NSP
From OpenOpt
 subjected to
 (continuous functions,
 sometimes with some numerical noise)
 OpenOpt NSP example
 FuncDesigner NSP example (with automatic differentiation)
In NSP default stencil value (for finitedifference derivatives approximation, if derivatives are not supplied by user or FuncDesigner automatic differentiation) is 3, while in NLP it is 1 (see DerApproximator documentation). Also, word NSP instead of NLP informs other programmers (who could edit your code) that your problem is nonsmooth.
NSP solvers
Solver  License  Made by  Info  

ralg  BSD  Dmitrey  For mediumscaled problems (nVars up to ~1000...1500); illconditioned, piecewise linear and polynomial, nonsmooth & noisy ones are also allowed. All types of constraints (lb <= x <= ub, A*x <= b, Aeq*x = beq, c(x) <= 0, h(x) = 0). ralgorithm with adaptive space dilation had been invented by Ukrainian academician Naum Z. Shor (my teacher //Dmitrey). This solver is enhanced from time to time (almost each OpenOpt release).  
interalg  BSD  Dmitrey  Solver with guaranteed userdefined accuracy fTol: abs(f  f*) < fTol. Handling of general constraints is available since r. 0.36  
gsubg  BSD  Dmitrey  For largescaled convex problems with guaranteed userdefined precision. Lots of work still remains to be done, especially for constrained problems.  
amsg2p  BSD  Dmitrey 
Currently unconstrained only, for mediumscaled problems (nVars up to ~1000...1500) Requires known fOpt (optimal value) and fTol (required objective function tolerance, may be very small). 

ShorEllipsoid  BSD  Dmitrey  currently it's a tentative implementation of Naum Z. Shor method of ellipsoids; it's unconstrained, for smallscale problems with nVars = 1..10, requires r0: norm(x0x*)<r0)  No 
scipy_fmin  BSD  an implementation of NelderMead simplex algorithm; unconstrained, cannot handle usersupplied derivatives  
sbplx  LGPL  Steven G. Johnson.  A variant of NelderMead algorithm. Requires nlopt installed. Can handle box bound constraints. 