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# What

## Brief

This is a standalone Red Black Tree data structure from the data-structure-typed collection. If you wish to access more data
structures or advanced features, you can transition to directly installing the
complete [data-structure-typed](https://www.npmjs.com/package/data-structure-typed) package

# How

## install

### npm

```bash
npm i red-black-tree-typed --save
```

### yarn

```bash
yarn add red-black-tree-typed
```


### snippet

#### TS

```typescript
import {RedBlackTree} from 'data-structure-typed';
// /* or if you prefer */ import {RedBlackTree} from 'red-black-tree-typed';

const rbTree = new RedBlackTree<number>();

const idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
rbTree.addMany(idsOrVals);

const node6 = rbTree.getNode(6);
node6 && rbTree.getHeight(node6)           // 3
node6 && rbTree.getDepth(node6)            // 1
const getNodeById = rbTree.getNodeByKey(10);
getNodeById?.id                             // 10

const getMinNodeByRoot = rbTree.getLeftMost();
getMinNodeByRoot?.id                        // 1

const node15 = rbTree.getNodeByKey(15);
const getMinNodeBySpecificNode = node15 && rbTree.getLeftMost(node15);
getMinNodeBySpecificNode?.id                // 12

const lesserSum = rbTree.lesserSum(10);
lesserSum                                   // 45

const node11 = rbTree.getNodeByKey(11);
node11?.id                                  // 11

const dfs = rbTree.dfs('in');
dfs[0].id                                   // 1 
rbTree.perfectlyBalance();
const bfs = rbTree.bfs('node');
rbTree.isPerfectlyBalanced() && bfs[0].id  // 8 

rbTree.delete(11, true)[0].deleted?.id     // 11
rbTree.isAVLBalanced();                    // true
node15 && rbTree.getHeight(node15)         // 2
rbTree.delete(1, true)[0].deleted?.id      // 1
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 4

rbTree.delete(4, true)[0].deleted?.id      // 4
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 4

rbTree.delete(10, true)[0].deleted?.id     // 10
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(15, true)[0].deleted?.id     // 15
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(5, true)[0].deleted?.id      // 5
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(13, true)[0].deleted?.id     // 13
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(3, true)[0].deleted?.id      // 3
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(8, true)[0].deleted?.id      // 8
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(6, true)[0].deleted?.id      // 6
rbTree.delete(6, true).length              // 0
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(7, true)[0].deleted?.id      // 7
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(9, true)[0].deleted?.id      // 9
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(14, true)[0].deleted?.id     // 14
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 1

rbTree.isAVLBalanced();                    // true
const lastBFSIds = rbTree.BFS();
lastBFSIds[0]                               // 12 

const lastBFSNodes = rbTree.BFS('node');
lastBFSNodes[0].id                          // 12
```

#### JS

```javascript
const {RedBlackTree} = require('data-structure-typed');
// /* or if you prefer */ const {RedBlackTree} = require('red-black-tree-typed');

const rbTree = new RedBlackTree();

const idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
rbTree.addMany(idsOrVals, idsOrVals);

const node6 = rbTree.getNodeByKey(6);
node6 && rbTree.getHeight(node6)           // 3
node6 && rbTree.getDepth(node6)            // 1
const getNodeById = rbTree.get(10, 'id');
getNodeById?.id                             // 10

const getMinNodeByRoot = rbTree.getLeftMost();
getMinNodeByRoot?.id                        // 1

const node15 = rbTree.getNodeByKey(15);
const getMinNodeBySpecificNode = node15 && rbTree.getLeftMost(node15);
getMinNodeBySpecificNode?.id                // 12

const node11 = rbTree.getNodeByKey(11);
node11?.id                                  // 11

const dfs = rbTree.dfs('in');
dfs[0].id                                   // 1 
rbTree.perfectlyBalance();
const bfs = rbTree.bfs('node');
rbTree.isPerfectlyBalanced() && bfs[0].id  // 8 

rbTree.delete(11, true)[0].deleted?.id     // 11
rbTree.isAVLBalanced();                    // true
node15 && rbTree.getHeight(node15)         // 2
rbTree.delete(1, true)[0].deleted?.id      // 1
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 4

rbTree.delete(4, true)[0].deleted?.id      // 4
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 4

rbTree.delete(10, true)[0].deleted?.id     // 10
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(15, true)[0].deleted?.id     // 15
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(5, true)[0].deleted?.id      // 5
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(13, true)[0].deleted?.id     // 13
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(3, true)[0].deleted?.id      // 3
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(8, true)[0].deleted?.id      // 8
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 3

rbTree.delete(6, true)[0].deleted?.id      // 6
rbTree.delete(6, true).length              // 0
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(7, true)[0].deleted?.id      // 7
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(9, true)[0].deleted?.id      // 9
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 2

rbTree.delete(14, true)[0].deleted?.id     // 14
rbTree.isAVLBalanced();                    // true
rbTree.getHeight()                         // 1

rbTree.isAVLBalanced();                    // true
const lastBFSIds = rbTree.bfs();
lastBFSIds[0]                               // 12 

const lastBFSNodes = rbTree.bfs('node');
lastBFSNodes[0].id                          // 12
```

