goprotobuf VS yaegi

Now let’s take a look at the source code of the protoc-gen-go plugin:

Wait, you say, in Go you can embed a struct with default method implementations to "inherit" them in your composed struct... sure, except any methods called by those methods are early-bound in the original struct, completely ignoring your wrapper, so the best you can do is "not implemented" rather than actually implement something. It is at least a way to prevent semver-major breakage, which the gRPC generator uses, but that's about as far as it gets you.

The classic answer is protobufs. You can serialize out to binary format.

Seems like go is pretty middle of the road. I can only guess as to why but it probably has to do with heavy usage of pointers and reflection which are much slower than other implementations. Gogo/protobuf (RIP) solved this performance with code generation, but the the official go protobuf implementation has essentially eschewed it. I do wonder how the benchmark would look using the new vitess proto library for Go (which has many of the benefits of gogo but with active development and an API built on top of the Google one)

Maybe I'm missing something, but my read of [golang/protobuf#364](https://github.com/golang/protobuf/issues/364) was that the re-organization in protobuf-go v2 was allow for optimizations like gogoprotobuf to be developed without requiring a complete fork. I totally understand that the authors of gogoprotobuf do not have the time to re-architect their library to use these hooks, but best I can figure this generator does not use these hooks either. Instead it defines additional member functions, and wrappers that look for those specialized functions and fallback to the generic ones if not found.

I am thinking about stuff like the [ProtoMethods](https://pkg.go.dev/google.golang.org/[email protected]/reflec...) API.

I wonder why not? Did the authors of the vtprotobuf extension not want to bite off that much work? Is the new API not sufficient to do what they want (thus failing some of the goals expressed in golang/protobuf#364?

In this case try approach with line by line generation. Very much like what protoc-gen-go does for Go code: https://github.com/golang/protobuf/blob/ae97035608a719c7a1c1c41bed0ae0744bdb0c6f/protoc-gen-go/grpc/grpc.go#L142, need to implement this kind of generator yourself.

Something like this: https://github.com/golang/protobuf/blob/master/internal/gengogrpc/grpc.go

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.