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.
Running the tests
The tests are in interfaces/Python/tests and use pytest.
From a clone of the repository, download the dependencies, install unopy with the test extra and run pytest from the root directory:
bash dependencies/scripts/download_dependencies.sh
pip install ".[test]"
pytest
The tests require the solvers shipped in the wheels: BQPD, HiGHS and MUMPS.
1 maintainer
Metadata
1 maintainer
Release files for unopy 0.4.17
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| unopy-0.4.17.tar.gz | 2.6 MB | With provenance | Details for unopy-0.4.17.tar.gz |
Built distributions (wheels)
Total release size: 476.9 MB
Release files / unopy-0.4.17.tar.gz
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Transparency logSecurity for unopy 0.4.17
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