[//]: # (No deletion!!! Start of Example Replace Section)

### Red-Black Tree with key-value pairs for lookups
```typescript
 interface Employee {
      id: number;
      name: string;
    }

    // Create tree with employee data
    const employees = new RedBlackTree<number, Employee>([
      [1, { id: 1, name: 'Alice' }],
      [3, { id: 3, name: 'Charlie' }],
      [2, { id: 2, name: 'Bob' }]
    ]);

    // Retrieve employee by ID
    const alice = employees.get(1);
    console.log(alice?.name); // 'Alice';

    // Verify sorted order by ID
    console.log([...employees.keys()]); // [1, 2, 3];
```

### Red-Black Tree range search for filtering
```typescript
 interface Product {
      name: string;
      price: number;
    }

    const products = new RedBlackTree<number, Product>([
      [10, { name: 'Item A', price: 10 }],
      [25, { name: 'Item B', price: 25 }],
      [40, { name: 'Item C', price: 40 }],
      [50, { name: 'Item D', price: 50 }]
    ]);

    // Find products in price range [20, 45]
    const pricesInRange = products.rangeSearch([20, 45], node => {
      return products.get(node)?.name;
    });

    console.log(pricesInRange); // ['Item B', 'Item C'];
```

### Red-Black Tree as database index for stock market data
```typescript
 interface StockPrice {
      symbol: string;
      volume: number;
      timestamp: Date;
    }

    // Simulate real-time stock price index
    const priceIndex = new RedBlackTree<number, StockPrice>([
      [142.5, { symbol: 'AAPL', volume: 1000000, timestamp: new Date() }],
      [335.2, { symbol: 'MSFT', volume: 800000, timestamp: new Date() }],
      [3285.04, { symbol: 'AMZN', volume: 500000, timestamp: new Date() }],
      [267.98, { symbol: 'META', volume: 750000, timestamp: new Date() }],
      [234.57, { symbol: 'GOOGL', volume: 900000, timestamp: new Date() }]
    ]);

    // Find highest-priced stock
    const maxPrice = priceIndex.getRightMost();
    console.log(priceIndex.get(maxPrice)?.symbol); // 'AMZN';

    // Find stocks in price range [200, 400] for portfolio balancing
    const stocksInRange = priceIndex.rangeSearch([200, 400], node => {
      const stock = priceIndex.get(node);
      return {
        symbol: stock?.symbol,
        price: node,
        volume: stock?.volume
      };
    });

    console.log(stocksInRange.length); // 3;
    console.log(stocksInRange.some((s: any) => s.symbol === 'GOOGL')); // true;
    console.log(stocksInRange.some((s: any) => s.symbol === 'META')); // true;
    console.log(stocksInRange.some((s: any) => s.symbol === 'MSFT')); // true;
```

[//]: # (No deletion!!! End of Example Replace Section)



