algoneer VS ParlAI

I gave a presentation on type checking at the EuroPython 2017 where I also investigated how many Python projects really use type checking, I present the results at the end (35 minutes in):

https://www.youtube.com/watch?v=vM2Zoy4Sxhk&t=2181s

My conclusion was that only a small fraction of projects really used them, there were a lot of projects that had type checks in their code but only in "homeopathic" doses.

I started using them for some of my Python projects as well (e.g https://github.com/algoneer/algoneer) and while I find them useful I think they're not as useful as a "real" type system in a fully typed language like Golang. Still, they're very useful for discovering simple mistakes that would only show up in unit testing otherwise.

You can also "misuse" them for other purposes, at the end of the presentation I e.g. show how you can implement software contracts with them. Of course this would wreck a type checker like mypy, so don't do that in your codebase. That's probably also one of my critiques as the annotation syntax can in principle be used for anything, but mypy and other tools are not able to deal with code that does that.

Do you have https://github.com/facebookresearch/ParlAI installed? Looks like they're doing something weird with their flake8 config.

There's quite a few open-source Reinforcement Learning challenges that you can explore with modest amounts of compute in order to build some experience training RL models, for example the Nethack Learning Environment, Atari, Minigrid, etc. For me personally, I had only worked in NLP / dialogue for years but got into RL by implementing Random Network Distillation models for NetHack. It's a fun area that definitely has its own unique challenges vs other domains. -AM

Further it uses the old GPT-2 tokenizer with a quite small token vocabulary and BPE so it will never be able to figure out how to rhyme, for instance.

I do really like that again they have shared a training logbook.

https://github.com/facebookresearch/ParlAI/blob/main/project...

You probably meant to link this: https://github.com/facebookresearch/ParlAI/blob/main/project...

I run a fairly large open source project (https://github.com/facebookresearch/ParlAI/) and we use mypy. Our experience has been that it can be quite difficult to placate, so we usually treat it only as a warning. However, having our code annotated with types in many places has significantly improved developer productivity, just from having less ambiguity with what you're dealing with.