iwopy
Fraunhofer IWES optimization tools in Python
Overview
Define your optimization problem once and use native or external solvers through a shared Python interface. Available external integrations include:
iwopy's GG and SLSQP optimizers are included. LocalFD supplies finite-difference
derivatives; DiscretizeRegGrid is the regular-grid problem wrapper. Population
evaluation batches candidates or derivative points when the chosen backend supports it.
The optimizer catalog lists every selectable optimizer with a short description and a runnable, explicit Python setup.
Documentation: https://fraunhoferiwes.github.io/iwopy
Source code: https://github.com/FraunhoferIWES/iwopy
PyPi reference: https://pypi.org/project/iwopy/
Anaconda reference: https://anaconda.org/conda-forge/iwopy
Citation
Please cite the JOSS paper IWOPY: Fraunhofer IWES optimization tools in Python
BibTeX is available on the citation page.
Requirements
Supported Python versions: 3.10 through 3.14. NumPy, SciPy, and matplotlib are base dependencies.
Installation
Install in an active virtual environment:
pip install iwopy
Optional extras are cma, nevergrad, optuna, deap, pymoo, and pygmo;
use pip install 'iwopy[opt]' for all backends. SciPy differential evolution
needs no extra. Nevergrad currently requires NumPy below 2.4.
Conda users can install the conda-forge package:
conda install -c conda-forge iwopy
See the installation guide for environment setup and development-branch installation.
Optimizer Creation
Select a backend family and algorithm through the standalone factory:
from iwopy.benchmarks import QuadraticProblem
from iwopy import create_optimizer
solver = create_optimizer(
family="iwopy",
optimizer="SLSQP",
problem=QuadraticProblem(),
max_iterations=100,
)
solver.initialize(verbosity=0)
results = solver.solve(verbosity=0)
Optimizer classes use explicit parameters and flat native keyword options. Existing class names remain available. See the creation API for all families, including SciPy methods and PyGMO-backed NLopt solvers. The shared parameter table explains population/batch units and supported native termination limits.
Development
git clone https://github.com/FraunhoferIWES/iwopy.git
cd iwopy
uv sync --extra dev --extra test --extra opt --upgrade
uv run pre-commit install
uv run pre-commit run --all-files
uv run pytest tests
Follow AGENTS.md and docs/development.md for test ownership and completion gates. Contributions are welcome through pull requests.
Support
For trouble shooting and support, please
Thanks for your help with improving iwopy!
1 maintainer
Metadata
1 maintainer
Release files for iwopy 1.0.0
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| File | Size | Uploaded | |
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|---|---|---|---|---|
| iwopy-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 386.3 kB
Release files / iwopy-1.0.0.tar.gz
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