Here are some pictures automatically generated by openopt (matplotlib should be installed) via setting p.plot = 1. Please note, that for some solvers with constrained problems they can turn out to be uninformative - for example objFun can go down while max constraint violation go up , or wise versa, so in future, would openopt get further development, one of features that should be implemented will be adding 2nd subplot - max constraint value. Also note, that some solvers like ALGENCAN has no cross-iter output function (at least for now) that could be easily connected to openopt's one, so their pictures looks like 2 points (start and finish), connected by single line.
Other possible directions of openopt development could be: connecting solvers of NLPy package, implementing 2nd derivatives, automatic scaling, using patterns of sparsity, connecting well-known NLP IPOPT solver, connecting some global solvers and/or writing openopt own ones, writing a good QP solver (that one is required by lincher).
However, since Google Summer of Code program is finished, it requires new sponsor(s), w/o this one openopt development will be very limited.