looking for nonlinear optimizer with constraints accessible from python

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I want to solve a small (a few hundred variables) nonlinear optimization
problem with constraints in Fedora. I've found the scipy optimization
routines, but they are for unconstrained problems.  And there are the
coin-or routines (ipopt, etc.), but they are not easily accessible from
python. Fedora doesn't package pyomo, which can access them, so I've
installed it to --user, but it seems like overkill, so I'm still
looking.

I would like something like pulp for linear programming; the closest
I've found is pyOpt, and I like its interface, but it hasn't been
maintained for 4 years, and it throws errors indicating that it might be
incompatible with more recent versions of numpy (f2py) and multiarray.
It can't find the shared libraries, compiled into python using f2py, of
the fortran77 optimization routines it uses.

So, before I go the pyomo route, does anyone have any recommendations
for simple python accessible software that would do this in Fedora?

Thanks.
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