Metadata-Version: 2.4
Name: quaq
Version: 0.0.1
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Rust
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Dist: numpy>=1.24 ; extra == 'numpy'
Provides-Extra: numpy
Summary: High-performance quantum computing simulator and analysis toolkit with a Rust core and Python bindings.
Keywords: quantum,simulation,machine-learning,reservoir-computing
Home-Page: https://github.com/EnriqueAnguianoVara/quac
Author: Enrique Anguiano Vara
Requires-Python: >=3.9
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Homepage, https://github.com/EnriqueAnguianoVara/quac
Project-URL: Issues, https://github.com/EnriqueAnguianoVara/quac/issues
Project-URL: Repository, https://github.com/EnriqueAnguianoVara/quac

# quaq

`quaq` is a quantum computing simulator and analysis toolkit with a Rust core and Python bindings built through `PyO3` and `maturin`.

## Install

```bash
pip install quaq
```

For local development:

```bash
maturin develop --release
```
 
## Build Distributions

```bash
maturin build --release
maturin sdist
```

This produces wheels and an sdist suitable for upload to PyPI.

## Publish

The repository includes `.github/workflows/release.yml`.

1. Create a PyPI project named `quaq`.
2. Configure PyPI Trusted Publishing for this GitHub repository, or add a `PYPI_API_TOKEN` repository secret.
3. Push a version tag like `v0.0.1`.

The workflow will build platform wheels, build the source distribution, and publish the artifacts to PyPI.

For a manual upload:

```bash
python -m twine check dist/*
python -m twine upload dist/quaq-*
```

