• with render_mode="human" you don't need to call .render(), rendering will happen automatically on env.step()
• with render_mode="rgb_array", .render() pops the list of frames rendered since the last .reset()
• with render_mode="single_rgb_array", .render() returns a single frame, like before.

Bug fixes

• Fixed car racing termination where if the agent finishes the final lap, then the environment ends through truncation not termination. This added a version bump to Car racing to v2 and removed Car racing discrete in favour of gym.make("CarRacing-v2", continuous=False) @araffin
• In v0.24.0, opencv-python was an accidental requirement for the project. This has been reverted. @KexianShen @pseudo-rnd-thoughts
• Updated utils.play such that if the environment specifies keys_to_action, the function will automatically use that data. @Markus28
• When rendering the blackjack environment, fixed bug where rendering would change the dealers top car. @balisujohn
• Updated mujoco docstring to reflect changes that were accidently overwritten. @Markus28

Misc

• The whole project is partially type hinted using pyright (none of the project files is ignored by the type hinter). @RedTachyon @pseudo-rnd-thoughts (Future work will add strict type hinting to the core API)
• Action masking added to the taxi environment (no version bump due to being backwards compatible) @pseudo-rnd-thoughts
• The Box space shape inference is allows high and low scalars to be automatically set to (1,) shape. Minor changes to identifying scalars. @pseudo-rnd-thoughts
• Added option support in classic control environment to modify the bounds on the initial random state of the environment @psc-g
• The RecordVideo wrapper is becoming deprecated with no support for TextEncoder with the new render API. The plan is to replace RecordVideo with a single function that will receive a list of frames from an environment and automatically render them as a video using MoviePy. @johnMinelli
• The gym py.Dockerfile is optimised from 2Gb to 1.5Gb through a number of optimisations @TheDen