Metadata-Version: 2.4
Name: openBES
Version: 0.1.0
Summary: Python implementation of the Open Building Energy Simulation (OpenBES) tool.
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: pvlib
Requires-Dist: numba
Provides-Extra: dev
Requires-Dist: line_profiler; extra == "dev"

# OpenBES-py

[![Unittest](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/unittest.yml/badge.svg)](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/unittest.yml)
[![ASHRAE 140 Suite](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/test_cases.yml/badge.svg)](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/test_cases.yml)
[![.github/workflows/package_test.yml](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/package_test.yml/badge.svg)](https://github.com/OxfordRSE/OpenBES-py/actions/workflows/package_test.yml)

OpenBES-py is an open-source building energy simulation tool written in Python. It is designed to provide transparent, reproducible, and extensible energy modeling for buildings, supporting research, education, and practical analysis.

## Features

- **Modular simulation engine**: Each energy category is implemented as a separate module for clarity and extensibility.
- **Comprehensive test suite**: All core modules are covered by unit and integration tests.
- **Standardized test cases**: Planned integration with ASHRAE Standard 140 test cases (see `cases_ashrae_std140_...` directory).
- **Modern dependency management**: Uses [UV](https://github.com/astral-sh/uv) for fast, reliable Python environment setup (`uv.lock` included).

## Current Status

The Python code reproduces the Excel spreadsheet simulation results for the Holywell House specification to at least 6 decimal places.

The next step is to validate the Python code against ASHRAE Standard 140 test cases.

## Installation

1. Install [UV](https://github.com/astral-sh/uv) if you do not have it: `pip install uv`

2. Set up a virtual environment (recommended): `uv venv`

3. Install dependencies: `uv sync`

4. Run tests to verify installation: `uv run python -m unittest discover -s tests`

## License

The license for this project is under consideration. 

## Credits

We use Pandas for data manipulation and NumPy for numerical calculations.

We use PVLib.iotools for reading EPW (energy plus weather) files.

    Jensen, A., Anderson, K., Holmgren, W., Mikofski, M., Hansen, C., Boeman, L., Loonen, R. “pvlib iotools — Open-source Python functions for seamless access to solar irradiance data.” Solar Energy, 266, 112092, (2023). DOI: 10.1016/j.solener.2023.112092.

