Flake8-pyproject VS Gymnasium

I must try this some time https://pypi.org/project/Flake8-pyproject/ since the flake8 author refuses to add pyproject.toml support themselves. Marking the ticket as "too heated" and pull requests as spam, like he has something against the pyproject.toml format or something.

If you're sufficiently annoyed to accept an extra dependency over this (like I was), there's this: https://pypi.org/project/Flake8-pyproject/

Regarding setup.cfg, it's currently used for flake8 related configuration. Flake8 doesn't support pyproject.toml: https://github.com/PyCQA/flake8/issues/234. There are some workarounds, such as https://github.com/john-hen/Flake8-pyproject, but, in my opinion, getting rid of additional config file doesn't really justify additional dependency. However, as setup.cfg is currently used only for flake8 related configs, perhaps it could be replaced by .flake8 file.

"Show HN: Ghidra Plays Mario" (2023) https://news.ycombinator.com/item?id=37475761 :

[RL, MuZero reduxxxx ]

> Farama-Foundation/Gymnasium is a fork of OpenAI/gym and it has support for additional Environments like MuJoCo: https://github.com/Farama-Foundation/Gymnasium#environments

> Farama-Foundatiom/MO-Gymnasiun: "Multi-objective Gymnasium environments for reinforcement learning": https://github.com/Farama-Foundation/MO-Gymnasium

https://github.com/Farama-Foundation/Gymnasium#environments

Farama-Foundatiom/MO-Gymnasiun:

https://github.com/Farama-Foundation/Gymnasium - A framework Python library to build and train your own AI to play games

The only change in the environment from the one here is the reward function which is given its return value using the following code snippet (replacing lines 648-672 in the above url):

This may be useful: https://github.com/Farama-Foundation/Gymnasium

Here are all the environments. So for example, if instead of Hopper-v2 you want the acrobat environment from classic control you can write: env = gym.make('Acrobot-v1')

This release also includes a large number of documentation updates, minor bug fixes, and other minor improvements; the full release notes are available here if you’d like to learn more: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.28.0.

Thanks! It really depends on the task that you want to implement. But in general, sticking to the standard gymnasium API is important. If you want to implement a 2D environment then PyGame is promising. If it's more like a game, check out Unity ML-Agents or Godot RL Agents. Anything simpler can also be just pure python code. You also need to carefully design your observation space, action space and reward function. My advice is to explore design choices of related environments.

You can read the release notes here: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.27.0. You can upgrade from 0.26 without any changes unless you're doing something very uncommon; this is how releases will generally be going forward.