home:juzbun:kde-plasma

various packages

https://download.opensuse.org/repositories/home:/juzbun:/kde-plasma/openSUSE_Factory_zSystems/ openSUSE:Factory:zSystems

openSUSE Factory Port for s390x

This is a project clone to build the entire openSUSE:Factory for IBM zSystems and LinuxONE. https://download.opensuse.org/repositories/openSUSE:/Factory:/zSystems/standard/ openSUSE:Factory

The next openSUSE distribution

openSUSE Tumbleweed: The Bleeding Edge, Perfected. Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing. * Always Current: Get the newest kernel, IDEs, desktops, and applications automatically. * Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on. * Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job. If you demand the latest stable software, your choice is Tumbleweed. Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects Have a look at http://en.opensuse.org/Portal:Factory for more details. https://download.opensuse.org/repositories/openSUSE:/Factory/ports/ python-pfzy

Python port of the fzy fuzzy string matching algorithm

[](https://github.com/kazhala/pfzy/actions?query=workflow%3ACI) [](https://readthedocs.org/projects/pfzy/) [](https://ap-southeast-2.console.aws.amazon.com/codesuite/codebuild/378756445655/projects/pfzy/history?region=ap-southeast-2&builds-meta=eyJmIjp7InRleHQiOiIifSwicyI6e30sIm4iOjIwLCJpIjowfQ) [](https://coveralls.io/github/kazhala/pfzy?branch=master) [](https://pypi.org/project/pfzy/) [](https://pypi.org/project/pfzy/) [](https://github.com/kazhala/pfzy/blob/master/LICENSE) <!-- start elevator-pitch-intro --> Python port of the [fzy](https://github.com/jhawthorn/fzy) fuzzy string matching algorithm. - [Async fuzzy match function](https://pfzy.readthedocs.io/en/latest/pages/usage.html#matcher) - [Fzy scorer (fuzzy string match)](https://pfzy.readthedocs.io/en/latest/pages/usage.html#fzy-scorer) - [Substring scorer (exact substring match)](https://pfzy.readthedocs.io/en/latest/pages/usage.html#substr-scorer) ``` python >= 3.7 ``` ```sh pip install pfzy ``` **Full documentation: [https://pfzy.readthedocs.io/](https://pfzy.readthedocs.io/)** ```python import asyncio from pfzy import fuzzy_match result = asyncio.run(fuzzy_match("ab", ["acb", "acbabc"])) ``` ``` >>> print(result) [{'value': 'acbabc', 'indices': [3, 4]}, {'value': 'acb', 'indices': [0, 2]}] ``` <!-- end elevator-pitch-intro --> [fuzzywuzzy](https://github.com/seatgeek/fuzzywuzzy) is a famous python package for performing fuzzy matching between strings powered by [python-Levenshtein](https://github.com/miohtama/python-Levenshtein). While it does its job well it doesn't calculate/provide the matching indices which is essential in a fuzzy finder applications. The [fzy](https://github.com/jhawthorn/fzy) fuzzy matching algorithm can calculate the matching score while also providing the matching indices which fuzzy finder applications can use to provide extra highlights. The initial implementation of this algorithm can be found at [sweep.py](https://github.com/aslpavel/sweep.py) which is a python implementation of the terminal fuzzy finder. The code snippet is later used by the project [vim-clap](https://github.com/liuchengxu/vim-clap). **I found myself needing this logic across multiple projects hence decided to strip out the logic and publish a dedicated package with detailed documentation and unittest.** <!-- start elevator-pitch-ending --> - [fzy](https://github.com/jhawthorn/fzy) - [sweep.py](https://github.com/aslpavel/sweep.py) - [vim-clap](https://github.com/liuchengxu/vim-clap) > All 3 projects mentioned in [Credit](#credit) are all licensed under [MIT](https://opensource.org/licenses/MIT). This project is licensed under [MIT](https://github.com/kazhala/pfzy). Copyright (c) 2021 Kevin Zhuang <!-- end elevator-pitch-ending -->