Net status return codes.

A netstring parser and emitter

Ruby Library for NetSuite REST API. Originally developed by HueiYi Lucy Cheng.

RESTlet-based client for Netsuite

Ruby wrapper for the NetSuite SuiteTalk SOAP Web Services API (v2025.2). Targets the final supported SOAP endpoint (scheduled for removal in 2028.2 per Oracle's deprecation timeline). Includes async bulk operations (asyncAddList, asyncUpdateList, asyncUpsertList, asyncDeleteList, asyncGetList).

Netty is an asynchronous event-driven network application framework for rapid development of maintainable high performance protocol servers & clients.

Networking utitlities to operate network equipment made by Cisco, AlaxalA, NEC IX, Palo Alto, Aruba Wireless LAN Controller and so on.

network-client is a drop-in thin layer on top of Net::HTTP classes for JSON web requests with retry functionality and simple error handling

Utilizing the official NetworkManager DBus API

Networkr is a Ruby gem inspired by the Python package NetworkX. It includes basic functionality for the creation, manipulation, and analysis of graphs. Graphs supported include undirected single-edge graphs (weighted or unweighted), directed single-edge graphs (weighted or unweighted), and undirected multi-edge graphs (weighted or unweighted). Algorithms available include Dijkstra's shortest paths, Karger's minimum cut, Kosaraju's strongly connected components, and Prim's minimum spanning tree.

Provides a Ruby wrapper for consuming Network Rail Data Feeds

Continuously pings a host and announces response times. Alerts audibly when latency exceeds a threshold.

A set of utils to get URL info before downloading a resource, work with ports, etc.

P2P Networking library for us in games.

Includes cancan controller helpers in all netzke components.

Configure Netzke modules as plugins for a Netzke app and link ExtJS library to boot

Gives you the ability to use any decorator in netzke components with almost no effort

Neural Network

neural network ruby implementaiton

Identify Neuropeptides using powerful Hidden Markov Models. For further information please refer to: https://github.com/wurmlab/neurohmmer