service VS ent

Ultimate Service was useful for me. None of the "backend" concepts were new, but you get to see how Bill would layout/design an API-based service. If you're experienced you'll notice the opinionated choices he makes, and I found myself saying "Nah, I'm not sure I'd do it like that". I appreciated its use of Kubernetes and KIND as I'd never played with them before. How he uses Docker to spin up a DB instance for tests is pretty cool. There's a lot of copy & paste as you code along with him (you copy from the "finished project" and paste into your work in progress). The full example project is online at https://github.com/ardanlabs/service. You won't write all that code, and this version is newer than the one I did, but it gives you an idea of what you might learn.

So what can you do insted? For testing databases, setup a docker instance for tests (e.g. like in https://github.com/ardanlabs/service), or start an embedded-postgres daemon (see https://github.com/fergusstrange/embedded-postgres). For communication with external APIs, just pass the http.Client (either in context.Context or as a field on the struct). Then in tests, you can override the http.Client.Transport func.

Take a look at https://github.com/ardanlabs/service from Bill Kennedy. You can probably simplify the structure a bit since your project is minimal, but that repo is gold.

Checkout https://github.com/ardanlabs/service for inporation. Tip: try to avoid creating a service package with all services, a domain package with all domain structs, etc.

Or go through this repo https://github.com/ardanlabs/service

I've seen this handler modification and wrapping pattern in Ardan Labs' service repository. https://github.com/ardanlabs/service/tree/master/foundation/web

https://github.com/ardanlabs/service This is something which I really like and has taken into account a lot of engineering decisions.

In this article, we'll delve into the world of concurrency control in Go, specifically focusing on the optimistic locking approach. We'll explore its implementation using Ent ORM to illustrate how to manage data consistency when multiple users interact with the same resource. Keep in mind that this example serves as a simplified illustration, and real-world booking systems involve a many of additional complexities. However, the core concepts presented here provide a solid foundation for understanding optimistic locking in Go applications. Feel free to explore the complete source code in my GitHub repository for a more in-depth look at the implementation.

ent is a fairly recent ORM that uses a code-first approach where you define your schema in Go code. Ent is popular thanks to its ability to handle complex data models and relationships elegantly. It's statically typed, which can help catch errors at compile time. However, the learning curve might be steeper compared to more straightforward ORMs like GORM. It's a good fit for applications where complex data models and type safety are priorities.

If you found this article, than you are probably similar to how I was a few months ago. I started a project in Go that required a SQL backend and I wanted to use any tool that would help me build this backend quickly. I stumbled upon entgo (an ORM for Go) and decided to give it a try.

The ent orm for golang actually does some useful work for you. https://github.com/ent/ent

Backend Database interaction with entgo

You can use entgo.io for ORM stuff, it also has entgql extension that integrated with GQLGen. See more at the document: https://entgo.io/docs/tutorial-todo-gql