With Uno, finally take full control of your SQP/barrier solver for nonlinearly constrained optimization

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unopy

unopy is the Python interface for Uno, a modern and modular solver for nonlinearly constrained optimization. Uno unifies Lagrange-Newton (SQP and interior-point) methods by breaking them down into a set of common building blocks such as constraint reformulation, step computation, and globalization.

Installation

unopy is a registered Python package that can be installed via pip:

pip install unopy

unopy allows you to solve an optimization model described by callback functions. An example of the Hock-Schittkowski model hs015 is available in the file example_hs015.py.

Getting started

To get started with Uno, check out the official documentation.

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