python_program.py file, run the command:

mesi lab-one/*/deliverables/python_program.py

A lower distance in the produced table equates to a higher degree of similarity.

See the help menu (mesi --help) for additional options and configuration.

Algorithms

There are many algorithms to choose from when comparing string similarity! Mesi implements all the algorithms provided by TextDistance. In general levenshtein is never a bad choice, which is why it is the default.

Bugs/Requests

Please use the GitHub issue tracker to submit bugs or request new features, options, or algorithms.

Dependencies

Mesi uses two primary dependencies for text similarity calculation: polyleven, and TextDistance. Polyleven is the default, as its singular implementation of Levenshtein distance can be faster in most situations. However, if a different edit distance algorithm is requested, TextDistance's implementations will be used.

License

Distributed under the terms of the GPL v3 license, mesi is free and open source software.

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Releases(v1.1.0)

v1.1.0(Dec 8, 2021)

This release adds an --average option, which prints the average distance computed against the given files after the individual comparison distances. An unimplemented --distribution option, intended for use in the future, was also added.
Source code(tar.gz)
Source code(zip)
v1.0.2(Oct 26, 2021)

This release adds more documentation, a --version option, and removes the bright white table styling from previous versions that were hard to read on light-themed terminals.

Full Changelog: https://github.com/Michionlion/mesi/compare/v1.0.1...v1.0.2
Source code(tar.gz)
Source code(zip)
v1.0.1(Oct 26, 2021)

This release fixes a bug where in some situations, some distinct parts of compared file names were not displayed. Additionally, a new option, --table-format, was added. This allows configuration of the output table format, using tabulate's table formats.

Full Changelog: https://github.com/Michionlion/mesi/compare/v1.0.0...v1.0.1
Source code(tar.gz)
Source code(zip)
v1.0.0(Oct 25, 2021)
Mesi is a tool to check the similarity between many different files; this is its first release, with support for many basic features and lots of text similarity/distance algorithms. You can even try out Mesi without downloading it!

pipx run mesi --help

If you don't have pipx installed, you may need to install it, but that's something you should do anyways. :smile:
Source code(tar.gz)
Source code(zip)

Owner

GatorEducator

Software tools developed at Allegheny College for computer science courses

GitHub Repository

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