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# What

## Brief

This is a standalone Deque 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 deque-typed --save
```

### yarn

```bash
yarn add deque-typed
```

### snippet

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

### Deque as sliding window for stream processing
```typescript
 interface DataPoint {
      timestamp: number;
      value: number;
      sensor: string;
    }

    // Create a deque-based sliding window for real-time data aggregation
    const windowSize = 3;
    const dataWindow = new Deque<DataPoint>();

    // Simulate incoming sensor data stream
    const incomingData: DataPoint[] = [
      { timestamp: 1000, value: 25.5, sensor: 'temp-01' },
      { timestamp: 1100, value: 26.2, sensor: 'temp-01' },
      { timestamp: 1200, value: 25.8, sensor: 'temp-01' },
      { timestamp: 1300, value: 27.1, sensor: 'temp-01' },
      { timestamp: 1400, value: 26.9, sensor: 'temp-01' }
    ];

    const windowResults: Array<{ avgValue: number; windowSize: number }> = [];

    for (const dataPoint of incomingData) {
      // Add new data to the end
      dataWindow.push(dataPoint);

      // Remove oldest data when window exceeds size (O(1) from front)
      if (dataWindow.length > windowSize) {
        dataWindow.shift();
      }

      // Calculate average of current window
      let sum = 0;
      for (const point of dataWindow) {
        sum += point.value;
      }
      const avg = sum / dataWindow.length;

      windowResults.push({
        avgValue: Math.round(avg * 10) / 10,
        windowSize: dataWindow.length
      });
    }

    // Verify sliding window behavior
    console.log(windowResults.length); // 5;
    console.log(windowResults[0].windowSize); // 1; // First window has 1 element
    console.log(windowResults[2].windowSize); // 3; // Windows are at max size from 3rd onwards
    console.log(windowResults[4].windowSize); // 3; // Last window still has 3 elements
    console.log(dataWindow.length); // 3;
```

### Convert deque to array
```typescript
 const dq = new Deque<number>([10, 20, 30]);
    console.log(dq.toArray()); // [10, 20, 30];
```

[//]: # (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>Deque</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/Deque.html"><span>Deque</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>Deque&lt;E&gt;</td>
    <td>deque&lt;T&gt;</td>
    <td>ArrayDeque&lt;E&gt;</td>
    <td>deque</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'>deque</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>1,000,000 push</td><td>14.55</td><td>68.72</td><td>6.91e-4</td></tr><tr><td>1,000,000 push & pop</td><td>23.40</td><td>42.73</td><td>5.94e-4</td></tr><tr><td>1,000,000 push & shift</td><td>24.41</td><td>40.97</td><td>1.45e-4</td></tr><tr><td>1,000,000 unshift & shift</td><td>22.56</td><td>44.32</td><td>1.30e-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>
  
  </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>