A queue persist on filesytem to save memory
Local development World implementation for Workflow SDK
Tiny queue data structure
fast, tiny `queueMicrotask` shim for modern engines
A shim for the setImmediate efficient script yielding API
Promise queue with concurrency control
Headless CLI client for the Agent Client Protocol (ACP) — talk to coding agents from the command line
Light multi-platform disk space checker without third party for Node.js
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
A simple key/value storage using files to persist the data
Next tick shim that prefers process.nextTick over queueMicrotask for compat
Simple JS queue with auto run for node and browsers
In memory queue system prioritizing tasks
Promise-based queue
LRU 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.
Simple JS queue with auto run for node and browsers
RANKIGI canonical SDK. Passive sidecar with durable on-disk queue, Ed25519-signed events, and Retry-After-aware error classification.
Sequential asynchronous lock-based queue for promises
Get the first path that exists on disk of multiple paths
asynchronous function queue with adjustable concurrency
Fast, in memory work queue
This package provides reliable messaging and persistent queues for building asynchronous applications in Ruby. It supports transaction processing, message selectors, priorities, delivery semantics, remote queue managers, disk-based and MySQL message stores and more.
# Sparrow is a really fast lightweight queue written in Ruby that speaks memcached. # That means you can use Sparrow with any memcached client library (Ruby or otherwise). # # Basic tests shows that Sparrow processes messages at a rate of 850-900 per second. # The load Sparrow can cope with increases exponentially as you add to the cluster. # Sparrow also takes advantage of eventmachine, which uses a non-blocking io, offering great performance. # # Sparrow is a in-memory queue but will persist the data to disk when receiving a term signal. # # Sparrow comes with built in support for daemonization and clustering. # Also included are example libraries and clients. For example: # # require 'memcache' # m = MemCache.new('127.0.0.1:11212') # m['queue_name'] = '1' # Publish to queue # m['queue_name'] #=> 1 Pull next msg from queue # m['queue_name'] #=> nil # m.delete('queue_name) # Delete queue # # # or using the included client: # # class MyQueue < MQ3::Queue # def on_message # logger.info "Received msg with args: #{args.inspect}" # end # end # # MyQueue.servers = [ # MQ3::Protocols::Memcache.new({:host => '127.0.0.1', :port => 11212, :weight => 1}) # ] # MyQueue.publish('test msg') # MyQueue.run # # Messages are deleted as soon as they're read and the order you add messages to the queue probably won't # be the same order when they're removed. # # Additional memcached commands that are supported are: # flush_all # Deletes all queues # version # quit # The memcached commands 'add', and 'replace' just call 'set'. # # Call sparrow with --help for usage options # # The daemonization won't work on Windows. # # Check out the code: # svn checkout http://sparrow.googlecode.com/svn/trunk/ sparrow # # Sparrow was inspired by Twitter's Starling
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