sortcraft 0.1.5

A collection of classic and practical sorting algorithms

SortCraft is a comprehensive Python package providing an extensive collection of sorting algorithms suitable for educational, research, and benchmarking purposes. All implementations are type-annotated, documented for clarity, and exposed through a clean flat API for easy import and exploration.

Features

• More than twenty sorting algorithms, including classical, integer/distribution, advanced, parallel, and theoretical types.
• All functions have PEP 484 type annotations and rich, standardized docstrings suitable for IDE/hover documentation and Sphinx autodoc.
• Simple import model: from sortcraft import merge_sort, quick_sort, cycle_sort, ....
• Designed for reliability, readability, and educational use cases as well as algorithmic experimentation.

Installation

Install the latest release from PyPI:

pip install sortcraft

Or, for the latest development version:

pip install git+https://github.com/arijitkroy/sortcraft

Quick Usage

from sortcraft import merge_sort, heap_sort
data = [5, 2, 9, 1]
sorted_data = merge_sort(data)  # [1, 2, 5, 9]

Included Algorithms

• Classical comparison sorts: bubble_sort, selection_sort, insertion_sort, merge_sort, quick_sort, heap_sort
• Counting/distribution sorts: counting_sort, radix_sort, pigeonhole_sort, flash_sort, bucket_sort
• Advanced or hybrid: shell_sort, comb_sort, cocktail_sort, timsort, bitonic_sort, cycle_sort
• Educational or theoretical: pancake_sort, gnome_sort, stooge_sort, bogo_sort, odd_even_sort

All functions require a sequence of comparable elements and return a new sorted list.

Type Annotations and Docstring Standards

• All user-facing APIs are type-annotated (PEP 484/561 compliant via the included py.typed marker).
• Docstrings follow the Google style, suitable for Sphinx autodoc and IDE hover documentation.
• Each algorithm documents its stability, complexity, and typical usage.

License

SortCraft is licensed under the MIT License. See the LICENSE file for details.

Contributing

Contributions by way of issue reports, algorithm additions, or improvements to documentation are welcome. Please open an issue or submit a pull request on GitHub.