It would be nice to be able to print all of the decisions/intermediate states of the model. Something like

>>> print(model.states)
BinaryVariable(5) = [0, 1, 0, 0, 0]
IntegerVariable((2, 3)) = [[0, 15, 5], [1, 4, 2]]

something like this can be accomplished now with

for symbol in model.iter_decisions():
    print(type(symbol))
    print(symbol.state())

but there are many design issues here.

1. What order do we print the symbols? Topological? Do we require a locked model in order to print? And without some sort of labeling (see Add symbol labels #17) and/or symbol printing (see Consider adding Symbol.__str__() overload #133) it would be hard to disambiguate the symbol that's being printed
2. Do we print the state of all intermediate symbols or just the decisions? Do we want to make this configurable?
3. Do we always print all states? Just the first? Make this configurable?