Queue in runtime base promise
A shim for the setImmediate efficient script yielding API
Tiny queue data structure
fast, tiny `queueMicrotask` shim for modern engines
A JS library for finding optimal label position inside a polygon
Call an array of promise-returning functions, restricting concurrency to a specified limit.
Promise queue with concurrency control
The smallest and simplest JavaScript priority queue
A simple tool to keep requests to be executed in order.
queue-lit is a tiny queue data structure in case you `Array#push()` or `Array#shift()` on large arrays very often
Next tick shim that prefers process.nextTick over queueMicrotask for compat
Simple JS queue with auto run for node and browsers
an opinionated implementation of resque in node
In memory queue system prioritizing tasks
Promise-based queue
The fastest javascript implementation of a double-ended queue. Used by the official Redis, MongoDB, MariaDB & MySQL libraries for Node.js and many other libraries. Maintains compatability with deque.
LRU Queue
Simple JS queue with auto run for node and browsers
Sequential asynchronous lock-based queue for promises
asynchronous function queue with adjustable concurrency
Throttles arbitrary code to execute a maximum number of times per interval. Best for making throttled API requests.
Fast, in memory work queue
A promise based, dynamic priority queue runner, with concurrency limiting.
Microsoft Azure Storage SDK for JavaScript - Queue
A production-ready Sidekiq gem that provides both queue-level concurrency limits and job-level throttling capabilities, combining the best of sidekiq-limit_fetch and sidekiq-throttled.
Calculates algorithms and data structures for sorting and searching. Selects best one to use for particular data set. Currently supports: Bubble Sort, Insertion Sort, Selection Sort, Merge Sort, Quick Sort, Heap Sort, Stack, Queue, Linked List, Binary Search Tree
Proper related posts plugin for Jekyll - uses document correlation matrix on TF-IDF (optionally with Latent Semantic Indexing). Each document is tokenized and stemmed, every word found is treated as keyword for analysis (except for some stop words). TF-IDF matrix for the whole site is calculated (including extra provided weights), then if given accuraccy is lower than 1.0, LSI algorithm is used to compute new simplified vector space. Document correlation matrix is created using dot product of the matrix and its transpose. For each of the post' related documents are inserted into priority queue (sorted by score from document correlation matrix), assuming the score is greater than minimal required score. Selected few bests related posts are retrieven from the queue. Liquid template for each post is rendered and <related-posts /> is replaced with the outcomes of algorithm.
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