tree-multimap-typed
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Markdown







# What
## Brief
This is a standalone Tree Multiset 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 tree-multimap-typed --save
```
### yarn
```bash
yarn add tree-multimap-typed
```
### snippet
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## 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>Tree Multimap</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/TreeMultimap.html"><span>TreeMultimap</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>TreeMultimap<K, V></td>
<td>multimap<K, V></td>
<td>-</td>
<td>-</td>
</tr>
</tbody>
</table>
## Benchmark
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<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>
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## 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>