Metadata-Version: 2.4
Name: dagua
Version: 0.0.2
Summary: GPU-accelerated differentiable graph layout engine built on PyTorch
Author: John Mark Taylor
License-Expression: MIT
Project-URL: Homepage, https://github.com/johnmarktaylor91/dagua
Project-URL: Repository, https://github.com/johnmarktaylor91/dagua
Project-URL: Issues, https://github.com/johnmarktaylor91/dagua/issues
Keywords: graph,layout,visualization,pytorch,dag,graphviz,hierarchical
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
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: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=1.9
Provides-Extra: render
Requires-Dist: matplotlib>=3.5; extra == "render"
Provides-Extra: graphviz
Requires-Dist: graphviz>=0.20; extra == "graphviz"
Provides-Extra: dev
Requires-Dist: matplotlib>=3.5; extra == "dev"
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: ruff>=0.4; extra == "dev"
Requires-Dist: mypy; extra == "dev"
Requires-Dist: pip-audit; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Provides-Extra: test
Requires-Dist: pytest>=7.0; extra == "test"
Requires-Dist: matplotlib>=3.5; extra == "test"
Dynamic: license-file

# dagua

GPU-accelerated differentiable graph layout engine built on PyTorch.

**DAG + agua.** Directed acyclic graphs + water. Named after the Dagua River in Colombia — a river flows downhill (like a DAG), never cycles back (acyclic), and finds its own path through the landscape (like gradient descent finding optimal node positions).

## Why?

Graphviz has dominated graph visualization for 30 years but has hard scaling limits. No existing Python package provides pip-installable, hierarchical (Sugiyama-style) graph layout. Dagua fills this gap: `pip install dagua`, pure Python + PyTorch, GPU-accelerated, hierarchical layout with composable constraints.

## Status

Pre-alpha. Under active development.

## License

MIT
