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Zeng zrwusa@gmail.com"},"license":"MIT","homepage":"https://data-structure-typed-docs.vercel.app","keywords":["tree multiset","treemultiset","tree-multiset","multiset","multi-set","bag","sorted multiset","sorted bag","duplicate elements","count","multiplicity","red black tree","self-balancing","binary search tree","javascript","typescript","data structure","data-structure","sorted","ordering","collection","Node.js","CommonJS","ES6","UMD","esmodule","c++ std::multiset","guava Multiset","stl"],"repository":{"type":"git","url":"git+https://github.com/zrwusa/data-structure-typed.git"},"description":"TreeMultiSet - A sorted multiset (bag) that allows duplicate elements","maintainers":[{"name":"zrwusa.org","email":"zrwusa@gmail.com"}],"readme":"![NPM](https://img.shields.io/npm/l/red-black-tree-typed)\n![GitHub top language](https://img.shields.io/github/languages/top/zrwusa/data-structure-typed)\n![npm](https://img.shields.io/npm/dw/red-black-tree-typed)\n![eslint](https://aleen42.github.io/badges/src/eslint.svg)\n![npm bundle size](https://img.shields.io/bundlephobia/minzip/red-black-tree-typed)\n![npm bundle size](https://img.shields.io/bundlephobia/min/red-black-tree-typed)\n![npm](https://img.shields.io/npm/v/red-black-tree-typed)\n\n# What\n\n## Brief\n\nThis is a standalone Red Black Tree data structure from the data-structure-typed collection. If you wish to access more data\nstructures or advanced features, you can transition to directly installing the\ncomplete [data-structure-typed](https://www.npmjs.com/package/data-structure-typed) package\n\n# How\n\n## install\n\n### npm\n\n```bash\nnpm i red-black-tree-typed --save\n```\n\n### yarn\n\n```bash\nyarn add red-black-tree-typed\n```\n\n\n### snippet\n\n#### TS\n\n```typescript\nimport {RedBlackTree} from 'data-structure-typed';\n// /* or if you prefer */ import {RedBlackTree} from 'red-black-tree-typed';\n\nconst rbTree = new RedBlackTree();\n\nconst idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];\nrbTree.addMany(idsOrVals);\n\nconst node6 = rbTree.getNode(6);\nnode6 && rbTree.getHeight(node6) // 3\nnode6 && rbTree.getDepth(node6) // 1\nconst getNodeById = rbTree.getNodeByKey(10);\ngetNodeById?.id // 10\n\nconst getMinNodeByRoot = rbTree.getLeftMost();\ngetMinNodeByRoot?.id // 1\n\nconst node15 = rbTree.getNodeByKey(15);\nconst getMinNodeBySpecificNode = node15 && rbTree.getLeftMost(node15);\ngetMinNodeBySpecificNode?.id // 12\n\nconst lesserSum = rbTree.lesserSum(10);\nlesserSum // 45\n\nconst node11 = rbTree.getNodeByKey(11);\nnode11?.id // 11\n\nconst dfs = rbTree.dfs('in');\ndfs[0].id // 1 \nrbTree.perfectlyBalance();\nconst bfs = rbTree.bfs('node');\nrbTree.isPerfectlyBalanced() && bfs[0].id // 8 \n\nrbTree.delete(11, true)[0].deleted?.id // 11\nrbTree.isAVLBalanced(); // true\nnode15 && rbTree.getHeight(node15) // 2\nrbTree.delete(1, true)[0].deleted?.id // 1\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 4\n\nrbTree.delete(4, true)[0].deleted?.id // 4\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 4\n\nrbTree.delete(10, true)[0].deleted?.id // 10\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(15, true)[0].deleted?.id // 15\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(5, true)[0].deleted?.id // 5\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(13, true)[0].deleted?.id // 13\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(3, true)[0].deleted?.id // 3\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(8, true)[0].deleted?.id // 8\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(6, true)[0].deleted?.id // 6\nrbTree.delete(6, true).length // 0\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(7, true)[0].deleted?.id // 7\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(9, true)[0].deleted?.id // 9\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(14, true)[0].deleted?.id // 14\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 1\n\nrbTree.isAVLBalanced(); // true\nconst lastBFSIds = rbTree.BFS();\nlastBFSIds[0] // 12 \n\nconst lastBFSNodes = rbTree.BFS('node');\nlastBFSNodes[0].id // 12\n```\n\n#### JS\n\n```javascript\nconst {RedBlackTree} = require('data-structure-typed');\n// /* or if you prefer */ const {RedBlackTree} = require('red-black-tree-typed');\n\nconst rbTree = new RedBlackTree();\n\nconst idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];\nrbTree.addMany(idsOrVals, idsOrVals);\n\nconst node6 = rbTree.getNodeByKey(6);\nnode6 && rbTree.getHeight(node6) // 3\nnode6 && rbTree.getDepth(node6) // 1\nconst getNodeById = rbTree.get(10, 'id');\ngetNodeById?.id // 10\n\nconst getMinNodeByRoot = rbTree.getLeftMost();\ngetMinNodeByRoot?.id // 1\n\nconst node15 = rbTree.getNodeByKey(15);\nconst getMinNodeBySpecificNode = node15 && rbTree.getLeftMost(node15);\ngetMinNodeBySpecificNode?.id // 12\n\nconst node11 = rbTree.getNodeByKey(11);\nnode11?.id // 11\n\nconst dfs = rbTree.dfs('in');\ndfs[0].id // 1 \nrbTree.perfectlyBalance();\nconst bfs = rbTree.bfs('node');\nrbTree.isPerfectlyBalanced() && bfs[0].id // 8 \n\nrbTree.delete(11, true)[0].deleted?.id // 11\nrbTree.isAVLBalanced(); // true\nnode15 && rbTree.getHeight(node15) // 2\nrbTree.delete(1, true)[0].deleted?.id // 1\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 4\n\nrbTree.delete(4, true)[0].deleted?.id // 4\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 4\n\nrbTree.delete(10, true)[0].deleted?.id // 10\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(15, true)[0].deleted?.id // 15\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(5, true)[0].deleted?.id // 5\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(13, true)[0].deleted?.id // 13\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(3, true)[0].deleted?.id // 3\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(8, true)[0].deleted?.id // 8\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 3\n\nrbTree.delete(6, true)[0].deleted?.id // 6\nrbTree.delete(6, true).length // 0\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(7, true)[0].deleted?.id // 7\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(9, true)[0].deleted?.id // 9\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 2\n\nrbTree.delete(14, true)[0].deleted?.id // 14\nrbTree.isAVLBalanced(); // true\nrbTree.getHeight() // 1\n\nrbTree.isAVLBalanced(); // true\nconst lastBFSIds = rbTree.bfs();\nlastBFSIds[0] // 12 \n\nconst lastBFSNodes = rbTree.bfs('node');\nlastBFSNodes[0].id // 12\n```\n\n[//]: # (No deletion!!! Start of Example Replace Section)\n\n### basic Red-Black Tree with simple number keys\n```typescript\n // Create a simple Red-Black Tree with numeric keys\n const tree = new RedBlackTree([5, 2, 8, 1, 9]);\n\n tree.print();\n // _2___\n // / \\\n // 1 _8_\n // / \\\n // 5 9\n\n // Verify the tree maintains sorted order\n console.log([...tree.keys()]); // [1, 2, 5, 8, 9];\n\n // Check size\n console.log(tree.size); // 5;\n```\n\n### Red-Black Tree with key-value pairs for lookups\n```typescript\n interface Employee {\n id: number;\n name: string;\n }\n\n // Create tree with employee data\n const employees = new RedBlackTree([\n [1, { id: 1, name: 'Alice' }],\n [3, { id: 3, name: 'Charlie' }],\n [2, { id: 2, name: 'Bob' }]\n ]);\n\n // Retrieve employee by ID\n const alice = employees.get(1);\n console.log(alice?.name); // 'Alice';\n\n // Verify sorted order by ID\n console.log([...employees.keys()]); // [1, 2, 3];\n```\n\n### Red-Black Tree range search for filtering\n```typescript\n interface Product {\n name: string;\n price: number;\n }\n\n const products = new RedBlackTree([\n [10, { name: 'Item A', price: 10 }],\n [25, { name: 'Item B', price: 25 }],\n [40, { name: 'Item C', price: 40 }],\n [50, { name: 'Item D', price: 50 }]\n ]);\n\n // Find products in price range [20, 45]\n const pricesInRange = products.rangeSearch([20, 45], node => {\n return products.get(node)?.name;\n });\n\n console.log(pricesInRange); // ['Item B', 'Item C'];\n```\n\n### Red-Black Tree as database index for stock market data\n```typescript\n interface StockPrice {\n symbol: string;\n volume: number;\n timestamp: Date;\n }\n\n // Simulate real-time stock price index\n const priceIndex = new RedBlackTree([\n [142.5, { symbol: 'AAPL', volume: 1000000, timestamp: new Date() }],\n [335.2, { symbol: 'MSFT', volume: 800000, timestamp: new Date() }],\n [3285.04, { symbol: 'AMZN', volume: 500000, timestamp: new Date() }],\n [267.98, { symbol: 'META', volume: 750000, timestamp: new Date() }],\n [234.57, { symbol: 'GOOGL', volume: 900000, timestamp: new Date() }]\n ]);\n\n // Find highest-priced stock\n const maxPrice = priceIndex.getRightMost();\n console.log(priceIndex.get(maxPrice)?.symbol); // 'AMZN';\n\n // Find stocks in price range [200, 400] for portfolio balancing\n const stocksInRange = priceIndex.rangeSearch([200, 400], node => {\n const stock = priceIndex.get(node);\n return {\n symbol: stock?.symbol,\n price: node,\n volume: stock?.volume\n };\n });\n\n console.log(stocksInRange.length); // 3;\n console.log(stocksInRange.some((s: any) => s.symbol === 'GOOGL')); // true;\n console.log(stocksInRange.some((s: any) => s.symbol === 'META')); // true;\n console.log(stocksInRange.some((s: any) => s.symbol === 'MSFT')); // true;\n```\n\n[//]: # (No deletion!!! End of Example Replace Section)\n\n\n\n## API docs & Examples\n\n[API Docs](https://data-structure-typed-docs.vercel.app)\n\n[Live Examples](https://vivid-algorithm.vercel.app)\n\nExamples Repository\n\n## Data Structures\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Data StructureUnit TestPerformance TestAPI Docs
Red Black Tree\"\"\"\"RedBlackTree
\n\n## Standard library data structure comparison\n\n\n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n
Data Structure TypedC++ STLjava.utilPython collections
RedBlackTree<K, V>map<K, V>TreeMap<K, V>-
\n\n## Benchmark\n\n[//]: # (No deletion!!! Start of Replace Section)\n
\n
rb-tree
\n
test nametime taken (ms)executions per secsample deviation
100,000 add85.8511.650.00
100,000 add & delete randomly211.544.730.00
100,000 getNode37.9226.371.65e-4
\n
\n\n[//]: # (No deletion!!! End of Replace Section)\n\n## Built-in classic algorithms\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
AlgorithmFunction DescriptionIteration Type
Binary Tree DFSTraverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree,\n and then the right subtree, using recursion.\n Recursion + Iteration
Binary Tree BFSTraverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level\n from left to right.\n Iteration
Binary Tree MorrisMorris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree\n traversal without additional stack or recursion.\n Iteration
\n\n## Software Engineering Design Standards\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
PrincipleDescription
PracticalityFollows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.
ExtensibilityAdheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.
ModularizationIncludes data structure modularization and independent NPM packages.
EfficiencyAll methods provide time and space complexity, comparable to native JS performance.
MaintainabilityFollows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.
TestabilityAutomated and customized unit testing, performance testing, and integration testing.
PortabilityPlans for porting to Java, Python, and C++, currently achieved to 80%.
ReusabilityFully decoupled, minimized side effects, and adheres to OOP.
SecurityCarefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.
ScalabilityData structure software does not involve load issues.
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