indexed-heapq 0.1.0

Indexed Heap Queue (Priority Queue)

Python Indexed Heap Queue

A Python implementation of an indexed priority queue using a min heap data structure. This data structure maintains a mapping between keys and their priorities while providing efficient O(log n) access to the minimum priority element.

Key Features

• Fast O(log n) operations for insertion, deletion, and priority updates
• Direct key-based access to priorities in O(1) time
• Type-safe implementation with full generic type support
• Dictionary-like interface implementing the Python Mapping protocol
• Memory efficient with O(n) space complexity

Requirements

• Python 3.9+
• No external dependencies

Installation

Install using pip:

pip install indexed-heapq

Basic Usage

from indexed_heapq import IndexedHeapQueue

# Create an empty queue
queue = IndexedHeapQueue()

# Add some items
queue['task1'] = 3
queue['task2'] = 1
queue['task3'] = 2

# Get the highest priority item (lowest number)
next_task, priority = queue.peek()  # ('task2', 1)

# Remove and return the highest priority item
next_task, priority = queue.pop()   # ('task2', 1)

# Update a priority
queue['task1'] = 0  # Move task1 to the front

# Access a priority directly
priority = queue['task3']  # 2

# Remove an item
del queue['task3']

# Check if an item exists
if 'task1' in queue:
    print("Task1 is in the queue")

Performance

Operation	Time Complexity
getitem	O(1)
peek()	O(1)
pop()	O(log n)
insert	O(log n)
update	O(log n)
delete	O(log n)

Type Hints

The class is fully generic and type-safe:

from indexed_heap_queue import IndexedHeapQueue

# With explicit type hints
queue: IndexedHeapQueue[str, float] = IndexedHeapQueue()
queue['task1'] = 1.5

# Or let type inference work
queue = IndexedHeapQueue({ 'task1': 1.5 })
queue['task2'] = 1

Common Use Cases

• Task schedulers with priority management
• Graph algorithms (Eager Dijkstra's shortest path, Eager Prim's MST)
• Event scheduling systems
• Any application requiring a priority queue with key-based access

License

This project is licensed under the MIT License - see the LICENSE file for details.