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Zeng","email":"zrwusa@gmail.com"},"license":"MIT","homepage":"https://data-structure-typed-docs.vercel.app","keywords":["data structures","typescript","javascript","data structures library","typescript data structures","javascript data structures","binary tree","binary search tree","BST","AVL tree","red black tree","tree map","tree set","treemap javascript","treeset javascript","sorted map","sorted set","ordered map","ordered set","tree multi map","tree multi set","heap","min heap","max heap","priority queue","queue","deque","double ended queue","stack","linked list","singly linked list","doubly linked list","skip list","trie","prefix tree","graph","directed graph","undirected graph","hash map","hash table","segment tree","binary indexed tree","fenwick tree","matrix","rank query","range query","order statistic tree","getRank","getByRank","rangeByRank","dijkstra","bellman ford","topological sort","DFS","BFS","leetcode","coding interview","algorithm","zero dependency","production ready","type safe","ES6","CommonJS","UMD","collection","sorted collection"],"repository":{"type":"git","url":"git+https://github.com/zrwusa/data-structure-typed.git"},"description":"Production-ready TypeScript data structures: Heap, Deque, Trie, Graph, Red-Black Tree, TreeMap, TreeSet, and more. Zero dependencies, type-safe, with getRank/getByRank/rangeByRank support.","maintainers":[{"name":"zrwusa.org","email":"zrwusa@gmail.com"}],"readme":"# data-structure-typed\n\nEnglish | [简体中文](./README_CN.md)\n\nA production-ready TypeScript data structures library featuring **Heap, Linked List, Deque, Trie, Graph, Red-Black Tree, TreeMap, TreeSet, SkipList, Segment Tree**, and more — with APIs that align with JavaScript's native **Array, Map, and Set**. Zero dependencies. Type-safe. ES2025 Set operations. O(log n) rank & range queries.\n\n> **Looking for a TreeMap, TreeSet, or PriorityQueue in TypeScript/JavaScript?** Familiar API, set operations, rank queries, sorted access — no more repeated `Array.sort()`.\n\n![npm](https://img.shields.io/npm/dm/data-structure-typed)\n![GitHub contributors](https://img.shields.io/github/contributors/zrwusa/data-structure-typed)\n![GITHUB Star](https://img.shields.io/github/stars/zrwusa/data-structure-typed)\n[![codecov](https://img.shields.io/codecov/c/github/zrwusa/data-structure-typed)](https://codecov.io/gh/zrwusa/data-structure-typed)\n![eslint](https://aleen42.github.io/badges/src/eslint.svg)\n![NPM](https://img.shields.io/npm/l/data-structure-typed)\n![npm](https://img.shields.io/npm/v/data-structure-typed)\n\n**📦 [Installation](#-installation) • 🎮 [Playground](#-playground) • ⚡ [Quick Start](#-quick-start-30-seconds) • 📖 [Docs](#-documentation) • 📋 [API](https://data-structure-typed-docs.vercel.app/) • 💡 [Examples](./docs/GUIDES.md) • ❓ [FAQ](#-faq)**\n\n---\n\n## Table of Contents\n\n1. [Installation](#-installation)\n2. [Playground](#-playground)\n3. [Quick Start](#-quick-start-30-seconds)\n4. [Who Should Use This?](#-who-should-use-this)\n5. [Why Not Just Array or Map?](#-why-not-just-array-or-map)\n6. [Key Features](#-key-features)\n7. [Data Structures](#-data-structures-available)\n8. [Documentation](#-documentation)\n9. [FAQ](#-faq)\n\n---\n\n## 📦 Installation\n\n```bash\nnpm i data-structure-typed\n```\n\n```bash\nyarn add data-structure-typed\n```\n\n```bash\npnpm add data-structure-typed\n```\n\n### Subpath Imports (Tree-Shaking Friendly)\n\nImport only what you need — bundlers automatically tree-shake unused code:\n\n```typescript\n// Full bundle — everything available\nimport { RedBlackTree, Deque, HashMap } from 'data-structure-typed';\n\n// Subpath — smaller bundle, only loads the category you need\nimport { RedBlackTree, TreeMap, AVLTree } from 'data-structure-typed/binary-tree';\nimport { Deque, Queue } from 'data-structure-typed/queue';\nimport { HashMap } from 'data-structure-typed/hash';\nimport { Heap, MinHeap } from 'data-structure-typed/heap';\nimport { Trie } from 'data-structure-typed/trie';\nimport { Stack } from 'data-structure-typed/stack';\nimport { DoublyLinkedList } from 'data-structure-typed/linked-list';\nimport { DirectedGraph } from 'data-structure-typed/graph';\nimport { Matrix } from 'data-structure-typed/matrix';\nimport { MinPriorityQueue } from 'data-structure-typed/priority-queue';\n```\n\n> **Note:** With `\"sideEffects\": false` and modern bundlers (Vite, Webpack 5, Rollup), even the full import `from 'data-structure-typed'` will tree-shake unused structures. Subpath imports give you explicit control and faster IDE autocomplete.\n\n### Individual Packages\n\nStandalone packages are also available:\n\n```bash\nnpm i avl-tree-typed bst-typed heap-typed\n```\n\n---\n\n## 🎮 Playground\n\nTry it instantly:\n\n- [Node.js TypeScript](https://stackblitz.com/github/zrwusa/dst-playgrounds/tree/main/apps/nodejs-ts?file=src%2Findex.ts&title=data-structure-typed%20%E2%80%94%20Node.js%20TypeScript)\n- [Node.js JavaScript](https://stackblitz.com/github/zrwusa/dst-playgrounds/tree/main/apps/nodejs-js?file=src%2Findex.js&title=data-structure-typed%20%E2%80%94%20Node.js%20JavaScript)\n- [React TypeScript](https://stackblitz.com/github/zrwusa/dst-playgrounds/tree/main/apps/reactjs?file=src%2FApp.tsx&title=data-structure-typed%20%E2%80%94%20React%20Playground)\n- [NestJS](https://stackblitz.com/github/zrwusa/dst-playgrounds/tree/main/apps/nestjs?file=src%2Fproduct%2Fservices%2Fproduct-price-index.service.ts&title=data-structure-typed%20%E2%80%94%20NestJS%20Product%20API)\n\n---\n\n## 🎯 Who Should Use This?\n\n**If you are building ranked collections, scheduling queues, or sorted data structures in TypeScript,**  \n**consider `data-structure-typed` instead of hand-rolled Arrays or Maps.**\n\n### Perfect for:\n\n- **Leaderboards & Rankings** — Maintain top-K efficiently without repeated sorting\n- **Task Scheduling** — Priority queues, ordered execution, time-based operations\n- **Real-Time Dashboards** — Grafana-style workloads with instant lookups\n- **Time-Series Data** — Sorted insertion + fast range queries\n- **Search & Autocomplete** — Prefix matching at scale\n- **Graph Problems** — Pathfinding, cycle detection, topological sorting\n\n---\n\n## ⚡ Why Not Just Array or Map?\n\n| Use Case               | Array                | Map              | data-structure-typed |\n|------------------------|----------------------|------------------|:--------------------:|\n| **Sorted Lookup**      | ❌ O(n)               | ❌ Unordered      |    ✅ **O(log n)**    |\n| **Insert at Position** | ❌ O(n) shift         | ❌ No position    |    ✅ **O(log n)**    |\n| **Leaderboard Top-K**  | ❌ Re-sort O(n log n) | ❌ Manual sort    |    ✅ **Instant**     |\n| **Remove from Front**  | ❌ O(n)               | ❌ No dequeue     |      ✅ **O(1)**      |\n| **Prefix Search**      | ❌ O(n*m)             | ❌ Not applicable |    ✅ **O(m + k)**    |\n| **Familiar API**       | ✅ Yes                | ✅ Yes            |      ✅ **Same**      |\n\n### Real-World Pain Point\n\n```javascript\n// ❌ WITHOUT data-structure-typed\nconst queue = [1, 2, 3, ..., 100000\n]\n;\nfor (let i = 0; i < 100000; i++) {\n  queue.shift();  // O(n) - Reindexes EVERY element!