Skip to main content

Measure similarity in a many-to-many fashion

Project description

Mesi

Lint and Test codecov PyPI PyPI - Downloads License


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:

projects
├── project-one
│   ├── pyproject.toml
│   ├── deliverables
│   │   └── python_program.py
│   └── README.md
├── project-two
│   ├── pyproject.toml
│   ├── deliverables
│   │   └── python_program.py
│   └── README.md
│

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

mesi projects/*/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.

Table Formats

Mesi uses tabulate for table formatting. The table format can be configured with the --table-format option to one of the formats listed in tabulate's documentation.

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.

Bugs/Requests

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

License

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mesi-1.0.2.tar.gz (20.8 kB view details)

Uploaded Source

Built Distribution

mesi-1.0.2-py3-none-any.whl (20.9 kB view details)

Uploaded Python 3

File details

Details for the file mesi-1.0.2.tar.gz.

File metadata

  • Download URL: mesi-1.0.2.tar.gz
  • Upload date:
  • Size: 20.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.0a2 CPython/3.9.7 Linux/5.8.0-1042-azure

File hashes

Hashes for mesi-1.0.2.tar.gz
Algorithm Hash digest
SHA256 5d56b2b9989d6d5109727ee2d70fc00a23fa62de8cae107bdd2ed36adb213c2d
MD5 a21228234513b7524f4ec0ea5315333e
BLAKE2b-256 c6a3b313a785fddb37e5ef2b78e55b8eac87cda3f89021514484b4d3734bb853

See more details on using hashes here.

File details

Details for the file mesi-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: mesi-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 20.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.0a2 CPython/3.9.7 Linux/5.8.0-1042-azure

File hashes

Hashes for mesi-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 1983df96282feb2c397c23f9bce7e1264bb5672606f143213ddfbc9e1b7c6b5d
MD5 d7266696e012ca8caa3ec3cbc8e2d6f3
BLAKE2b-256 f975250c283a430658895bb0319a5b3d2634e4cfac66f50db6cc6b74f214fec1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page