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65 lines
2 KiB
Markdown
65 lines
2 KiB
Markdown
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# yocto-queue [![](https://badgen.net/bundlephobia/minzip/yocto-queue)](https://bundlephobia.com/result?p=yocto-queue)
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> Tiny queue data structure
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You should use this package instead of an array if you do a lot of `Array#push()` and `Array#shift()` on large arrays, since `Array#shift()` has [linear time complexity](https://medium.com/@ariel.salem1989/an-easy-to-use-guide-to-big-o-time-complexity-5dcf4be8a444#:~:text=O(N)%E2%80%94Linear%20Time) *O(n)* while `Queue#dequeue()` has [constant time complexity](https://medium.com/@ariel.salem1989/an-easy-to-use-guide-to-big-o-time-complexity-5dcf4be8a444#:~:text=O(1)%20%E2%80%94%20Constant%20Time) *O(1)*. That makes a huge difference for large arrays.
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> A [queue](https://en.wikipedia.org/wiki/Queue_(abstract_data_type)) is an ordered list of elements where an element is inserted at the end of the queue and is removed from the front of the queue. A queue works based on the first-in, first-out ([FIFO](https://en.wikipedia.org/wiki/FIFO_(computing_and_electronics))) principle.
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## Install
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```
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$ npm install yocto-queue
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```
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## Usage
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```js
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import Queue from 'yocto-queue';
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const queue = new Queue();
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queue.enqueue('🦄');
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queue.enqueue('🌈');
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console.log(queue.size);
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//=> 2
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console.log(...queue);
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//=> '🦄 🌈'
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console.log(queue.dequeue());
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//=> '🦄'
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console.log(queue.dequeue());
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//=> '🌈'
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```
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## API
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### `queue = new Queue()`
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The instance is an [`Iterable`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols), which means you can iterate over the queue front to back with a “for…of” loop, or use spreading to convert the queue to an array. Don't do this unless you really need to though, since it's slow.
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#### `.enqueue(value)`
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Add a value to the queue.
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#### `.dequeue()`
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Remove the next value in the queue.
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Returns the removed value or `undefined` if the queue is empty.
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#### `.clear()`
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Clear the queue.
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#### `.size`
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The size of the queue.
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## Related
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- [quick-lru](https://github.com/sindresorhus/quick-lru) - Simple “Least Recently Used” (LRU) cache
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