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@0bipinnata0/heap

v1.0.3

Published

A TypeScript implementation of a min heap data structure

Readme

@0bipinnata0/heap

A high-performance TypeScript implementation of a min heap data structure that supports both ESM and CommonJS. This implementation is optimized for handling large datasets and provides stable ordering for elements with equal priorities.

Installation

pnpm add @0bipinnata0/heap

Features

  • 🚀 High performance implementation
  • 🔄 Stable ordering for equal priorities
  • 💪 Handles large datasets efficiently
  • 📦 Support for both ESM and CommonJS
  • 🎯 Type-safe with TypeScript
  • 🧪 Comprehensive test coverage

Usage

import { push, pop, peek } from '@0bipinnata0/heap'

// Create a min heap array for objects with sortIndex
const heap: Array<{id: number, sortIndex: number}> = []

// Push elements
push(heap, { id: 1, sortIndex: 5 })
push(heap, { id: 2, sortIndex: 3 })
push(heap, { id: 3, sortIndex: 7 })
push(heap, { id: 4, sortIndex: 1 })

// Peek at minimum element without removing it
console.log(peek(heap)) // { id: 4, sortIndex: 1 }

// Pop elements in ascending order
console.log(pop(heap)) // { id: 4, sortIndex: 1 }
console.log(pop(heap)) // { id: 2, sortIndex: 3 }
console.log(pop(heap)) // { id: 1, sortIndex: 5 }
console.log(pop(heap)) // { id: 3, sortIndex: 7 }

API

Functions

  • push(heap: T[], value: T): void

    • Adds a new element to the heap
    • Time complexity: O(log n)
  • peek(heap: T[]): T | null

    • Returns the minimum element without removing it
    • Returns null if heap is empty
    • Time complexity: O(1)
  • pop(heap: T[]): T | null

    • Removes and returns the minimum element
    • Returns null if heap is empty
    • Time complexity: O(log n)

Performance Characteristics

  • Push operation: O(log n)
  • Pop operation: O(log n)
  • Peek operation: O(1)
  • Space complexity: O(n)

Edge Cases Handling

  • Empty heap operations return null
  • Stable ordering for elements with equal priorities
  • Supports negative priority values
  • Handles very large priority values (up to Number.MAX_SAFE_INTEGER)

Use Cases

  • Priority queues
  • Task scheduling systems
  • Graph algorithms (Dijkstra's, Prim's)
  • Event scheduling
  • Real-time data processing

Testing

The package includes comprehensive test coverage for:

  • Basic operations (push, pop, peek)
  • Edge cases and boundary conditions
  • Performance with large datasets
  • Stability of ordering
  • Stress testing with random operations

Run tests with:

pnpm test

License

MIT