agent see, examples modes are "human", "rgb_array", "ansi" for text.
- :meth:`close` - Closes the environment, important when external software is used, i.e. pygame for rendering, databases

Environments have additional attributes for users to understand the implementation

- :attr:`action_space` - The Space object corresponding to valid actions, all valid actions should be contained within the space.
- :attr:`observation_space` - The Space object corresponding to valid observations, all valid observations should be contained within the space.
- :attr:`spec` - An environment spec that contains the information used to initialize the environment from :meth:`gymnasium.make`
- :attr:`metadata` - The metadata of the environment, e.g. `{"render_modes": ["rgb_array", "human"], "render_fps": 30}`. For Jax or Torch, this can be indicated to users with `"jax"=True` or `"torch"=True`.
- :attr:`np_random` - The random number generator for the environment. This is automatically assigned during
  ``super().reset(seed=seed)`` and when assessing :attr:`np_random`.

.. seealso:: For modifying or extending environments use the :class:`gymnasium.Wrapper` class

Note:
    To get reproducible sampling of actions, a seed can be set with ``env.action_space.seed(123)``.

Note:
    For strict type checking (e.g. mypy or pyright), :class:`Env` is a generic class with two parameterized types: ``ObsType`` and ``ActType``.
    The ``ObsType`` and ``ActType`` are the expected types of the observations and actions used in :meth:`reset` and :meth:`step`.
    The environment's :attr:`observation_space` and :attr:`action_space` should have type ``Space[ObsType]`` and ``Space[ActType]``,
    see a space's implementation to find its parameterized type.
Ú