Description
Aside from generator specific keyword arguments I believe that there should be a simple standard set for specifying an input space (at least) as every generator (even random generators) need to know this information. This comes with the potential need to define if the input space is discrete or continuous.
For example: Xopt
currently handles only continuous spaces specified by a dictionary of lists that specify the minimum and maximum of the bounds for each variable. This information is contained in a more complex object known as VOCS https://github.com/ChristopherMayes/Xopt/blob/main/xopt/vocs.py which also defines objectives/constraints/constants/observables and does validation on inputs. An example of this (taken from https://github.com/ChristopherMayes/Xopt/blob/main/docs/examples/single_objective_bayes_opt/bo_tutorial.ipynb) is below:
vocs = VOCS(
variables={"x": [0, 2 * math.pi]},
objectives={"f": "MINIMIZE"},
)