## API docs & Examples

[API Docs](https://data-structure-typed-docs.vercel.app)

[Live Examples](https://vivid-algorithm.vercel.app)

<a href="https://github.com/zrwusa/vivid-algorithm" target="_blank">Examples Repository</a>

## Data Structures

<table>
<thead>
<tr>
<th>Data Structure</th>
<th>Unit Test</th>
<th>Performance Test</th>
<th>API Docs</th>
</tr>
</thead>
<tbody>

<tr>
<td>Red Black Tree</td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><a href="https://data-structure-typed-docs.vercel.app/classes/RedBlackTree.html"><span>RedBlackTree</span></a></td>
</tr>

</tbody>
</table>

## Standard library data structure comparison

<table>
  <thead>
  <tr>
    <th>Data Structure Typed</th>
    <th>C++ STL</th>
    <th>java.util</th>
    <th>Python collections</th>
  </tr>
  </thead>
  <tbody>

  <tr>
    <td>RedBlackTree&lt;K, V&gt;</td>
    <td>map&lt;K, V&gt;</td>
    <td>TreeMap&lt;K, V&gt;</td>
    <td>-</td>
  </tr>
 
  </tbody>
</table>

## Benchmark

[//]: # (No deletion!!! Start of Replace Section)
<div class="json-to-html-collapse clearfix 0">
      <div class='collapsible level0' ><span class='json-to-html-label'>rb-tree</span></div>
      <div class="content"><table style="display: table; width:100%; table-layout: fixed;"><tr><th>test name</th><th>time taken (ms)</th><th>executions per sec</th><th>sample deviation</th></tr><tr><td>100,000 add</td><td>85.85</td><td>11.65</td><td>0.00</td></tr><tr><td>100,000 add & delete randomly</td><td>211.54</td><td>4.73</td><td>0.00</td></tr><tr><td>100,000 getNode</td><td>37.92</td><td>26.37</td><td>1.65e-4</td></tr></table></div>
    </div>

[//]: # (No deletion!!! End of Replace Section)

## Built-in classic algorithms

<table>
  <thead>
  <tr>
    <th>Algorithm</th>
    <th>Function Description</th>
    <th>Iteration Type</th>
  </tr>
  </thead>
  <tbody>
  <tr>
    <td>Binary Tree DFS</td>
    <td>Traverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree,
      and then the right subtree, using recursion.
    </td>
    <td>Recursion + Iteration</td>
  </tr>
  <tr>
    <td>Binary Tree BFS</td>
    <td>Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level
      from left to right.
    </td>
    <td>Iteration</td>
  </tr>
 
  <tr>
    <td>Binary Tree Morris</td>
    <td>Morris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree
      traversal without additional stack or recursion.
    </td>
    <td>Iteration</td>
  </tr>
  
  </tbody>
</table>

## Software Engineering Design Standards
<table>
    <tr>
        <th>Principle</th>
        <th>Description</th>
    </tr>
    <tr>
        <td>Practicality</td>
        <td>Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.</td>
    </tr>
    <tr>
        <td>Extensibility</td>
        <td>Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.</td>
    </tr>
    <tr>
        <td>Modularization</td>
        <td>Includes data structure modularization and independent NPM packages.</td>
    </tr>
    <tr>
        <td>Efficiency</td>
        <td>All methods provide time and space complexity, comparable to native JS performance.</td>
    </tr>
    <tr>
        <td>Maintainability</td>
        <td>Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.</td>
    </tr>
    <tr>
        <td>Testability</td>
        <td>Automated and customized unit testing, performance testing, and integration testing.</td>
    </tr>
    <tr>
        <td>Portability</td>
        <td>Plans for porting to Java, Python, and C++, currently achieved to 80%.</td>
    </tr>
    <tr>
        <td>Reusability</td>
        <td>Fully decoupled, minimized side effects, and adheres to OOP.</td>
    </tr>
    <tr>
        <td>Security</td>
        <td>Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.</td>
    </tr>
    <tr>
        <td>Scalability</td>
        <td>Data structure software does not involve load issues.</td>
    </tr>
</table>