deque-typed

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

npm

npm i deque-typed --save

yarn

yarn add deque-typed

snippet

prize roulette

    class PrizeRoulette {
      private deque: Deque<string>;

      constructor(prizes: string[]) {
        // Initialize the deque with prizes
        this.deque = new Deque<string>(prizes);
      }

      // Rotate clockwise to the right (forward)
      rotateClockwise(steps: number): void {
        const n = this.deque.length;
        if (n === 0) return;

        for (let i = 0; i < steps; i++) {
          const last = this.deque.pop(); // Remove the last element
          this.deque.unshift(last!); // Add it to the front
        }
      }

      // Rotate counterclockwise to the left (backward)
      rotateCounterClockwise(steps: number): void {
        const n = this.deque.length;
        if (n === 0) return;

        for (let i = 0; i < steps; i++) {
          const first = this.deque.shift(); // Remove the first element
          this.deque.push(first!); // Add it to the back
        }
      }

      // Display the current prize at the head
      display() {
        return this.deque.first;
      }
    }

    // Example usage
    const prizes = ['Car', 'Bike', 'Laptop', 'Phone', 'Watch', 'Headphones']; // Initialize the prize list
    const roulette = new PrizeRoulette(prizes);

    // Display the initial state
    console.log(roulette.display()); // 'Car' // Car

    // Rotate clockwise by 3 steps
    roulette.rotateClockwise(3);
    console.log(roulette.display()); // 'Phone' // Phone

    // Rotate counterclockwise by 2 steps
    roulette.rotateCounterClockwise(2);
    console.log(roulette.display()); // 'Headphones'

sliding window

    // Maximum function of sliding window
    function maxSlidingWindow(nums: number[], k: number): number[] {
      const n = nums.length;
      if (n * k === 0) return [];

      const deq = new Deque<number>();
      const result: number[] = [];

      for (let i = 0; i < n; i++) {
        // Delete indexes in the queue that are not within the window range
        if (deq.length > 0 && deq.first! === i - k) {
          deq.shift();
        }

        // Remove all indices less than the current value from the tail of the queue
        while (deq.length > 0 && nums[deq.last!] < nums[i]) {
          deq.pop();
        }

        // Add the current index to the end of the queue
        deq.push(i);

        // Add the maximum value of the window to the results
        if (i >= k - 1) {
          result.push(nums[deq.first!]);
        }
      }

      return result;
    }

    const nums = [1, 3, -1, -3, 5, 3, 6, 7];
    const k = 3;
    console.log(maxSlidingWindow(nums, k)); // [3, 3, 5, 5, 6, 7]

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

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

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.