mux VS GORM

This attention to detail also can mean that for key abstractions in a tool or framework, what concretely goes on doesn't go unexplained. For example, when I was learning Go for web development, my first stumbling block was understanding how interfaces worked, particularly http.Handler, which is key to doing web development with Go's powerful net/http package and the fits-like-a-glove package built on top of it, the Gorilla Mux router. My way of finding out how that worked, and seeing the elegance of that interface, was pretty unorthodox - I figured out how Handlers worked by looking directly at Go's source code (which also is a demonstration of Go's readability, if you're interested in joining the Gophers!). And coming out of that was my very first tech talk at in 2015, on learning Gorilla from its Node.js counterpart, Express.js!

In this ApiGateway implementation, we've employed the Gorilla Mux router for enhanced route handling. Let's break down the key components:

Now that we have set up the Go environment, we can start building our API. The first step is to choose a framework. There are several popular frameworks for building APIs in Go, such as Gorilla mux, Echo, and Gin. For this article, we'll use Gorilla mux.

Mir is a toolkit to develop RESTful API backend service like develop service of gRPC. It adapt some HTTP framework sush as Gin, Chi, Hertz, Echo, Iris, Fiber, Macaron, Mux, httprouter。

My personal favorite tools: - https://github.com/go-kit/ for building services (although it's not necessary a great tool for prototyping) - https://github.com/gorilla/mux router (although it's been recently deprecated, so I'm looking for a similar, maintained library) - https://entgo.io/ ORM - https://watermill.io/ for messaging

We will be using Gorilla Mux to create the APIs locally. Gorilla Mux implements a request router and dispatcher to match the incoming requests.

FYI, Gorilla Mux has been archived. It’s easy to write this without it.

GORM is a comprehensive ORM tool in Go, offering a code-first approach which allows defining database schemas using struct tags in Go. It's known for its developer-friendly nature, making it suitable for both beginners and experienced users. GORM supports a variety of SQL databases like MySQL, PostgreSQL, and SQLite. It's designed to be flexible, allowing developers to drop down to raw SQL when necessary. However, it's important to be cautious about its performance implications in large-scale applications.

Homepage: https://gorm.io/

Since most of these APIs will be simple CRUD (Create/Read/Update/Delete) endpoints, let's build this service using GORM, an ORM library that makes building CRUD endpoints really simple.

After successfully configuring the application, it's time to delve into integrating the data layer. For this purpose, I will utilize gorm, a powerful SQL ORM that facilitates rapid development of the data layer using model structs.

For basic INSERT ... VALUES ... or SELECT ... WHERE ... JOIN ..., use a library such as GORM. For INSERT .... SELECT ... statements where one combines two round trips (SELECT and INSERT) into one, ORMs have a hard time performing this query. Particularly when you start doing joins. Joins are the heart of Relational database theory (they denote relationships). So get to know what an INNER, LEFT, RIGHT and OUTER join is and why you would use them. Also learn INSERT ... SELECT ...

I have never hated gorm and it serves me well. However I tend to feed it raw SQL very often.

Array of values with embedded value all pointed to the last value, reflect code was broken: https://github.com/go-gorm/gorm/pull/5901 data corruption