\n}\n// Time: 2829ms ❌\n```\n\n```javascript\n// ✅ WITH data-structure-typed (Deque)\nconst deque = new Deque([1, 2, 3, ..., 100000])\n;\nfor (let i = 0; i < 100000; i++) {\n  deque.shift();  // O(1) - Just moves a pointer\n}\n// Time: 5.83ms ✅\n// **484x faster!**\n```\n\n---\n\n## 🚀 Performance (TL;DR)\n\n- **Optimized for V8 hot paths** (see [PERFORMANCE.md](./docs/PERFORMANCE.md) for measured benchmarks)\n  - Repeated Array.shift() O(n) → Deque O(1)\n  - Frequent update + keep-sorted workflows → RedBlackTree O(log n) operations\n  - Avoid repeated `Array.sort()` if you must maintain sorted order after each update\n\n- **Optimized for V8 JIT** (Node.js 18+, modern browsers)\n\n- **Tree-shakable** ESM / CJS / legacy builds\n\n[//]: # (No deletion!!! Start of README Performance Section)\n\n| Data Structure | Test Case | DST (ms) | Native (ms) | C++ (ms) | js-sdsl (ms) |\n|----------------|-----------|----------|-------------|----------|---------------|\n| Queue | 1M push | 26.93 | 23.83 | 1.70 | 27.59 |\n| Deque | 1M push | 9.77 | 26.81 | 1.76 | 7.79 |\n| DoublyLinkedList | 100k push | 5.70 | 2.40 | 5.70 | 1.90 |\n| SinglyLinkedList | 100K unshift & shift | 3.77 | 1958.39 | 4.80 | - |\n| PriorityQueue | 100K add | 4.00 | - | 1.05 | 4.96 |\n| TreeSet | 1M add | 995.72 | - | 462.00 | 677.58 |\n| TreeMap | 1M set | 978.72 | - | 512.00 | 623.23 |\n| TreeMultiSet | 1M add (TreeMultiSet expanded iteration) | 217.73 | - | 752.00 | - |\n| TreeMultiMap | 1M add (TreeMultiMap bucketed) | 366.19 | - | 731.00 | - |\n| RedBlackTree | 1M get | 99.24 | - | 52.97 | - |\n| BST | 10K add randomly | 5.50 | - | - | - |\n| BinaryTree | 1K add randomly | 9.77 | - | - | - |\n| HashMap | 1M set | 146.17 | 144.83 | 76.26 | 94.16 |\n| Trie | 100K add | 141.10 | - | - | - |\n| DirectedGraph | 1K addVertex | 0.05 | - | - | - |\n| Stack | 1M push | 46.38 | 30.28 | 1.65 | 32.38 |\n\n[//]: # (No deletion!!! End of README Performance Section)\n\n📊 [Full benchmarks →](./docs/PERFORMANCE.md) | [Interactive report →](./docs/benchmark.html)\n\n---\n\n## ✨ Key Features\n\n### 🏠 Uniform API\n\nDon't learn new APIs. Just use `push`, `pop`, `map`, `filter`, and `reduce` everywhere.\n\n```javascript\n// All linear structures use THE SAME 4 methods\nconst deque = new Deque([1, 2, 3]);\nconst queue = new Queue([1, 2, 3]);\nconst doublyLinkeList = new DoublyLinkedList([1, 2, 3]);\nconst singlyLinkedList = new SinglyLinkedList([1, 2, 3]);\n\n// They ALL support:\nstructure.push(item);          // Add to end\nstructure.pop();               // Remove from end\nstructure.shift();             // Remove from start\nstructure.unshift(item);       // Add to start\n```\n\n### 🛡️ Type Safe\n\nFull generics and strict TypeScript support out of the box.\n\n```typescript\nconst tree = new RedBlackTree<number, string>();\ntree.set(1, 'Alice');\ntree.set(2, 'Bob');\n\n// Type-safe access\nconst value = tree.get(1);  // Type: string | undefined\n```\n\n### ✨ Zero Friction\n\nWorks everywhere. Spread it `[...]`, loop it `for..of`, convert it instantly. Pass raw data with `toEntryFn`/`toElementFn` — no pre-processing needed.\n\n```javascript\n// All data structures work with iterator protocol\nconst tree = new RedBlackTree([5, 2, 8]);\nconst sorted = [...tree];              // Spread operator\nfor (const item of tree) {\n}           // for...of loop\nconst set = new Set(tree);             // Set constructor\n\n// Pass raw data directly\nconst map = new TreeMap(users, { toEntryFn: u => [u.id, u.name] });\n```\n\n### 🔄 Working with Raw Data\n\nGot raw objects? Three ways to use them — pick based on what you want to store:\n\n```typescript\ninterface User {\n  id: number;\n  name: string;\n}\n\nconst users: User[] = [\n  { id: 3, name: 'Charlie' },\n  { id: 1, name: 'Alice' },\n  { id: 2, name: 