
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[]) {
this.deque = new Deque<string>(prizes);
}
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();
this.deque.unshift(last!);
}
}
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();
this.deque.push(first!);
}
}
display() {
return this.deque.first;
}
}
const prizes = ['Car', 'Bike', 'Laptop', 'Phone', 'Watch', 'Headphones'];
const roulette = new PrizeRoulette(prizes);
console.log(roulette.display());
roulette.rotateClockwise(3);
console.log(roulette.display());
roulette.rotateCounterClockwise(2);
console.log(roulette.display());
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++) {
if (deq.length > 0 && deq.first! === i - k) {
deq.shift();
}
while (deq.length > 0 && nums[deq.last!] < nums[i]) {
deq.pop();
}
deq.push(i);
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));
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. |