linguist VS ent

I dunno if this interests you, but you actually have influence over the formatting of https://github.com/someengineering/fix-cf/blob/main/fix-role... via .gitattributes communicating to GH that it's actually yaml: https://github.com/github-linguist/linguist/blob/master/docs...

There’s already a draft pr for this: https://github.com/github-linguist/linguist/pull/6686

GitHub uses Linguist to

I have found that: https://github.com/github-linguist/linguist/blob/master/docs/troubleshooting.md, but I'm also currently not at home, so I will check it out later.

Another option is to use Linguist which is what GitHub uses (I use linguist via .gitattributes files for all of my code projects). It is community driven and supports essentially every language possible: see languages.yml.

Once you selected a topic you can further filter the projects by language. This means programming language as recognized by the linguist tool of GitHub. See what they say about repository languages

As I later found out, GitHub uses the Linguist library to measure the amount of lines written in a specific language... which is still pretty magic 🪄.

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