'Bob' }\n];\n\n// 1. Extract a field — store only that field\nconst ids = new TreeSet<number, User>(\n  users,\n  { toElementFn: u => u.id }\n);\n// [1, 2, 3] — numbers only, original objects not kept\n\n// 2. Store full objects — sort by a field\nconst fullSet = new TreeSet<User>(\n  users,\n  { comparator: (a, b) => a.id - b.id }\n);\n// [{ id: 1, name: 'Alice' }, { id: 2, ... }, { id: 3, ... }]\n\n// 3. Split into key-value — field as key, anything as value\nconst map = new TreeMap<number, User, User>(\n  users,\n  { toEntryFn: u => [u.id, u] }\n);\n// map.get(1) → { id: 1, name: 'Alice' }\n```\n\nWorks across all data structures — `toElementFn` for single-value types (Heap, Queue, Stack, LinkedList, Trie), `toEntryFn` for key-value types (TreeMap, HashMap, SkipList), and `comparator` for any sorted structure.\n\n---\n\n## 💡 When Should I Consider This Library?\n\n✅ **When you need:**\n\n- Top-K / Leaderboard queries without repeated sorting\n- Insertion order + lookup performance simultaneously\n- Priority queues with fast position-based access\n- Time-series data with range queries\n- Red-Black Tree / Heap performance without learning new APIs\n- **Pass raw objects directly** — no `.map()` pre-processing needed (unique to this library in JS/TS)\n\n✅ **When your current code has:**\n\n- `array.sort()` in hot paths (request handlers, loops)\n- Manual index tracking after insertions\n- `Array.shift()` on large lists (queues)\n- Custom sorting logic you repeat across files\n- Map that needs to be ordered\n- `.map()` calls just to reshape data before putting it in a collection\n\n---\n\n## 🚀 Quick Start: 30 Seconds\n\n### Leaderboard (Ranked Collections)\n\n```typescript\nimport { RedBlackTree } from 'data-structure-typed';\n\n// Descending comparator — highest scores first\nconst leaderboard = new RedBlackTree<number, string>([\n  [100, 'Alice'],\n  [85, 'Bob'],\n  [92, 'Charlie']\n], { comparator: (a, b) => b - a });\n\n// Top-2 via lazy iterator — O(k log n), no array copy\nconst iter = leaderboard.entries();\nconst { value: [topScore, topPlayer] } = iter.next();\nconsole.log(`${topScore}: ${topPlayer}`); // 100: Alice\n\n// Update score — O(log n)\nleaderboard.delete(85);\nleaderboard.set(95, 'Bob');\n\n// Range query — players scoring 90~100, O(log n + k)\nconst scores90to100 = leaderboard.rangeSearch([90, 100]);\n// [100, 95, 92] — automatically respects tree order\n\n// For O(log n) top-k, rank, and pagination → see Order-Statistic Tree below\n```\n\n### Order-Statistic Tree (Rank Queries)\n\n```typescript\nimport { RedBlackTree } from 'data-structure-typed';\n\nconst tree = new RedBlackTree<number, string>([\n  [100, 'Alice'], [85, 'Bob'], [92, 'Charlie'],\n  [78, 'Diana'], [95, 'Eve']\n], { comparator: (a, b) => b - a, enableOrderStatistic: true });\n\n// select(k) — find k-th element, O(log n)\ntree.getByRank(0);              // 100 (1st in tree order)\ntree.getByRank(2);              // 92  (3rd in tree order)\n\n// rank(key) — count elements preceding key in tree order, O(log n)\ntree.getRank(92);               // 2 (2 elements before 92 in tree order)\n\n// rangeByRank — pagination, O(log n + k)\ntree.rangeByRank(0, 2);      // [100, 95, 92] — top 3\n\n// Also works with TreeMap, TreeSet, TreeMultiMap, TreeMultiSet\n```\n\n### Task Queue (Scheduling)\n\n```typescript\nimport { MaxPriorityQueue } from 'data-structure-typed';\n\nconst taskQueue = new MaxPriorityQueue<{priority: number; task: string}>([], {\n  comparator: (a, b) => b.priority - a.priority\n});\n\ntaskQueue.add({ priority: 5, task: 'Email' });\ntaskQueue.add({ priority: 9, task: 'Alert' });  // Instant priority handling\n\nconst nextTask = taskQueue.pop();  // { priority: 9, task: 'Alert' }\n```\n\n### Set Operations (ES2025)\n\n```typescript\nimport { TreeSet } from 'data-structure-typed';\n\nconst a = new TreeSet([1, 2, 3, 4, 5]);\nconst b = new TreeSet([3, 4, 5, 6, 7]);\n\n[...a.union(b)];               // [1,2,3,4,5,6,7]\n[...a.intersection(b)];        // [3,4,5]\n[...a.difference(b)];          // [1,2]\n[...a.symmetricDifference(b)]; // [1,2,6,7]\na.isSubsetOf(b);               // false\n\n// Works with any Iterable — native Set, arrays, generators\na.intersection(new Set([2, 4, 6]));  // TreeSet [2, 4]\n```\n\n### Fast Queue (FIFO)\n\n```typescript\nimport { Deque } from 'data-structure-typed';\n\nconst queue = new Deque([1, 2, 3, 4, 5]);\nqueue.shift();  // Remove from front: O(1) not O(n)\nqueue.push(6);  // Add to back: O(1)\n```\n\n---\n\n## 📊 Data Structures Available\n\n| Structure                | Use Case                          | Time Complexity | NPM                                                       |\n|--------------------------|-----------------------------------|-----------------|-----------------------------------------------------------|\n| **RedBlackTree**         | Sorted collections, range queries | O(log n)        | [npm](https://www.npmjs.com/package/red-black-tree-typed) |\n| **Heap / PriorityQueue** | Task scheduling, top-K elements   | O(log n)        | [npm](https://www.npmjs.com/package/heap-typed)           |\n| **Deque**                | Fast front/back operations        | O(1)            | [npm](https://www.npmjs.com/package/deque-typed)          |\n| **Trie**                 | Autocomplete, prefix search       | O(m+k)          | [npm](https://www.npmjs.com/package/trie-typed)           |\n| **DirectedGraph**        | Pathfinding, DAG algorithms       | O(V+E)          | [npm](https://www.npmjs.com/package/directed-graph-typed) |\n| **Stack**                | Undo/redo, expression parsing     | O(1)            | [npm](https://www.npmjs.com/package/stack-typed)          |\n| **LinkedList**           | Dynamic sizing, no index shift    | O(1)*           | [npm](https://www.npmjs.com/package/linked-list-typed)    |\n| **AVLTree**              | Stricter balance than RB-Tree     | O(log n)        | [npm](https://www.npmjs.com/package/avl-tree-typed)       |\n| **SkipList**             | Sorted KV, TreeMap alternative    | O(log n) avg    | —                                                         |\n| **SegmentTree**          | Range sum/min/max/custom queries  | O(log n)        | —                                                         |\n| **BinaryIndexedTree**    | Prefix sums, frequency counting   | O(log n)        | —                                                         |\n| **Matrix**               | 2D grid arithmetic                | O(n²) add       | —                                                         |\n\n👉 [See all 20+ structures →](./docs/OVERVIEW.md) | [Full API docs →](https://data-structure-typed-docs.vercel.app/)\n\n---\n\n## 📖 Documentation\n\n### For Different Use Cases\n\n| Your Goal                 | Start Here                                | Next Steps                              |\n|---------------------------|-------------------------------------------|-----------------------------------------|\n| **Learn concepts**        | [CONCEPTS.md](./docs/CONCEPTS.md)         | [GUIDES.md](./docs/GUIDES.md)           |\n| **Use in my project**     | [GUIDES.md](./docs/GUIDES.md)             | [OVERVIEW.md](./docs/OVERVIEW.md)       |\n| **Look up API**           | [API Docs](https://data-structure-typed-docs.vercel.app/) | [PERFORMANCE.md](./docs/PERFORMANCE.md) |\n| **Performance