Metadata-Version: 2.5
Name: flowprog
Version: 1.0.0
Summary: Define material flows models as programs
Project-URL: Homepage, https://github.com/probs-lab/flowprog
Project-URL: Repository, https://github.com/probs-lab/flowprog
Project-URL: Issues, https://github.com/probs-lab/flowprog/issues
Project-URL: Changelog, https://github.com/probs-lab/flowprog/blob/main/CHANGELOG.md
Author-email: Rick Lupton <mail@ricklupton.name>
License-Expression: MIT
License-File: LICENSE
Keywords: lca,material flow analysis,mfa,sympy
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
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
Requires-Python: >=3.10
Requires-Dist: pandas>=2.2.0
Requires-Dist: rdflib>=6.0
Requires-Dist: sympy>=1.11.1
Provides-Extra: benchmarks
Requires-Dist: brightway25>=1.1.1; extra == 'benchmarks'
Requires-Dist: doit>=0.37.0; extra == 'benchmarks'
Requires-Dist: scikit-umfpack>=0.4.2; extra == 'benchmarks'
Provides-Extra: definitions
Requires-Dist: sphinx-probs-rdf[loader]>=0.6.0; extra == 'definitions'
Provides-Extra: numpyro
Requires-Dist: jax>=0.4; extra == 'numpyro'
Requires-Dist: jaxlib>=0.4; extra == 'numpyro'
Requires-Dist: numpyro>=0.12; extra == 'numpyro'
Description-Content-Type: text/markdown

# flowprog: procedural generation of material flow model

This Python package defines a framework for building up mass flow models using Sympy symbolic equations.

## Getting started

Install `flowprog` from PyPI. For example, using [uv](https://docs.astral.sh/uv):

``` shellsession
uv add flowprog
```

or using pip (with a suitable virtual environment activated):

``` shellsession
pip install flowprog
```

See the documentation in `docs/` for more details and examples.

## Developing

If you don't have [uv installed already, install it](https://docs.astral.sh/uv/getting-started/installation/).

Then install dependencies using `uv`:

``` shellsession
uv sync
```

Build the documentation and examples using Jupyter Book:

``` shellsession
uv run jb build docs
```

Then open the resulting HTML files in `docs/_build/html/index.html` in your browser.

Run the tests using `pytest`:

``` shellsession
uv run pytest tests
```
