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# What

## Brief

This is a standalone Min Priority Queue 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 min-priority-queue-typed --save
```

### yarn

```bash
yarn add min-priority-queue-typed
```

### snippet

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

### Shortest job first scheduling
```typescript
 const jobs = new MinPriorityQueue<number>();

    jobs.add(8);  // 8 seconds
    jobs.add(2);  // 2 seconds
    jobs.add(5);  // 5 seconds
    jobs.add(1);  // 1 second

    // Shortest job first
    console.log(jobs.poll()); // 1;
    console.log(jobs.poll()); // 2;
    console.log(jobs.poll()); // 5;
    console.log(jobs.poll()); // 8;
```

### Event-driven simulation with timestamps
```typescript
 interface Event {
      time: number;
      action: string;
    }

    const timeline = new MinPriorityQueue<Event>([], {
      comparator: (a, b) => a.time - b.time
    });

    timeline.add({ time: 300, action: 'Timeout' });
    timeline.add({ time: 100, action: 'Request received' });
    timeline.add({ time: 200, action: 'Processing done' });
    timeline.add({ time: 150, action: 'Cache hit' });

    const order = [];
    while (timeline.size > 0) {
      order.push(timeline.poll()!.action);
    }
    console.log(order); // [
 //      'Request received',
 //      'Cache hit',
 //      'Processing done',
 //      'Timeout'
 //    ];
```

### Huffman coding frequency selection
```typescript
 // Character frequencies for Huffman tree building
    const freq = new MinPriorityQueue<[number, string]>([], {
      comparator: (a, b) => a[0] - b[0]
    });

    freq.add([5, 'a']);
    freq.add([9, 'b']);
    freq.add([12, 'c']);
    freq.add([2, 'd']);

    // Always pick two lowest frequencies
    const first = freq.poll()!;
    const second = freq.poll()!;
    console.log(first[1]); // 'd';  // freq 2
    console.log(second[1]); // 'a'; // freq 5

    // Combined node goes back
    freq.add([first[0] + second[0], first[1] + second[1]]);
    console.log(freq.peek()![0]); // 7;
```

[//]: # (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>Min Priority Queue</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/MinPriorityQueue.html"><span>MinPriorityQueue</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>PriorityQueue&lt;E&gt;</td>
    <td>priority_queue&lt;T&gt;</td>
    <td>PriorityQueue&lt;E&gt;</td>
    <td>-</td>
  </tr>
 
  </tbody>
</table>

## Benchmark

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

[//]: # (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>
  
  </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>