wire VS ent

code generation is a mostly disjoint topic from DI. Granted, some solutions like https://github.com/google/wire use code generation, but you're exactly right about their pitfalls. If your dev environment doesn't have good support for generated code, it is a nightmare. If you can goto-definition the generated code, then it is suddenly feasible, but perhaps still a bad choice.

We use https://github.com/google/wire for every bigger project, take a look at it, it beautifully solves initialisation and also gives you a guideline on how to do it.

Im by no means a "purist" in such things, I love my magic and QoL-features/libs, but havent seen something that is so easy to use in go, that I immediately wanted to add it. And to be fair, I only looked closely at https://github.com/google/wire , others I have just skipped - and I will be looking into uber-fx as mentioned in the other comment.

If you have such a complex and deep dependency graph, and you don't want to manually maintain it, you could use some DI library to handle that for you. Something like https://github.com/google/wire for small-medium size stuff, or https://github.com/uber-go/fx for larger scale, more enterprise projects.

Try https://github.com/google/wire. Compile time generated like dagger 2 in java.

Most people probably do it by hand (I do). But otherwise, probably https://github.com/google/wire is the most popular, maybe followed by https://github.com/uber-go/fx.

For larger object graphs do you roll everything by hand or encourage something like https://github.com/google/wire

The other thing is that I'm lazy, so I don't construct all dependencies in main.go manually but use wire to generate the construction of my dependency tree.

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