pure-python-ds 1.0.5

A strictly typed, 100% test-covered data structures and algorithms library.

pure-python-ds 🚀

A strictly-typed, 100% test-covered, and benchmarked Data Structures & Algorithms library.

🏗️ Architecture & Engineering

This library is engineered for Systems Architects and developers who require predictable performance and strict type safety. Every structure is built using Python's __slots__ to ensure a minimal memory footprint and high-speed attribute access.

[Image of a software architecture diagram showing layers of data structures and algorithms]

🛡️ Technical Milestones

• 100% Test Coverage: Verified 100% line coverage across the entire core library using pytest and coverage.py.
• Performance Benchmarked: Custom AVL Tree implementation demonstrated search operations up to 436x faster than standard Python list lookups in large-scale datasets.
• Type Safety: 100% mypy compliance with strict type hinting for all inputs and return values.

🛠️ Key Features

1. Linear Structures

• Linked Lists: Singly and Doubly Linked Lists with $O(1)$ head/tail operations.
• Stacks & Queues: Built on optimized nodes for strict LIFO/FIFO behavior.
• Hash Tables: Linear probing implementation with dynamic resizing.

2. Hierarchical & Network Structures

• AVL Trees: Self-balancing trees with rotation logic guaranteeing $O(\log n)$ performance.
• Red-Black Trees: Memory-optimized nodes with $O(\log n)$ height guarantees.
• Graphs: Adjacency-list based supporting Dijkstra’s, Bellman-Ford, and Kruskal’s (via custom DSU).

3. Advanced Data Structures

• Segment Trees: Range Query/Point Update in $O(\log n)$.
• Tries: Space-efficient prefix trees for string operations.
• Heaps: Min/Max Binary Heaps for $O(1)$ priority access.