Metadata-Version: 2.4
Name: optora
Version: 0.0.3
Summary: A research-oriented optimization library for deterministic and stochastic methods.
Author: Optora contributors
License-Expression: MIT
Keywords: optimization,stochastic optimization,deterministic optimization,machine learning,scientific computing
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=2.2
Provides-Extra: dev
Requires-Dist: build>=1.2; extra == "dev"
Requires-Dist: pytest>=8; extra == "dev"
Requires-Dist: ruff>=0.5; extra == "dev"
Requires-Dist: mypy>=1.10; extra == "dev"
Requires-Dist: twine>=5; extra == "dev"
Provides-Extra: docs
Requires-Dist: zensical>=0.0.11; extra == "docs"
Requires-Dist: mkdocstrings-python>=1.10; extra == "docs"
Dynamic: license-file

# Optora

Optora is an early-stage, GPU-first Python library for composable research
components in optimization, uncertainty-aware decision-making, and
transport-based geometry. The first milestone is intentionally small:
PyTorch-native problem, objective, result, and solver interfaces that can later
grow into stochastic methods, differentiable programming backends, optimal
transport, and Bayesian decision geometry.

