Data Structures Library

A comprehensive, zero-dependency collection of fundamental data structures for Python. The package is designed to be production-ready, strongly typed, and easy to use.

Installation

pip install data-structures-lib

Quick Start

from data_structures_lib import DynamicArray, HashMap, MinHeap, Trie, LRUCache

arr = DynamicArray()
arr.append(10)
arr.append(20)
print(arr[0])  # 10

m = HashMap()
m['name'] = 'Alice'
print(m['name'])  # Alice

heap = MinHeap()
heap.push(5)
heap.push(1)
print(heap.pop())  # 1

t = Trie()
t.insert('cat')
t.insert('car')
print(t.starts_with('ca'))  # True

cache = LRUCache(capacity=2)
cache['a'] = 1
cache['b'] = 2
cache['c'] = 3  # evicts 'a'
print('a' in cache)  # False

Features

• Zero runtime dependencies: No external packages required
• Comprehensive coverage: Linear, hashing, trees, heaps, tries, graphs, caches, and probabilistic structures
• Type safe: Includes py.typed marker for type checkers
• Well tested: Full test coverage for normal use, edge cases, and invalid operations
• Clear error messages: Explicit, helpful exceptions

Supported Data Structures

Linear

• DynamicArray: automatically resizing array
• SinglyLinkedList, DoublyLinkedList, CircularLinkedList: linked lists
• Stack: LIFO stack
• Queue: FIFO queue

Hashing

• HashMap: separate-chaining hash map
• HashSet: separate-chaining hash set

Trees

• BinarySearchTree: standard binary search tree
• AVLTree: self-balancing AVL tree

Heaps

• MinHeap, MaxHeap: binary heaps

Others

• Trie: prefix tree
• AdjacencyListGraph, AdjacencyMatrixGraph: graph representations
• LRUCache: least-recently-used cache
• BloomFilter: probabilistic membership filter

Usage Examples

Binary Search Tree

from data_structures_lib import BinarySearchTree

tree = BinarySearchTree()
for value in [5, 3, 7, 1, 4]:
    tree.insert(value)
print(tree.search(4))  # True

AVL Tree

from data_structures_lib import AVLTree

tree = AVLTree()
for value in [10, 20, 30, 40, 50]:
    tree.insert(value)
print(tree.height())  # small balanced height

Graph

from data_structures_lib import AdjacencyListGraph

g = AdjacencyListGraph()
g.add_edge('a', 'b')
g.add_edge('a', 'c')
print(g.bfs('a'))  # ['a', 'b', 'c']

Bloom Filter

from data_structures_lib import BloomFilter

bf = BloomFilter(expected_items=1000, false_positive_rate=0.01)
bf.add('hello')
print(bf.has('hello'))  # True
print(bf.has('world'))  # probably False

Development

pip install -e ".[dev]"
pytest test_data_structures_lib.py -v

License

MIT License. See LICENSE for details.