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PyOptInterface Modeling Guidelines

When modeling with pyoptinterface_native, adhere to these patterns.

Solver Initialization

Use pyoptinterface.<solver>.Model(). Supported: highs, gurobi, copt, ipopt, knitro, mosek, xpress.
For Gurobi, you can manage environments with poi.gurobi.Env().

Variables

model.add_variable(lb=None, ub=None, domain=poi.VariableDomain.Continuous, name="", start=None)
model.add_m_variables(shape, ...) returns a NumPy array of variables.

Constraints

Linear: model.add_linear_constraint(expr, sense, rhs) or model.add_linear_constraint(lhs <= rhs).
Quadratic: model.add_quadratic_constraint(expr, sense, rhs).
Matrix: model.add_m_linear_constraints(A, x, sense, b).
Nonlinear: Wrap in with nl.graph(): and use model.add_nl_constraint(expr).

Objective

model.set_objective(expr, sense).
Nonlinear: with nl.graph(): model.add_nl_objective(expr, sense).

Attributes

Get: model.get_model_attribute(poi.ModelAttribute.TerminationStatus).
Set: model.set_variable_attribute(v, poi.VariableAttribute.LowerBound, 0.0).
Results: model.get_variable_attribute(v, poi.VariableAttribute.Value).

Common Utilities

poi.quicksum(terms): Efficiently sum variables/expressions.
poi.Eq, poi.Leq, poi.Geq: Aliases for constraint senses.