$ show keon/algorithms
This repository is a comprehensive, educational library of data structures and algorithms implemented in Python 3. It is organized into subpackages by algorithmic category (sorting, searching, graph, dynamic programming, backtracking, bit manipulation, string, tree, math, matrix, compression, streaming, etc.), each containing self-contained modules with clear function signatures, docstrings, complexity analysis, and often multiple implementation variants. The library is installable via pip and intended for learning, reference, and reuse in competitive programming or software development. It is not an application or data pipeline; it has no web server, CLI entry point, or external runtime dependencies beyond the Python standard library. The architecture is a flat library with a shared `algorithms/common` module providing reusable data types (`TreeNode`, `ListNode`, `Graph`) and each subpackage re-exporting its public API through `__init__.py` files. The codebase demonstrates a mix of modern and legacy Python styles, with newer modules using type hints, dataclasses, and doctests, while older modules rely on bare comments and local node definitions. Despite some inconsistencies and minor bugs, the repository is a well-structured, actively maintained collection that serves as a valuable reference for algorithm implementations.
The LLM identified 6 files worth highlighting for reuse:
Provides `Monomial` and `Polynomial` classes with exact arithmetic using `Fraction`, supporting addition, multiplication, substitution, and long division. This is a self-contained symbolic algebra system that can be extracted and reused in any project requiring polynomial manipulation, demonstrating non-trivial object-oriented design and mathematical logic.
Implements Huffman encoding and decoding with bit-level I/O, including tree serialization. The module is self-contained and can be used as a standalone lossless compression utility. It demonstrates careful bit-buffer management and tree construction, making it a reusable component for projects needing efficient symbol coding.
A van Emde Boas tree implementation supporting insert, delete, and predecessor/successor queries in O(log log u) time. This is a rare and complex data structure that is self-contained and can be extracted for use in specialized applications requiring fast integer set operations. The implementation showcases recursive decomposition and bit-level tricks.
Implements the Blossom algorithm for finding maximum matchings in general graphs. This is a sophisticated graph algorithm that is self-contained and can be reused in projects requiring optimal matching. The implementation demonstrates advanced graph theory concepts and careful handling of blossom contraction.
Implements the Misra-Gries algorithm for finding heavy hitters in a data stream using limited memory. This is a classic streaming algorithm that is self-contained and can be extracted for use in real-time data processing or network monitoring. The implementation is concise and demonstrates the k-counter summary technique.
Implements Manacher's algorithm for finding all palindromic substrings in linear time. This is a non-trivial string algorithm that is self-contained and can be reused in text processing or bioinformatics. The implementation demonstrates clever use of symmetry and dynamic programming to achieve O(n) complexity.