questions** | [PERFORMANCE.md](./docs/PERFORMANCE.md)   | [ARCHITECTURE.md](./docs/ARCHITECTURE.md)    |\n| **Framework integration** | [INTEGRATIONS.md](./docs/INTEGRATIONS.md) | [GUIDES.md](./docs/GUIDES.md)           |\n| **Understand design**     | [ARCHITECTURE.md](./docs/ARCHITECTURE.md)      | [CONCEPTS.md](./docs/CONCEPTS.md)       |\n\n### Documentation Files\n\n1. **[CONCEPTS.md](./docs/CONCEPTS.md)** - Core Fundamentals & Theory\n  - Big Three Concepts (BST, Balanced Trees, Heap)\n  - 13 Plain Language Explanations\n  - Iterator Protocol Design\n  - 5 Comparisons with Native JavaScript\n  - Complete Decision Guide\n\n2. **[API Docs](https://data-structure-typed-docs.vercel.app/)** - Full API Reference (TypeDoc)\n  - Complete method signatures, parameters, return types\n  - Real-world `@example` code for every method\n  - Inheritance hierarchy and type details\n\n3. **[OVERVIEW.md](./docs/OVERVIEW.md)** - Data Structures Overview\n  - Quick Reference Table\n  - All 20+ Structures with Examples\n  - CRUD Operations\n  - Common Methods\n  - TypeScript Support\n\n4. **[ARCHITECTURE.md](./docs/ARCHITECTURE.md)** - Design & Implementation\n  - Design Philosophy & Principles\n  - 3 Pain Points Solved\n  - Why Deque is 484x Faster\n  - Iterator Protocol Design\n  - Self-Balancing Strategy\n  - V8 JIT Optimizations\n\n5. **[PERFORMANCE.md](./docs/PERFORMANCE.md)** - Benchmarks & Comparisons\n  - Performance Summary\n  - 3 Real-World Scenarios\n  - Detailed Benchmarks\n  - When to Use What\n  - Optimization Tips\n\n6. **[GUIDES.md](./docs/GUIDES.md)** - Real-World Examples\n  - 4 Design Patterns\n  - 5 Production Code Examples\n  - Common Mistakes\n  - Best Practices\n\n7. **[INTEGRATIONS.md](./docs/INTEGRATIONS.md)** - Framework Integration\n  - React Integration (State Management, Leaderboard)\n  - Express Integration (LRU Cache, Rate Limiting)\n  - Nest.js Integration (Ranking Service, Task Queue)\n  - TypeScript Configuration\n\n---\n\n## 💻 Real-World Examples\n\n### LRU Cache\n\n```typescript\nclass LRUCache<K, V> {\n  private cache = new Map<K, V>();\n  private order = new DoublyLinkedList<K>();\n\n  get(key: K): V | null {\n    if (!this.cache.has(key)) return null;\n    // Move to end (recently used)\n    // Efficient with O(1) operations\n    return this.cache.get(key)!;\n  }\n}\n```\n\n### Leaderboard\n\n```typescript\n\ntype Player = {\n  id: string;\n  name: string;\n  score: number;\n};\n\nconst seedPlayers: Player[] = [\n  { id: 'player_01HZX4E8Q2K8Y3J9M7T1A6B3C4', name: 'Pablo', score: 65 },\n  { id: 'player_01HZX4E9R6V2D8K1P0N5S4T7U8', name: 'Bunny', score: 10 },\n  { id: 'player_01HZX4EA3M9Q7W1E2R8T6Y5U0I', name: 'Jeff', score: 99 },\n];\n\nclass ScoreLeaderboard {\n  private readonly byScore: RedBlackTree<number, Player, Player>;\n\n  constructor(initialPlayers: Player[]) {\n    this.byScore = new RedBlackTree<number, Player, Player>(initialPlayers, {\n      isMapMode: false,// Use \"node value\" storage rather than Map-style.\n      toEntryFn: (player) => [player.score, player], // Convert a player object into the tree entry: key = score, value = player.\n    });\n  }\n\n  /**\n   * Returns players whose scores fall within the given range.\n   * Supports either a tuple [min, max] or a Range object for inclusive/exclusive bounds.