yaegi VS GORM

Yes. There are long standing feature requests for (e.g.) the reflect package that simply don't get done because they'd break this assumption and/or force further indirection in hot paths to support "no code generation at runtime, ever".

Packages like Yaegi (that offers an interpreted Go REPL) have "know limitations, won't be addressed" also because of these assumptions.

https://github.com/golang/go/issues/4146

https://github.com/golang/go/issues/16522

https://github.com/traefik/yaegi?tab=readme-ov-file#limitati...

There is always https://github.com/traefik/yaegi - a Go interpreter written to make it easy to write plugins.

I think https://github.com/traefik/yaegi comes as close as using the python interpreter in you CLI, but for Go

There's a go interpreter: https://github.com/traefik/yaegi It could run programs without compiling them, but there're some limitations.

I'd recommend looking into a different approach for plugins such as hashicorp/go-plugin (which uses multiple process PIDs and RPC communication between them) or traefik/yaegi (which implements a Go-compatible scripting language that can be interpreted at runtime and which still supports most Go modules).

Why do we need a language like Rust when we have Rust. Why not just create a Rust interpreter. (There's such an interpreter for Go, BTW, https://github.com/traefik/yaegi )

A cool solution I saw was Traefik's yaegi module. They basically created an interpreted scripting language with Go compatible syntax (turning Go into an interpreted, not compiled, language). I haven't tried this but it sounds like it brings the better parts of dynamic languages like Python's plugin support to Go - plugin writers can still write "Go" code, which can load dynamically.

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