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2,737–2,760 of 4,970 · Most stars

Reporter classes for the jasmine test framework. Includes JUnitXmlReporter for generating junit xml output for running in CI environments like Jenkins.

Unofficial Dante Controller alternative for iOS/iPadOS, Linux, macOS, Windows, and the web. Discover, route, configure, meter, and monitor Dante audio devices with a native iPhone/iPad app, CLI, browser interface, daemon, and API.

734 animated ASCII art pieces for web pages, READMEs, wallpapers and terminals. Browse them in your terminal with npx ascii-magic-art and add one to your project in one prompt.

  • animation
  • ascii
  • ascii-art
  • cli

🍡 HTTP Input for Go - HTTP Request from/to Go Struct (Bi-directional Data Binding between Go Struct and http.Request)

  • go-http
  • go-http-middleware
  • go-api
  • go-rest-api

Marshmallow provides a flexible and performant JSON unmarshalling in Go. It specializes in dealing with unstructured struct - when some fields are known and some aren't, with zero performance overhead nor extra coding needed.

  • go
  • golang
  • json
  • performance

[Go]Distributed Actor/Grain framework for Golang with goodies

  • actor-model
  • actors
  • actorsystem
  • golang

HIBA is a system built on top of regular OpenSSH certificate-based authentication that allows to manage flexible authorization of principals on pools of target hosts without the need to push customized authorized_users files periodically.

TranslatedGenerate a complete planet in the browser and simulate its history, producing an editable map and chronicle. Designed for creating original worlds for novels, setting books, tabletop role-playing games, and similar projects.

Siemens Industrial Experience is a design system for designers and developers, to consistently create the perfect digital experience for industrial software products.

Ruby library to perform server-side tracking into the official Google Analytics Measurement Protocol

  • ruby
  • google-analytics
  • analytics
  • analytics-tracking

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.