!NPM
!GitHub top language
!npm
!eslint
!npm bundle size
!npm bundle size
!npm

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 package

How

install

$3

``bash npm i deque-typed --save`

`$3`

`bash yarn add deque-typed`

`$3`

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

`$3`

typescript
 // Create a simple Deque with initial values
    const deque = new Deque([1, 2, 3, 4, 5]);
    // Verify the deque maintains insertion order
    console.log([...deque]); // [1, 2, 3, 4, 5];
    // Check length
    console.log(deque.length); // 5;
    // Push to the end
    deque.push(6);
    console.log(deque.length); // 6;

// Pop from the end const last = deque.pop(); console.log(last); // 6;`

`$3`

typescript
 const deque = new Deque([20, 30, 40]);
    // Unshift adds to the front
    deque.unshift(10);
    console.log([...deque]); // [10, 20, 30, 40];
    // Shift removes from the front (O(1) complexity!)
    const first = deque.shift();
    console.log(first); // 10;

// Verify remaining elements console.log([...deque]); // [20, 30, 40]; console.log(deque.length); // 3;`

`$3`

typescript
 const deque = new Deque([10, 20, 30, 40, 50]);
    // Get first element without removing
    const first = deque.at(0);
    console.log(first); // 10;
    // Get last element without removing
    const last = deque.at(deque.length - 1);
    console.log(last); // 50;

// Length unchanged console.log(deque.length); // 5;`

`$3`

typescript
 const deque = new Deque(['A', 'B', 'C', 'D']);
    // Iterate forward
    const forward: string[] = [];
    for (const item of deque) {
      forward.push(item);
    }
    console.log(forward); // ['A', 'B', 'C', 'D'];

// Reverse the deque deque.reverse(); const backward: string[] = []; for (const item of deque) { backward.push(item); } console.log(backward); // ['D', 'C', 'B', 'A'];`

`$3`

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();
    // 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;``

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

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure	Unit Test	Performance Test	API Docs
Deque			Deque

Standard library data structure comparison

Data Structure Typed	C++ STL	java.util	Python collections
Deque<E>	deque<T>	ArrayDeque<E>	deque

Benchmark

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

deque

test name	time taken (ms)	executions per sec	sample deviation
1,000,000 push	14.55	68.72	6.91e-4
1,000,000 push & pop	23.40	42.73	5.94e-4
1,000,000 push & shift	24.41	40.97	1.45e-4
1,000,000 unshift & shift	22.56	44.32	1.30e-4

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

Built-in classic algorithms

Algorithm	Function Description	Iteration Type

Software Engineering Design Standards

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

!NPM
!GitHub top language
!npm
!eslint
!npm bundle size
!npm bundle size
!npm

What

Brief

How

install

$3

``bash npm i deque-typed --save`

`$3`

`bash yarn add deque-typed`

`$3`

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

`$3`

typescript
 // Create a simple Deque with initial values
    const deque = new Deque([1, 2, 3, 4, 5]);
    // Verify the deque maintains insertion order
    console.log([...deque]); // [1, 2, 3, 4, 5];
    // Check length
    console.log(deque.length); // 5;
    // Push to the end
    deque.push(6);
    console.log(deque.length); // 6;

// Pop from the end const last = deque.pop(); console.log(last); // 6;`

`$3`

typescript
 const deque = new Deque([20, 30, 40]);
    // Unshift adds to the front
    deque.unshift(10);
    console.log([...deque]); // [10, 20, 30, 40];
    // Shift removes from the front (O(1) complexity!)
    const first = deque.shift();
    console.log(first); // 10;

// Verify remaining elements console.log([...deque]); // [20, 30, 40]; console.log(deque.length); // 3;`

`$3`

typescript
 const deque = new Deque([10, 20, 30, 40, 50]);
    // Get first element without removing
    const first = deque.at(0);
    console.log(first); // 10;
    // Get last element without removing
    const last = deque.at(deque.length - 1);
    console.log(last); // 50;

// Length unchanged console.log(deque.length); // 5;`

`$3`

typescript
 const deque = new Deque(['A', 'B', 'C', 'D']);
    // Iterate forward
    const forward: string[] = [];
    for (const item of deque) {
      forward.push(item);
    }
    console.log(forward); // ['A', 'B', 'C', 'D'];

// Reverse the deque deque.reverse(); const backward: string[] = []; for (const item of deque) { backward.push(item); } console.log(backward); // ['D', 'C', 'B', 'A'];`

`$3`

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();
    // 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
      });
    }

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

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure	Unit Test	Performance Test	API Docs
Deque			Deque

Standard library data structure comparison

Data Structure Typed	C++ STL	java.util	Python collections
Deque<E>	deque<T>	ArrayDeque<E>	deque

Benchmark

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

deque

test name	time taken (ms)	executions per sec	sample deviation
1,000,000 push	14.55	68.72	6.91e-4
1,000,000 push & pop	23.40	42.73	5.94e-4
1,000,000 push & shift	24.41	40.97	1.45e-4
1,000,000 unshift & shift	22.56	44.32	1.30e-4

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

Built-in classic algorithms

Algorithm	Function Description	Iteration Type

Software Engineering Design Standards

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