[worldsayshi]

I often think of go as a "better" python. As in, easy to learn and easy to use. But also performant and the module system and package manager seem to be a little neater. (sorry for flamebait)

But I wonder how well it can cover similar use cases? Go is great for devops and web backends. But what about AI and data science?

[jochem9]

I used to do lots of data engineering in Python, then started doing all kinds of engineering in primarily Go.

The Go ecosystem for data is very limited. There are no widely supported dataframe libraries (like the og pandas and the newer polars written in rust and also available as a crate). Very few data science libs, a few decent gen AI libraries, but not as popular as their Python cousins.

Most of the work I do now is streaming data and very small batches. For that Go is amazing. I don't need dataframes to transform a json, combine it with a bunch of other data and write to a database. I just need to write that logic and make it go fast. Very easy in Go.

[chubot]

If Go interfaced with C as well as Python, I’d use it a lot more.

But I’m using the slower language because it still integrates with more things

For example, one reason AI is all in Python is because CUDA is basically part of the C ecosystem (ie build system)

[impulser_]

Have you tried purego?

You can just embed the C library into the binary of the Go app call it directly in Go. Most of the time I have found calling C from Go faster or on par with calling C from Python.

https://github.com/ebitengine/purego

[tardedmeme]

Go interfaces with C better than Python does...