\n   */\n  public findPlayersByScoreRange(range: [number, number] | Range<number>): (Player | undefined)[] {\n    return this.byScore.rangeSearch(range, (node) => node.value);\n  }\n  \n  public upsertPlayer(player: Player) {\n    return this.byScore.set(player.score, player);\n  }\n}\n\nconst leaderboard = new ScoreLeaderboard(seedPlayers);\n\nconsole.log(leaderboard.findPlayersByScoreRange([65, 100]));\n\nleaderboard.upsertPlayer({\n  id: 'player_01HZX4EB7C4N2M9Q8R1T3Y6U5I',\n  name: 'Alex',\n  score: 80,\n});\n\nconsole.log(leaderboard.findPlayersByScoreRange(new Range(65, 100, true, true)));\n```\n\n### Message Queue\n\n```typescript\ntype Message = {\n  id: string;\n  type: string;\n  payload: unknown;\n  priority: 'urgent' | 'normal';\n  createdAt: number;\n  retryCount?: number;\n};\n\nclass MessageQueue {\n  private urgent = new Deque<Message>();\n  private normal = new Deque<Message>();\n\n  dequeue(): Message | null {\n    return this.urgent.shift() || this.normal.shift();\n  }\n}\n```\n\n👉 [More examples in GUIDES.md](./docs/GUIDES.md)\n\n---\n\n## 🎯 Use Cases by Industry\n\n### 📊 Finance\n\n- Price-sorted order book\n- Real-time portfolio rankings\n- Option chain ordering\n\n### 🎮 Gaming\n\n- Player leaderboards\n- Enemy priority queues\n- Game event scheduling\n\n### 📱 Social Media\n\n- Trending posts (top-K)\n- Feed ordering\n- Notification scheduling\n\n### 🏥 Healthcare\n\n- Patient priority queues\n- Appointment scheduling\n- Medical record organization\n\n### 🛒 E-commerce\n\n- Product price ranges\n- Inventory management\n- Order scheduling\n\n---\n\n## ✨ Why Developers Love This\n\n| Pain Point                         | Solution                                  |\n|------------------------------------|-------------------------------------------|\n| Repeated sorting slowing down code | TreeSet auto-maintains order              |\n| Array.shift timeout in loops       | Deque O(1) shift instead of O(n)          |\n| Learning different APIs            | All structures use push/pop/shift/unshift |\n| Type safety nightmares             | Full TypeScript generics support          |\n| Browser compatibility issues       | Works everywhere: Node, browsers, CDN     |\n\n---\n\n## 📦 What You Get\n\n✅ **20+ data structures** (production-ready)  \n✅ **50+ code examples** (real-world patterns)  \n✅ **Full TypeScript support** (strict typing)  \n✅ **Performance benchmarks** (484x speedups)  \n✅ **Framework integrations** (React, Express, Nest.js)  \n✅ **6 core documentation files** (2500+ lines)\n\n---\n\n## 🚀 Getting Started\n\n### Step 1: Install\n\n```bash\nnpm i data-structure-typed\n```\n\n### Step 2: Import\n\n```typescript\nimport { RedBlackTree, Deque, MaxPriorityQueue } from 'data-structure-typed';\n```\n\n### Step 3: Use\n\n```typescript\nconst tree = new RedBlackTree([5, 2, 8]);\nconsole.log([...tree]);  // [2, 5, 8] - Automatically sorted!\n```\n\n## 📊 Comparison Chart\n\n```\nNeed frequent head/tail operations?\n  → Deque (O(1) shift/unshift/push/pop)\n\nNeed sorted + fast lookup?\n  → RedBlackTree (O(log n) guaranteed)\n\nNeed highest/lowest priority?\n  → Heap/PriorityQueue (O(log n) add/remove)\n\nNeed prefix/text matching?\n  → Trie (O(m+k) where m=prefix)\n\nNeed graph operations?\n  → DirectedGraph/UndirectedGraph\n\nNeed range queries on array (sum/min/max)?\n  → SegmentTree (any merge op) or BinaryIndexedTree (prefix sums only)\n\nNeed sorted key-value with same API as TreeMap?\n  → SkipList (O(log n) avg, probabilistic balancing)\n\nOtherwise?\n  → Use Array (simplest case)\n```\n\n---\n\n## 🤝 Contributing\n\nFound a bug? Have suggestions? [Open an issue](https://github.com/zrwusa/data-structure-typed/issues)\n\n---\n\n## 📄 License\n\nMIT\n\n---\n\n## 📚 Full Documentation Structure\n\n```\nREADME.md (this file)\ndocs/\n├── CONCEPTS.md (theory & fundamentals)\n├── OVERVIEW.md (Data structures overview)\n├── ARCHITECTURE.md (design principles)\n├── PERFORMANCE.md (benchmarks)\n├── GUIDES.md (real-world examples)\n└── INTEGRATIONS.md (framework guides)\n```\n\n---\n\n## 🎓 Learn More\n\n**Just started?