[theshrike79]

I'm in a similar place, but my stack is Python->Go

With Python I can easily iterate on solutions, observe them as they change, use the REPL to debug things and in general just write bad code just to get it working. I do try to add type annotations etc and not go full "yolo Javascript everything is an object" -style :)

But in the end running Python code on someone else's computer is a pain in the ass, so when I'm done I usually use an LLM to rewrite the whole thing in Go, which in most cases gives me a nice speedup and more importantly I get a single executable I can just copy around and run.

In a few cases the solution requires a Python library that doesn't have a Go equivalent I just stick with the Python one and shove it in a container or something for distribution.

[millerm]

I'm in the camp of "If your target is Go, then prototype in Go." I don't bother with the intermediate step. Go is already so very close to being a dynamic language that I don't get the point. Just write "bad" Go to prototype quickly. Skip the error checks. Panic for fun. Write long functions. Make giant structs. Don't worry about memory.

You mentioned running someone else's python is painful, and it most certainly is. No other language have I dealt with more of the "Well, it works on my machine" excuse, after being passed done the world's worst code from a "data scientist". Then the "well, use virtual environments"... Oh, you didn't provide that. What version are you using? What libraries did you manually copy into your project? I abhor the language/runtime. Since most of us don't work in isolation, I find the intermediate prototype in another language for Go a waste of time and resources.

Now... I do support an argument for "we prototype in X because we do not run X in production". That means that prototype code will not be part of our releases. Let someone iterate quickly in a sandbox, but they can't copy/paste that stuff into the main product.

Just a stupid rant. Sorry. I'm unemployed. Career is dead. So, I shouldn't even hit "reply"... but I will.

[vjdingdong]

I second your experience with Python. I've been coding in Python for 10+ years. When I get passed down some 'data scientist' code, I often it breaks.

With Rust, it was amazing - it was a pain to get it compiled and get past the restrictions (coming from a Python coder) - the code just ran without a hitch, and it was fast, never even tried to optimize it.

As a Python 'old-timer' , I also am not impressed with all the gratuitous fake typing , and especially Pydantic. Pydantic feels so un-pythonic, they're trying to make it like Go or Rust, but its falling flat, at least for me.

[ixsploit]

Is there a good resource on how to get better at python prototyping?

The typing system makes it somewhat slow for me and I am faster prototyping in Go then in Python, despite that I am writing more Python code. And yes I use type annotations everywhere, ideally even using pydantic.

I tend to use it a lot for data analytics and exploration but I do this now in nushell which holds up very well for this kind of tasks.

[theshrike79]

Just do it I guess? :D

When I'm receiving some random JSON from an API, it's so much easier to drop into a Python REPL and just wander around the structure and figure out what's where. I don't need to have a defined struct with annotations for the data to parse it like in Go.

In the first phase I don't bother with any linters or type annotations, I just need the skeleton of something that works end to end. A proof of concept if you will.

Then it's just iterating with Python, figuring out what comes in and what goes out and finalising the format.

[ixsploit]

Thank you, but the JSON API stuff is exactly what i am using nushell for at the moment. Makes it trivial to navigate large datasets.

For me it's pretty hard to work without type annotations, it just slows me down.

Don't get me wrong, I really like python for what it is, I simply missing out on the fast prototype stuff that everyone else is capable of.