Skip to main content

A simple Union Find Class for Python.

Project description

Project Name: UF-Toolkit

Description

UF-Toolkit is a Python package providing an efficient and robust implementation of the Union Find algorithm, also known as Disjoint Set Union (DSU). This data structure is essential for managing a set of elements divided into several disjoint, non-overlapping subsets. It's particularly useful in computer science for applications like network connectivity, image segmentation, clustering, and more.

Our implementation offers features like path compression and union by rank, ensuring optimal time complexity for both find and union operations. Whether you're dealing with graph algorithms or just need a fast way to handle disjoint sets, UF-Toolkit is designed to offer straightforward, reliable, and efficient performance.

Features

Efficient Union Find Operations: Implements both path compression and union by rank for fast operation. Easy-to-Use API: Designed with simplicity in mind, our API makes it easy to integrate into your existing Python projects. Versatile Applications: Suitable for use cases ranging from network analysis to algorithmic problem solving in competitive programming. Fully Documented: Each method and class is thoroughly documented, making it easy to get started and understand how the package works.

Installation

Install UF-Toolkit using pip:

pip install uf-toolkit

Usage

Here's a quick example of how to use UF-Toolkit:

from uf_toolkit import UnionFind

Create a Union Find instance with 10 elements

uf = UnionFind(10)

Union some sets

uf.union(1, 2)
uf.union(2, 3)

Check if two elements are in the same set

print(uf.connected([1, 3])) # True

Count the number of distinct sets

print(uf.count_sets()) # 3

Check all elements of the set that contains given element

print(uf.get_all_elements_of_set(1)) # [1, 2, 3]

Requirements

Python 3.x

Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Chas Huggins - hugginsc10@gmail.com

Project Link: https://github.com/hugginsc10/uf-toolkit/

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

uf-toolkit-0.2.0.tar.gz (3.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

uf_toolkit-0.2.0-py3-none-any.whl (3.8 kB view details)

Uploaded Python 3

File details

Details for the file uf-toolkit-0.2.0.tar.gz.

File metadata

  • Download URL: uf-toolkit-0.2.0.tar.gz
  • Upload date:
  • Size: 3.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.6

File hashes

Hashes for uf-toolkit-0.2.0.tar.gz
Algorithm Hash digest
SHA256 080e0e5e4f2964ca4406d3b149bc70ee0f0480af84ae49ce7dcae64fc2060a0e
MD5 e6293b0db7f94156c56ba690b485d60e
BLAKE2b-256 a27aa84c30fe91466567ff2aac7026d612324e7f868bbe28d51779e3cb43cabf

See more details on using hashes here.

File details

Details for the file uf_toolkit-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: uf_toolkit-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 3.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.6

File hashes

Hashes for uf_toolkit-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 cc73b9e89c34fcd82fa6f3d1742b7c883da17893d593621d6e7181534d7629e1
MD5 23759c4d1e95fe008b70a0830f0ae772
BLAKE2b-256 c1219cb6f4e65c979e3537a5822855fbd339d79b1fb7ff12ee3257570a226f14

See more details on using hashes here.

Supported by

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