Search Results for "gin"

Gin Boilerplate is a starter template for building RESTful APIs with the Gin web framework in Go. It includes a preconfigured project structure, authentication, middleware, and PostgreSQL integration out of the box. This boilerplate is designed to speed up the development of scalable and maintainable Go web applications.

Gin JWT Middleware is a JWT authentication middleware for applications built with the Gin web framework in Go. It gives developers ready-to-use handlers for login, logout, token refresh, and protected routes. The middleware supports custom authentication logic, authorization checks, claims, token lookup rules, and response callbacks.

...The repository generates a markdown table that includes each framework’s name, star and fork counts, open issue counts, a short description, and the timestamp of the last commit, making it a quick way to compare ecosystem maturity and activity. It includes well-known frameworks and toolkits such as Gin, Fiber, Beego, Echo, go-zero, chi, Kratos, and many more, giving Go developers a broad overview of their options. The data is derived from a simple source file (list.txt) and rendered via a Go utility (list2md.go), so contributors can update the list with minimal friction. Because the table also records last commit times, it helps developers spot projects that are actively maintained versus ones that may be deprecated or stagnant.

...It lists major Chinese Go communities (such as Golang 中国, Study Golang, GoCN Forum) and numerous QQ groups, alongside English-language communities like the official golang-nuts mailing list and Go Forum. The index also categorizes popular web frameworks (Gin, Echo, Beego, Macaron, Revel, Iris), ORMs and database drivers (xorm, gorm, mgo, gosql), helper sites (Go Walker, gobuild.io, regex testers, JSON-to-struct converters).

Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings.