f1d51b8cc8
- Foldable left panel (user profile) and right panel (task details) - Clicking a task in the list or graph node selects it and shows details - Both views (task list + graph) always mounted via absolute inset-0 for correct canvas dimensions; tabs toggle visibility with opacity - Graph node selection animation: other nodes repel outward (charge -600), then selected node smoothly slides to center (500ms cubic ease-out), then charge restores to -120 and graph stabilizes - Graph re-fits on tab switch and panel resize via ResizeObserver - Fix UUID string IDs throughout (backend returns UUIDs, not integers) - Add TaskDetailPanel, UserPanel components - Add CLAUDE.md project documentation Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2.0 KiB
yocto-queue 
Tiny queue data structure
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 O(n) while Queue#dequeue() has constant time complexity O(1). That makes a huge difference for large arrays.
A queue 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) principle.
Install
$ npm install yocto-queue
Usage
const Queue = require('yocto-queue');
const queue = new Queue();
queue.enqueue('🦄');
queue.enqueue('🌈');
console.log(queue.size);
//=> 2
console.log(...queue);
//=> '🦄 🌈'
console.log(queue.dequeue());
//=> '🦄'
console.log(queue.dequeue());
//=> '🌈'
API
queue = new Queue()
The instance is an Iterable, 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.
.enqueue(value)
Add a value to the queue.
.dequeue()
Remove the next value in the queue.
Returns the removed value or undefined if the queue is empty.
.clear()
Clear the queue.
.size
The size of the queue.
Related
- quick-lru - Simple “Least Recently Used” (LRU) cache