** → [Quick Start](#-quick-start-30-seconds)\n\n**Need concepts?** → [CONCEPTS.md](./docs/CONCEPTS.md)\n\n**Want to build?** → [GUIDES.md](./docs/GUIDES.md)\n\n**Need API?** → [API Docs](https://data-structure-typed-docs.vercel.app/) | [Overview](./docs/OVERVIEW.md)\n\n**Curious about performance?** → [PERFORMANCE.md](./docs/PERFORMANCE.md)\n\n**Framework questions?** → [INTEGRATIONS.md](./docs/INTEGRATIONS.md)\n\n---\n\n**Ready to supercharge your TypeScript data structures? [Get started now →](#-quick-start-30-seconds)**\n\n---\n\n## ❓ FAQ\n\n### Does JavaScript have a TreeMap or TreeSet?\n\nNot natively. JavaScript's `Map` and `Set` are hash-based (unordered). This library provides `TreeMap` and `TreeSet` backed by Red-Black Trees — offering sorted iteration, `floor`/`ceiling`/`higher`/`lower` lookups, and `getRank`/`getByRank`/`rangeByRank` queries.\n\n### When should I use a Heap instead of sorting an array?\n\nWhen you need to repeatedly access the smallest or largest element. Sorting an array is O(n log n) every time; a Heap gives you O(log n) insert and O(1) access to the top element. Use `Heap`, `MinHeap`, or `MaxHeap` for priority queues, top-k problems, and scheduling.\n\n### Does this library support rank and range queries?\n\nYes. Enable with `{ enableOrderStatistic: true }` on any tree-based structure (RedBlackTree, TreeMap, TreeSet, etc.):\n- `getRank(key)` — how many elements precede this key in tree order\n- `getByRank(k)` — get the element at position k\n- `rangeByRank(start, end)` — get all elements between two positions\n\n### Is it faster than native arrays for ordered operations?\n\nFor ordered insert + lookup: yes. Array insert into sorted position is O(n) (shift elements). Red-Black Tree insert is O(log n). For 10,000+ elements, the difference is significant. See [PERFORMANCE.md](./docs/PERFORMANCE.md) for benchmarks.\n\n### Can I use this in React / Node.js / browser?\n\nYes. The library ships ESM, CJS, and UMD builds. It works in Node.js, browsers, React, Vue, Angular, Next.js, and any JavaScript runtime. Zero dependencies means no compatibility concerns.\n\n### What data structures are included?\n\nHeap, MinHeap, MaxHeap, Priority Queue, Deque, Queue, Stack, Linked List (Singly / Doubly), Red-Black Tree, AVL Tree, BST, TreeMap, TreeSet, TreeMultiMap, TreeMultiSet, SkipList, Trie, HashMap, Graph (Directed / Undirected), Segment Tree, Binary Indexed Tree (Fenwick Tree), Matrix. See [full list](#-data-structures-available).\n\n### Is this library production-ready?\n\nYes. 2600+ tests, 99%+ code coverage, zero dependencies, and used in production. Every release passes typecheck, lint, and full test suite.\n\n### How does this compare to js-sdsl or other libraries?\n\n`data-structure-typed` offers more data structures (20+), a unified Array-like API across all structures, tree-shakeable subpath exports, and active maintenance. See [PERFORMANCE.md](./docs/PERFORMANCE.md) for benchmark comparisons.\n\n### Can I pass raw data without converting it first?\n\nYes. Three patterns:\n- **`toElementFn`** — extract a field, store only that (TreeSet, Heap, Queue, Stack, LinkedList, Trie)\n- **`comparator`** — store full objects, sort by a field (all sorted structures)\n- **`toEntryFn`** — split into key-value pairs (TreeMap, HashMap, SkipList)\n\nSee the [Raw Data section](#-working-with-raw-data) for examples.\n\n### What is the bundle size?\n\nUMD bundle: ~143KB minified. With subpath imports (e.g., `data-structure-typed/heap`), you only load what you use — as small as 18KB for Stack, 30KB for Heap. `sideEffects: false` enables full tree-shaking.\n","readmeFilename":"README.md"}